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Demand Response Market Potential in
Xcel Energy’s Northern States Power
Service Territory
PREPARED FOR
Xcel Energy
PREPARED BY
The Brattle Group
Ahmad Faruqui
Ryan Hledik
YouGov America
David Lineweber
April 2014
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Table of Contents
Executive Summary .............................................................................................................................. 1
1. Introduction ...................................................................................................................................... 5
2. Our Approach ................................................................................................................................... 6
2.1. The DR Measures.................................................................................................................. 6
2.2. Defining DR Potential .......................................................................................................... 8
2.3. Developing the DR Supply Curves .................................................................................... 10
3. Customer Interest in the DR Options ............................................................................................ 12
3.1. Sizing the Market for New DR Options ............................................................................ 12
3.2. Likely Residential Response to DR Options ..................................................................... 13
3.3. Likely Business Customer Response to DR Options ......................................................... 15
3.4. Medium and Larger Business Customer Response to DR Options .................................. 16
3.5. Identifying Likely DR Program Adopters ......................................................................... 18
3.6. Final Participation Rates for the DR Potential Study....................................................... 20
4. NSP’s DR Potential ......................................................................................................................... 22
4.1. Measure-Level DR Potential .............................................................................................. 22
4.2. Portfolio-Level DR Potential ............................................................................................. 26
4.3. The DR Supply Curve......................................................................................................... 29
5. Market and Policy Developments .................................................................................................. 32
5.1. Market Developments ........................................................................................................ 32
5.2. Policy Initiatives ................................................................................................................. 34
6. Conclusions and Recommendations .............................................................................................. 35
Appendix A: DR Potential Study Details
Appendix B: Market Research Study Details
Appendix C: Market Research Questionnaires
Appendix D: Additional Methodological Notes on the Market Research Study
Appendix E: Annual DR Impact Tables
Appendix F: DR Supply Curves
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Acknowledgements and Disclaimer
This report was prepared for Xcel Energy. All results and any errors are the responsibility of the
authors and do not represent the opinion of The Brattle Group, Inc. or its clients. Opinions
expressed in this report, as well as any errors or omissions, are the authors’ alone. The examples,
facts, and requirements summarized in this report represent our interpretations. Nothing herein
is intended to provide a legal opinion.
The authors would like to thank Jessie Peterson, the Xcel Energy project manager, and Brian
Doyle, Steve Huso, Bruce Nielson, Jeremy Peterson, Deb Sundin, and Steve Wishart of Xcel
Energy for their responsiveness to our questions and for their valuable insights.
About the Authors
Ahmad Faruqui is a Principal and Ryan Hledik is a Senior Associate at The Brattle Group, an
economic consulting firm with offices in Cambridge, Massachusetts, Washington DC, San
Francisco, London, New York, Rome, and Madrid. They can be contacted at www.brattle.com.
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Executive Summary
The purpose of our study is to quantify the market potential for demand response (DR) programs
to reduce peak demand within Xcel Energy’s Northern States Power service territory (“NSP-MN”
and “NSP-WI”). The peak demand reduction estimates developed through our study are
intended to be used as key inputs to NSP’s long term resource planning activities. This report
summarizes our methodology and findings, and provides a discussion of future market and policy
developments that could further influence NSP’s DR program offerings.
We considered 22 different programmatic DR options and segmented NSP’s market into four
customer classes. Nine of the DR options we analyzed are currently offered by NSP. For these
options, we assessed the incremental potential that could be achieved through additional
marketing and outreach, and possibly through a redesign of the programs. The other 13 DR
options would be new programs that are not currently offered by NSP. These are primarily
options that would be enabled through the deployment of advanced metering infrastructure
(AMI), but also include a demand bidding program that could be offered without a system-wide
infrastructure upgrade.
A key feature of the study is that it is based on primary market research that was conducted with
NSP’s customers in order to establish likely DR enrollment estimates that are specifically tailored
to NSP’s service territory. These enrollment rates are combined with detailed estimates of perparticipant peak demand reductions to produce system-level peak reduction capability
projections. The peak reduction projections, combined with program cost estimates, create a
“supply curve” of DR resources. Our DR potential estimates do not account for the costeffectiveness of the DR measures. The "supply curve" will be used by NSP within their integrated
resource plan (IRP) to determine cost-effectiveness and optimal portfolio use.
NSP’s existing DR portfolio is substantial. In its existing programs, NSP currently has the
capability to reduce peak demand by 997 MW, or 10.9% of its system peak. If participation rates
remain constant as a percent of the eligible population, this could grow slightly in absolute terms
to 1,054 MW (10.4% of peak) by 2028. 1
Through our market research, we find that DR participation is sensitive to the participation
incentive that is being offered. For each DR option, we estimated likely enrollment at five
different price points representing a reasonable range of marginal costs that could be observed
over the forecast horizon. If current incentive payments were dropped to the low end of the
plausible range, participation in the programs would decrease by between 10% and 30%.
Increasing the incentive payments to the high end of the range could result in increases in
participation of between 10% and 50%, depending on the DR option.
1
The impact drops in percentage terms, because the system peak is projected to grow at a rate that is
faster than growth in the number of customers.
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We find that there is some room for incremental growth through traditional DR programs such
as direct load control (DLC), Interruptible Tariffs, and Demand Bidding. An expanded portfolio
including these traditional programs could reduce peak by 1,455 MW (14.4% of peak) by 2028,
an incremental increase of 401 MW relative to the existing portfolio. This leads us to some
recommendations for the traditional DR program offerings:
•
Consider modifying the interruptible program such that it is price-triggered (in addition
to reliability-triggered). This could allow for more frequent dispatch to address both
reliability and economic needs and, if combined with a higher incentive payment to
account for more frequent interruptions, could result in greater participation according to
our market research.
•
Consider expanding the residential DLC program to include multi-dwelling units. The
cost-effectiveness of this expansion will need to be explored in further detail, as multifamily dwelling units provide smaller peak reductions than the average single family
home and can often include additional installation costs.
•
Evaluate the opportunity for a demand bidding program. Customer interest in such a
program was modest based on market research, with around 10% of small/medium
customers and 8% of large customers being interested. However, if future scenarios
include higher and more volatile energy prices, the program could potentially be a
valuable addition to NSP’s DR portfolio. Participation by small customers would require
some form of aggregation/third party involvement.
We also find that AMI-enabled programs, while not technically feasible in the short run with
existing technology, could further increase DR potential within the next decade. As an
incremental addition to the expanded DR portfolio described above, an opt-in redesigned TOU
rate for all customers would result in peak reduction capability of 1,425 MW (14.1% of the
system peak) by 2028. 2 Offering the TOU rate as the default rate structure would result increase
peak reduction capability to 1,528 MW (15.1% of the system peak). Alternatively, including a
2
In this study, we have assumed that a single customer could not be enrolled simultaneously in more
than one DR option. When TOU is offered as a mutually exclusive option in our portfolio, some of
the customers who otherwise would have enrolled in a traditional DR option like an interruptible
tariff instead choose to enroll in the TOU rate. The TOU rate produces significantly lower peak
reductions per participant than the traditional DR options that we have included and, in this case, the
result is a lower estimate of total peak reduction potential than if the TOU rate had not been offered.
In practice, it would alternatively be possible to allow customers to enroll in both the TOU rate and
another DR option (e.g., the interruptible tariff). That is how NSP’s programs are currently offered.
In this scenario, the total potential impact would be higher, but it would be necessary to carefully
design incentives and rates to avoid overcompensating participants for the load reductions they
provide.
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default critical peak pricing (CPP) rate with automating technology for all customers could
increase potential impacts to 1,952 MW (19.3% of peak) by 2028. Recommendations related to
these AMI-enabled pricing programs include:
•
Empirically evaluate dynamic pricing options through a pilot. In particular, given
emerging interest in around-the-clock DR, the pilot could focus on automated real-time
price response that could be a useful future resource for integrating renewables, which
are rapidly emerging in the Midwestern U.S.
•
Consider combining the DLC program with a critical peak pricing (CPP) rate or a peak
time rebate (PTR). Some utilities have offered a higher price-based financial incentive to
customers who are equipped with enabling technology in recognition of their higher
degree of certainty in price response.
•
A redesign of the TOU rate would likely lead to increased enrollment. A reduced peak
period duration will lead to greater customer interest, according to market research. At
high levels of market penetration, though, the economics of a full-scale AMI deployment
would need to be revisited.
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1. Introduction
The purpose of our study is to quantify the potential for demand response (DR) programs to
reduce peak demand within NSP-MN and NSP-WI. The peak demand reduction estimates
developed through our study are intended to be used as key inputs to NSP’s long term resource
planning activities. This report summarizes our methodology and findings, and provides a
discussion of market and policy developments that could influence NSP’s DR program offerings.
Our study builds upon a previous (2012) analysis that assessed DR potential in Minnesota. We
have expanded this research in several ways. 3 Most notably, we conducted primary market
research with NSP’s customers to establish DR program enrollment estimates that are specifically
tailored to NSP’s customer base. This ensures that our conclusions will reflect the preferences of
NSP’s own customers, rather than being drawn from national averages that may not account for
unique characteristics of NSP’s service territory.
Another key feature of our study is the construction of detailed “supply curves” of DR resources.
These supply curves can be used as input to NSP’s integrated resource planning (IRP) process to
identify economically optimal DR investments. The supply curves represent the peak reduction
potential of each DR option at five different incentive payment levels. This allows Xcel Energy
to model DR for their integrated resource plan. Other features of our study include: New
definitions of DR portfolios that closely align with the types of offerings that NSP could provide
in the future, new customer class definitions that are consistent with logical market
segmentations (e.g. all large customers have interval meters), and estimates of participant impacts
that reflect actual program experience in NSP’s service territory and across North America.
Our study explores the extent to which greater peak demand reductions could be achieved both
through increased participation in the existing programs and through entirely new program
offerings. We estimate this potential individually for 22 different DR options. We also assemble
these options into for four plausible DR program portfolios to better understand the potential
aggregate impacts at the system level. We worked closely with NSP staff to assemble a database
of system characteristics that are needed to conduct such an assessment. NSP was involved
throughout the course of our study and provided substantial input as we constructed the DR
portfolios and assessed their peak reduction potential.
Finally, it is important to note that our potential estimates do not account for the costeffectiveness of the DR measures. Each DR option’s potential is reported without consideration
for the cost of the option. It could be the case that the costs of some of the DR options we have
analyzed outweigh the benefits. The cost-effectiveness of each DR option will be determined by
NSP.
3
KEMA, “Xcel Energy Minnesota DSM Market Potential Assessment: Final Report, Volume I,” April
20, 2012.
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2. Our Approach
This section describes the overall approach that was used to estimate NSP’s DR potential. This
includes identification of the DR measures to be considered, an overview of the bottom-up DR
potential estimation methodology, and discussion of data sources supporting the key
assumptions. For additional detailed information on the approach, see Appendix A.
2.1. THE DR MEASURES
NSP’s customer base was divided into four customer classes. Customer class definitions were
determined based on both applicability of DR programs and data availability.
•
•
•
•
Residential: All residential accounts
Small Commercial & Industrial (C&I): Less than 25 kW of demand
Medium C&I: 25 kW to 1,000 kW of demand
Large C&I: More than 1,000 kW of demand (all have interval meters)
Non-metered customers, such as street lighting, were excluded from the analysis.
We consider 22 different DR options, which were developed in close coordination with NSP.
The menu of DR options is tailored to emerging market conditions that NSP expects to encounter
over the forecast horizon. For example, we assess two different types of Interruptible Tariff
programs, to test customer interest in reliability-triggered versus price-triggered options. We
quantitatively assess a Demand Bidding option for all commercial and industrial customers, as
there is emerging interest in the ability of DR to participate in MISO’s energy market. We
consider a redesign of NSP’s TOU rate, to test market acceptance of different rate designs. And
we also consider an expanded DLC program that includes multi-dwelling units (MDUs).
We considered three “traditional” DR options in the study:
•
Direct Load Control (DLC): NSP’s Savers Switch program is a DLC option. In a DLC
program, the participant’s central air-conditioner (CAC) is remotely cycled using a
switch. Participants are given an incentive payment during summer months. For
residential participants, it is a 15% average monthly bill discount (roughly $10 to $15 per
summer month for the typical customer). For business participants, it is $5 per ton of A/C
per month (average of all NSP participants). We model separate programs for single
family homes (SFH) and MDUs.
•
Interruptible Tariff: We modeled two different interruptible tariff options for Medium
and Large C&I customers. Option 1 is a reliability-triggered option. This is NSP’s
Electric Rate Savings Plan. Customers agree to reduce demand to a pre-specified level
and receive an incentive payment in the form of a discounted demand charge, which
varies with the load curtailment level and control type. The program is triggered for
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extreme reliability events. Option 2 is a price-triggered option. 4 It is similar to the
reliability-triggered option, but can also be triggered by high wholesale prices and is
likely to be called more frequently. In our analysis, in return for agreeing to the
possibility of more frequent interruptions, customers receive larger incentive payments.
The option can be utilized for both reliability and economic purposes. It would be
unlikely for both options to be offered simultaneously.
•
Demand Bidding: This type of program is not currently offered by NSP. Participants
submit hourly curtailment schedules on a daily basis. NSP “clears” the market based on
wholesale energy prices and informs bidders as to whether their bid was accepted, and at
what price. Participants must curtail the bid load amount to receive the bid incentive
payment, or otherwise may be subject to a non-compliance penalty (i.e. the cost of
replacement power). We modeled this program for Medium and Large C&I, and have
also considered Small C&I as they could potentially participate through an Aggregator.
In addition to the reliability-based programs, two AMI-enabled rate options were considered
(they are also referred to as “time-varying rates” and “dynamic pricing options” interchangeably
throughout this report). AMI would need to be deployed before these options were offered to
customers that do not currently have interval metering. The time-varying retail rates are
revenue neutral for the class (i.e., the customer with a load profile similar to the class load profile
will not see a bill change without shifting load. With load shifting, he or she will see a lower
bill.).
4
•
Redesigned time-of-use (TOU) rate: TOU rates are currently offered to all customer
classes and are mandatory for Large C&I customers. NSP’s current TOU rates have a long
peak period (9 am to 9 pm) with peak-to-off-peak energy price ratios that are higher for
residential customers than for C&I customers. We tested a redesigned TOU rate with
more manageable features such as a 6-hour peak period and a peak-to-off-peak price ratio
that is consistent with rates being offered in other jurisdictions (based on a review of
more than 160 rate offerings from around the globe). The redesigned TOU rate is
modeled for all customer segments.
•
Critical peak pricing (CPP): CPP rates are not currently offered by NSP. A CPP rate
provides customers with a discounted rate during most hours of the year, and a much
higher rate (typically between 50 cents/kWh and $1.00/kWh) during peak hours on up to
10 or 15 days per summer. Critical peak events are called in response to high market
prices or reliability concerns; participants are given day-ahead notification. We modeled
a CPP rate with an 8-to-1 price ratio (including fuel costs) for all customer classes, based
on a review of CPP rates in other jurisdictions. We also included an option in which
NSP’s ERS program has a price-triggered option (Energy Controlled Tier I) but only a few customers
are currently enrolled.
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customers would be equipped with “enabling technology” that would automate load
reductions for certain end uses during critical events (e.g. a programmable
communicating thermostat for residential customers).
We modeled a total of 22 DR options across four customer classes. They are shown in Table 1
below, with options that are currently offered by NSP being shaded in gray.
Table 1: DR Measures Included in Study
Residential
Small C&I
Medium C&I
X
X
X
Large C&I
Traditional DR Options
Direct load control (Central A/C)
Interruptible tariff (reliability-based)
X
X
Interruptible tariff (price-based)
X
X
X
X
X
Demand bidding
AMI-enabled Rate Options
Revised time-of-use (TOU) pricing
X
X
X
X
Critical peak pricing (CPP)
X
X
X
X
CPP with enabling technology
X
X
X
X
Notes:
Shading indicates DR option is already offered by NSP
TOU w/tech is not included as an option, because TOU does not have a "dispatchable" price signal like CPP
Residential DLC is divided into two measures - one for single-family homes (SFH) and one for multi-dwelling units (MDU)
Interruptible (reliability) is structured like NSP's current program
Interruptible (price) is price-triggered, with more interruptions and a different (higher) incentive structure
2.2. DEFINING DR POTENTIAL
Our study focuses on estimating the “market potential” for DR. Market potential captures the
potential impact of DR on peak demand if participation reaches achievable levels as identified
through primary market research. In other words, it is a plausible estimate of DR potential,
given practical considerations about customer enrollment rates.
We estimated market potential individually for each DR measure. Then, four portfolios of DR
measures were constructed based on a range of programmatic offerings and deployment
strategies, and aggregate peak reduction potential was estimated for each of these portfolios. The
measures were not screened for cost-effectiveness. Cost-effectiveness screening will be
implemented by NSP for traditional DR options. Dynamic pricing options will be analyzed
separately.
Two variations of market potential were estimated for the AMI-enabled rate options. The two
variations are based on different assumptions about the manner in which these programs (CPP
and redesigned TOU) are offered to customers. Opt-in participation assumes that customers
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would remain on the currently existing rate and would need to proactively enroll in the dynamic
rate. Opt-out participation assumes that customers are automatically enrolled in a dynamic rate
with the option to revert back to the otherwise applicable tariff. This is typically expected to
result in significantly higher enrollment than when offered on an opt-in basis. Opt-out
deployment of dynamic pricing for residential customers is currently uncommon, although TOU
rates have been rolled out on an opt-out basis across the province of Ontario, Canada and
throughout Italy. PTR has been offered on an opt-out basis in Southern California, Maryland,
and Washington, D.C.
In our study, the redesigned TOU is modeled as being offered on a mandatory basis for Large C&I
customers, since that is NSP’s current practice. We assume opt-in deployment for all reliabilitybased DR measures. It is very uncommon for customers to be defaulted onto such programs.
DR potential is estimated using empirically-based assumptions about the eligible customer base,
participation, and per-customer impacts. The fundamental equation for calculating the potential
system impact of a given DR option is shown in Figure 1 below.
Figure 1: The DR Potential Estimation Framework
Potential DR
Impact
=
Total Demand of
Customer Base
X
% of Base Eligible
to Participate
X
% of Eligible
Customers
Participating
X
% Reduction in
demand per
participant
Market characteristics (e.g. system peak demand forecast, customer load profiles, number of
customers in each class, appliance saturations) were provided by NSP. Whenever possible, we
relied on per-participant impacts observed in existing NSP DR programs or otherwise developed
through NSP research. In the case of AMI-enabled rate options, there is limited experience in
NSP’s service territory. Therefore, we simulated the impacts of these programs using an
extensive library of more than 160 different pricing tests from recent pricing pilots. See the
appendix for details on how these simulations were carried out. A summary of the final perparticipant average peak reductions for each measure is provided in Table 2 below.
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Table 2: Average Per-Participant Peak Reduction
Segment
Residential
Residential
Residential
Residential
Residential
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
DR Measure
DLC - Single Family Homes
DLC - Multi-Dwelling Units
TOU
CPP
CPP w/Tech
DLC
Demand Bidding
TOU
CPP
CPP w/Tech
DLC
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Per-customer impact
0.62 kW, based on Savers Switch program
0.47 kW, assuming smaller impact than SFH
0.2 kW (7.4% of avg customer peak), simulated based on pilot results
0.3 kW (14.8% of avg customer peak), simulated based on pilot results
0.5 kW (23% of avg customer peak), simulated based on pilot results
1.9 kW, based on Savers Switch program
0.02 kW (0.6% of avg customer peak), simulated based on pilot results
0.01 kW (0.3% of avg customer peak), simulated based on pilot results
0.02 kW (0.7% of avg customer peak), simulated based on pilot results
0.21 kW (8.2% of avg customer peak), simulated based on pilot results
3.9 kW, based on Savers Switch program
132.6 kW, based on Electric Rate Savings Plan results
132.6 kW, based on Electric Rate Savings Plan results
7.1 kW (8.1% of avg customer peak), simulated based on pilot results
3.7 kW (4.2% of avg customer peak), simulated based on pilot results
7.6 kW (8.7% of avg customer peak), simulated based on pilot results
9.6 kW (10.9% of avg customer peak), simulated based on pilot results
1295.6 kW, based on Electric Rate Savings Plan results
1295.6 kW, based on Electric Rate Savings Plan results
270.1 kW (9.2% of avg customer peak), simulated based on pilot results
143.1 kW (4.9% of avg customer peak), simulated based on pilot results
291.5 kW (10% of avg customer peak), simulated based on pilot results
406.1 kW (13.9% of avg customer peak), simulated based on pilot results
Notes:
Per-customer impacts for time-varying rate options are based on opt-in deployment
Per-customer impacts are lower for opt-out deployments
See appendix for description of time-varying rates impact simulation
Demand bidding impacts simulated using results of dynamic pricing pilots & benchmarked to programs in other jurisdictions
Medium C&I Interruptible impacts for new participants are established such that long run average per-customer impacts trend toward
the average Interruptible Tariff impact observed in FERC's 2012 Assessment of Demand Response and Advanced Metering
Participation rates are a key input to the analysis. To develop participation estimates, we worked
with a market research firm, YouGov America, to survey NSP customers and obtain estimates of
their preferences for each of the DR options. The methodology for conducting the market
research and the key findings of that research are summarized in Section 3 of this report.
2.3. DEVELOPING THE DR SUPPLY CURVES
Ultimately, the purpose of our study is to produce estimates of DR potential that can be used as
input to NSP’s IRP process. For NSP’s resource planning model to identify the optimal level and
timing of DR investments over the forecast horizon, we have developed annual supply curves of
DR resources. The DR supply curves indicate the incremental cost of obtaining increasing
quantities of peak demand reductions through DR investments.
The DR supply curves account for a range of incentive levels that could be offered in each DR
option. Depending on the market outlook, it may be optimal to offer a higher or lower incentive
payment than is currently offered (and get higher or lower enrollment – and impacts - as a
result). We tested five price points for each DR option through market research, to estimate
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likely enrollment levels at each, and incorporated these price points into the supply curves. The
price points represent a plausible range of future avoided costs that we developed in coordination
with NSP. The incentive levels that are embodied in the existing programs are included in this
range. Table 3 summarizes the five price points for each DR option. Additional detail on other
program costs is included in the Appendix.
Table 3: Incentive Levels Included in DR Supply Curves
DLC
($/kW-year)
Reliability-based
Interruptible
($/kW-year)
Price-based
Interruptible
($/kW-year)
Demand
Bidding
($/MWh)
Very low
30
30
55
100
Low
55
55
80
300
Mid
85
85
110
500
High
110
110
135
750
Very High
150
150
175
1,000
The DR supply curves include all traditional DR options (DLC, Interruptible Tariffs, and Demand
Bidding) for all customer classes. The AMI-enabled DR options (TOU and CPP) were not
included in the supply curves. This is because the integrated resource planning framework
cannot fully account for the costs and benefits of AMI. Such analysis must be done outside of the
IRP process in order to account for benefits such as reduced operating costs (e.g. automated
meter reading, faster outage detection, and improved outage avoidance and restoration).
Similarly, it is difficult to fully evaluate the impacts of new rate designs in an IRP context. Key
criteria to be considered when evaluating new rate designs – such as equity, simplicity, and
economic efficiency – would not be fully accounted for in the IRP framework. Therefore, we
include the AMI-enabled options in the DR potential estimates described in Section 4 below, but
do not include them in the DR supply curve, which is an input to NSP’s IRP modeling.
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3. Customer Interest in the DR Options
This section summarizes the findings of research conducted with customers in Xcel Energy’s NSP
service territory on issues having to do with their likely response to new DR options. Appendix
B provides additional detail on the findings of the research. Appendix C includes the
questionnaires that were used in conducting the research. Appendix D provides additional detail
on the methodology.
Research was conducted during the fall of 2013 with both residential and business customers.
The questionnaires used in the research were developed jointly by the NSP DR assessment team,
representatives of The Brattle Group, and the YouGov America (YGA) team. Key objectives of
the work were to:
•
Quantify the size of the market within each customer strata that would likely choose to
either opt-in to a new DR option, or would be likely to opt-out if customers were
defaulted onto some of the rates
•
Specify the characteristics of customers that make them either more or less likely than
average to adopt new DR options
Data on these issues was collected from a total of 409 residential customers. These respondents
were solicited from an online panel source and qualified on the basis of their stated utility
provider and the location of their primary home. Surveys were also completed among 537
business customers, with 337 collected from businesses with less than 25 kW maximum demand,
124 collected from businesses with 25 – 300 kW of maximum demand, and 76 collected from
businesses with a maximum demand of 300 - 750 kW. NSP provided the sample that was used to
survey business customers and all of the business customer interviews were conducted by
telephone. 5
3.1. SIZING THE MARKET FOR NEW DR OPTIONS
Since the primary goal of the market research was to size the potential market for new DR
options, we begin by summarizing the results of the analysis on this point. Each customer strata
(residential, and then small, medium, and larger business customers) was asked about the
likelihood that they would adopt each of several measures that were appropriate for them.
Customers were provided with a summary description of each measure and asked, on a “0” to
“10” scale, how interested they would be in adopting each measure.
Our team used these survey responses to estimate the likely number of customers (among those
who would be eligible for each program) who would adopt each program. The analytical
5
See the discussion on “Market Research Methodological Notes” in the Appendix for more information
on this subject.
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approach used to calculate this number of “likely takers” assumes that all of the customers who
are eligible for each program are aware of those programs and that they have information about
each program that is approximately similar to the information provided to them in the survey
questionnaires. Additionally, the survey team used existing information about how survey
respondents tend to overstate their likelihood of buying new products or acquiring new services
to deflate stated likelihoods to adopt (this is known as adjusting for the “say / do” problem). In
calculating the likely program adoption rates, then, we use customer responses to drive these
estimates, but we do not simply take customers at their word, but adjust for the fact that they
tend to be more optimistic about their actions than is realistic 6.
3.2. LIKELY RESIDENTIAL RESPONSE TO DR OPTIONS
Residential customers were asked about their interest in four broad types of DR programs, with
several specific options tested within some of those types of programs:
•
Saver’s Switch Direct Load Control (DLC) program offered with monthly summer bill
savings specified at five levels: $5, $9, $14, $18, $25
•
Critical Peak Pricing (CPP) program offered with critical peak periods occurring on up to
10 days each summer, with monthly summer bill savings specified at five levels: 6%, 8%,
11%, 13%, 15%
•
Critical Peak Pricing (CPP) program with enabling technology offered with critical peak
periods occurring on up to 10 days each summer, with monthly summer bill savings
specified at five levels: 8%, 11%, 15%, 17%, 20%
•
Time-of-Use (TOU) program offered without any peak days, with monthly summer bill
savings specified at five levels: 4%, 6%, 10%, 12%, 14%
As Figure 2 indicates below, the Savers Switch Program (DLC) among multifamily customers and
CPP w/ Tech have the highest likelihood of participation (40% and 39%, respectively). Roughly
half of all respondents did not exhibit strong likelihood of participating in a DR program.
6
See the discussion on “Adjusting for Say / Do Overstatement,” in the Appendix.
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Figure 2: Residential Market Potential for Tested DR Options
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3.3. LIKELY BUSINESS CUSTOMER RESPONSE TO DR OPTIONS
Small business customers (less than 25 kW) were asked about their likely response to each of the
following DR options:
•
The Saver’s Switch DLC program at $1, $3, $4, $5, and $7 dollars per ton of CAC per
summer (or $20, $60, $80, $100, and $112 per summer for an estimated average five ton
CAC unit)
•
Critical Peak Pricing (CPP) program offered with critical peak periods occurring on up to
10 days each summer, with per-bill savings specified at five levels: 6%, 8%, 11%, 13%,
15%
•
Critical Peak Pricing (CPP) program with enabling technology offered with critical peak
periods occurring on up to 10 days each summer, with per-bill savings specified at five
levels: 8%, 11%, 15%, 17%, 20%
•
Time-of-Use (TOU) program offered without any peak days, with per-bill savings
specified at five levels: 4%, 6%, 10%, 12%, 14%
Figure 3 reports the aggregate results for these programs when they were offered to the small
business strata. The most popular programs among Small C&I closely parallel top programs
among residential customers: CPP w/ Tech takes the lead, followed by DLC and CPP.
Figure 3: Small Business Market Potential for Tested DR Options
*Note: Small C&I Demand Bidding data represents estimates based on Medium C&I data.
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3.4. MEDIUM AND LARGE BUSINESS CUSTOMER RESPONSE TO DR OPTIONS
The two commercial and industrial (C&I) customer strata (25-300 kW and 300-750 kW,
respectively) were asked about the likelihood that they would sign up for the following DR
options:
•
The Saver’s Switch DLC program at $1, $3, $4, $5, and $7 dollars per ton of CAC per
summer (or $40, $120, $160, $200, and $280 per summer for an estimated average ten ton
CAC unit) 7
•
Critical Peak Pricing (CPP) program offered with critical peak periods occurring on up to
10 days each summer, with per-bill savings specified at five levels: 6%, 8%, 11%, 13%,
15%
•
Critical Peak Pricing (CPP) program with enabling technology offered with critical peak
periods occurring on up to 10 days each summer, with per-bill savings specified at five
levels: 8%, 11%, 15%, 17%, 20%
•
Time-of-Use (TOU) program offered without any peak days, with per-bill savings
specified at five levels: 4%, 6%, 10%, 12%, 14%
•
Interruptible Rate plan offering an average monthly bill credit of $2, $3.50, $5.50, $7,
$9.50 per kW of demand reduced during a few critical peak periods every summer.
•
Interruptible Rate plan offering an average monthly bill credit of $3.50, $5, $7, $8.50, $11
per kW of demand reduced during up to 15 critical peak periods per year.
Likely adoption rates within these two customer strata are slightly lower than we observed for
the small business strata for similar programs. Among Medium business customers, Demand
Bidding and Time of Use plans are fairly unattractive; CPP w/ Tech is the leader, but only by a
small margin.
7
This option was only presented to the Medium C&I segment.
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Figure 4: Medium C&I Customer Market Potential for Tested DR Options
CPP with Tech is also the most attractive DR program among Larger business customers. But
note, however, that price sensitivity for most of these options is relatively low – and even lower
than it is for other customer segments -- meaning that customers are likely to either adopt or not
adopt the option, based primarily on non-price-related considerations, and as a result, regardless
of the price offered (at least for the price points tested).
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Figure 5: Large C&I Customer Market Potential for Tested DR Options
A limited number of qualitative interviews with Larger business customers (over 750 kW) were
also conducted and, despite being generally happy with their service from Xcel Energy,
likelihood to participate in the DR programs appear to be generally low. Participation appears to
hinge both on getting more information, and on being able to avoid any disruption or discomfort
in company functions.
3.5. IDENTIFYING LIKELY DR PROGRAM ADOPTERS
One of the other key goals of the work was to determine which portions of the customer
population were more likely to say that they would adopt these new programs. Clearly, if
customers who used less energy on average (for example) were more likely than others to adopt a
given DR option, this could have a potential effect on program impacts. Similarly, if “likely
takers” can be targeted with clearly identifiable observable characteristics, then it would make
targeting program communications easier.
As Table 4 below indicates, however – at least for residential customers - most of the factors that
differentiate likely DR takers are psychographic, rather than demographic, characteristics. Likely
DR takers, in other words are more likely to generally support the notion of energy efficiency,
and are more likely to approve of Xcel Energy and its actions.
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Table 4: Attributes of Likely / Unlikely Residential DR Program Adopters
The notable differences between likely and unlikely DR program adopters among business
customers include only a limited set of both psychographic, and firmographic, factors (see Table
5 below). Among Small business customers, likely DR program takers are more are very similar
to others in their attitudes and perceptions of Xcel Energy. The key difference is that likely
adopters tend to be smaller.
Among Medium and Larger business customers, likely program adopters have more positive
perceptions of Xcel Energy and are more likely to be participating in the Interruptible Rate plan.
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Table 5: Attributes of Likely / Unlikely Business DR Program Adopters by Strata
3.6. FINAL PARTICIPATION RATES FOR THE DR POTENTIAL STUDY
Based on the findings of the above described market research, the individual measure-level
participation rates that were used for estimating DR potential are summarized in Table 6 below.
Note that participation rates are expressed as a percentage of eligible customers (e.g. only
customers with central air-conditioning are eligible to participate in DLC).
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Table 6: Assumed Participation Rates in 2028
Segment
Residential
Residential
Residential
Residential
Residential
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
DR Measure
DLC - Single Family Homes
DLC - Multi-Dwelling Units
TOU
CPP
CPP w/Tech
DLC
Demand Bidding
TOU
CPP
CPP w/Tech
DLC
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Current
52%
0%
1%
0%
0%
15%
0%
2%
0%
0%
42%
6%
0%
0%
28%
0%
0%
46%
0%
0%
100%
0%
0%
Opt-in
Potential
66%
35%
24%
29%
32%
35%
10%
15%
19%
22%
53%
24%
27%
11%
16%
20%
22%
52%
54%
8%
100%
22%
25%
Opt-out
Potential
N/A
N/A
86%
90%
91%
N/A
N/A
73%
76%
79%
N/A
N/A
N/A
N/A
72%
79%
80%
N/A
N/A
N/A
100%
81%
86%
Notes:
Participation rates are expressed as % of eligible population
"Current" rates are projections for 2014
Existing programs ramp up to full participation over a two year period
New programs ramp up to full participation over a five year period
AMI deployment assumed to reach full market penetration in 2025
Time-varying rate options are first offered in 2025 and reach full participation by 2028
Large C&I TOU participation is mandatory and therefore always 100%
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4. NSP’s DR Potential
This section summarizes our DR potential estimates. It includes an overview of the results at the
measure-level and the portfolio-level, and an illustration of the DR supply curve. For additional
detailed information on our findings, see Appendix A. Annual impact tables are included in
Appendix E.
Before summarizing our DR potential estimates, it is important to emphasize that we did not
conduct a cost-benefit analysis of each DR option, as that evaluation will be performed through
NSP’s integrated resource planning process for traditional DR programs. Therefore, while the
DR potential estimates that we report are useful for understanding the magnitude of peak
reduction impacts that could be achieved if offering any of the DR options, these estimates
should not be interpreted as an indication of the DR potential that is economic for NSP’s service
territory.
4.1. MEASURE-LEVEL DR POTENTIAL
NSP’s existing DR programs currently provide roughly 997 MW of peak demand reduction
capability. Assuming a constant participation rate over our forecast horizon, this would grow to
1,054 MW by 2028 (roughly 10% of the system peak). We refer to this as the “current trends”
scenario. The impacts in 2028 are summarized by measure in Figure 6 below.
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Figure 6: Peak Reduction Capability in Existing Programs in 2028
Our study was designed to quantify the incremental peak reduction capability that could be
achieved above and beyond the impacts of the existing programs, as currently designed and
marketed. Among the traditional DR options, the largest incremental potential is in
Interruptible Tariffs for Medium and Large C&I customers. The results are summarized in Figure
7. Note that these estimates assume the DR options are offered in isolation – they do not account
for overlap in participation when the options are offered simultaneously as part of a portfolio (we
address that issue later in this report). Therefore, they are not additive. Additionally,
incremental potential in the price-triggered Interruptible option appears large because this form
of interruptible program is not currently offered by NSP; it would not be offered simultaneously
with a reliability-triggered Interruptible program.
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Figure 7: Peak Reduction Potential in all Traditional DR Options in 2028
It is interesting to compare the results for the price-based and reliability-based Interruptible
Tariff options. There appears to be more peak reduction potential in the price-based option (see
Figure 8 below). Our assumption is that the price-based option would include more frequent
interruptions, and in return for this added flexibility, it would offer an incentive payment that is
roughly 30% higher than the reliability-based option. The higher incentive payment attracts
more customers to the price-based program, and the possibility of a higher frequency of
interruptions does not appear to be a major deterrent. Advantages of the price-based
interruptible option are that it has better dispatch flexibility and larger potential. The
disadvantages are that it is more expensive and would require re-designing the existing program.
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Figure 8: Potential in the Two Interruptible Tariff Alternatives
AMI-enabled DR options represent significant additional potential, but would require that smart
meters be in place before they can be offered on a large scale. Technology-enabled CPP would
produce the largest impact, but is also the most expensive option due to the cost of the
automating technology. The small C&I segment is the only customer segment that has been
found in pricing pilots to be fairly un-responsive to time-varying rates in the absence of any
automating technology. Potential in opt-out rate offerings is significantly higher than in opt-in
rate offerings. This is because a much higher number of customers are likely to remain enrolled
in the new rates if they are defaulted on to them, rather than having to proactively enroll.
Results are summarized in Figure 9. These results assume the measures are offered independently
and are not additive.
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Figure 9: Peak Reduction Potential in All AMI-Enabled DR Options in 2028
4.2. PORTFOLIO-LEVEL DR POTENTIAL
The measure-level DR potential estimates reported above are not additive, because it would be
economically inefficient for NSP to allow customers to participate in multiple DR measures at
the same time. This would potentially result in participants being paid twice for the same peak
demand reduction. Therefore, we created four plausible portfolios of DR programs that account
for overlap in participation. The four portfolios are defined in Table 7 below.
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Table 7: The Four DR Portfolios
Porfolio Description
Comments
Portfolio #1
Voluntary traditional DR options only
Would not require broad metering infrastructure upgrade; essentially
an expansion of NSP's current DR offering
Portfolio #2
Voluntary traditional DR options
with opt-in revised TOU
Represents an expansion of NSP's current DR offering, plus a
redesign of the current TOU rate options
Portfolio #3
Voluntary traditional DR options
with opt-out revised TOU
Represents an emerging option being considered by several utilities;
the Sacramento Municipal Utility District (SMUD), the province of
Ontario, Canada, and Italy have all commited to opt-out TOU
Portfolio #4
Voluntary traditional DR options
with opt-out CPP & enabling tech
Represents a "prices-to-devices" environment in which customers
are equipped with technology that automates load reductions in
response to price changes; could potentially be used to integrate
renewables
Note: In Portfolios 2 and 3, the redesigned TOU is considered mandatory for all Large C&I customers, which would be
consistent with the way TOU rates are currently offered to this segment. For the purposes of this study, the interruptible
tariff included in each portfolio is reliability-triggered (rather than price-triggered)
Participation rates for the DR measures in each portfolio were derived from the primary market
research described in Section 3. Customer survey responses were used to determine which DR
program they would choose when presented with a menu of DR options. Participation
assumptions by portfolio are described in the appendix.
NSP’s existing DR programs – as currently designed - would have peak reduction capability of
1,054 MW by 2028 if participation grows only at the projected rate of customer growth over that
time horizon. The incremental potential in the four portfolios described above is incrementally
higher than this existing capability by between 371 MW and 899 MW, depending on the
portfolio. These impacts assume that AMI has been deployed (for portfolios 2, 3, and 4) and that
all of the measures in the portfolio are offered without consideration for cost-effectiveness.
Figure 10 summarizes the portfolio-level impacts by DR option.
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Figure 10: Portfolio Peak Reduction Potential by Type in 2028
Among the four portfolios, the one with the lowest potential is Portfolio 2. This result may
appear to be counter-intuitive, since Portfolio 2 includes all of the same DR measures as Portfolio
1, but also includes opt-in TOU rates. Including TOU in the portfolio of DR impacts actually
decreases the potential in this instance. When TOU is offered as a mutually exclusive option in a
portfolio, some of the customers who otherwise would have enrolled in a traditional DR option
like an interruptible tariff instead choose to enroll in the TOU rate. The TOU rate produces
significantly lower peak reductions per participant than the traditional DR options that we have
included and, in this case, the result is a lower estimate of total peak reduction potential than if
the TOU rate had not been offered. In practice, it would alternatively be possible to allow
customers to enroll in both the TOU rate and another DR option (e.g., the interruptible tariff). 8
That is how NSP’s programs are currently offered. In this scenario, the total potential impact
would be higher.
There is incremental growth potential in each customer segment. Figure 11 summarizes the DR
potential by segment.
8
This requires careful design the incentives and rates such that they do not compensate participants for
more than the value of the load reduction that they provide.
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Figure 11: Portfolio Peak Reduction Potential by Segment in 2028
4.3. THE DR SUPPLY CURVE
The DR potential estimates are combined with cost estimates to produce the DR supply curve
described in Section 2. The DR supply curve illustrates the rising incremental costs that are
associated with achieving increasingly larger DR impacts. Figure 12 shows the DR supply curve
for 2028. For illustrative purposes, we have identified on the curve the projected impact of
existing programs in 2028 relative to the total peak reduction capability that could potentially be
achieved under a cost of $90/kW-year (an avoided cost assumption commonly used to evaluate
the cost-effectiveness of DR programs). Data behind the annual supply curves is provided
separately as an electronic file.
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Figure 12: DR Supply Curve in 2028 (All Traditional DR Options)
It is important to consider additional benefits that are difficult to quantify within the framework
of an integrated resource planning process, but which certainly add to the overall attractiveness
of the DR measures. Qualitative factors such as these should be taken into consideration when
conducting a more detailed assessment of the benefits and costs of moving forward with a new
portfolio of DR offerings. Examples include:
•
More equitable retail rates. By providing a price signal that more accurately reflects the
cost of supplying electricity over the course of a day, time-varying pricing is more
equitable than a flat rate and reduces the cross-subsidization that currently exists
between customers with “peaky” or “flat” load shapes.
•
Possible environmental benefits. To the extent that the DR programs result in a net
reduction in energy consumption, there could be additional environmental benefits in
the form of reduced emissions. Some TOU rates have been found to have such a
conservation effect. Even in the absence of overall conservation, load shifting may lead
to a small reduction in emissions, although this will depend on the emissions rates of
marginal units during peak and off-peak hours. Further, time-varying rates (TOU rates in
particular) could facilitate the adoption of distributed resources like rooftop solar by
providing a price signal that improves the economics of investment in these technologies.
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•
Improved customer satisfaction. Providing customers with new DR services and
opportunities to reduce their electricity bills could enhance NSP’s reputation and
customer satisfaction rating.
•
Improved post-outage power restoration. After an outage, it is necessary to control the
rate at which power is restored in order to avoid over-stressing the system. Some load
control technologies have a feature which brings the controlled end-uses on in a
staggered fashion in order to “spread out” the ramping of load over time.
•
Improved distribution-level reliability. With knowledge of the geographical location of
program participants, DR programs can be dispatched to address local congestion issues
on the transmission or distribution system. For example, some utilities have used direct
load control to manage loads at specific substations and transformers that were at or near
capacity. This may be a particularly valuable aspect of DR in the future if NSP
experiences growth in electric vehicle adoption; direct control of charging would help to
manage potential reliability issues on the distribution system.
•
Integration of renewables. If the DR programs can be repurposed to provide ancillary
services, then they could provide additional value, particularly if intermittent sources of
generation are brought online in the future in quantities large enough to significantly
increase ancillary service market prices.
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5. Market and Policy Developments
Future market developments and policy initiatives could have significant implications for NSP’s
DR portfolio. Further research would be needed to quantify the likely impact of these
developments on the portfolio, but it is important to qualitatively understand the implications of
these new market and policy developments for NSP’s DR initiatives. In this section, we provide
a brief overview and discussion of some of the key developments that are on NSP’s horizon.
5.1. MARKET DEVELOPMENTS
NSP is a member of MISO, an independent system operator (ISO) that manages the grid for
several Midwestern and Southern states. ISOs can facilitate the adoption of DR by allowing it to
participate – and be compensated - as a resource in wholesale energy, capacity, and ancillary
services markets.
MISO offers multiple opportunities for DR to participate in its markets. One such program is
MISO’s Demand Response Resources (DRR) product. DRR is a supply-side program through
which load reductions are bid into the capacity market and are treated like generating capacity.
DR can participate in the capacity, energy, and ancillary services markets in this way. MISO also
offers a product called Load Modifying Resources (LMR), which is similar to DRR but with less
extensive requirements. LMR allows DR to be bid into the capacity market. Emergency
Demand Response (EDR) is a third product, and is a special initiative through which participants
are compensated for curtailments during NERC emergency events.
According to FERC’s 2013 Assessment of Demand Response and Advanced Metering, MISO’s
peak reduction capability in 2012 was 7.3% of the system peak, which is higher than the average
capability of 6% across all ISOs. 9 Virtually all of this DR capability is concentrated in MISO’s
capacity market. 10
Emerging factors may lead to expanded energy market participation in MISO in the future.
Rising electricity prices are one such consideration. Over the past several years there has been a
capacity surplus in the Midwest, keeping energy prices relatively low. However, as reserve
margins tighten due to either rising demand or coal plant retirements, energy prices could
increase and become more volatile, thus making the market more attractive for DR resources.
Renewables integration needs could also lead to increased DR penetration in energy and
ancillary services markets. As intermittent resources such as wind and solar come online in large
9
FERC, “2013 Assessment of Demand Response and Advanced Metering,” Staff Report, October 2013.
10
MISO Website (accessed November 25, 2013):
https://www.misoenergy.org/Library/Repository/Market%20Reports/Demand_Response_Participation
.pdf
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quantities, new flexible resources will be needed to maintain grid reliability. There is an
emerging interest in around-the-clock DR to help fill this need, with flexible load that would
rapidly decrease and increase in response to changing prices. 11
New opportunities for aggregators of retail customers (ARCs) could also expand DR participation
in all markets. Ongoing efforts to open the market to ARCs may lead to the introduction of new
retail program designs and more aggressive participant recruitment in the region.
Despite these emerging factors, however, it is important to recognize that energy market
participation is likely to continue to remain significantly lower than capacity market
participation. Experience in other regions with more mature energy market participation
suggests that capacity payments will continue to be the primary driver of DR. In these markets,
energy payments have provided enough financial benefit for some customers to participate, but
at a much lower level than in capacity markets. Figure 13 summarizes DR participation in
capacity, ancillary services, and energy markets in other regions. 12
Figure 13: DR Market Participation in Organized Wholesale Markets
In ERCOT, large
industrial customers
provide significant
amounts of
responsive
(spinning) reserve
Energy market
participation is
lower than capacity
market participation
in every region,
typically by very
significant margins
11
See, for example, EnerNOC Utility Solutions and The Brattle Group, “The Role of Demand Response
in Integrating Variable Energy Resources,” prepared for the Western Interstate Energy Board,
December 2013. http://www.westgov.org/sptsc/documents/12-20-13SPSC_EnerNOC.pdf
12
Totals do not include price-responsive loads not enrolled in RTO programs. For example, we estimate
that in ERCOT price-responsive loads may represent about of 1,000 MW of demand. Similarly,
distribution companies in Texas manage as much reliability DR as ERCOT itself.
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The reason that capacity markets have been the most attractive opportunities for DR can be
illustrated with a simple example. Consider a typical (or even slightly conservative) hypothetical
capacity market price of $50/kW-year. The typical number of hours of interruption in a DR
program is around 50 hours per year. So in this example, the hourly equivalent of the capacity
payment to DR participants is $1,000/MWh ($50 per kW-year / 50 hours per year = $1 per kWh
= $1,000 per MWh). Comparatively, the energy price would need to reach $1,000/MWh in 50
hours of the year in order to provide the equivalent annual financial incentive as a modest
capacity payment. It is likely that the incentives offered in these two markets will begin to
converge in coming years for the reasons described above, but it remains unlikely that incentives
to participate in energy markets will reach those of capacity markets.
5.2. POLICY INITIATIVES
Environmental policy could also affect the DR landscape in Minnesota. One such policy
initiative is the Environmental Protection Agency’s (EPA’s) 2010 Reciprocating Internal
Combustion Engines (RICE) National Emission Standards for Hazardous Air Pollutants
(NESHAP) Rule. The RICE NESHAP rule restricts the extent to which backup generators can
participate in emergency DR programs. At least one-third of MISO’s DR capability is estimated
to come from backup generation, and this figure was higher prior to the establishment of the
Rule. NSP estimates that it lost 20 MW of peak reduction capability due to the Rule in the
summer of 2013. Additional restrictions could further reduce the amount of DR that is provided
by backup generators, although in January 2013 the requirements were lessened to be more
flexible.
Other EPA emissions regulations – or a national CO2 policy – will lead to coal retirements in the
Midwest. A 2012 Brattle Group study projects that 17% to 24% of MISO’s coal capacity (9% to
13% of total capacity) could be retired as a result of new EPA regulations. 13 As discussed above,
coal retirements are likely to lead to tighter supply conditions, which could lead to an increased
need for DR.
In summary, factors such as rising electricity prices, renewable generation integration needs, coal
retirements, and expanded ARC participation could increase NSP’s DR market potential in the
future. Energy market participation, however, is likely to remain well below that of capacity
market participation. Policies that constrain the participation of backup generators as DR
resources could dampen the DR potential.
13
Metin Celebi, Frank Graves, and Charles Russell, “Potential Coal Plant Retirements: 2012 Update,”
The Brattle Group whitepaper, October 2012.
http://brattle.com/system/publications/pdfs/000/004/678/original/Potential_Coal_Plant_Retirements__2012_Update.pdf?1378772119
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6. Conclusions and Recommendations
Our study has utilized a detailed bottom-up approach to estimating NSP’s peak demand
reduction potential through DR programs. These estimates were carefully tailored to NSP’s
system conditions through primary market research on likely adoption rates, per-customer
impacts that are consistent with NSP’s experience from existing programs and pilots, and load
conditions that are consistent with utility projections. We have assessed the market potential for
a range of plausible DR portfolios that are differentiated both in the programs that they include
as well as the manner in which the programs are offered to customers.
We find that, by 2028, plausible portfolios of DR options could increase NSP’s peak reduction
capability from a little over 1,000 MW in current programs to between 1,425 MW and 1,952
MW in new programs (depending on the options included in the new portfolios). This is an
incremental increase of market potential between 371 MW and 899 MW. Our findings have led
us to a number of specific recommendations for NSP’s future DR activities (which may be further
refined through the integration of our results into the IRP process):
Consider modifying the interruptible program such that it is price-triggered (in addition to
reliability-triggered). This could allow for more frequent dispatch to address both reliability and
economic needs and, if combined with a higher incentive payment to account for more frequent
interruptions, could result in greater participation according to our market research.
Consider expanding the residential DLC program to include multi-dwelling units. The costeffectiveness of this expansion will need to be explored in further detail, as multi-family dwelling
units provide smaller peak reductions than the average single family home and can often include
additional installation costs.
Evaluate the opportunity for a demand bidding program. Customer interest in such a program
was modest based on market research, with around 10% of small/medium customers and 8% of
large customers being interested. However, under future scenarios with higher and more volatile
energy prices, the program could be a valuable addition to NSP’s DR portfolio. Participation by
small customers would require some form of aggregation/third party involvement.
Empirically evaluate dynamic pricing options through a pilot. In particular, given emerging
interest in around-the-clock DR, the pilot could focus on automated real-time price response that
could be a useful future resource for integrating renewables, which are rapidly emerging in the
Midwestern U.S.
Consider combining the DLC program with a critical peak pricing (CPP) rate or a peak time
rebate (PTR). Some utilities have offered a higher price-based financial incentive to customers
who are equipped with enabling technology in recognition of their higher degree of certainty in
price response.
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A redesign of the TOU rate would likely lead to increased enrollment. A reduced peak period
duration will lead to greater customer interest, according to market research. At high levels of
market penetration, though, the economics of a full-scale AMI deployment would need to be
revisited.
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Appendix A:
DR Potential Study Details
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Demand Response Potential in
Xcel Energy’s Northern States
Power (NSP) Service Territory
Final
PRESENTED TO
Xcel Energy
PRESENTED BY
Ahmad Faruqui
Ryan Hledik
January 10, 2014
Copyright © 2013 The Brattle Group, Inc.
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Our presentation is organized into five sections
1.
Executive Summary
2.
Minnesota’s DR Landscape
3.
Our Approach
4.
Our Findings
5.
Key Assumptions
Appendices
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Executive Summary
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Our purpose
  The purpose of this study is to:
 Quantify the potential peak demand reduction that could be achieved through an expanded portfolio of demand response (DR) options in NSP’s service territory, without cost considerations
 Identify future DR opportunities for NSP
  We considered 22 different programmatic DR options and segmented the market into four customer classes
 9 of the options are currently offered and 13 are possible new options
 10 are considered “traditional” DR options and 12 are AMI‐enabled options
  We also estimated program costs which, when combined with the peak reduction estimates, produce a “supply curve” of traditional DR resources that can be used as input to NSP’s integrated resource planning (IRP) process, which relies on the Strategist model
  This provides NSP with the data necessary to identify economically optimal DR investments through the IRP process
Note: Our DR potential estimates do not account for the cost-effectiveness
of the DR measures; this will be done through IRP modeling
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The DR options
  Currently offered options
▀
▀
▀
Direct load control (DLC): Participant’s central air‐conditioner is remotely cycled using a switch
Interruptible rates: Participants agree to reduce demand to a pre‐specified level and receive an incentive payment in the form of a discounted rate
Time‐of‐use (TOU) rates: NSP currently offers TOU rates, which are replaced in our analysis by re‐designed rates (see discussion below)
  Possible new options
▀
▀
▀
Demand bidding: Participants submit hourly curtailment schedules on a daily basis and, if the bids are accepted, must curtail the bid load amount to receive the bid incentive payment or may be subject to a non‐compliance penalty
Critical peak pricing (CPP) rates: Provides customers with a discounted rate during most hours of the year, and a much higher rate (typically between 50 cents/kWh and $1.00/kWh) during peak hours on up to 10 or 15 days per summer; can be offered with “enabling technology” which automates load reductions in response to the higher priced hours
Redesigned time‐of‐use (TOU) rates: Existing TOU rates were redesigned to be more manageable and targeted, with a shorter peak period and a revised peak‐to‐off‐peak price ratio
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Key assumptions
  Participation varies by customer segment; the range of potential participation rates among eligible customers is based on primary market research, which was conducted by YouGov as part of this study and is summarized in an accompanying presentation:
  Direct load control = 35% to 65%
  Interruptible rates = 25% to 50%
  Demand bidding = ~10%
  Redesigned time‐of‐use (TOU) rates
▀
▀
Opt‐in = 15% to 25%
Opt‐out = 70% to 85% (mandatory for large C&I)
  Critical peak pricing (CPP) rates
▀
▀
Opt in = 20% to 30%
Opt out = 75% to 90%
  Per‐customer peak demand impacts are derived from NSP program experience where available, and are otherwise based on similar programs offered by other utilities
Note: Participation rates represent enrollment if DR options were offered in isolation; since simultaneous enrollment in multiple programs would not be allowed, participation rates are adjusted downward when calculating the peak reduction potential for a portfolio of options to avoid double‐counting
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Key findings
  NSP’s existing DR portfolio is substantial
▀
▀
In its existing DR programs, NSP currently has the capability to reduce peak demand by 997 MW, or 10.9% of its system peak
If participation rates remain constant, this could grow slightly in absolute terms to 1,054 MW (10.4% of peak) by 2028
  There is some room for incremental growth through traditional DR programs (DLC, Interruptible Tariffs, Demand Bidding) ▀
An expanded portfolio of traditional programs could reduce peak by 1,455 MW (14.4% of peak) by 2028, an incremental increase of 401 MW
  AMI‐enabled programs, while not technically feasible in the short run with existing technology, could further increase DR potential within the next decade
▀
▀
Including a redesigned time‐of‐use rate in the above portfolio for all customers would increase potential to 1,528 MW (15.1% of peak)
Alternatively, including a critical peak pricing (CPP) rate with automating technology for all customers could increase potential impacts to 1,952 MW (19.3% of peak)
Note: All reported peak impacts are coincident with NSP’s system peak
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Key findings (concluded)
  DR potential is sensitive to the participation incentive that is being offered
▀
▀
▀
For each DR option, we estimated likely enrollment at five different price points representing a reasonable range of marginal costs that could be observed over the forecast horizon
If current incentive payments were dropped to the low end of the plausible range, participation in the programs would decrease by between 10% and 30%
Increasing the incentive payments to the high end of the range could result in increases in participation of between 10% and 50%, depending on the DR option
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Recommendations for current program offerings
  Consider modifying the interruptible program such that it is price‐
triggered (in addition to reliability‐triggered). This could allow for more frequent dispatch to address both reliability and economic needs and, if combined with a higher incentive payment to account for more frequent interruptions, could result in greater participation according to our market research
  Consider expanding the residential DLC program to include multi‐dwelling units. The cost‐effectiveness of this expansion will need to be explored in further detail, as multi‐family dwelling units provide smaller peak reductions than the average single family home and can often include additional installation costs
  Evaluate the opportunity for a demand bidding program. Customer interest in such a program was modest based on market research, with around 10% of small/medium customers and 8% of large customers interested. However, under future scenarios with higher and more volatile energy prices, the program could be a valuable addition to NSP’s DR portfolio. Participation by small customers would require some form of aggregation/third party involvement
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Recommendations for new program offerings
  Empirically evaluate dynamic pricing options through a pilot. In particular, given emerging interest in around‐the‐clock price response, the pilot could focus on automated real‐time price response that could be a useful future resource for integrating renewables, which are rapidly emerging in the Midwestern U.S.
  Consider combining the DLC program with a critical peak pricing (CPP) rate or a peak time rebate (PTR). Some utilities have offered a higher price‐based financial incentive to customers who are equipped with enabling technology in recognition of their higher degree of certainty in price response
  A redesign of the TOU rate would likely lead to increased enrollment.
A reduced peak period duration will lead to greater customer interest, according to market research; at high levels of market penetration, though, the economics of a full‐scale AMI deployment would need to be revisited
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Minnesota's
DR Landscape
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Minnesota’s DR landscape is influenced by its
membership in MISO
NSP is a member of MISO, an
independent system operator
that manages the grid for
several Midwestern and
Southern states
ISOs can facilitate DR
adoption by allowing it to
participate as a resource in
wholesale energy, capacity,
and ancillary services markets
Source: ISO/RTO Council
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MISO offers multiple opportunities for DR to
participate as a resource in wholesale markets
  MISO program offerings include…
  Demand Response Resources (DRR)
▀ A supply‐side program through which load reductions are bid into the market and are treated like generating capacity
▀ Can participate in the capacity, energy, and ancillary services markets
  Load Modifying Resources (LMR)
▀ Similar to DRR, but with less extensive requirements
▀ Can include utility DLC programs, interruptible tariffs, and behind‐the‐
meter generation (BTMG)
▀ Can participate in the capacity market
  Emergency Demand Response (EDR)
▀ A special initiative through which participants are compensated for curtailments during NERC emergency events
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DR can reduce MISO’s peak by roughly 7%, but
virtually all of this is in the capacity market
While MISO has significant overall peak
reduction capability…
Source: FERC, Assessment of Demand Response & Advanced Metering, October 2013.
Xcel Energy Northern States Power Service Territory
… it is virtually all concentrated in the
capacity market
Source: MISO Website:
https://www.misoenergy.org/Library/Repository/Market%20Reports/Demand_Response_
Participation.pdf, accessed November 25, 2013
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Emerging market factors may lead to expanded
DR participation in MISO in the future
▀
Rising electricity prices: Over the past several years there has been a capacity surplus in the Midwest; as reserve margins tighten due to rising demand or coal plant retirements, energy prices could increase and become more volatile, thus making the market more attractive for DR resources
▀
Renewables integration needs: As intermittent resources such as wind and solar come online in large quantities, new flexible resources will be needed to maintain grid reliability; there is an emerging interest in around‐the‐clock DR to help fill this need and the result would be increased participation in ancillary services markets
▀
New opportunities for Aggregators: Ongoing efforts to open the market to Aggregators of Retail Customers (ARCs) may lead to the introduction of new retail program designs and more aggressive participant recruitment in the region
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However, DR energy market participation is likely to
continue to be lower than capacity market participation
  Experience in other regions with more mature energy market participation suggests that capacity payments will continue to be the primary driver of DR
  Energy payments have provided enough financial benefit for some customers to participate, but at a much lower level
  It is easy to understand this dynamic with a simple example:
▀ Typical capacity market price (illustrative) = $50 per kW‐year
▀ Typical number of hours of DR interruption per year = 50 hours
▀ Hourly equivalent of capacity market payment = $50 per kW‐year / 50 hours per year = $1 per kWh = $1,000 per MWh
▀ So the energy price has to reach $1,000/MWh in 50 hours of the year in order to provide the same annual financial incentive as a modest capacity payment
  Capacity vs. energy market participation observed in other regions reflects this relationship and is summarized on the following slide
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Experience in other regions shows that DR
participation is concentrated in capacity markets
Capacity market
participation
estimates to not align
perfectly with
estimates on slide 13
due to differences in
vintage of available
data
In ERCOT, large
industrial customers
provide significant
amounts of
responsive
(spinning) reserve
Energy market
participation is
lower than capacity
market participation
in every region,
typically by very
significant margins
Note: Totals do not include price-responsive loads not enrolled in RTO programs. For example, we
estimate that in ERCOT price-responsive loads may represent about of 1,000 MW of demand.
Similarly, distribution companies in Texas manage as much reliability DR as ERCOT itself.
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Environmental policy could also affect the DR
landscape in Minnesota
  EPA’s 2010 RICE standard limits use of backup generation as DR
▀
▀
▀
At least one‐third of MISO’s DR is from backup generation
NSP estimates a current loss of 20 MW of DR capability due to the rule
Additional restrictions could further reduce the amount of DR that is provided by backup generators (although in January 2013 the requirements were lessened to be more flexible)
  EPA emissions regulations – or a national CO2 policy – will lead to new coal retirements in the Midwest
▀
▀
The ISO/RTO Council projects that 17 to 24% of MISO’s coal capacity (8 to 11% of total capacity) could be retired as a result of new EPA regulations
Tighter supply conditions could lead to an increased need for DR
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Our Approach
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Our approach addresses several limitations in
NSP’s previous (2012) DR potential study
  New features of our study include:
▀
▀
▀
▀
▀
Development of a “DR Supply Curve” that can be used as input to NSP’s integrated resource planning process to identify economically optimal DR investments for traditional DR options
Primary market research to establish participation estimates that are tailored to NSP’s customer base
New portfolio definitions that more closely align with the types of offerings that NSP could provide in the future New customer class definitions that more closely align with logical market segmentations (e.g. all large customers have interval meters)
Estimates of existing per‐customer impacts that more closely align with actual program experience
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We estimated DR potential for four market
segments
  Residential
▀
All residential accounts
  Small Commercial & Industrial (C&I)
▀
Less than 25 kW of demand
  Medium C&I
▀
25 kW to 1,000 kW of demand
  Large C&I
▀
▀
More than 1,000 kW of demand
All customers in this segment have interval meters
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We analyzed 22 programmatic options
Residential
Small C&I
Medium C&I
X
X
X
Large C&I
Traditional DR Options
Direct load control (Central A/C)
Interruptible tariff (reliability‐based)
X
X
Interruptible tariff (price‐based)
X
X
X
X
X
Demand bidding
AMI‐enabled Rate Options
Revised time‐of‐use (TOU) pricing
X
X
X
X
Critical peak pricing (CPP)
X
X
X
X
CPP with enabling technology
X
X
X
X
Notes:
Shading indicates DR option is already offered by NSP
TOU w/tech is not included as an option, because TOU does not have a "dispatchable" price signal like CPP
Residential DLC is divided into two measures ‐ one for single‐family homes (SFH) and one for multi‐dwelling units (MDU)
Interruptible (reliability) is structured like NSP's current program
Interruptible (price) is price‐triggered, with more interruptions and a different (higher) incentive structure
The following slides describe these DR options in detail
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The DR measures were selected in close
collaboration with NSP
  Brattle and NSP reviewed a comprehensive list of DR options and identified new program offerings that could potentially be offered
  The selected DR options are an improvement over the options included in the previous (2012) DR study
▀ We assess two different types of Interruptible Tariff programs, to test customer interest in reliability‐triggered versus price‐triggered options
▀ We quantitatively assess a Demand Bidding option for all commercial and industrial customers, as there is emerging interest in the ability of DR to participate in MISO markets
▀ We consider a redesign of NSP’s TOU rate, to test market acceptance of different rate designs
▀ We examine an expanded DLC program
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The direct load control (DLC) option
  NSP’s Savers Switch program is a DLC option
  In the direct load control program, the participant’s central air‐
conditioner (CAC) is remotely cycled using a switch
  Participants are given an incentive payment during summer months
▀
▀
15% average monthly bill discount for residential (roughly $10 to $15 per summer month for typical customer)
$5 per ton of A/C per month for business (average of all NSP participants)
  We model separate programs for single family homes (SFH) and multi‐dwelling units (MDU); the latter is not currently offered
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The interruptible tariff option
  We modeled two different interruptible tariff options for Medium and Large C&I customers
  Option 1: Reliability‐triggered
▀
▀
▀
This is NSP’s Electric Rate Savings Plan
Customers agree to reduce demand to a pre‐specified level and receive an incentive payment in the form of a discounted rate, which varies with the load curtailment level and control type
The program is triggered for extreme reliability events
  Option 2: Price‐triggered
▀
▀
▀
Similar to option 1, but the program is triggered by high wholesale prices and likely to be called more frequently
In return for agreeing to the possibility of more frequent interruptions, customers receive larger incentive payments
The program can be utilized for both reliability and economic purposes
  A price–triggered option and a reliability‐triggered option could be offered as two separate programs, although it would likely be more efficient to offer a single program that is triggered by both reliability events and price conditions
Note: NSP’s ERS program has a price-triggered option but only a few customers are currently enrolled
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The demand bidding option
  This type of program is not currently offered by NSP
  Participants submit hourly curtailment schedules on a daily basis
  NSP “clears” the market based on wholesale energy prices and informs bidders as to whether their bid was accepted, and at what price
  Participants must curtail the bid load amount to receive the bid incentive payment, or otherwise may be subject to a non‐compliance penalty (i.e. the cost of replacement power)
  We modeled this program for Medium and Large C&I, and have also considered Small C&I as they could potentially participate through an Aggregator
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The redesigned time-of-use (TOU) pricing option
  TOU rates are currently offered to all customer classes and are mandatory for Large C&I customers
  NSP’s current TOU rates have a long peak period (9 am to 9 pm) with peak‐to‐off‐peak price ratios that are higher for residential customers than for C&I customers
  We tested a redesigned TOU rate with customer‐friendly features such as a 6‐hour peak period and a peak‐to‐off‐peak price ratio that is consistent with rates being offered in other jurisdictions (based on a review of more than 160 rate offerings)
  The redesigned TOU rate is modeled for all customer segments
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The critical peak pricing (CPP) option
  CPP rates are not currently offered by NSP
  A CPP rate provides customers with a discounted rate during most hours of the year, and a much higher rate (typically between 50 cents/kWh and $1.00/kWh) during peak hours on up to 10 or 15 days per summer
  Critical peak events are called in response to high market prices or reliability concerns; participants are given day‐ahead notification
  We modeled a CPP rate with an 8‐to‐1 price ratio (including fuel costs) for all customer classes, based on a review of CPP rates in other jurisdictions
  We also included an option in which customers would be equipped with “enabling technology” that would automate load reductions for certain end uses during critical events (e.g. a programmable communicating thermostat for residential customers)
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Our study estimates “market potential” but does
not account for cost-effectiveness
  “Market potential” is the potential impact of DR on peak demand if participation reaches achievable levels identified through primary market research
  An estimate of market potential was developed for each DR measure   The measures were not screened for cost‐effectiveness; this will be done by NSP in its IRP modeling
  Two “flavors” of market potential are estimated for dynamic pricing measures (see next slide)
  All other DR measures assume opt‐in deployment
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There are two types of time-varying rate
deployment
  The two variations are based on different assumptions about the manner in which the pricing programs (TOU and CPP) are offered to customers
  Opt‐in participation assumes that customers would remain on the currently existing rate and would need to proactively enroll in the time‐varying rate (typically expected to result in 5% to 25% enrollment)
  Opt‐out participation assumes that customers are automatically enrolled in a time‐varying rate with the option to revert back to the otherwise applicable tariff (typically expected to result in 50% to 90% enrollment)
  Opt‐out deployment of dynamic pricing for residential customers is currently uncommon, although TOU rates have been rolled out on an opt‐
out basis across the province of Ontario, Canada and in the entire country of Italy , and peak time rebates been offered on an opt‐out basis in San Diego and in Maryland and will soon be offered in Washington, D.C.
  Note: The revised TOU is modeled as being offered on a mandatory basis for Large C&I customers, since that is NSP’s current practice
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DR potential is estimated using the following
fundamental equation
Potential DR
Impact
=
Total Demand of X
Customer Base
% of Base Eligible to Participate
X
% of Eligible Customers Participating
X
% Reduction in demand per participant
  Data and assumptions:
▀
Market characteristics and program costs were provided by NSP
▀
When available, we rely on per‐customer impacts based on actual NSP program experience and research; in the case of dynamic pricing, we simulate impacts using a library of recent dynamic pricing pilot results
▀
Participation rates are based on the findings of primary market research in NSP’s service territory
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The potential estimates do not account for costeffectiveness of the DR options
  We have estimated the peak reduction potential for each DR option that was determined to be of interest for this study
  However, we do not conduct a cost‐benefit analysis of these programmatic options, as that evaluation will be performed through NSP’s integrated resource planning process
  Therefore, while the DR potential estimates that we report in the following slides are useful for understanding the magnitude of peak reduction impacts that could be achieved if offering any of the DR options, these estimates should not be interpreted as an indication of the DR potential that is economic for NSP’s service territory
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Our Findings
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Existing programs – with little assumed future growth – will provide
slightly over 1,000 MW of peak reduction capability (~10% of peak)
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The largest incremental market potential in traditional DR options is
in Interruptible programs for Medium/Large C&I
Comments
▀
▀
▀
Xcel Energy Northern States Power Service Territory
Estimates assume measures are offered in isolation and do not account for participation overlap when offered simultaneously as part of a portfolio
Incremental potential in the price‐triggered Interruptible option is large because this form of interruptible program is not currently offered by NSP; it would not be offered simultaneously with a reliability‐triggered Interruptible program
These numbers are not additive
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Among the two interruptible pricing alternatives, the
price-based option has more peak reduction potential
Comments
▀
▀
▀
▀
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A larger number of customers is likely to enroll in the price‐based program due to the higher incentive payment
Advantages of the price‐
based interruptible option are that it has better dispatch flexibility and larger potential
The disadvantages of the price‐based option are that it is more expensive and would require re‐
designing the program
Its cost‐effectiveness should be explored further
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AMI-enabled options represent significant additional
potential, but would require smart meters
Comments
▀
▀
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With the exception of Large C&I customers, who all already have interval meters, these rate options would require a meter upgrade for participants in other segments
The impact of existing TOU rates on peak demand is already accounted for in the load forecast; TOU impacts presented here are for a redesigned rate and are incremental to any existing impacts
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We also assessed DR potential at the portfolio
level
  The measure‐level potential estimates on the previous slides are not additive, because customers would not be allowed to participate in multiple DR measures at the same time
  This would result in NSP double‐paying for the same peak demand reduction
  Therefore, we created four portfolios of DR programs that account for overlap in participation
  The portfolios are designed to represent plausible future DR program offerings; they are defined on the next slide
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The four DR portfolios represent a range of
programmatic offerings
Porfolio Description
Comments
Portfolio #1
Voluntary traditional DR options only
Would not require broad metering infrastructure upgrade; essentially an expansion of NSP's current DR offering
Portfolio #2
Voluntary traditional DR options with opt‐in revised TOU
Represents an expansion of NSP's current DR offering, plus a redesign of the current TOU rate options
Portfolio #3
Voluntary traditional DR options with opt‐out revised TOU
Represents an emerging option being considered by several utilities; the Sacramento Municipal Utility District (SMUD), the province of Ontario, Canada, and Italy have all commited to opt‐out TOU
Voluntary traditional DR options with opt‐out CPP & enabling tech
Represents a "prices‐to‐devices" environment in which customers are equipped with technology that automates load reductions in response to price changes; could potentially be used to integrate renewables
Portfolio #4
Note: In Portfolios 2 and 3, the redesigned TOU is considered mandatory for all Large C&I customers, which would be
consistent with the way TOU rates are currently offered to this segment. For the purposes of this study, the interruptible
tariff included in each portfolio is reliability‐triggered (rather than price‐triggered)
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Portfolio 1 assumes opt-in traditional DR programs
and no new AMI-enabled programs
Residential Participation
Non‐
Participant
59.3%
Small C&I Participation
DLC
8.0% (Current)
7.9% DLC
DLC‐SFH (Current)
30.7%
(New)
3.2%
DLC‐SFH (New)
Demand Bidding
(New)
Non‐Participant
5.9%
80.8%
4.2% DLC‐MDU (New)
Medium C&I Participation
DLC
16% (Current)
Large C&I Participation
6% Interruptible 66%
Non‐
Participant
‐ Reliability
(Current)
DLC
2%(New)
Non‐
Participant Interruptible ‐ Reliability
43%
(Current)
8%
Interruptible ‐ Reliability (New)
11% Demand Bidding
(New)
45%
Demand Bidding
(New) 8%
Interruptible 4% ‐ Reliability (New)
Note: The charts represent participation as % of class load. All participation rates are shown for the year 2028.
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Portfolio 2 assumes opt-in traditional DR programs as
well as opt-in redesigned TOU
Small C&I Participation
DLC
8.0% (Current)
Residential Participation
Non‐
Participant
44.3%
6.6% DLC
DLC‐SFH (Current)
(New)
2.1%
30.7%
Demand Bidding
(New)
DLC‐SFH (New)
Non‐Participant
4.2%
Opt‐in
TOU (New)
DLC‐MDU 16.9%
7.3%
75.9%
Opt‐in TOU (New)
3.8% (New)
Note: TOU participation estimate only reflects enrollment in the redesigned TOU rate
Note: TOU participation estimate only reflects enrollment in the redesigned TOU rate
DLC
Medium C&I Participation 16%
(Current)
Large C&I Participation
6% Interruptible ‐ Reliability
(Current)
2% DLC
(New)
60%
7%
Non‐
Participant
Interruptible ‐ Reliability (New)
8% Demand Note: TOU participation estimate only reflects enrollment in the redesigned TOU rate
Opt‐in 10% TOU
(New)
Bidding
(New)
Opt‐in
TOU (New)
11%
Demand Bidding
(New) 6%
Non‐
Interruptible Participant
‐ Reliability
35%
(Current)
45%
Interruptible ‐ Reliability 3% (New)
Note: TOU participation estimate only reflects enrollment in the redesigned TOU rate
Note: The charts represent participation as % of class load. All participation rates are shown for the year 2028.
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Portfolio 3 assumes opt-in traditional DR programs as
well as opt-out redesigned TOU
DLC
Small C&I Participation
8.0% (Current)
Residential Participation
8.9%
Non‐
Participant
DLC‐SFH (Current)
Opt‐out
TOU (New)
52.4%
6.6% DLC
Non‐
Participant
(New)
2.1%
22.8%
30.7%
DLC‐SFH (New)
Opt‐out
TOU (New)
4.2%
DLC‐MDU Demand Bidding
(New)
60.4%
3.8% (New)
Medium C&I Participation 16% DLC
Large C&I Participation
(Current)
6% Interruptible Non‐
Participant
19%
‐ Reliability
(Current)
2%
Opt‐out
TOU (New)
DLC
(New)
7%
44%
Opt‐out
TOU (New)
Interruptible ‐ Reliability (New)
8% Demand Bidding
(New)
46%
Demand Bidding
(New) 6%
Interruptible ‐ Reliability
(Current)
45%
Interruptible ‐ Reliability 3% (New)
Note: The charts represent participation as % of class load. All participation rates are shown for the year 2028.
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Portfolio 4 assumes opt-in traditional DR programs and
opt-out CPP with enabling technology
Small C&I Participation
DLC
(Current)
8.0%
Non‐
Residential Participation
Non‐ 5.0%
Participant
6.6% DLC
Participant
Opt‐Out CPP/tech
(New)
56.3%
(New)
14.4%
DLC‐SFH (Current)
2.1%
30.7%
DLC‐SFH (New)
Opt‐Out CPP/tech
(New)
4.2%
DLC‐MDU Demand Bidding
(New)
68.8%
3.8% (New)
DLC
Medium C&I Participation 16%
(Current)
Non‐
Participant
12%
6% Interruptible ‐ Reliability
(Current)
2% DLC
(New)
50%
Opt‐Out CPP/tech (New)
7%
Interruptible ‐ Reliability (New)
8% Demand Bidding
(New)
Large C&I Participation
Non‐
6%
Participant
Opt‐Out CPP/tech (New)
Demand Bidding
(New) 6%
40%
Interruptible ‐ Reliability
(Current)
45%
Interruptible ‐ Reliability 3% (New)
Note: The charts represent participation as % of class load. All participation rates are shown for the year 2028.
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The portfolios represent incremental potential of
between 401 and 899 MW
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There is incremental growth potential in each
customer segment
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Portfolio impacts range from 14.1% to 19.3% by
2028 (an incremental increase of 3.7% to 8.9%)
Comments
▀
▀
Xcel Energy Northern States Power Service Territory
When TOU pricing is introduced in Portfolio #2, DR impacts decrease slightly; this is because some customers that would otherwise participate in a non‐rate program instead choose the revised TOU rate, and their peak reductions are smaller in response to the revised TOU rate than in response to the non‐rate option
Rate options are assumed not to be offered until 2025, as this is the earliest that AMI would be deployed by NSP (except for Large C&I, where the necessary metering technology is already in place)
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The DR potential estimates were used to establish
a DR supply curve
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There are benefits of DR options that will not likely be quantitatively
captured in the IRP process, but should still be considered
▀
More accurate pricing signals provide more equitable cost allocation
▀
Possible environmental benefits
▀
Improved customer satisfaction
▀
Improved post‐outage power restoration
▀
Improved distribution‐level reliability
▀
Support for more reliable integration of renewables
▀
Option value
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Recommendations for current program offerings
  Consider modifying the interruptible program such that it is price‐
triggered (in addition to reliability‐triggered). This could allow for more frequent dispatch to address both reliability and economic needs and, if combined with a higher incentive payment to account for more frequent interruptions, could result in greater participation according to our market research
  Consider expanding the residential DLC program to include multi‐dwelling units. The cost‐effectiveness of this expansion will need to be explored in further detail, as multi‐family dwelling units provide smaller peak reductions than the average single family home and can often include additional installation costs
  Evaluate the opportunity for a demand bidding program. Customer interest in such a program was modest based on market research, with around 10% of small/medium customers and 8% of large customers interested. However, under future scenarios with higher and more volatile energy prices, the program could be a valuable addition to NSP’s DR portfolio. Participation by small customers would require some form of aggregation/third party involvement
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Recommendations for new program offerings
  Empirically evaluate dynamic pricing options through a pilot. In particular, given emerging interest in around‐the‐clock price response, the pilot could focus on automated real‐time price response that could be a useful future resource for integrating renewables, which are rapidly emerging in the Midwestern U.S.
  Consider combining the DLC program with a critical peak pricing (CPP) rate or a peak time rebate (PTR). Some utilities have offered a higher price‐based financial incentive to customers who are equipped with enabling technology in recognition of their higher degree of certainty in price response
  A redesign of the TOU rate would likely lead to increased enrollment.
A reduced peak period duration will lead to greater customer interest, according to market research; at high levels of market penetration, though, the economics of a full‐scale AMI deployment would need to be revisited
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Key Assumptions
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Participation rates are based on primary market
research
Assumed Participation Rates by 2028 (% of Eligible)
Segment
Residential
Residential
Residential
Residential
Residential
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
DR Measure
DLC ‐ Single Family Homes
DLC ‐ Multi‐Dwelling Units
TOU
CPP
CPP w/Tech
DLC
Demand Bidding
TOU
CPP
CPP w/Tech
DLC
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
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Current
52%
0%
1%
0%
0%
15%
0%
2%
0%
0%
42%
6%
0%
0%
28%
0%
0%
46%
0%
0%
100%
0%
0%
Opt‐in Potential
66%
35%
24%
29%
32%
35%
10%
15%
19%
22%
53%
24%
27%
11%
16%
20%
22%
52%
54%
8%
100%
22%
25%
Opt‐out Potential
N/A
N/A
86%
90%
91%
N/A
N/A
73%
76%
79%
N/A
N/A
N/A
N/A
72%
79%
80%
N/A
N/A
N/A
100%
81%
86%
Notes
▀
▀
▀
▀
▀
▀
▀
Participation rates are expressed as % of eligible population
"Current" rates are projections for 2014
Existing programs ramp up to full participation over a two year period
New programs ramp up to full participation over a five year period
AMI deployment assumed to reach full market penetration in 2025
Time‐varying rate options are first offered in 2025 and reach full participation by 2028
Large C&I TOU participation is mandatory and therefore always 100%; the opt‐in scenario measures the potential if Large C&I customers were offered two rates – the existing TOU and a redesigned TOU
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Per-customer impacts are based on experience
with NSP programs when available
Segment
Residential
Residential
Residential
Residential
Residential
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
DR Measure
DLC ‐ Single Family Homes
DLC ‐ Multi‐Dwelling Units
TOU
CPP
CPP w/Tech
DLC
Demand Bidding
TOU
CPP
CPP w/Tech
DLC
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Per‐customer impact
0.62 kW, based on Savers Switch program
0.47 kW, assuming smaller impact than SFH
0.2 kW (7.4% of avg customer peak), simulated based on pilot results
0.3 kW (14.8% of avg customer peak), simulated based on pilot results
0.5 kW (23% of avg customer peak), simulated based on pilot results
1.9 kW, based on Savers Switch program
0.02 kW (0.6% of avg customer peak), simulated based on pilot results
0.01 kW (0.3% of avg customer peak), simulated based on pilot results
0.02 kW (0.7% of avg customer peak), simulated based on pilot results
0.21 kW (8.2% of avg customer peak), simulated based on pilot results
3.9 kW, based on Savers Switch program
132.6 kW, based on Electric Rate Savings Plan results
132.6 kW, based on Electric Rate Savings Plan results
7.1 kW (8.1% of avg customer peak), simulated based on pilot results
3.7 kW (4.2% of avg customer peak), simulated based on pilot results
7.6 kW (8.7% of avg customer peak), simulated based on pilot results
9.6 kW (10.9% of avg customer peak), simulated based on pilot results
1295.6 kW, based on Electric Rate Savings Plan results
1295.6 kW, based on Electric Rate Savings Plan results
270.1 kW (9.2% of avg customer peak), simulated based on pilot results
143.1 kW (4.9% of avg customer peak), simulated based on pilot results
291.5 kW (10% of avg customer peak), simulated based on pilot results
406.1 kW (13.9% of avg customer peak), simulated based on pilot results
Notes:
Per‐customer impacts for time‐varying rate options are based on opt‐in deployment
Per‐customer impacts are lower for opt‐out deployments
See appendix for description of time‐varying rates impact simulation
Demand bidding impacts simulated using results of dynamic pricing pilots & benchmarked to programs in other jurisdictions
Medium C&I Interruptible impacts for new participants are established such that long run average per‐customer impacts trend toward
the average Interruptible Tariff impact observed in FERC's 2012 Assessment of Demand Response and Advanced Metering
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A range of incentives were analyzed in order to
establish the DR supply curve
Incentives Tested in Supply Curve Development
DLC
($/kW‐year)
Reliability‐based Interruptible
($/kW‐year)
Price‐based Interruptible
($/kW‐year)
Demand Bidding
($/MWh)
Revised TOU
(price ratio)
CPP
(price ratio)
Very low
30
30
55
100
1.5
4.0
Low
55
55
80
300
2.0
6.0
Mid
85
85
110
500
3.0
8.0
High
110
110
135
750
4.0
10.0
Very High
150
150
175
1,000
5.0
12.0
▀
▀
▀
Incentive levels were established in coordination with NSP staff
They represent a plausible range of incentives based on avoided costs under a variety of possible system conditions
Note that TOU and CPP were not included in the supply curve; the range of price ratios was used to test customer sensitivity to the rate design
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Additional program costs were included when
developing the supply curves
Program Costs
Source
Residential
DLC ‐ SFH
$150/participant ‐ equipment
$80/participant ‐ marketing and admin
$12/participant/year ‐ O&M and admin
Based on Saver's Switch program costs
Residential
DLC ‐ MDU
$200/participant ‐ equipment
$65/participant ‐ marketing and admin
$12/participant/year ‐ O&M and admin
Hypothetical costs developed by NSP
DLC
$150/participant ‐ equipment
$80/participant ‐ marketing and admin
$12/participant/year ‐ O&M and admin
Assumed equal to residential Saver's Switch program costs
Medium C&I
DLC
$300/participant ‐ equipment
$80/participant ‐ marketing and admin
$12/participant/year ‐ O&M and admin
Assumed equal to residential Saver's Switch program costs, but with 2x equipment cost (impacts suggest more than one A/C unit)
Small C&I
Demand Bidding
$620,000/year marketing and admin
Small C&I allocation of annual Business Saver's Switch marketing & admin cost, based on kW participation (used as proxy for demand bidding)
Medium C&I
Demand Bidding
$240,000/year marketing and admin
Medium C&I allocation of annual Electric Rate Savings marketing & admin cost, based on kW participation (used as proxy for demand bidding)
Large C&I
Demand Bidding
$270,000/year marketing and admin
Large C&I allocation of annual Electric Rate Savings marketing & admin cost, based on kW participation (used as proxy for demand bidding)
Medium C&I
Interruptible
$240,000/year marketing and admin
Medium C&I allocation of annual Electric Rate Savings marketing & admin cost, based on kW participation
Large C&I
Interruptible
$270,000/year marketing and admin
Medium C&I allocation of annual Electric Rate Savings marketing & admin cost, based on kW participation
Small C&I
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Eligibility for certain DR options is determined by
end-use ownership
  Customers must have central air‐conditioning in order to participate in the DLC program
▀
▀
▀
Residential ownership = 79%
Small C&I ownership = 47% (est. through market research)
Medium C&I ownership = 39% (est. through market research)
  Similarly, central air‐conditioning ownership is a pre‐requisite to qualify for enabling technologies for residential, small, and medium C&I customers; for Large C&I, the customers must be able to use Auto‐DR technology
▀
Large C&I Auto‐DR eligibility = 40% (assumption consistent with FERC National DR Potential Assessment)
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Presentation
Appendix A:
Estimating Impacts of
Time-Varying Rates
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Impacts of time-varying rates were simulated
using pilot results
  Due to limited experience with dynamic pricing in NSP’s service territory, we could not rely on existing programs to estimate per‐customer peak reductions
  Instead, for residential customers, we rely on results from more than 160 pricing tests that have been conducted in the U.S. and internationally
  Small and Medium C&I impacts are based on results of a dynamic pricing pilot in California
  Large C&I impacts are based on experience with full‐scale programs in the Northeastern U.S.
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To estimate residential impacts, we begin with a
survey of impacts from recent pilots
Results of All Residential Time‐Varying Pricing Tests
60%
Peak Reduction
50%
40%
30%
20%
10%
0%
1
2
3
4
Note: Chart includes 92 data points
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5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21
Peak to Off‐Peak Price Ratio
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To estimate impacts of the revised TOU, we
focus only on those pilots which tested TOU rates
Results of Residential TOU Pricing Tests
60%
Peak Reduction
50%
40%
30%
20%
10%
0%
1
Note: Chart includes 42 data points
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2
3
4
5
6
7
Peak to Off‐Peak Price Ratio
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We then fit a curve to the data to capture the
relationship between price ratio and impacts
Results of Residential TOU Pricing Tests with Arc
60%
TOU Only Arc
Price only TOU data points
Peak Reduction
50%
40%
30%
20%
10%
0%
1
Note: Chart includes 42 data points
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2
3
4
5
6
7
Peak to Off‐Peak Price Ratio
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We use the arc to simulate the impact of the
redesigned residential TOU rate for our study
Results of Residential TOU Pricing Tests with Arc
60%
TOU Only Arc
Price only TOU data points
Peak Reduction
50%
40%
Residential TOU impact at 3‐to‐1 price ratio = 7.4%
30%
20%
10%
0%
1
Note: Chart includes 42 data points
Xcel Energy Northern States Power Service Territory
2
3
4
5
6
7
Peak to Off‐Peak Price Ratio
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A similar approach was used to estimate CPP
impacts
Results of Residential CPP Pricing Tests with Arc
60%
PTR, CPP, & VPP Arc
PTR, CPP, & VPP Price Only Data Points
Peak Reduction
50%
Residential CPP impact at 8‐to‐1 price ratio = 14.8%
40%
30%
20%
10%
0%
1
2
3
4
5
6
Note: 50 data points included in the chart and 2 Outliers were removed from the regression
Xcel Energy Northern States Power Service Territory
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21
Peak to Off‐Peak Price Ratio
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Several pilots tested the impacts of enabling technology;
we relied on these for the CPP w/ tech option
Results of Residential CPP Pricing Tests with and without Tech
60%
CPP, PTR & VPP Price Only
CPP, PTR & VPP Price + Tech
CPP, PTR, & VPP Price Only Arc
CPP, PTR, & VPP Price + Tech Arc
Peak Reduction
50%
CPP impact with tech = 24.9%
40%
30%
20%
CPP impact without tech = 14.8%
10%
0%
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21
Peak to Off‐Peak Price Ratio
Xcel Energy Northern States Power Service Territory
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C&I impacts were estimated using a similar approach, but
fewer pilots have been conducted for these customers
C&I Arcs with Tech
C&I Arcs without Tech
60%
50%
40%
30%
20%
10%
Small C&I Price + Tech Arc
Medium C&I Price + Tech Arc
Large C&I Price + Tech Arc
50%
Peak Reduction
Peak Reduction
60%
Small C&I Price Only Arc
Medium C&I Price Only Arc
Large C&I Price Only Arc
40%
30%
20%
10%
0%
0%
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21
Peak to Off‐Peak Price Ratio
Xcel Energy Northern States Power Service Territory
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21
Peak to Off‐Peak Price Ratio
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Per-customer pricing impacts are scaled down
in the opt-out deployment scenario
  A new dynamic pricing pilot by the Sacramento Municipal Utility District (SMUD) found that the average residential participant’s peak reduction was smaller under opt‐out deployment than under opt‐in deployment
  This is likely due to a lower level of awareness/engagement among participants in the opt‐out deployment scenario; note that, due to higher enrollment rates in the opt‐out deployment scenario, aggregate impacts are still larger
  Per‐customer TOU impacts were 40% lower when offered on an opt‐
out basis
  Per‐customer CPP impacts were roughly 50% lower
  We have accounted for this relationship in our modeling
Xcel Energy Northern States Power Service Territory
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Presentation
Appendix B:
NSP Market
Characteristics
Xcel Energy
Northern States Power Service Territory
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Over 1.6 million of NSP’s customers are eligible
to participate in DR programs
NSP's Customer Base
Class
Residential
Small C&I
Medium C&I
Large C&I
Total
Number of Customers Average Annual Growth
in 2013
(2014 ‐ 2028)
1,469,795
0.5%
149,169
0.6%
42,073
0.6%
607
0.0%
1,661,644
Source: Xcel Energy
Xcel Energy Northern States Power Service Territory
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Average customer demand will grow at less
than 1 percent per year
Average Customer Coincident Peak Demand
Class
Residential
Small C&I
Medium C&I
Large C&I
2012 Avg. Customer Coincident Peak (kW at generator)
2.3
2.5
89
2,948
Average Annual Growth
(2014 ‐ 2028)
0.2%
0.1%
0.1%
0.7%
Source: Xcel Energy
Xcel Energy Northern States Power Service Territory
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The Residential and Medium C&I segments account for
roughly three-fourths of the system peak
Source: Xcel Energy
Xcel Energy Northern States Power Service Territory
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The system peak is projected to grow at around
0.7% per year
Source: Xcel Energy
Xcel Energy Northern States Power Service Territory
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Existing DR programs currently provide close to
1,000 MW of peak reduction capability
Xcel Energy Northern States Power Service Territory
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Presentation
Appendix C:
DR Potential
Sensitivity Case
Xcel Energy
Northern States Power Service Territory
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National DR participation estimates form the
basis for our sensitivity case
  A key area in which our analysis diverged from NSP’s prior (2012) study is that our participation rates are based on primary market research conducted with NSP’s customers
  An alternative approach – which was used in NSP’s prior study and in the 2009 FERC Assessment of DR Potential ‐ is to survey participation rates in DR programs being offered around the country and to establish the 75th percentile for each program as the basis for the potential study
  We do not recommend using this approach now that primary data is available to NSP; however, given interest by some parties in these estimates, we have developed a second scenario that is based on 75th
percentile estimates in the national survey of DR participation
Xcel Energy Northern States Power Service Territory
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DR participation estimates are derived from
FERC’s 2011 survey of utility DR programs
  Our participation estimates are derived from FERC’s survey of utility DR programs in its 2012 Assessment of Demand Response and Advanced Metering (utilities were surveyed in 2011); this is the most recent comprehensive dataset available
  We considered all DR programs in our assessment but excluded outliers for which reported participation estimates were (1) unrealistic and likely a reporting error or (2) below 1% of eligible customers
  Some programs are not offered on a large scale (e.g., dynamic pricing) or have little data available in the FERC database (e.g., demand bidding); in these instances, we could not calculate a reliable 75th
percentile and instead used participation estimates from successful programs or pilots, or otherwise relied on market research data
Xcel Energy Northern States Power Service Territory
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The sensitivity case participation assumptions
Class
Residential
Residential
Residential
Residential
Residential
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Program
DLC ‐ SFH
DLC ‐ MDU
TOU
CPP
CPP w/Tech
DLC
Demand Bidding
TOU
CPP
CPP w/Tech
DLC
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Opt‐in
37%
37%
20%
20%
20%
16%
7%
20%
20%
20%
10%
20%
27%
7%
20%
20%
20%
31%
31%
7%
100%
20%
20%
Xcel Energy Northern States Power Service Territory
Opt‐out
N/A
N/A
75%
75%
75%
N/A
N/A
75%
75%
75%
N/A
N/A
N/A
N/A
60%
60%
60%
N/A
N/A
N/A
100%
60%
60%
Note
Estimate of national 75th percentile (2011)
Estimate of national 75th percentile (2011)
Opt‐out from FERC Assessment of DR Potential; opt‐in is standard assumption from other studies
Opt‐out from FERC Assessment of DR Potential; opt‐in is standard assumption from other studies
Opt‐out from FERC Assessment of DR Potential; opt‐in is standard assumption from other studies
Estimate of national 75th percentile (2011)
Based on Southern California Edison's Demand Bidding Program (DBP)
Opt‐out from FERC Assessment of DR Potential; opt‐in is standard assumption from other studies
Opt‐out from FERC Assessment of DR Potential; opt‐in is standard assumption from other studies
Opt‐out from FERC Assessment of DR Potential; opt‐in is standard assumption from other studies
Estimate of national 75th percentile (2011)
Estimate of national 75th percentile (2011)
Estimate of national 75th percentile (2011)
Based on Southern California Edison's Demand Bidding Program (DBP)
Opt‐out from FERC Assessment of DR Potential; opt‐in is standard assumption from other studies
Opt‐out from FERC Assessment of DR Potential; opt‐in is standard assumption from other studies
Opt‐out from FERC Assessment of DR Potential; opt‐in is standard assumption from other studies
Estimate of national 75th percentile (2011)
Estimate of national 75th percentile (2011)
Based on Southern California Edison's Demand Bidding Program (DBP)
TOU already default for NSP
Opt‐out from FERC Assessment of DR Potential; opt‐in is standard assumption from other studies
Opt‐out from FERC Assessment of DR Potential; opt‐in is standard assumption from other studies
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We compare DR potential estimates based on
market research and the national 75th percentile
  DR potential estimates based on primary market research in NSP’s service territory are similar to – but consistently slightly higher than – estimates based on the national 75th percentile of participation rates
  The following slides show, individually for each DR option considered in this study, a comparison of peak demand reduction potential in 2028 using these two different approaches
  The estimates assume each DR measure is offered in isolation and do not account for overlap in participation if they were to be offered as part of any given portfolio
Xcel Energy Northern States Power Service Territory
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Comparison of scenario results:
Traditional options
Xcel Energy Northern States Power Service Territory
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Comparison of scenario results:
AMI-enabled options
Xcel Energy Northern States Power Service Territory
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Appendix B:
Market Research Study Details
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Customer Preferences for
Demand Response Programs in
Xcel Energy’s Northern States
Power Service Territory
PRESENTED TO
Xcel Energy
PRESENTED BY
David Lineweber, PhD – YouGov I Definitive Insights
Ahmad Faruqui, PhD – The Brattle Group
December 10, 2013
Copyright © 2013 The Brattle Group, Inc.
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Agenda
• Objective, Methodology, & Participant Profiles
• Executive Summary
• Key Results
• Overview: Opinions of Xcel and Overall DR Take Rates
• Residential Findings
• Business Findings
• Appendix
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Objective, Methodology, & Participant Profiles
Objective & Methodology
• Key Objective
•
Provide Xcel Energy with a complete picture of factors
driving DR potential in the service territory.
Participant Profiles
Age Distribution Gender Distribution
(Residential)
(Residential)
Male
• Online and Phone Quantitative Research
Survey
•
•
Data for Residential customers were collected via an
online survey, with a total of 409 residents of the Xcel
Energy service area in Minnesota, Wisconsin, North
Dakota, South Dakota, and Michigan.
Data for Business customers were collected via a
phone survey, with a total of 337 small businesses and
200 medium/large businesses in the company’s
service area.
• Participant Requirements
•
•
•
•
Customer of Xcel Energy
Responsible for electricity-related household / business
decisions
Billed directly for their electricity use
Not employed in a competitive industry (i.e. advertising
/ marketing / PR, energy utility, environmental
protection)
Female
29%
21%
14% 13%
19%
4%
44%
56%
Strata
(Business)
63%
32%
6%
Smaller
(less than 25 KW)
Medium
(25‐249 KW)
Larger
(250+ kW)
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Estimating Aggregate DR Program Opt-In Response
•
•
The team calculated the proportion of respondents who would actually be likely to sign‐up for (opt‐in) each of the DR programs tested if they were aware of the program and had approximately the amount of information about the program that was provided in the questionnaire These estimates of likely opt‐in rates account for the widely recognized “say‐do” problem (i.e., the issue that survey respondents typically overstate their likely response to a tested new product or service)
– The say/do adjustment algorithm used by the YGDI team is based on proprietary research conducted during 2010. This research captured stated likelihood to adopt / purchase a variety of new products / services, at one point in time, and then tracked actual product / service adoption / purchase over 6 ‐12 months. As we expected, people were less likely to actually purchase products / services than they estimated they would at an earlier time. – The primary adjustment factors that were observed in that research were used here to translate “stated intent” to realistic estimates of likely behavior, and they are outlined in the table below. Scale Rating
Adjustment Value
Not at all likely to participate
Extremely likely to participate
0
1
2
3
4
5
6
7
8
9
10
0%
5%
5%
6%
6%
18%
20%
31%
38%
44%
56%
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Estimating Aggregate DR Program Opt-Out
Response
•
Opt Outs
– Opt Outs represent the proportion of the population who would choose to exit the program if they were defaulted onto the program
– The questions that were asked of respondents only asked about their likelihood to adopt the DR options, not about their likelihood to reject those options if they were defaulted onto them initially. We obviously recognize that actual program experience would have a critical effect on opt‐out rates, but for purposes of estimation, the team chose to interpret strongly negative reaction to the rates as an indication of the people who would be most likely to reject (opt‐out of) those rates if they had the chance. – For this reason, the team used the opt‐in questions, but inverted the adjustment values for those responding 0‐5 to estimate total likely opt‐outs
Scale Rating
Adjustment Value
Extremely likely to participate
Not at all likely to participate
10
9
8
7
6
5
4
3
2
1
0
0%
5%
5%
6%
6%
18%
20%
31%
38%
44%
56%
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Defining Highly Likely Takers and Low, or Unlikely,
Takers
•
Note that the definition of the portion of the population that is likely to adopt any given DR program is estimated probabilistically in the aggregate
•
Since the team also wanted to attempt to understand which specific customer types within each customer segment were most (and least) likely to adopt the programs, the team also assigned customers to “Likely Taker” and “Unlikely Taker” groups
•
“Likely Takers” are those individual customers most likely to adopt the given DR option, while “Unlikely Takers” are the opposite
• Criteria vary by strata, but Likely Takers are generally those who rated a program (or multiple programs) at a 7 or higher in terms of likelihood to participate.
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Agenda
• Objective, Methodology, & Participant Profiles
• Executive Summary
• Key Results
• Overview: Opinions of Xcel and Overall DR Take Rates
• Residential Findings
• Business Findings
• Appendices
• Appendix A: Overall Attitudes and Descriptors
• Appendix B: Exploring DR Program Interest Based on Current DR Participation
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Executive Summary - Residential
•
Overall, likely DR program participation among Residential customers is relatively strong – at least at the high incentive levels.
–
CPP w/ Tech and the Savers’ Switch Program are the most popular programs: at the highest incentive levels, more than 1/3 of customers would participate in each one. •
•
•
Residential customers in multi‐family housing are particularly interested in the Saver’s Switch Program – they are up to 11 percentage points more likely to opt in than are customers in single‐family housing; this is most likely due to the fact that the program has not been offered to occupants of multi‐family dwellings up to this point. Those customers considered Likely Takers have a strong sense of environmentalism and are very positive in their perceptions of Xcel Energy.
–
Likely Takers care about the environment, believing that global warming is real and that reducing their household energy use feels like the right thing to do.
–
However, cost savings are still important to this group: about half see low energy costs as a higher priority than energy efficiency programs, and only a small minority (7%) would be willing to pay more for energy efficiency programs. –
Likely Takers are demographically very similar to Unlikely Takers – despite substantial attitudinal differences between the two groups, key markers like age, income, and education are all quite similar.
Unlikely Takers’ strong dislike for, and distrust of, Xcel Energy appears to be a major barrier to signing up for DR programs.
–
This group is less concerned with environmental factors, but does think about saving costs on energy use. They are not “comfort is king” customers.
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Executive Summary - Business
•
Small business (< 25 KW) and Medium business customers (25‐999 kW) are more likely to participate in more programs than Larger business customers.
– About a quarter of Small and Medium customers indicate a likelihood to participate in the Savers Switch program, and CPP gets similar opt‐in rates. – CPP w/ Tech, the most popular program, has even higher opt‐in rates: up to 28% for Medium business and 29% for Small businesses. •
However, for the popular programs CPP and CPP w/ Tech, Larger business customers are about as likely to adopt as Small and Medium companies •
When looking at the differences between Likely and Unlikely Takers, relatively few things stand out as clear markers of higher participation likelihood. – Among Small businesses, having a greater number of employees appears to decrease a businesses likelihood to participate.
– Among Medium and Larger Businesses, Likely Takers are significantly more likely to already be participating in the Interruptible Rate program
– Likely Takers across all business sizes tend to give Xcel Energy higher satisfaction scores
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Agenda
• Objective, Methodology, & Participant Profiles
• Executive Summary
• Key Results
• Overview: Opinions of Xcel and Overall DR Take Rates
• Residential Findings
• Business Findings
• Appendices
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Only a small minority of customers is highly favorable to
DR plans across the board; and around half reject all of
the proposed DR options
• While 17% of residential customers say they would adopt all of the plans offered, business customers are a harder target: more than three‐fourths of businesses of any size reject half or more of programs offered.
• And in fact, approximately half of all of the customers in each segment say they would not adopt ANY of the proposed plans
Percentage Of Plans That Each Participant Would Adopt (All respondents)
About half would not
participate in any of the plans
Residential…
45%
Small C&I…
A small minority say they would
participate in all of the plans
4%
55%
Med C&I…
10%
51%
Large C&I…
1‐24%
16%
11%
14%
53%
0%
15%
18%
25‐49%
50‐74%
2%
17%
11%
4% 8%
18%
13%
17%
75‐99%
5% 1%
11% 1%
100%
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Though few accept all plans, customers are open to
DR: the highest incentives yield up to 40% opt-in
Overview: Measure‐Level Opt‐In Rates
• The chart at the right shows opt‐in rates for each plan at each incentive level
•
Opt‐in rates range from 6% to 40% .
•
CPP w/ Tech is the overall leader across incentive levels & segments, but for specific segments other plans are similar or lead. •
DLC is a close competitor, particularly among multi‐
family dwellers.
•
Interruptible (Price) plans are strong among medium C&I. • In general, customers who participate in current NSP DR programs are more likely to say they would participate in new programs (See Appendix B for data on this issue).
Incentive level ‐‐‐‐>
Very Low
Low
Medium
High
Very High
Opt‐in
17%
26%
16%
23%
25%
Opt‐in
20%
31%
19%
26%
28%
Opt‐in
24%
35%
24%
29%
33%
Opt‐in
28%
37%
27%
31%
35%
Opt‐in
34%
40%
29%
33%
39%
16%
8%
12%
17%
21%
19%
9%
13%
18%
22%
21%
10%
15%
19%
25%
22%
13%
17%
20%
26%
24%
16%
19%
22%
29%
DLC
Interruptible (Reliability)
Interruptible (Price)
Medium C&I (Strata 2‐4) Demand Bidding
TOU
CPP
CPP w/Tech
18%
17%
19%
8%
12%
18%
21%
19%
18%
21%
10%
13%
19%
22%
20%
19%
23%
11%
16%
20%
24%
21%
22%
25%
14%
17%
22%
26%
23%
26%
27%
16%
19%
22%
28%
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
12%
13%
6%
100%
20%
25%
13%
15%
7%
100%
21%
26%
14%
16%
8%
100%
22%
28%
16%
18%
10%
100%
24%
31%
18%
19%
11%
100%
25%
34%
Segment
Residential
DR Measure
DLC ‐ SFH
DLC ‐ MDU
TOU
CPP
CPP w/Tech
DLC
Demand Bidding
TOU
CPP
CPP w/Tech
Small C&I
Large C&I (Strata 5)
Lowest opt‐in in each segment
Highest opt‐in in each segment
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Healthy satisfaction among Medium and Large C&I,
somewhat lower among Small C&I and Residential
• The most satisfied customers are Medium and Large C&I: Xcel’s satisfaction rate among this group is similar to leading consumer goods companies. •
Satisfaction is somewhat lower among Residential and Small C&I customers.
• Further improvement in satisfaction ratings and increasing trust for Xcel Energy is likely to help increase customer willingness to consider DR. Overall Satisfaction with Xcel Energy (top 3 box)
(All respondents)
Residential
(n=409)
59%
Small C&I
(n=337)
61%
Med C&I
(n=200)
Large C&I
(n=76)
68%
71%
See slide notes for question numbers
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Agenda
• Objective, Methodology, & Participant Profiles
• Executive Summary
• Key Results
• Overview: Opinions of Xcel and Overall DR Take Rates
• Residential Findings
• Business Findings
• Appendices
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The Savers Switch Program among multifamily customers
and CPP w/ Tech have the highest likelihood of participation
• At lower incentive levels, the adoption gap between CPP and CPP w/ Tech is likely to be too small to justify investment in CPP technology: this plan is most likely to have good ROI at the higher incentive levels. Likely Takers Across All Programs
DLC - Single Family
DLC - Multi Family
CPP
CPP w/ Tech
Time of Use
(Total Residential Customers, n=409)
35%
33%
29%
31%
28%
26%
26% 25%
23%
17%
37%
20%
24%
28%
40%
35%
31%
34%
39%
33%
29%
27%
24%
19%
16%
Incentive level
Very Low
Low
Medium
High Very high
DLC
$5/month
$9/month
$14/month
$18/month
$25/month
CPP
6% /month
8% /month
11% /month
13% /month
15% /month
CPP w/ Tech
8% /month
11% /month
15% /month
17% /month
20% /month
ToU
4% /month
6% /month
10% /month
12% /month
14% /month
See slide notes for question numbers
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If all customers were assigned to a pricing plan, TOU plans
would have substantially higher opt-out than other plans
• CPP has substantially fewer opt‐outs at all incentive levels; consistent with opt‐in results showing CPP plans to be more attractive to respondents than Time of Use pricing. Likely Opt‐Outs Across All Programs
(Total Residential Customers, n=409)
DLC - Single Family (n/a)
DLC - Multi Family (n/a)
CPP
CPP w/ Tech
Time of Use
24%
20%
15% 15%
0% 0%
12% 12%
0% 0%
14%
12%
10%
8%
0% 0%
9%
12%
8%
7%
0% 0%
6%
0% 0%
Incentive level
Very Low
Low
Medium
High Very high
DLC
$5/month
$9/month
$14/month
$18/month
$25/month
CPP
6% /month
8% /month
11% /month
13% /month
15% /month
CPP w/ Tech
8% /month
11% /month
15% /month
17% /month
20% /month
ToU
4% /month
6% /month
10% /month
12% /month
14% /month
See slide notes for question numbers
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Single- and Multi-Family customers provide very similar
responses, except on DLC (the Saver’s Switch program)
• There are meaningful differences between single‐family and multi‐family respondents on their response to the Saver’s Switch (SS) program, but those differences are easily explained (see the following page).
• For the CPP and the CPP w/ Tech options, single‐family dwellers are marginally more likely to adopt the programs, especially at the higher price points
Likely Takers Across All Programs
40%
(Single vs. Multi-Family Residential Customers)
39%
38%
37%
35%
34%
34%
32%
31%
28%
26%
24%
36%
35%
30%
30%
28%
33%
32%
31%
26%26%
24%
23%
29%29%
29%
28%
27%
27%
27%
25%
23%
24%
20%
19%
18%
17%
16%
17%
$5
Single Family
(n=282)
Multi Family
(n=127)
$9 $14 $18 $25
6% 8% 11% 13% 15%
DLC (Saver’s Switch)*
(Asked only of current SS non‐
participants)
CPP
8% 11% 15% 17% 20%
4% 6% 10% 12% 14%
CPP w/ Tech
Time of Use
See slide notes for question numbers
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The Saver’s Switch program appears less attractive to
single-family customers largely because they have
already had the opportunity to participate in the program
• It is important to note that only current Saver’s Switch program non‐participants were asked about their likelihood to participate in a similar program at the tested price points, and as a result, all of the current single‐family program participants were excluded from these results
• Among single‐family homes that were technically eligible to participate in the Saver’s Switch program approximately 33% said they were already participating in the program
• Since single‐family dwellers have had the opportunity to participate in this program, while multi‐family dwellers have effectively not had that opportunity, those single‐family dwellers most positive toward the SS program have already been “siphoned off” into current program participants
• As a results, the findings on the prior page indicate that – on average – multi‐family dwellers are more likely to participate in the SS program at all price points, but this is largely due to the fact that a substantial proportion of the single‐family “likely takers” have been excluded from the analysis because they have already “taken” the program.
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Likely Takers and Unlikely Takers have very similar
demographic profiles
• No statistically significant demographic differences between the two groups
By Age
By Housing Type
Single‐
family
0%
29%
35‐54
100%
By Ownership Status
20%
40%
34%
29%
0%
50%
100%
By Gender
0%
50%
40%
Personally responsible
100%
S12 / S4 / D9 / S7 / D5 / D6 / S5 / S8 / D2
Δ indicates a significant difference between High and Low Likely Takers
13%
12%
50%
0%
20%
30%
31%
40%
60%
Someone Home on Weekdays
68%
69%
Yes
40%
39%
0%
Bachelors
60%
60%
61%
Share decision‐
making
62%
52%
Female
40%
39%
Some coll/tr sch
Grad/prof sch
20%
EE Decision Making Role
38%
48%
Male
17%
13%
0%
100%
17%
17%
HS or less
54%
54%
Rural
50%
By Level of Education
Suburban
Rent
0%
60%
28%
34%
Urban
15%
16%
$100K+
54%
By Community Type
66%
71%
Own
43%
0%
64%
59%
$30K‐$100K
40%
55+
50%
18%
22%
<$30K
12%
15%
25‐34
33%
30%
Multi‐
family
4%
3%
18‐24
67%
70%
By Household Income
32%
31%
No
100%
0%
20%
40%
60%
80%
Likely Takers (n=123)
Unlikely Takers (n=185)
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Opinions of Xcel Energy: large differences between
Unlikely and Likely Takers
Overall Ratings of Xcel Energy
(Total Residential Customers)
Likely Takers (n=123)
Unlikely Takers (N=185)
Overall satisfaction with Xcel Energy
72%
46%
Actively encourage its customers to participate in energy saving and cost saving programs
45%
A company that can be trusted
38%
Operate its business in a completely environmentally friendly manner
A credible information source for the community on energy issues
A leader in energy conservation and energy efficiency
A company that actively promotes programs to help its customers save money
0%
76%
59%
36%
35%
32%
20%
40%
59%
54%
Δ
Δ
Δ
56%
60%
Δ
Δ
65%
37%
Δ
Δ
80%
100%
Q2 / Q3 / Q4, % Top Box (8‐10)
Δ indicates a significant difference between High and Low Likely Takers
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Likely Takers are significantly more concerned
about environmental issues than Unlikely Takers
Energy Efficiency Attitudes
(High and Low Taker Residential Customers)
The threat from global warming is real, and significant
Saving money on energy costs is something you focus on
every day
57%
36%
You are very concerned about the environmental effects of
electric power plants
46%
21%
Comfort is very important to your household - even if it means
spending more each month for energy
41%
25%
You are an early adopter of new home technologies
30%
8%
You would do more to make your home more energy efficient,
but you don't know where to start
12%
Conserving energy at your home will make no difference to
the quality of the environment overall
10%
You just want to be left alone to use energy however you want
in your home
27%
20%
Δ
Δ
Δ
Δ
Δ
Δ
Likely Takers
(N=123)
Unlikely
Takers
(n=185)
20%
16%
Realistically, there isn't much you can do to save money on
energy costs
Δ
58%
39%
14%
9%
0%
20%
40%
60%
80%
Q6, % Top Box (8‐10)
Δ indicates a significant difference between High and Low Likely Takers
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When it comes to prioritizing energy efficiency
initiatives vs. energy costs, the two groups have only
minor differences
Energy Efficiency vs. Energy Costs
(High and Low Taker Residential Customers)
High Takers
(n=123)
Low Takers
(n=185)
Do everything possible to keep energy
costs as low as possible
49%
55%
Energy costs and energy efficiency
initiatives are equally important
45%
41%
Pursue these and other initiatives even
if you would have to pay a little more
7%
4%
0%
10%
20%
30%
40%
50%
60%
70%
Q5, % Top Box (8‐10)
Δ indicates a significant difference between High and Low Likely Takers
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Summary of Likely vs. Unlikely Takers
Likely Takers
Household
Energy Usage
& Attitudes
• Higher on all positive EE attitudes and
more focused on actively reducing energy
usage
• More than 3x as likely to describe
themselves as early adopters of home
technologies
• More than half participate in Saver’s Switch
Program
Unlikely Takers
• Significantly less likely to believe “the
threat from global warming is real”
• Significantly less concerned about the
environmental affects of power plants
• Less focused on reducing energy usage,
but aren’t “comfort is king” people, either
• 11% live in homes >2,500 square feet;
about half as many as High Takers
• 20% live in homes >2,500 square feet
• More familiar with Xcel Energy, more
positive on all perceptions of Xcel, and
more satisfied with Xcel
Perceptions of
Xcel Energy
Demographics
• Higher ratings on importance of Xcel
pursuing EE efforts
• Only a third believe Xcel is a trustworthy
company
• Majority believe keeping costs low should
be the priority for Xcel
• Somewhat more likely to think it’s important
that Xcel do both: keep costs low and take
EE measures
• No significant demographic differences between the two groups in this service area
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Agenda
• Objective, Methodology, & Participant Profiles
• Executive Summary
• Key Results
• Overview: Opinions of Xcel and Overall DR Take Rates
• Residential Findings
• Business Findings
• Strata 1 (Small)
• Strata 2 (Medium)
• Strata 3 (Larger)
• Appendices
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SMALL
CPP w/ Tech is the most popular plan at all
incentive levels
• The most popular programs among Small C&I closely parallel top programs among residential customers: CPP w/ Tech takes the lead, followed by DLC and CPP. DLC
Demand Bidding
CPP
CPP w/ Tech
Time of Use
16%
Small C&I: Likely Takers Across All Programs
(Small C&I Customers, n=337)
29%
21%
17%
22%
19%
18%
13%
12%
9%
8%
25%
21%
19%
15%
26%
22%
20%
17%
13%
24%
22%
19%
16%
10%
Incentive level
Very Low
Low
Medium
High Very high
DLC
$1/ton of AC size
$3/ton of AC size
$4/ton of AC size
$5/ton of AC size
$7/ton of AC size
Demand Bid.
$0.10 /kWh
$0.30 /kWh
$0.50 /kWh
$0.75 /kWh
$1 /kWh
CPP
6% /month
8% /month
11% /month
13% /month
15% /month
CPP w/ Tech
8% /month
11% /month
15% /month
17% /month
20% /month
ToU
4% /month
6% /month
10% /month
12% /month
14% /month
See slide notes for question numbers
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SMALL
Small C&I respondents are most likely to opt out of ToU
plans, consistent with results showing low adoption
•
•
Opt‐out likelihood aligns closely with adoption likelihood: the least popular plans are the most likely to see customers opt‐out.
Note that CPP is relatively inelastic: changing the incentive level has only a small impact on likelihood of opting out. DLC
Demand Bidding
CPP
CPP w/ Tech
Time of Use
26%
Small C&I: Likely Opt‐Outs Across All Programs
(Small C&I Customers, n=337)
32%
23%
31%
27%
25%
24%
21%
23%
17%
0% 0%
0% 0%
0% 0%
25%
23%
16%
0% 0%
24%
14%
0% 0%
Incentive level
Very Low
Low
Medium
High Very high
DLC
$1/ton of AC size
$3/ton of AC size
$4/ton of AC size
$5/ton of AC size
$7/ton of AC size
Demand Bid.
$0.10 /kWh
$0.30 /kWh
$0.50 /kWh
$0.75 /kWh
$1 /kWh
CPP
6% /month
8% /month
11% /month
13% /month
15% /month
CPP w/ Tech
8% /month
11% /month
15% /month
17% /month
20% /month
ToU
4% /month
6% /month
10% /month
12% /month
14% /month
See slide notes for question numbers
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SMALL
In Small C&I, headcount is key difference between Likely and
Unlikely Takers: Likely Takers tend to be smaller
Number of Employees
Type of Facility
Retail
22%
24%
Office
16%
Lodging / housing facility
22%
Restaurant / food service
Manuf./ prod./ proc. Facility
16%
20%
10%
20%
21%
18%
19%
5,000 – 9,999
10,000 – 14,999
11%
16%
15,000 sq. ft. +
0%
30%
Share decision‐
making
50%
Central A/C
55%
63%
Packaged
A/C units
41%
39%
50%
100%
32%
35%
0%
20%
40%
8%
5%
80%
Hot water or
steam
65%
70%
50%
100%
Likely Takers (n=111)
Unlikely Takers (n=148)
92%
95%
No
60%
77%
66%
0%
Ownership Status
Yes
100%
76%
82%
Some / All Heating
19%
15%
60%
68%
65%
50%
Some / All Cooling
Backup Generator(s)
Lease
5%
7%
8%
2%
Air cooled
chiller
0%
Own
Not a DM, but knowledgeable
Uses of Electricity
18%
20%
Other
40%
100%
32%
34%
0%
26%
20%
63%
59%
Type of Cooling System
3%
5%
1,000 – 4,999
Personally responsible
7%
7%
0%
Square Footage
<1,000 sq. ft.
5–9
20+
Other
0%
48%
27%
26%
5%
19% Δ
10 – 19
12%
5%
7%
5%
6%
9%
6%
8%
Warehouse
<5
Energy Decision Making Role
60% Δ
0%
50%
100%
S4 / Q3 / Q1 / Q2 / Q5 / Q6 / S3 / Q4
Δ indicates a significant difference between High and Low Likely Takers
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SMALL
Similar attitudes towards Xcel Energy: a majority of
both groups are satisfied and see Xcel as a
credible info source
Overall Ratings of Xcel Energy
(Small Business Customers)
Likely Takers (n=111)
Unlikely Takers (n=148)
71%
Overall satisfaction with Xcel Energy
66%
64%
Credible information source on the kinds of things you can do to save energy
60%
50%
A company that actively promotes programs to help its business customers save money
Already participating in the Interruptible Rate program
0%
44%
14%
19%
20%
40%
60%
80%
100%
Q8 and Q9 % Top Box (8‐10), Q7a
Δ indicates a significant difference between High and Low Likely Takers
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SMALL
Both groups also have similar attitudes towards energy
management: a majority have taken at least some steps to
promote efficiency, but there is still room for improvement
Approach to Energy Management
(Small Business Customers)
We don’t really pay much attention to managing our energy use
6%
10%
We try and watch our energy use, but we haven’t actually done much in terms of changing out equipment or installing better energy management tools
Likely Takers
(n=111)
26%
25%
Unlikely Takers
(n=148)
We have done some things to better manage our energy use, but I wouldn’t say we have done everything we can
43%
47%
24%
18%
We make consistent and aggressive efforts to manage our energy use as effectively as possible
0%
20%
40%
60%
Q10
Δ indicates a significant difference between High and Low Likely Takers
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Agenda
• Objective, Methodology, & Participant Profiles
• Executive Summary
• Key Results
• Overview: Opinions of Xcel and Overall DR Take Rates
• Residential Findings
• Business Findings
• Strata 1 (Small)
• Strata 2 (Medium)
• Strata 3 (Larger)
• Appendices
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MEDIUM
Demand Bidding and Time of Use plans are unattractive; CPP
w/ Tech is the leader, but only by a small margin
Medium C&I: Likely Takers Across All Programs
(Medium C&I Customers, n=200)
DLC
Interruptible (Reliability)
21%
19%
18%17%
18%
Interruptible (Price)
22%
21%
19%
19%
18%
13%
12%
23%
20%19%
24%
20%
CPP
CPP w/Tech
26%
25%
22%
22%
21%
16%
11%
17%
14%
TOU
28%
27%
26%
23%
22%
19%
16%
8%
10%
Very Low
Low
Medium
High Very high
$1/ton of AC size
$3/ton of AC size
$4/ton of AC size
$5/ton of AC size
$7/ton of AC size
$3.50 $5.50 $7.00 $9.50
Incentive level
DLC
Demand Bidding
Interruptible (Reliability) $2.00 Interruptible (Price)
$3.50 $5.00 $7.00 $8.50 $11.00
Demand Bid.
$0.10 /kWh
$0.30 /kWh
$0.50 /kWh
$0.75 /kWh
$1 /kWh
CPP
6% /month
8% /month
11% /month
13% /month
15% /month
CPP w/ Tech
8% /month
11% /month
15% /month
17% /month
20% /month
ToU
4% /month
6% /month
10% /month
12% /month
14% /month
See slide notes for question numbers
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MEDIUM
Consistent with other audiences, Medium C&I customers are
most likely to opt-out of Time of Use plans
Medium C&I: Likely Opt-Outs Across All Programs
(Medium C&I Customers, n=200)
33%
31%
28%
24%
23%
23%
21%
CPP
21%
18%
26%
21%
21%
16%
24%
15%
CPP w/Tech
TOU
Incentive level
DLC
Very Low
Low
Medium
High Very high
$1/ton of AC size
$3/ton of AC size
$4/ton of AC size
$5/ton of AC size
$7/ton of AC size
$3.50 $5.50 $7.00 $9.50
Interruptible (Reliability) $2.00 Interruptible (Price)
$3.50 $5.00 $7.00 $8.50 $11.00
Demand Bid.
$0.10 /kWh
$0.30 /kWh
$0.50 /kWh
$0.75 /kWh
$1 /kWh
CPP
6% /month
8% /month
11% /month
13% /month
15% /month
CPP w/ Tech
8% /month
11% /month
15% /month
17% /month
20% /month
ToU
4% /month
6% /month
10% /month
12% /month
14% /month
See slide notes for question numbers
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MEDIUM
Likely Takers among Medium C&I tend to be larger
companies: almost half are 20 employees or more
Number of Employees
Type of Facility
<5
10%
13%
15%
14%
12%
7%
5%
3%
10%
5%
10%
4%
Office
Manuf./ prod./ proc. facility
Retail
School
Restaurant / food service
Lodging / housing facility
5–9
10 – 19
20+
37%
0%
20%
40%
54%
60%
Square Footage
12%
< 4,999 sq. ft.
5,000 – 9,999
15,000 – 24,999
47%
40%
60%
Central A/C
44%
44%
0%
20%
40%
60%
Ownership Status
0%
20%
40%
17%
18%
80%
76%
74%
Hot water or
steam
64%
54%
0%
50%
100%
Likely Takers (n=59)
83%
82%
No
60%
Δ
Unlikely Takers (n=76)
27%
24%
Lease
93%
82%
Some / All Heating
22%
19%
Backup Generator(s)
Own
100%
Some / All Cooling
60%
Yes
50%
15%
13%
Other
73%
76%
8%
14%
Uses of Electricity
20%
24%
Air cooled
chiller
40%
Not a DM, but knowledgeable
0%
36%
39%
20%
24%
29%
Type of Cooling System
Packaged
A/C units
25%
25,000 +
0%
20%
68%
57%
Share decision‐
making
20%
16%
15%
12%
12%
13%
10,000 – 14,999
Personally responsible
34%
0%
Other
Energy Decision Making Role
19%
25%
17%
20%
17%
21%
100%
0%
50%
100%
S4 / Q3 / Q1 / Q2 / Q5 / Q6 / S3 / Q4
∆ indicates a significant difference
between High and Low Likely Takers
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MEDIUM
Likely Takers are more open to Xcel’s initiatives:
they are more satisfied and are significantly more
likely to be participating in the Interruptible Rate
program already
Overall Ratings of Xcel Energy
(Medium Business Customers)
Likely Takers (n=59)
Unlikely Takers (n=76)
73%
Overall satisfaction with Xcel Energy
59%
Δ
Already participating in the Interruptible Rate program
0%
37%
20%
20%
40%
60%
80%
100%
Q9 and Q11 % Top Box (8-10)
∆ indicates a significant difference between High and Low Likely Takers
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Agenda
• Objective, Methodology, & Participant Profiles
• Executive Summary
• Key Results
• Overview: Opinions of Xcel and Overall DR Take Rates
• Residential Findings
• Business Findings
• Strata 1 (Small)
• Strata 2 (Medium)
• Strata 3 (Larger)
• Appendices
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LARGE
Again, CPP with Tech is the most attractive DR program
•
Note, however, that price sensitivity for most of these options is relatively low – and even lower than it is for other customer
segments ‐‐ meaning that customers are likely to either adopt or not adopt the option, based primarily on non‐price‐related considerations, and as a result, regardless of the price offered (at least for the price points tested)
Large C&I: Likely Takers Across All Programs
(Large C&I Customers, n=200)*
100%
Interruptible (Reliability)
100%
100%
100%
100%
34%
Interruptible (Price)
Demand Bidding
CPP
25%
CPP w/Tech
20%
Time of Use
15%
13%
13%
12%
6%
Incentive level
Interruptible (Reliability)
Interruptible (Price)
Demand Bid.
CPP
CPP w/ Tech
ToU
ToU assumed to be 26%
mandatory for Large 21%
C&I
7%
31%
28%
19%
18%
18%
16%
16%
14%
8%
25%
24%
22%
10%
11%
Very Low
Low
Medium
High Very high
$2.00 $3.50 $5.50 $7.00 $9.50
$3.50 $5.00 $7.00 $8.50 $11.00
$0.10 /kWh
$0.30 /kWh
$0.50 /kWh
$0.75 /kWh
$1 /kWh
6% /month
8% /month
11% /month
13% /month
15% /month
8% /month
11% /month
15% /month
17% /month
20% /month
4% /month
6% /month
10% /month
12% /month
14% /month
See slide notes for question numbers
*Large C&I opt-in/opt-out modeled based on data from 200 Medium C&I customers
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LARGE
CPP w/ Tech has lower incidence of opting out
compared to CPP
Large C&I: Likely Takers Across All Programs
(Large C&I Customers, n=200)*
CPP
CPP w/Tech
Incentive level
22%
18%
Very Low
Interruptible (Reliability) $2.00 21%
17%
19%
19%
14%
19%
13%
12%
Low
Medium
High Very high
$3.50 $5.50 $7.00 $9.50
Interruptible (Price)
$3.50 $5.00 $7.00 $8.50 $11.00
Demand Bid.
$0.10 /kWh
$0.30 /kWh
$0.50 /kWh
$0.75 /kWh
$1 /kWh
CPP
6% /month
8% /month
11% /month
13% /month
15% /month
CPP w/ Tech
8% /month
11% /month
15% /month
17% /month
20% /month
ToU
4% /month
6% /month
10% /month
12% /month
14% /month
See slide notes for question numbers
*Large C&I opt-in/opt-out modeled based on data from 200 Medium C&I customers
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LARGE
Unlikely Takers are somewhat more likely to be large
companies of 200+ employees, otherwise firmographics of the
two groups are similar
Number of Employees
Type of Facility
28%
23%
Manuf./ prod./ proc. facility
Office
Lodging / housing facility
5 – 49
Grocery
200+
0%
36%
Other
0%
20%
47%
50%
50,000 – 99,999
100,000 – 499,999
68%
63%
24%
13%
8%
20%
21%
60%
17%
20%
40%
16%
17%
Lease
0%
20%
28%
33%
60%
80%
100%
96%
80%
Some / All Heating
84%
80%
Hot water or
steam
52%
60%
50%
100%
150%
Likely Takers (n=25*)
Unlikely Takers (n=30)
72%
67%
No
40%
60%
Some / All Cooling
0%
Ownership Status
Own
40%
25%
Backup Generator(s)
Yes
20%
21%
21%
80%
84%
83%
16%
23%
Uses of Electricity
33%
33%
0%
40%
Not a DM, but knowledgeable
29%
Packaged
A/C units
Other
20%
36%
37%
0%
Air cooled
chiller
0%
500,000 – 1 MIL
3%
0%
0%
1 MIL +
0%
100%
60%
Square Footage
48%
40%
Share decision‐
making
Central A/C
< 50,000 sq. ft.
60%
Type of Cooling System
50%
40%
Personally responsible
20%
13%
8%
23%
50-199
3%
4%
0%
8%
3%
Retail
12%
17%
<5
12%
20%
12%
Energy Decision Making Role
0%
50%
100%
S4 / Q3 / Q1 / Q2 / Q5 / Q6 / S3 / Q4
Δ indicates a significant difference between High and Low Likely Takers
NOTE: * = indicates small sample size
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LARGE
Likely Takers are somewhat more positive about Xcel Energy and more likely to be participating in existing programs
Overall Ratings of Xcel Energy
(Larger Business Customers)
Likely Takers (n=25*)
Unlikely Takers (n=30)
76%
Overall satisfaction with Xcel Energy
67%
52%
Already participating in the Interruptible Rate
program
Δ
23%
0%
20%
40%
60%
80%
100%
Q9 and Q11 % Top Box (8‐10)
Δ indicates a significant difference between High and Low Likely Takers
NOTE: * = indicates small sample size
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LARGE
Summary of Larger Business Customer In-Depth
Interviews
•
Larger companies are generally happy with their service with Xcel Energy, most citing reliability of power and good support by their rep.
– Quality of the rep appears to play a key role in both perceptions of and satisfaction with Xcel Energy.
– Two companies reported having frequent outages, and their scores were somewhat lower.
•
Likelihood to participate in the DR programs is low and appears to hinge both on getting more information, and on being able to avoid any disruption in company functions.
– Most of the companies interviewed said they would need more information before being certain whether or not a DR program would be right for them.
– Those that are already on the Interruptible Rate plan were positive about their experience with that plan.
– Several respondents expressed concern that the Time of Use option would actually end up costing them more, instead of increasing savings.
– The Demand Bidding plan was perceived by most of the companies interviewed as being 'labor‐
intensive'.
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Agenda
• Objective, Methodology, & Participant Profiles
• Executive Summary
• Key Results
• Overview: Opinions of Xcel and Overall DR Take Rates
• Residential Findings
• Business Findings
• Appendix A: Overall Attitudes and Descriptors
• Appendix B: Exploring DR Program Interest Based on Current DR Participation
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Presentation Appendix A:
Overall Attitudes & Descriptors
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Overall Ratings of Xcel Energy
Overall Ratings of Xcel Energy
(Total Residential Customers)
Overall satisfaction with Xcel Energy
59%
Actively encourages its customers to participate in
energy saving and cost saving programs
60%
Operates its business in a completely
environmentally friendly manner
50%
A company that can be trusted
49%
A credible information source for the community
on energy issues
48%
A leader in energy conservation and energy
efficiency
45%
Actively promotes programs to help its customers
save money
44%
0%
20%
40%
60%
80%
Q2 / Q3, % Top Box (8‐10), Q4, % Top Box (8-10) (Total, n=409)
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Responses to Forced Choice Question on
EE / Green vs. Cost Options
EE vs. Cost Options
(Total Residential Customers)
Do everything possible to keep energy costs as
low as possible
54%
Both are equally important
40%
Pursue these and other initiatives even if you
would have to pay a little more
6%
0%
10%
20%
30%
40%
50%
60%
70%
Q5, (Total, n=409)
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Residential Customer Homes By Type
Residential Customer Homes By Type
(Total Residential Customers)
Mobile/Manufact
ured Home, 3%
Single Family
House
(Detached),
60%
Multi-Family Unit
(5+ Units), 20%
Multi-Family Unit
(2-4 units), 10%
Single Family
House
(Attached), 6%
S12 (Total, n=409)
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Presentation Appendix B:
Exploring DR Program Interest Based on
Current DR Participation
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Residential
Likely Takers are somewhat more positive about Xcel Energy and more Residential
Customers Currently Enrolled in DLC are
likely to be participating in existing programs
More Likely to Say They Will Adopt New DR Programs
DR Program Adoption Likelihood Cut by DLC Participation
(Residential customers)
No DLC / DK (n=154)
Current DLC (n=118)
Not eligible for DLC (n=137)
14%
23%
24%
ToU Adoption Likelihood
36%
CPP w/ Tech Adoption Likelihood
49%
45%
23%
CPP Adoption Likelihood
DLC Adoption Likelihood
44%
38%
36%
n/a
n/a
Adoption likelihood is defined as the percentage of respondents who rate each plan an 8 or higher. Incentive levels within each plan type are aggregated: e.g., if 8 of 10 accept at a high incentive and 2 of 10 accept at a lower level, the aggregated adoption likelihood would be 50%.
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Small
Likely Takers are somewhat more positive about Xcel Energy and more For Small Business Customers, Current Interruptible Rate
likely to be participating in existing programs
Enrollment is not Tied to Adoption Likelihood for New DR Programs
DR Program Adoption Likelihood Cut by Interruptible Rate Participation
(Small C&I customers)
Enrolled in Interruptible Rate
ToU
Adoption Likelihood
CPP w/ Tech Adoption Likelihood
CPP
Adoption Likelihood
DLC
Adoption Likelihood
Not enrolled in Interruptible Rate
Sample Sizes
Enrolled in Not Enrolled IR
in IR
13%
13%
31%
33%
20%
23%
22%
ToU
n=280
n=57
CPP w/ Tech
n=280
n=57
CPP
n=280
n=57
DLC
n=116
n=7 (insufficient sample)
Adoption likelihood is defined as the percentage of respondents who rate each plan an 8 or higher. Incentive levels within each plan type are aggregated: e.g., if 8 of 10 accept at a high incentive and 2 of 10 accept at a lower level, the aggregated adoption likelihood would be 50%.
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Medium
Likely Takers are somewhat more positive about Xcel Energy and more Medium Business Customers Enrolled in Interruptible Rates Are
likely to be participating in existing programs
Somewhat More Likely to Adopt Other DR Programs
DR Program Adoption Likelihood Cut by Interruptible Rate Participation
(Medium C&I customers)
Enrolled in Interruptible Rate
Not enrolled in Interruptible Rate
Demand Bidding Adoption Likelihood
Interruptible Rate (Price) Adoption Likelihood
Interruptible Rate (Reliability) Adoption
Likelihood
ToU
Adoption Likelihood
Enrolled in Not Enrolled IR
in IR
10%
8%
Demand Bidding
Interruptible Rate (Price)
23%
18%
20%
Interruptible Rate (Reliability)
16%
11%
CPP w/ Tech Adoption Likelihood
CPP
Adoption Likelihood
DLC
Adoption Likelihood
Sample Sizes
20%
n=53
n=147
n=53
n=38
n/a
n=38
33%
32%
ToU
n=53
n=147
CPP w/ Tech
n=53
n=147
33%
CPP
n=53
n=147
27%
n=13 DLC (insufficient sample)
n=64
Adoption likelihood is defined as the percentage of respondents who rate each plan an 8 or higher. Incentive levels within each plan type are aggregated: e.g., if 8 of 10 accept at a high incentive and 2 of 10 accept at a lower level, the aggregated adoption likelihood would be 50%.
* Denotes small sample, n<30. 48 | brattle.com
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Larger
Likely Takers are somewhat more positive about Xcel Energy and more Larger Business Customers Enrolled in Interruptible Rates Appear
likely to be participating in existing programs
Notably More Likely to Adopt Other DR Programs
DR Program Adoption Likelihood Cut by Interruptible Rate Participation
(Larger C&I customers)
Enrolled in Interruptible Rate
Not enrolled in Interruptible Rate
Demand Bidding Adoption Likelihood
3%
CPP w/ Tech Adoption Likelihood
CPP
Adoption Likelihood
DLC
Adoption Likelihood
Enrolled in Not Enrolled IR
in IR
11% *
Demand Bidding
Interruptible Rate (Price)
19% *
16% *
Interruptible Rate (Price) Adoption Likelihood
Interruptible Rate (Reliability) Adoption
Likelihood
ToU
Adoption Likelihood
Sample Sizes
18% *
8%
11%
n=49
n=27
n=22
n/a
n=22
ToU
n=27
n=49
CPP w/ Tech
n=27
n=49
CPP
n=27
n=49
Interruptible Rate (Reliability)
19% *
18%
n=27
30% *
39% *
n=4
n=10
DLC (insufficient (insufficient sample)
sample)
Adoption likelihood is defined as the percentage of respondents who rate each plan an 8 or higher. Incentive levels within each plan type are aggregated: e.g., if 8 of 10 accept at a high incentive and 2 of 10 accept at a lower level, the aggregated adoption likelihood would be 50%.
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Appendix C:
Market Research Questionnaires
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Xcel Energy Minnesota DR Market Potential – Residential 100813 – CLEAN FIELD FINAL VERSION INTRODUCTION
This survey is about how you receive and use electricity. Like most other things, the options that are available to you in
the way that you manage and use electricity may be changing, and this survey asks you about some of those possible
changes.
All of the information provided in this survey will be kept strictly confidential, and at no time will you be asked to purchase
anything.
If you need to discontinue the survey at any time, you can come back later and begin again where you left off. Simply
save your personalized link to access your survey again. The survey will automatically take you to the point where you
left off.
We’ll start by asking you just a few questions to see if you qualify for our survey.
SCREENER
S1.
In which state do you live?
[DROP DOWN LIST OF US STATES]
[IF S1=Minnesota, Wisconsin, North Dakota, South Dakota, or Michigan -- ASK S2, OTHERWISE TERMINATE]
S2.
And what is the zip code where you live?
[ENTER 5 DIGIT ZIP CODE. QUALIFYING ZIPS ARE IN TABLE BELOW.]
44947 49245 49247 49910 49911 49925 49938 49947 49949 49959 49967 49968 51016 51770 53333 53545 54001 54002 54004 54005 54007 54009 54011 54013 54014
54015
54016
54017
54018
54020
54021
54022
54023
54024
54025
54026
54027
54028
54082
54211
54405
54411
54420
54421
54422
54425
54426
54433
[IF S2 = QUALIFYING ZIP CODE (SEE LIST), ASK S3, OTHERWISE TERMINATE]
S3.
Are you or is anyone in your household employed by the following types of companies?
Please select all that apply:
1. Advertising
2. Broadcasting
3. Electric or natural gas utility
4. Environmental Protection
5. Manufacturing
6. Market research
7. Public transit provider
8. Public relations
9. Residential real estate company
10. Government / Governmental agency
11. None of the above
[IF S3 = 5, 7, 9-11, CONTINUE, OTHERWISE TERMINATE]
S4.
Which of the following categories represents your current age?
1. Less than 18 years old
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2.
3.
4.
5.
6.
7.
8.
18-24
25-34
35-44
45-54
55-64
65-74
75 or more years old
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[IF S4 = 2 -7, CONTINUE, OTHERWISE, TERMINATE]
S5.
What is your gender?
1. Male
2. Female
S6.
Which of the following best describes how your household is billed for electricity?
1. Our household is billed directly for electricity by our local utility
2. Electricity is included as part of my rent or condo fee; our household does not receive a separate electric
bill
3. Don’t know
[IF S6 = 1, CONTINUE, OTHERWISE TERMINATE]
S7.
Do you own or rent your residence?
1. Own / buying
2. Rent / lease
3. Neither
4. Refused
[IF S7=1 OR 2, CONTINUE, OTHERWISE TERMINATE]
S8.
How involved are you in decisions about the way that your household uses energy, including decisions about
whether or not to participate in energy-related programs or services that might be offered by your electric utility
provider?
1. I am personally responsible for these types of decisions
2. I share these types of decisions with others
3. I am not significantly involved in decisions like these
[IF S8 = 1 OR 2, CONTINUE; OTHERWISE TERMINATE]
S9.
What company provides your home with electricity?
[RANDOMIZE 1 THROUGH 4 BELOW]
1.
2.
3.
4.
5.
Minnesota Power
Alliant
Otter Tail Power
Xcel Energy
Some other company or organization [PLEASE SPECIFY ______________________]
[IF S9=4, CONTINUE, OTHERWISE TERMINATE]
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S10.
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What is the approximate square footage of your home? Please include only heated living space in your response.
If you are not certain, please give your best estimate.
1.
2.
3.
4.
5.
6.
7.
8.
9.
S11.
Less than 500 sq. ft.
500 – 999
1,000 – 1,499
1,500 – 1,999
2,000 – 2,499
2,500 – 2,999
3,000 – 3,499
3,500 – 3,999
4,000 sq. ft. or more
During the summer months, about how much is your summer electric bill?
If you are not certain, please give your best estimate.
1.
2.
3.
4.
5.
S12.
Less than $50
$50 - $99
$100 - $149
$150 - $199
$200 or more
Which of the following best describes your home?
1. Single-family house detached from any other houses
2. Single-family house attached to one or more houses
3. Multi-family house or building with 2-4 apartments/units
4. Multi-family house or building with 5 or more apartments/units
5. Mobile/manufactured home
990. Other [SPECIFY]
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QUOTAS
Total sample size of 400
HOUSING TYPE
VERSION A - Single
Family
N=200
Minimum Maximum
VERSION B - MultiFamily
N=200
Minimum Maximum
A. Single-family (S12 = 1 OR 2)
65
135
65
135
B. Multi-family (S12 = 3 OR 4)
65
135
65
135
VERSION A - Single
Family
N=200
REGION (These are goals - will
monitor)
Minnesota
(74-75%)
N. Dakota
(5-6%)
S. Dakota
(4-5%)
Wisconsin
(13-14%)
Michigan
(Try for 1%)
Gender (S5)
Minimum
Maximum
Minimum
Maximum
148
10
8
26
2
152
12
10
29
3
148
10
8
26
2
152
12
10
29
3
Minimum
Maximum
Minimum
Maximum
150
150
250
250
150
150
250
250
Minimum
Maximum
Minimum
Maximum
20
40
20
40
Male
Female
Age (S4)
Over 65 (Min 10% Max 20%)
Bill Size (S10)
Square Footage (S9)
VERSION B - MultiFamily
N=200
Monitor
Monitor
Monitor
Monitor
PROGRAMMER: THERE ARE TWO SECTIONS (P3‐P14 AND P15‐P26); EACH RESPONDENT RECEIVES EITHER SECTION A OR SECTION B; RANDOMLY ASSIGN RESPONDENTS TO SECTIONS. THERE IS A FILTER BUILT IN BEFORE P1 FOR SOME RESPONDENTS THOUGH, WHO WILL JUMP INTO THEIR RESPECTIVE SECTION AT A MIDWAY POINT (P6 OR P18). [PRICES TESTED: A (LOWER COSTS) BLOCK] [PRICING SECTION A: P3 – P14 (PRICE POINTS 1, 2, AND 3)] [Saver’s Switch: $5, $9, $14] [CPP: 6%, 8%, 11%] [CPP W/ TECH: 8%, 11%, 15%] [TOU: 4%, 6%, 10%] [PRICES TESTED: B (UPPER COSTS) BLOCK] [PRICING SECTION B: P15 – P26 (PRICE POINTS 3, 4, and 5)] [Saver’s Switch: $14, $18, $25] [CPP: 11%, 13%, 15%] [CPP W/ TECH: 15%, 17%, 20%] [TOU: 10%, 12%, 14%] 2016 – 2030 Upper Midwest Resource Plan
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TERMINATE LANGUAGE FOR NON‐QUALIFYING RESPONDENTS We truly appreciate your time and effort in responding to our survey invitation and answering these initial questions, which were designed to see if you are eligible to participate. In order to achieve a representative sample, quotas with specific criteria have been designated. At this point, we have reached the number of respondents we can accept from individuals with your type of experience or background. Again, we would like to thank you for your time and effort. INVITATION LANGUAGE FOR QUALIFYING RESPONDENTS Thank you for your responses so far! You qualify for the survey, which is being sponsored by Xcel Energy. As we indicated earlier, only a limited number of individuals have been invited to participate in this survey, so we appreciate your time in filling it out as completely as possible. Your answers will help Xcel Energy to design energy programs that work better for all customers. The survey should take no more than about 15‐20 minutes to complete. Your responses are important to us, so please press “Continue” to begin answering the survey questions. All information provided in this survey will be kept strictly confidential, and at no time will you be asked to purchase anything. If you need to discontinue the survey at any time, you can come back later and begin again where you left off. Simply save your personalized link to access your survey again. The survey will automatically take you to the point where you left off. As you complete the survey, you will not be able to use your browser’s “back” button. If you mistakenly press your browser’s “back” button, you will need to press the “refresh” button to continue the survey. 2016 – 2030 Upper Midwest Resource Plan
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I – ATTITUDES Q1. Overall, how familiar would you say you are with Xcel Energy as your electric utility? [RECORD NUMBER; 1=NOT AT ALL FAMILIAR, 10=EXTREMELY FAMILIAR] Not at all familiar 1 2 3 4 5 6 7 8 Extremely familiar 9 10     



 
Q2. Using a 10‐point scale where ‘1’ means you strongly disagree, and ‘10’ means you strongly agree, please indicate how much your household agrees or disagrees with each of the following statements about Xcel Energy. Note: If you don’t feel like you are very familiar with Xcel Energy on any of the following, please just give your best guess. Xcel Energy is… [RECORD NUMBER; 1=STRONGLY DISAGREE, 10=STRONGLY AGREE] Strongly disagree [ROTATE 1‐4] 1 2 3 4 5 6 1. …a leader in energy conservation       and energy efficiency      
2. …a company that can be trusted 3. …a credible information source       for the community on energy issues 4. …a company that actively       promotes programs to help its customers save money 7 8 Strongly agree 9 10     
           Q3. Overall, how satisfied would you say your household is with the service provided by Xcel Energy? [RECORD NUMBER; 1=NOT AT ALL SATISFIED, 10=EXTREMELY SATISFIED] Not at all satisfied 1 2 3 4 5 6 7 8 Extremely satisfied 9 10     



 
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Q4. Using a 10‐point scale, where ‘1’ means it is not at all important and ‘10’ means it is extremely important, please indicate how important it is to your household that Xcel Energy do the following things, even if that means you would have to pay a little more in order for the company to pursue these types of initiatives. [RECORD NUMBER; 1=NOT AT ALL IMPORTANT, 10=EXTREMELY IMPORTANT] Not at all important
1 2 3 [ROTATE 1‐2] 4 5 6 7 Extremely important
8 9 10 1. Actively encourage its customers to participate in energy saving and cost saving programs           2. Operate its business in a completely environmentally friendly manner           Q5. Considering the types of initiatives we asked about in the previous question, which would you prefer your electric utility do…? PLEASE SELECT ONE 1. Pursue these and other initiatives even if you would have to pay a little more 2. Do everything possible to keep energy costs as low as possible 3. Both are equally important 2016 – 2030 Upper Midwest Resource Plan
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Q6. We’d like to understand how your household as a whole thinks about using energy at your home. Using a 10‐point scale where ‘1’ means you strongly disagree, and ‘10’ means you strongly agree, please indicate how much you agree or disagree with each of the following statements. [RECORD NUMBER; 1=STRONGLY DISAGREE, 10=STRONGLY AGREE] [ROTATE 1‐9] 1. Comfort is very important to your household – even if it means spending more each month for energy 2. Saving money on energy costs is something you focus on every day 3. Realistically, there isn’t much you can do to save money on energy costs 4. You just want to be left alone to use energy however you want in your home 5. You are very concerned about the environmental effects of electric power plants 6. Conserving energy at your home will make no difference to the quality of the environment overall 7. You would do more to make your home more energy efficient, but you don’t know where to start 8. The threat from global warming is real, and significant 9. You are an “early adopter” of new home technologies Strongly disagree 1 2 3 4 5 6 7 8 Strongly
agree
9 10                                                                                           II – The Way You Use Electricity Q7. Which of the following best describes how you are billed for electricity? Please select the one response that best describes your current billing method. 1. We pay the same amount for each unit of electricity we use, regardless of when we use it 2. We pay more for each unit of electricity as we use more electricity (the price of each unit goes up as we use more) 3. We pay more for the electricity we use at certain times of the year 4. We pay more for the electricity we use at certain times of the day, at least for some part of the year 5. Not sure 2016 – 2030 Upper Midwest Resource Plan
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Q8.
We know that not everyone in any given household acts the same way. Thinking of your entire household, however, which of the following best describes your household’s overall approach to managing energy use around your home on a day‐to‐day basis? Please select one response. 1. People in my household consistently and actively look for ways to limit our electricity use every single day – making sure lights or other appliances are off when they are not in use, actively monitoring heating / cooling levels to make sure they are appropriate, and even making sure to unplug things like phone chargers when they are not being used 2. My household really does try to limit our electricity use as much as is reasonable, but we are not as systematic about this as some households might be 3. We care about using only as much electricity as we need, but we don’t really focus on minimizing our use. 4. Limiting our use of electricity on a day‐to‐day basis is not really something we worry about. Q9.
Which of the following best describes your household’s approach to buying new appliances, light bulbs, or other devices that use electricity? Please select one response. Q10. 1. We always make sure to get the highest energy efficient option available 2. We get the highest efficiency option that we can, as long as it meets our other needs 3. We take energy efficiency into account, but we don’t always get the most efficient option available 4. We don’t really take energy efficiency into account that much when we buy new appliances or devices 5. We really don’t take energy efficiency into account at all What is the primary type of fuel you use for each of the purposes listed below? Primary Fuel Type 1. 2. 3. Electricity Natural gas Propane
(piped gas) 4. Something else [SPECIFY] 5. 6. Not Not sure applicable 1. Hot water heating for your home       2. Cooking       3. Clothes dryer       Q11. Who is billed by your electric company for air conditioning or cooling all or some of the space in your house or unit, including any fans or dehumidifiers, etc.? 1.
2.
3.
4.
Your household Someone else (e.g., landlord, property manager) Not sure Not used in your home 2016 – 2030 Upper Midwest Resource Plan
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[IF Q11=1‐3, CONTINUE, OTHERWISE, SKIP TO SECTION III INTRO] Q12. Which of the following do you use to cool your home? Please select all that apply. 1.
2.
3.
4.
5.
6.
7.
A central air conditioner or heat pump An evaporative (or “swamp”) cooler One or more window / wall air conditioners Ceiling / portable fans Attic / whole house fan Something else None / nothing III – INTEREST IN POTENTIAL ENERGY MANAGEMENT PROGRAMS THAT COULD BE OFFERED BY XCEL ENERGY The next section of the survey asks for your reaction to a wide variety of energy management programs that Xcel Energy may offer to customers like you. For each of the programs you will see, we would like to know how likely you think your household would be to participate in the program. As you may know the demand for electricity tends to peak at certain times of the day and year. The rates that all customers pay could be better managed if it were possible to reduce electricity usage at those peak times. The energy management programs you will see here are designed to help manage those peaks in energy usage by rewarding customers who are able to change, or shift, their energy usage away from those peaks. [IF Q11‐1 AND Q12=1, ASK P1; OTHERWISE, SKIP TO P6 OR P18 – NOT INTRO BEFORE P6 OR P18] [PROGRAMMER, SEE NOTES BEFORE P3 – THERE ARE TWO SECTIONS THAT SHOULD BE RANDOMIZED] P1. One program currently offered by Xcel Energy is called the Saver’s Switch Program. Under this plan, Xcel Energy installs a device on your central air conditioner that allows them to turn off the unit at 15‐20 minute intervals between the hours of 2 pm and 7 pm on 5‐10 of the hottest summer weekday afternoons. In return for participating in this program, customers receive savings on their summer electric bills. Are you currently participating in Xcel Energy’s Saver’s Switch Program? 1. Yes 2. No / Not sure [IF P1=2, SKIP TO EITHER P3 OR P15 IN APPROPRIATE PRICING SECTION (A OR B); IF P1=1, SKIP TO EITHER INTRO BEFORE P6OR INTRO BEFORE P18 IN APPROPRIATE SECTION] [PROGRAMMER NOTE: THERE ARE TWO SECTIONS BELOW (P3‐P14 AND P15‐P26); EACH RESPONDENT RECEIVES EITHER SECTION A OR SECTION B; RANDOMLY ASSIGN RESPONDENTS TO SECTIONS] 2016 – 2030 Upper Midwest Resource Plan
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[PRICING SECTION A: P3 – P14 (PRICE POINTS 1, 2, AND 3)] P3. If you were likely to see an average savings of $9 off of your electric bill for each summer month as a result of participating in the Saver’s Switch Program, how likely would you be to participate? Remember that, under the program, Xcel Energy would install a switch on your primary air conditioner that would allow the company to turn off your AC system at 15‐20 minute intervals on 5‐10 of the hottest summer days from 2 pm to 7 pm. Please note that we are using a 0‐10 scale. [PROGRAMMER: 0‐10 SCALE WHERE “0” = NOT AT ALL LIKELY TO PARTICIPATE, “10”=VERY LIKELY TO PARTICIPATE] [ASK IF P3 = 0‐5, OTHERWISE SKIP TO P5] P4. And if you would see an average bill savings of $14 off of your electric bill for each summer month as a result of participating in the same Saver’s Switch program, how likely would you be to participate? [PROGRAMMER: 0‐10 SCALE WHERE “0” = NOT AT ALL LIKELY TO PARTICIPATE, “10”=VERY LIKELY TO PARTICIPATE] [IF P3=6‐10, ASK P5; OTHERWISE SKIP TO INTRO BEFORE P6] P5. And if you would see an average bill savings of $5 off of your electric bill for each summer month as a result of participating in the same Saver’s Switch program, how likely would you be to participate? [PROGRAMMER: 0‐10 SCALE WHERE “0” = NOT AT ALL LIKELY TO PARTICIPATE, “10”=VERY LIKELY TO PARTICIPATE] Now, we’d like to ask how interested you would be in different rate options that could make it possible for you to lower your overall electricity bill. P6. First, consider an electricity rate in which the price you pay for electricity more closely connects to the price of producing that electricity. This rate is called a “critical peak pricing” rate. Under this rate, the price that you pay for electricity would vary during certain times of the day. Specifically: o During “off‐peak” hours – which account for most hours of the day and year – the price you pay for electricity would be less than you pay now o On approximately 10 days each summer – days when the demand for electricity is especially high – critical peak pricing would be in effect from 2pm to 8pm and the cost for electricity would be several times as much as it is during regular off‐peak periods With an electricity rate like this, you could lower your monthly electric bill by as much as 8% if you chose to reduce or move some of your electricity use away from peak hours on all of those 10 days each summer. If you did not, or were not able to, move your electricity use away from these peak hours, your savings would be lower, and you might actually see a slightly higher bill. 2016 – 2030 Upper Midwest Resource Plan
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Using a 0‐10 scale, with 0 being “Not at all interested” and 10 being “Extremely interested”, if this electricity rate was available to you, how interested would you be in signing up for it? Not At All Interested In Signing Up 0 1 2 3 [IF P6=0‐5, ASK P7; OTHERWISE SKIP TO P8] P7. 4 5 6 7 Extremely Interested In Signing Up 8 9 10 Now, consider the same basic rate that you just evaluated, but under this scenario, you could lower your monthly electric bill by as much as 11% if you reduced or moved some of your electricity use away from summer peak hours on the 10 summer days on which peak prices occurred. Remember that if you did not move your electricity usage away from the peak periods of 2 pm to 8 pm on the 10 critical peak days, your savings would be lower, and you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P6=6‐10, ASK P8; OTHERWISE SKIP TO P9] P8. P9. Now, consider the same basic rate that you just evaluated, but under this scenario, you could lower your monthly electric bill by as much as 6% if you reduced or moved some of your electricity use away from summer peak hours on the 10 summer days on which peak prices occurred. Remember that if you did not move your electricity usage away from the peak periods of 2 pm to 8 pm on the 10 critical peak days, your savings would be lower, and you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 Now, please consider the same “critical peak pricing” rate you have been thinking about, only this time, you would be offered some new technology that would help you to respond automatically to changes in the price of electricity. Your utility could install a communicating thermostat, for example, that could be set up ahead of time to automatically change your air conditioner settings to the levels that you want to have whenever critical peak prices occur. With this kind of automated technology, and this type of rate, you might find it easier to lower your monthly electric bill by as much as 11% by reducing or moving some of your electricity use away from the peak hours of 2 pm to 8 pm on those 10 days each summer. Since the technology is automated, it would mean that it would be easier for you to respond as you want during these peak pricing days. 2016 – 2030 Upper Midwest Resource Plan
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Using a 0‐10 scale, with 0 being “Not at all interested” and 10 being “Extremely interested”, if this electricity rate was available to you, how interested would you be in signing up for it? Not At All Interested In Signing Up 0 1 2 3 4 5 6 7 Extremely Interested In Signing Up 8 9 10 [IF P9=0‐5, ASK P10; OTHERWISE SKIP TO P11] P10. Now, think again about the same rate that you just evaluated, and assume that you would still be offered the technology that would help you respond to those prices in an automated way. Under this scenario, however, imagine that you could lower your monthly electric bill by as much as 15% if you reduced or moved some of your electricity use away from peak hours on those 10 days each summer. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P9=6‐10, ASK P11; OTHERWISE SKIP TO P12] P11. P12. Now, think again about the same rate that you just evaluated, and assume that you would still be offered the technology that would help you respond to those prices in an automated way. Under this scenario, however, imagine that you could lower your monthly electric bill by as much as 8% if you reduced or moved some of your electricity use away from peak hours on those 10 days each summer. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 Now, consider another, similar rate that is called a “Time of Use” rate. Under this rate, during the “peak hours” hours of 2pm to 8pm, Monday through Friday, during the summer (June to September) the price you pay for electricity would be higher than what you pay now (in fact, about twice what you pay now). At all other hours, however, the price you pay for electricity would be less than you pay now. Unlike the Critical Peak Pricing rate, this rate does not have any critical peak days, and you would not be offered any technology that would help to respond to any price changes. With an electricity rate like this, you could lower your monthly electric bill by as much as 6% if you chose to reduce or move some of your electricity use away from summer peak hours. If you did not, or were not able to, move your electricity use away from these peak hours, your savings would be lower, and you might actually see a slightly higher bill. 2016 – 2030 Upper Midwest Resource Plan
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Using the 0‐10 scale where 0 is “Not at all interested” and 10 is “Extremely interested”, please indicate how interested you would be in signing up, if this electricity rate was available to you. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P12=0‐5, ASK P13; OTHERWISE SKIP TO P14] P13. Now, thinking about this Time of Use rate again, imagine that you could lower your monthly electric bill by as much as 10% if you chose to reduce or move some of your electricity use away from summer peak hours. Remember that if you did not move your electricity usage away from the weekday peak periods of 2 pm to 8 pm, your savings would be lower, and you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Extremely Not At All Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P12=6‐10, ASK P14; OTHERWISE SKIP TO D1] P14. Now, thinking about this Time of Use rate again, imagine that you could lower your monthly electric bill by as much as 4% if you chose to reduce or move some of your electricity use away from summer peak hours. Remember that if you did not move your electricity usage away from the weekday peak periods of 2 pm to 8 pm, your savings would be lower, and you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Extremely Not At All Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 2016 – 2030 Upper Midwest Resource Plan
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[PRICING SECTION B: P15 – P26 (PRICE POINTS 3, 4, and 5)] P15. If you were likely to see an average savings of $18 off of your electric bill for each summer month as a result of participating in the Saver’s Switch Program, how likely would you be to participate? Remember that, under the program, Xcel Energy would install a switch on your primary air conditioner that would allow the company to turn off your AC system at 15‐20 minute intervals on 5‐10 of the hottest summer days from 2 pm to 8 pm. Please note that we are using a 0‐10 scale. [PROGRAMMER: 0‐10 SCALE WHERE “0” = NOT AT ALL LIKELY TO PARTICIPATE, “10”=VERY LIKELY TO PARTICIPATE] [ASK IF P15 = 0‐5, OTHERWISE SKIP TO P17] P16. And if you would see an average bill savings of $25 off of your electric bill for each summer month as a result of participating in the same Saver’s Switch program, how likely would you be to participate? [PROGRAMMER: 0‐10 SCALE WHERE “0” = NOT AT ALL LIKELY TO PARTICIPATE, “10”=VERY LIKELY TO PARTICIPATE] [IF P15=6‐10, ASK P17; OTHERWISE SKIP TO INTRO BEFORE P18] P17. And if you would see an average bill savings of $14 off of your electric bill for each summer month as a result of participating in the same Saver’s Switch program, how likely would you be to participate? [PROGRAMMER: 0‐10 SCALE WHERE “0” = NOT AT ALL LIKELY TO PARTICIPATE, “10”=VERY LIKELY TO PARTICIPATE] Now, we’d like to ask how interested you would be in different rate options that could make it possible for you to lower your overall electricity bill. P18. First, consider an electricity rate in which the price you pay for electricity more closely connects to the price of producing that electricity. This rate is called a “critical peak pricing” rate. Under this rate, the price that you pay for electricity would vary during certain times of the day. Specifically: o During “off‐peak” hours – which account for most hours of the day and year – the price you pay for electricity would be less than you pay now o On approximately 10 days each summer – days when the demand for electricity is especially high – critical peak pricing would be in effect from 2pm to 8pm and the cost for electricity would be several times as much as it is during regular off‐peak periods With an electricity rate like this, you could lower your monthly electric bill by as much as 13% if you chose to reduce or move some of your electricity use away from peak hours on all of those 10 days each summer. If you did not, or were not able to, move your electricity use away from these peak hours, your savings would be lower, and you might actually see a slightly higher bill. 2016 – 2030 Upper Midwest Resource Plan
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Using a 0‐10 scale, with 0 being “Not at all interested” and 10 being “Extremely interested”, if this electricity rate was available to you, how interested would you be in signing up for it? Not At All Interested In Signing Up 0 1 2 3 4 [IF P18=0‐5, ASK P19; OTHERWISE SKIP TO P20] P19. 5 6 7 Extremely Interested In Signing Up 8 9 10 Now, consider the same basic rate that you just evaluated, but under this scenario, you could lower your monthly electric bill by as much as 15% if you reduced or moved some of your electricity use away from summer peak hours on the 10 summer days on which peak prices occurred. Remember that if you did not move your electricity usage away from the peak periods of 2 pm to 8 pm on the 10 critical peak days, your savings would be lower, and you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P18=6‐10, ASK P20; OTHERWISE SKIP TO P21] P20. Now, consider the same basic rate that you just evaluated, but under this scenario, you could lower your monthly electric bill by as much as 11% if you reduced or moved some of your electricity use away from summer peak hours on the 10 summer days on which peak prices occurred. Remember that if you did not move your electricity usage away from the peak periods of 2 pm to 8 pm on the 10 critical peak days, your savings would be lower, and you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 P21. Now, please consider the same “critical peak pricing” rate you have been thinking about, only this time, you would be offered some new technology that would help you to respond automatically to changes in the price of electricity. Your utility could install a communicating thermostat, for example, that could be set up ahead of time to automatically change your air conditioner settings to the levels that you want to have whenever critical peak prices occur. With this kind of automated technology, and this type of rate, you might find it easier to lower your monthly electric bill by as much as 17% by reducing or moving some of your electricity use away from the peak hours of 2 pm to 8 pm on those 10 days each summer. Since the technology is automated, it would mean that it would be easier for you to respond as you want during these peak pricing days. 2016 – 2030 Upper Midwest Resource Plan
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Using a 0‐10 scale, with 0 being “Not at all interested” and 10 being “Extremely interested”, if this electricity rate was available to you, how interested would you be in signing up for it? Not At All Interested In Signing Up 0 1 2 3 4 [IF P21=0‐5, ASK P22; OTHERWISE SKIP TO P23] P22. 5 6 7 Extremely Interested In Signing Up 8 9 10 Now, think again about the same rate that you just evaluated, and assume that you would still be offered the technology that would help you respond to those prices in an automated way. Under this scenario, however, imagine that you could lower your monthly electric bill by as much as 20% if you reduced or moved some of your electricity use away from peak hours on those 10 days each summer. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P21=6‐10, ASK P23; OTHERWISE SKIP TO P24] P23. P24. Now, think again about the same rate that you just evaluated, and assume that you would still be offered the technology that would help you respond to those prices in an automated way. Under this scenario, however, imagine that you could lower your monthly electric bill by as much as 15% if you reduced or moved some of your electricity use away from peak hours on those 10 days each summer. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 Now, consider another, similar rate that is called a “Time of Use” rate. Under this rate, during the “peak hours” hours of 2pm to 8pm, Monday through Friday, during the summer (June to September) the price you pay for electricity would be higher than what you pay now (in fact, about twice what you pay now). At all other hours, however, the price you pay for electricity would be less than you pay now. Unlike the Critical Peak Pricing rate, this rate does not have any critical peak days, and you would not be offered any technology that would help to respond to any price changes. With an electricity rate like this, you could lower your monthly electric bill by as much as 12% if you chose to reduce or move some of your electricity use away from summer peak hours. If you did not, or were not able to, move your electricity use away from these peak hours, your savings would be lower, and you might actually see a slightly higher bill. 2016 – 2030 Upper Midwest Resource Plan
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Using the 0‐10 scale where 0 is “Not at all interested” and 10 is “Extremely interested”, please indicate how interested you would be in signing up, if this electricity rate was available to you. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P24=0‐5, ASK P25; OTHERWISE SKIP TO P26] P25. Now, thinking about this Time of Use rate again, imagine that you could lower your monthly electric bill by as much as 14% if you chose to reduce or move some of your electricity use away from summer peak hours. Remember that if you did not move your electricity usage away from the weekday peak periods of 2 pm to 8 pm, your savings would be lower, and you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Extremely Not At All Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P24=6‐10, ASK P26; OTHERWISE SKIP TO D1] P26. Now, thinking about this Time of Use rate again, imagine that you could lower your monthly electric bill by as much as 10% if you chose to reduce or move some of your electricity use away from summer peak hours. Remember that if you did not move your electricity usage away from the weekday peak periods of 2 pm to 8 pm, your savings would be lower, and you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Extremely Not At All Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 2016 – 2030 Upper Midwest Resource Plan
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IV – HOUSEHOLD CHARACTERISTICS In order to help us classify your responses, the last few questions are on your household’s characteristics. D1. Including yourself, how many individuals normally live in your home? Please do not include anyone who is just visiting, or not currently living with you due to their enrollment in college and/or military service." [RECORD NUMBER 1‐20] individuals D2. Are there any individuals in your home that regularly stay at home during the day on all or most weekdays? 1. Yes 0. No D3. For about how many years have you lived in your present home? Your best estimate is fine, but please enter a whole number rather than a range of numbers. 1. Less than 1 year 2. [RECORD NUMBER 1‐100] years D4. How many bedrooms are in your home? 0. 0 / Studio/Efficiency apartment / SRO 1. 1 2. 2 3. 3 4. 4 5. 5 6. 6 or more D5. Which of the following best characterizes the city / town / community in which you live? 1. Urban 2. Suburban 3. Rural D6. What is the highest level of education you have completed? 1. Less than a high school degree 2. High school degree 3. Technical/trade school program 4. Associates degree or some college 5. Bachelors degree 6. Graduate / professional degree, e.g., J.D., MBA, MD, etc. 7. Professional certification, e.g., CPA, CNP, etc. 2016 – 2030 Upper Midwest Resource Plan
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D8. D8. D9. What is your current employment status? 1. Employed full‐time 2. Employed part‐time 3. Not currently employed 4. Retired 5. Disabled / Receiving disability benefits 990. Other [SPECIFY] Which of the following categories includes your household’s total annual income before taxes in 2012? Please include the income of all people living in your home in this figure. 1. Less than $60,000 2. $60,000 or more Which of the following categories includes your household’s total annual income before taxes in 2012? Please include the income of all people living in your home in this figure. [IF D8=1, DISPLAY OPTIONS 1‐7 AND 13; IF D8=2, DISPLAY OPTIONS 8‐13] 1. Less than $10,000 2. $10,000 – $14,999 3. $15,000 – $19,999 4. $20,000 – $29,999 5. $30,000 – $39,999 6. $40,000 –$49,999 7. $50,000 – $59,999 8. $60,000 – $74,999 9. $75,000 – $99,999 10. $100,000 – $124,999 11. $125,000 – $149,999 12. $150,000 or more 13. Prefer not to say D11. When thinking about your household’s current financial situation compared to what it was a year ago, would you say that overall your current financial situation is…? 1. Better than it was a year ago 2. The same as it was a year ago 3. Worse than it was a year ago 4. Prefer not to say D12. When thinking about your household’s current financial situation compared to what you anticipate it will be in a year from now, would you say that overall your anticipated financial situation in a year from now will be…? 2016 – 2030 Upper Midwest Resource Plan
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1. Better than your current financial situation 2. The same as your current financial situation 3. Worse than your current financial situation 4. Prefer not to say D13. Which of the following best describes your race or ethnic background? 1. White, Caucasian 2. Black, African American, Caribbean American 3. American Indian (Native American), Alaska Native 4. Asian 6. Hispanic, Latino 5. Native Hawaiian, Pacific Islander 990. Other [SPECIFY] 7. Prefer not to say Thank you for taking the time to answer our survey questions. Have a nice day! If you would like information on how your household can save money on energy bills, please visit Xcel Energy at www.xcelenergy.com. 2016 – 2030 Upper Midwest Resource Plan
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Brattle Xcel Energy MN DR Interest – Small Business Questionnaire 092613 READ IN SAMPLE INFORMATION STRATA: 1=SMALLER (LESS THAN 25 KW) SERVICE_ADD (ADDRESS) OTHER FIELDS TBD WHEN SAMPLE RECEIVED, BUT WILL INDICATE BUSINESS NAME, BILLING ADDRESS, PHONE NUMBER AND OTHER FIELDS] QUOTAS: STRATA=1: SMALLER (LESS THAN 25 KW); N=200 INTRODUCTION Hello. My name is ___________________ and I’m calling from _____________, conducting a market research study for Xcel Energy. I’d like to speak to the person who is responsible for making energy‐related decisions at [SERVICE_ADD]. [WHEN YOU REACH THE RIGHT PERSON – REINTRODUCE AS APPROPRIATE] Hello. My name is ___________________ and I’m calling from _____________, conducting a market research study for Xcel Energy. We are conducting a market research study today for Xcel Energy. The goal of the study is to help Xcel Energy to deliver programs that enable its customers to use energy more cost effectively. Your answers to this survey will help the company to improve these programs. Your business is one of a small number being asked to respond to the survey. I would like to ask you a few questions first to make sure that your business qualifies for our survey. If you do qualify and are able to complete the survey, you will be compensated for your time. It should only take a couple of minutes to see if you qualify for the survey. [IF NEEDED: If you qualify for and complete the survey, we will send you a check for $25. We first need to ask you a few questions to make sure your business qualifies for participation. If you do qualify, you will then be invited to complete the full survey. S1. While this may not be the address where you are located, all of my questions here will be about your company’s operation at [SERVICE_ADD]. Is this a facility about which you are knowledgeable? [DO NOT READ; SELECT ONE] 1. Yes 2. No – not an address at which this business operates – [POLITELY TERMINATE] 3. No – the business operates at that address but they are not knowledgeable about it [GET REFERRAL AND RESTART AT BEGINNING] S2. Does your operation at this location occupy any enclosed space, or is it an outdoor structure or operation, such as a billboard, a parking lot, a communications tower, or the like? Is it… 1. ONLY an enclosed space 2016 – 2030 Upper Midwest Resource Plan
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2. ONLY an outdoor structure or facility – [POLITELY TERMINATE] 3. or does it include both an enclosed space AND an outdoor structure or operation? S3. S4. Which of the following statements best describes your role in making energy‐related decisions for your operations at this location. By energy‐related decisions, we mean things like deciding whether or not your company might participate in a new electric rate option that might be offered by Xcel Energy. 1. I am the person who would make that decision 2. I am one of a group of people who would contribute to that decision. 3. I am not a decision maker, but I would be knowledgeable about, or involved in, those decisions. 4. I would not be involved in that type of decision in a meaningful way. [ASK FOR REFERRAL TO SOMEONE WHO WOULD BE INVOLVED IN THESE DECISIONS – RESTART AS APPROPRIATE ABOVE] What type of facility does your organization occupy or operate at this location? [INTERVIEWER: ONLY READ CATEGORIES AS NECESSARY TO CLARIFY] 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. Office (finance, insurance, real estate, law, etc.) Retail (department stores, services, boutiques, etc.) Grocery (supermarkets, convenience store, market, etc.) Restaurant / food service (sit‐down, fast food, coffee shop, etc.) Warehouse School (day care, pre‐school, elementary, secondary) College, university or trade school Health Care (health practitioner office, hospital, urgent care center, etc.) Nursing home / assisted living facility / residential treatment facility Lodging / housing facility (hotel, motel, bed and breakfast, apartment building, etc.) Not‐for profit housing facility (shelter, prison, jail, etc.) Entertainment / recreation facility (movie theater, bowling alley, health club/gym, library, museum, etc.) 13. Public assembly facility (convention / conference center, etc.) 14. Worship (church, temple, etc.) 15. Multi‐use or shopping mall (i.e., mixed use of space for offices, restaurants, stores, service, apartments, etc.) [INTERVIEWER NOTE: USE AS LITTLE AS POSSIBLE – TRY TO FOCUS ON PRIMARY USE; THAT WHICH ACCOUNTS FOR 75%+ OF SPACE] 16. Manufacturing, production, or processing facility (including for‐profit businesses and governmental facilities) 17. Agricultural (farms, ranches, dairies, greenhouses, nurseries, orchards, hatcheries, etc.) 990. Other [SPECIFY] [PROGRAMMER NOTE: MAXIMUM COMPLETE QUOTA OF 20 WHO ANSWER S4=6 (SCHOOL) 2016 – 2030 Upper Midwest Resource Plan
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TERMINATE TEXT Thank you for your help but, at this point, we have reached the number of respondents we can accept from companies like yours. Again, we would like to thank you for your time and effort. Have a nice day! INVITATION LANGUAGE FOR QUALIFYING RESPONDENTS Thank you for your responses so far. You and your business have qualified to complete this survey, which should take about 20 minutes to complete. Once you complete the survey you will be eligible to receive the $25 ‘thank you’ payment. Of course, if your company’s policies require that you decline the payment you can do so, or you can direct us to donate it to Habitat for Humanity. Is this a good time for you to continue? 1. YES –CONTINUE 2. NO – SCHEDULE APPT. [PRICES TESTED: A (LOWER) BLOCK] [Saver’s Switch: $1 / ton, $3 / ton, $4 / ton] [CPP: 6%, 8%, 11%] [CPP W/ TECH: 8%, 11%, 15%] [TOU: 4%, 6%, 10%] [DEMAND BIDDING: 10 cents/kWh, 30 cents/kWh, 50 cents/kWh] [PRICES TESTED: B (UPPER) BLOCK] [Saver’s Switch: $4 / ton, $5 / ton, $7 / ton] [CPP: 11%, 13%, 15%] [CPP W/ TECH: 15%, 17%, 20%] [TOU: 10%, 12%, 14%] [DEMAND BIDDING: 50 cents/kWh, 75 cents/kWh, $1/kWh] 2016 – 2030 Upper Midwest Resource Plan
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Please note that all of my questions will be about your company’s operations at [SERVICE_ADD] Q1. Does your business own or lease the building space at this location? [INTERVIEWER: IF RESPONDENTS SAYS THEY LEASE SOME SPACE AND OWN SOME SPACE AT THIS LOCATION, ASK WHICH ACCOUNTS FOR THE MAJORITY OF THE SPACE HERE] 1. Own (or in the process of buying it) 2. Lease / rent Q2. Approximately how many employees work at this location? [DO NOT READ CATEGORIES] 1. Less than 5 employees 2. 5 – 9 3. 10 – 19 4. 20 – 49 5. 50 – 99 6. 100 – 199 7. 200 – 299 8. 300 – 399 9. 400 – 499 10. 500 – 999 11. 1,000 – 2,499 12. 2,500 – 4,999 13. 5,000 – 9,999 14. 10,000 – 24,999 15. 25,000 or more employees Q3. What is the approximate square footage of all of the enclosed floor space at your business’s location, including all buildings and any heated or cooled space, including heated or cooled enclosed parking areas? [DO NOT READ CATEGORIES: IF RESPONDENT IS UNSURE; ASK FOR THEIR BEST ESTIMATE] 1. Less than 1,000 sq. ft. 2. 1,000 – 4,999 3. 5,000 – 9,999 4. 10,000 – 14,999 5. 15,000 – 24,999 6. 25,000 – 49,999 7. 50,000 – 99,999 8. 100,000 – 499,999 9. 500,000 – 1 million 10. 1 million sq. ft. or more 2016 – 2030 Upper Midwest Resource Plan
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Q4. Which of the following uses of electricity does your company pay for at this location? In other words, does your electric bill include the cost of…? [INTERVIEWER: READ OPTIONS AND SELECT ALL THAT APPLY] 1. Heating some or all of your space 2. Cooling some or all of your space 3. Providing hot water or steam for your use [IF Q4 =2, ASK Q5; OTHERWISE, GO TO Q6] Q5. What type of cooling system is your primary means to cool your space? [INTERVIEWER: READ OPTIONS IF NECESSARY TO CLARIFY] [IF NEEDED:] By primary, we mean the cooling system that is used for the largest amount of space. 1. Air cooled chiller 2. Water cooled chiller 3. Central air conditioner 4. Packaged air conditioner units (such as HVAC units) 5. Floor‐by‐floor packaged water cooled DX (Direct Expansion) units 6. Wall or window air conditioner units 7. Air‐source heat pump 8. Geothermal heat pump 9. [DO NOT READ] Other [SPECIFY] 10. [DO NOT READ] Not sure Q6. Does your operation at this address have any source of back‐up generation, such as diesel generators? 1. Yes 2. No / Not sure Q7a. Some customers are able to take advantage of an arrangement called an “interruptible rate,” under which you agree to reduce your electricity load at certain times, and in return, you receive a credit on your bill for doing so when you are asked to do so. Does your company utilize an “interruptible rate” like this? 1. Yes 2. No / Not sure [IF Q7a=2, ASK Q7ab; OTHERWISE, GO TO Q8] Q7b. Why has your company not participated in an “interruptible rate”? 1. [DO NOT READ] Did not know about it / Not aware 2. OTHER [RECORD RESPONSE] [ASK AS OPEN END, BUT CODE IF POSSIBLE] 2016 – 2030 Upper Midwest Resource Plan
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Now, let’s turn specifically to your organization’s thoughts about Xcel Energy. Q8. Using a 1‐10 scale where 1 means “strongly disagree” and 10 means “strongly agree” please indicate how much your organization agrees or disagrees with each of the following statements about Xcel Energy. Xcel Energy is… [RECORD NUMBER; 1=STRONGLY DISAGREE, 10=STRONGLY AGREE] Strongly Strongly
disagree agree
[ROTATE 1‐2] 1 2 3 4 5 6 7 8 9 10 1. …a credible information source on the kinds of things you           can do to save energy 2. …a company that actively           promotes programs to help its business customers save money Q9. And on a 1‐10 scale where 1 means “not at all satisfied,” and “10” means “extremely satisfied”, overall, how satisfied would you say your organization is with Xcel Energy as your electric utility? [RECORD NUMBER; 1=NOT AT ALL SATISFIED, 10=EXTREMELY SATISFIED] Q10. Which of the following statements best describes your organization’s approach to implementing energy management actions at this facility? [READ RESPONSES; SELECT ONE] 1. We don’t really pay much attention to managing our energy use 2. We try and watch our energy use, but we haven’t actually done much in terms of changing out equipment or installing better energy management tools 3. We have done some things to better manage our energy use, but I wouldn’t say we have done everything we can 4. We make consistent and aggressive efforts to manage our energy use as effectively as possible 2016 – 2030 Upper Midwest Resource Plan
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Now we’d like to ask you about some new energy management programs that could be offered by Xcel Energy. As you may know, the demand for electricity tends to peak at certain times of the day and year. The rates that all customers pay could be better managed if it were possible to reduce electricity usage at those peak times. The energy management programs you will see here are designed to help manage those peaks in energy usage by rewarding customers who are able to change, or shift, their energy usage away from those peaks. [PROGRAMMER NOTE: THERE ARE TWO SECTIONS BELOW (P1‐P16 AND P17 – P32); EACH RESPONDENT RECEIVES EITHER SECTION A OR SECTION B; RANDOMLY ASSIGN RESPOPNDENTS TO SECTIONS] [PRICING SECTION A: P1 – P16 (PRICE POINTS 1, 2, AND 3)] [IF Q4 = 2 AND Q5= 3, ASK P1; OTHERWISE SKIP TO P4 – NOT INTRO BEFORE P4] P1. One program that is currently offered by Xcel Energy for small business customers is called the Saver’s Switch Program. Under this plan, Xcel Energy installs a device on your air conditioner that allows them to turn off the unit at 15‐20 minute intervals between the hours of 2 pm and 7 pm on 5‐10 of the hottest summer weekday afternoons. In return for participating in this program, customers receive a rebate on their electric bill each summer. The amount of the rebate you would receive depends on the size of your central air conditioner. Please assume that you were offered a rebate of $3 per ton of air conditioner size – or around $60 each summer for the average small business AC unit – but more or less than that depending on the size of your AC unit ‐‐ for participating in the Saver’s Switch Program. With this amount of rebate, how likely would you be to participate? Remember that, under the program, Xcel Energy would install a switch on your primary air conditioner that would allow the utility to turn off your AC system at 15‐20 minute intervals on 5‐10 of the hottest summer days from 2 pm to 7 pm. Please use a scale from 0‐10, where 0 means “not at all likely to participate and “10” means “very likely to participate.” [“0” = NOT AT ALL LIKELY TO PARTICIPATE, “10”=VERY LIKELY TO PARTICIPATE] [ASK IF P1 = 0‐5, OTHERWISE SKIP TO P3] P2. And if you were offered a rebate of $4 per ton of air conditioner size, or $80 for an average sized unit, each summer for participating in the same Saver’s Switch program, how likely would you be to participate using the same 0‐10 scale? [“0” = NOT AT ALL LIKELY TO PARTICIPATE, “10”=VERY LIKELY TO PARTICIPATE] [IF P1=6‐10, ASK P3; OTHERWISE SKIP TO P4] P3. And if you were offered a rebate of $1 per ton of air conditioner size, or $20 for an average size unit each summer for participating in the same Saver’s Switch program, how likely would you be to participate? [“0” = NOT AT ALL LIKELY TO PARTICIPATE, “10”=VERY LIKELY TO PARTICIPATE] 2016 – 2030 Upper Midwest Resource Plan
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Next, we’d like to ask how interested you would be in different rate options that could make it possible for you to lower your overall electricity bill. P4. First, consider an electricity rate in which the price you pay for electricity more closely connects to the price of producing that electricity. This rate is called a “critical peak pricing” rate. Under this rate, the price that you pay for electricity would vary during certain times of the day. Specifically: o During “off‐peak” hours – which account for most hours of the day and year – the price you pay for electricity would be less than you pay now o On approximately 10 days each summer – days when the demand for electricity is especially high – critical peak pricing would be in effect from 2pm to 7pm and the cost for electricity would be several times as much as it is during regular off‐peak periods With an electricity rate like this, you could lower your monthly electric bill by as much as 8% if you chose to reduce or move some of your electricity use away from peak hours on all of those 10 days each summer. If you did not, or were not able to, move your electricity use away from these peak hours, your savings would be lower, and you might actually see a slightly higher bill. Using a 0‐10 scale, with 0 being “Not at all interested” and 10 being “Extremely interested”, if this electricity rate was available to you, how interested would you be in signing up for it? Not At All Interested Extremely Interested In Signing Up In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P4=0‐5, ASK P5; OTHERWISE SKIP TO P6] P5. Now, consider the same basic rate that you just evaluated, but under this scenario, you could lower your monthly electric bill by as much as 11% if you reduced or moved some of your electricity use away from summer peak hours on the 10 summer days on which peak prices occurred. Remember that if you did not move your electricity usage away from the peak periods of 2 pm to 7pm on the 10 critical peak days, your savings would be lower, and you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 2016 – 2030 Upper Midwest Resource Plan
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[IF P4=6‐10, ASK P6; OTHERWISE SKIP TO P7] P6. Now, consider the same basic rate that you just evaluated, but under this scenario, you could lower your monthly electric bill by as much as 6% if you reduced or moved some of your electricity use away from summer peak hours on the 10 summer days on which peak prices occurred. Remember that if you did not move your electricity usage away from the peak periods of 2pm to 7pm on the 10 critical peak days, your savings would be lower, and you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 P7. Now, please consider the same “critical peak pricing” rate you have been thinking about, only this time, you would be offered some new technology that would help you to respond automatically to changes in the price of electricity. Your utility could install a communicating thermostat, for example, that could be set up ahead of time to automatically change your air conditioner settings to the levels that you want to have whenever critical peak prices occur. With this kind of automated technology, and this type of rate, you might find it easier to lower your monthly electric bill by as much as 11% by reducing or moving some of your electricity use away from the peak hours of 2 pm to 7 pm on those 10 days each summer. Since the technology is automated, it would mean that it would be easier for you to respond as you want during these peak pricing days. Using a 0‐10 scale, with 0 being “Not at all interested” and 10 being “Extremely interested”, if this electricity rate was available to you, how interested would you be in signing up for it? Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P7=0‐5, ASK P8; OTHERWISE SKIP TO P9] P8. Now, think again about the same rate that you just evaluated, and assume that you would still be offered the technology that would help you respond to those prices in an automated way. Under this scenario, however, imagine that you could lower your monthly electric bill by as much as 15% if you reduced or moved some of your electricity use away from peak hours on those 10 days each summer. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Would Not Try For Would Try Very Hard 2016 – 2030 Upper Midwest Resource Plan
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The Rebates At All 0 1 2 3 For The Rebates 9 10 4 5 6 7 8 [IF P7=6‐10, ASK P9; OTHERWISE SKIP TO P10] P9. Now, think again about the same rate that you just evaluated, and assume that you would still be offered the technology that would help you respond to those prices in an automated way. Under this scenario, however, imagine that you could lower your monthly electric bill by as much as 8% if you reduced or moved some of your electricity use away from peak hours on those 10 days each summer. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 P10. Now, consider another, similar rate that is called a “Time of Use” rate. Under this rate, during the “peak hours” hours of 2pm to 8pm, Monday through Friday, during the summer (June to September) the price you pay for electricity would be higher than what you pay now (in fact, about twice what you pay now). At all other hours, however, the price you pay for electricity would be less than you pay now. Unlike the Critical Peak Pricing rate, this rate does not have any critical peak days, and you would not be offered any technology that would help to respond to any price changes. With an electricity rate like this, you could lower your monthly electric bill by as much as 6% if you chose to reduce or move some of your electricity use away from summer peak hours. If you did not, or were not able to, move your electricity use away from these peak hours, your savings would be lower, and you might actually see a slightly higher bill. Using the 0‐10 scale where 0 is “Not at all interested” and 10 is “Extremely interested”, please indicate how interested you would be in signing up, if this electricity rate was available to you. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P10=0‐5, ASK P11; OTHERWISE SKIP TO P12] P11. Now, thinking about this Time of Use rate again, imagine that you could lower your monthly electric bill by as much as 10% if you chose to reduce or move some of your electricity use away from summer peak hours. Remember that if you did not move your electricity usage away from the weekday peak periods of 2 pm to 7pm, your savings would be lower, and you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 2016 – 2030 Upper Midwest Resource Plan
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[IF P10=6‐10, ASK P12; OTHERWISE SKIP TO P13] P12. Now, thinking about this Time of Use rate again, imagine that you could lower your monthly electric bill by as much as 4% if you chose to reduce or move some of your electricity use away from summer peak hours. Remember that if you did not move your electricity usage away from the weekday peak periods of 2 pm to 7pm, your savings would be lower, and you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [PRICING SECTION B: P17 – P32 (PRICE POINTS 3, 4, AND 5)] [IF Q4 = 2 AND Q5= 3, ASK P17; OTHERWISE SKIP TO P20 – NOT INTRO BEFORE P20] P17. One program is currently offered by Xcel Energy for small business customers is called the Saver’s Switch Program. Under this plan, Xcel Energy installs a device on your air conditioner that allows them to turn off the unit at 15‐20 minute intervals between the hours of 2 pm to 7pm on 5‐10 of the hottest summer weekday afternoons. In return for participating in this program, customers receive a rebate on their electric bill each summer. The amount of the rebate you would receive depends on the size of your central air conditioner. Please assume that you were offered a rebate of $5 per ton of air conditioner size – or around $100 each summer for the average small business AC unit – but more or less than that depending on the size of your AC unit ‐‐ for participating in the Saver’s Switch Program. With this amount of rebate, how likely would you be to participate? Remember that, under the program, Xcel Energy would install a switch on your primary air conditioner that would allow the utility to turn off your AC system at 15‐20 minute intervals on 5‐10 of the hottest summer days from 2pm to 7pm. Please use a scale from 0‐10, where 0 means “not at all likely to participate and “10” means “very likely to participate.” [“0” = NOT AT ALL LIKELY TO PARTICIPATE, “10”=VERY LIKELY TO PARTICIPATE] [ASK IF P17 = 0‐5, OTHERWISE SKIP TO P19] P18. And if you were offered a rebate of $7 per ton of air conditioner size, or $112 for an average size unit each summer for participating in the same Saver’s Switch program, how likely would you be to participate? [“0” = NOT AT ALL LIKELY TO PARTICIPATE, “10”=VERY LIKELY TO PARTICIPATE] [IF P17=6‐10, ASK P19; OTHERWISE SKIP TO P20] 2016 – 2030 Upper Midwest Resource Plan
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P19. And if you were offered a rebate of $4 per ton of air conditioner size, or $80 for an average size unit each summer for participating in the same Saver’s Switch program, how likely would you be to participate? [“0” = NOT AT ALL LIKELY TO PARTICIPATE, “10”=VERY LIKELY TO PARTICIPATE] Next, we’d like to ask how interested you would be in different rate options that could make it possible for you to lower your overall electricity bill. P20. First, consider an electricity rate in which the price you pay for electricity more closely connects to the price of producing that electricity. This rate is called a “critical peak pricing” rate. Under this rate, the price that you pay for electricity would vary during certain times of the day. Specifically: o During “off‐peak” hours – which account for most hours of the day and year – the price you pay for electricity would be less than you pay now o On approximately 10 days each summer – days when the demand for electricity is especially high – critical peak pricing would be in effect from 2 pm to 7pm and the cost for electricity would be several times as much as it is during regular off‐peak periods With an electricity rate like this, you could lower your monthly electric bill by as much as 13% if you chose to reduce or move some of your electricity use away from peak hours on all of those 10 days each summer. If you did not, or were not able to, move your electricity use away from these peak hours, your savings would be lower, and you might actually see a slightly higher bill. Using a 0‐10 scale, with 0 being “Not at all interested” and 10 being “Extremely interested”, if this electricity rate was available to you, how interested would you be in signing up for it? Not At All Interested Extremely Interested In Signing Up In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P20=0‐5, ASK P21; OTHERWISE SKIP TO P22] P21. Now, consider the same basic rate that you just evaluated, but under this scenario, you could lower your monthly electric bill by as much as 15% if you reduced or moved some of your electricity use away from summer peak hours on the 10 summer days on which peak prices occurred. Remember that if you did not move your electricity usage away from the peak periods of 2pm to 7pm on the 10 critical peak days, your savings would be lower, and you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 2016 – 2030 Upper Midwest Resource Plan
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[IF P20=6‐10, ASK P22; OTHERWISE SKIP TO P23] P22. Now, consider the same basic rate that you just evaluated, but under this scenario, you could lower your monthly electric bill by as much as 11% if you reduced or moved some of your electricity use away from summer peak hours on the 10 summer days on which peak prices occurred. Remember that if you did not move your electricity usage away from the peak periods of 2pm to 7pm on the 10 critical peak days, your savings would be lower, and you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 P23. Now, please consider the same “critical peak pricing” rate you have been thinking about, only this time, you would be offered some new technology that would help you to respond automatically to changes in the price of electricity. Your utility could install a communicating thermostat, for example, that could be set up ahead of time to automatically change your air conditioner settings to the levels that you want to have whenever critical peak prices occur. With this kind of automated technology, and this type of rate, you might find it easier to lower your monthly electric bill by as much as 17% by reducing or moving some of your electricity use away from the peak hours of 2 pm to 8 pm on those 10 days each summer. Since the technology is automated, it would mean that it would be easier for you to respond as you want during these peak pricing days. Using a 0‐10 scale, with 0 being “Not at all interested” and 10 being “Extremely interested”, if this electricity rate was available to you, how interested would you be in signing up for it? Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P23=0‐5, ASK P24; OTHERWISE SKIP TO P25] P24. Now, think again about the same rate that you just evaluated, and assume that you would still be offered the technology that would help you respond to those prices in an automated way. Under this scenario, however, imagine that you could lower your monthly electric bill by as much as 20% if you reduced or moved some of your electricity use away from peak hours on those 10 days each summer. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Would Not Try For Would Try Very Hard The Rebates At All For The Rebates 0 1 2 3 4 5 6 7 8 9 10 2016 – 2030 Upper Midwest Resource Plan
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[IF P23=6‐10, ASK P25; OTHERWISE SKIP TO P26] P25. Now, think again about the same rate that you just evaluated, and assume that you would still be offered the technology that would help you respond to those prices in an automated way. Under this scenario, however, imagine that you could lower your monthly electric bill by as much as 15% if you reduced or moved some of your electricity use away from peak hours on those 10 days each summer. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 P26. Now, consider another, similar rate that is called a “Time of Use” rate. Under this rate, during the “peak hours” hours of 2pm to 8pm, Monday through Friday, during the summer (June to September) the price you pay for electricity would be higher than what you pay now (in fact, about twice what you pay now). At all other hours, however, the price you pay for electricity would be less than you pay now. Unlike the Critical Peak Pricing rate, this rate does not have any critical peak days, and you would not be offered any technology that would help to respond to any price changes. With an electricity rate like this, you could lower your monthly electric bill by as much as 12% if you chose to reduce or move some of your electricity use away from summer peak hours. If you did not, or were not able to, move your electricity use away from these peak hours, your savings would be lower, and you might actually see a slightly higher bill. Using the 0‐10 scale where 0 is “Not at all interested” and 10 is “Extremely interested”, please indicate how interested you would be in signing up, if this electricity rate was available to you. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P26=0‐5, ASK P27; OTHERWISE SKIP TO P28] P27. Now, thinking about this Time of Use rate again, imagine that you could lower your monthly electric bill by as much as 14% if you chose to reduce or move some of your electricity use away from summer peak hours. Remember that if you did not move your electricity usage away from the weekday peak periods of 2pm to 7pm, your savings would be lower, and you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 2016 – 2030 Upper Midwest Resource Plan
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[IF P26=6‐10, ASK P28; OTHERWISE SKIP TO P29] P28. Now, thinking about this Time of Use rate again, imagine that you could lower your monthly electric bill by as much as 10% if you chose to reduce or move some of your electricity use away from summer peak hours. Remember that if you did not move your electricity usage away from the weekday peak periods of 2pm to 7pm, your savings would be lower, and you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 2016 – 2030 Upper Midwest Resource Plan
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CLOSE / INCENTIVE INFO We appreciate your time and effort in responding to our questions. In order to send you the $25 compensation we promised for your help with this research, I will need your name and address information for the check. C0. [DO NOT READ] 1. RESPONDENT REFUSES INCENTIVE [GO TO C0_1] 2. GO TO PAYMENT INFO SCREEN (C1‐7) CO_1. You indicated that you do not wish to receive the $25 for completing the survey. Is that correct? [INTERVIEWER, DO NOT READ CHOICES; SELECT 1] 1. CORRECT – NO INCENTIVE AT ALL [GO TO NO INCENTIVE CLOSE] 2. DONATE INCENTIVE TO HABITAT FOR HUMANITY [GO TO NO INCENTIVE CLOSE] 3. INCORRECT, RESPONDENT DOES WANT INCENTIVE; GO TO C1 [IF CO_1=1 OR 2, READ ‘NO INCENTIVE CLOSE’; OTHERWISE, GOT TO INCENTIVE INFO CAPTURE SCREEN] [NO INCENTIVE CLOSE:] Thank you again for your participation. If you would like information on how your business can save money on energy bills, please visit Xcel Energy at www.xcelenergy.com. Have a nice day!” [END OF SURVEY] [INCENTIVE INFO CAPTURE SCREEN] C1. NAME: C2. COMPANY NAME (OPTIONAL): C3. ADDRESS 1: C4. ADDRESS 2: C5. CITY: C6: STATE: C7: ZIP: C8. {PROGRAMMER, RESTORE NAME & ADDRESS INFO FOR VERIFICATION} [INTERVIEWER, READ RESTORED INFO TO RESPONDENT AND ASK:] Is this information correct? 1. Yes 2. No [IF C8=2, RE‐ENTER INFO UNTIL CORRECT; WHEN CORRECT, READ:] Thank you for your participation. It will take 2‐4 weeks to process and mail your check. If you would like information on how your business can save money on energy bills, please visit Xcel Energy at www.xcelenergy.com Have a nice day. 2016 – 2030 Upper Midwest Resource Plan
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Brattle Xcel Energy MN DR Interest – Medium/Large Business Questionnaire 092613 READ IN SAMPLE INFORMATION STRATA: [TBD] – TOTAL SAMPLE 200 [NOTE: ALSO TRY FOR 6‐10 ADDITIONAL TDI’S WITH LARGEST BUSINESSES – FOCUSING ON THE PROGRAMS AS DESCRIBED HERE] SERVICE_ADD (ADDRESS) OTHER FIELDS TBD WHEN SAMPLE RECEIVED, BUT WILL INDICATE BUSINESS NAME, BILLING ADDRESS, PHONE NUMBER AND OTHER FIELDS] QUOTAS: STRATA=TBD INTRODUCTION
Hello. My name is ___________________ and I’m calling from _____________, conducting a market research study for Xcel Energy. I’d like to speak to the person who is responsible for making energy‐related decisions at [SERVICE_ADD]. [WHEN YOU REACH THE RIGHT PERSON – REINTRODUCE AS APPROPRIATE] Hello. My name is ___________________ and I’m calling from _____________, conducting a market research study for Xcel Energy. We are conducting a market research study today for Xcel Energy. The goal of the study is to help Xcel Energy to deliver programs that enable its customers to use energy more cost effectively. Your answers to this survey will help the company to improve these programs. Your business is one of a small number being asked to respond to the survey. I would like to ask you a few questions first to make sure that your business qualifies for our survey. If you do qualify and are able to complete the survey, you will be compensated for your time. It should only take a couple of minutes to see if you qualify for the survey. [IF NEEDED: If you qualify for and complete the survey, we will send you a check for $50. We first need to ask you a few questions to make sure your business qualifies for participation. If you do qualify, you will then be invited to complete the full survey. S1. While this may not be the address where you are located, all of my questions here will be about your company’s operation at [SERVICE_ADD]. Is this a facility about which you are knowledgeable? [DO NOT READ; SELECT ONE] 1. Yes 2. No – not an address at which this business operates – [POLITELY TERMINATE] 3. No – the business operates at that address but they are not knowledgeable about it [GET REFERRAL AND RESTART AT BEGINNING] 2016 – 2030 Upper Midwest Resource Plan
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S2. S3. S4. Does your operation at this location occupy any enclosed space, or is it an outdoor structure or operation, such as a billboard, a parking lot, a communications tower, or the like? Is it… 1. ONLY an enclosed space 2. ONLY an outdoor structure or facility – [POLITELY TERMINATE] 3. or does it include both an enclosed space AND an outdoor structure or operation? Which of the following statements best describes your role in making energy‐related decisions for your operations at this location. By energy‐related decisions, we mean things like deciding whether or not your company might participate in a new electric rate option that might be offered by Xcel Energy. 5. I am the person who would make that decision 6. I am one of a group of people who would contribute to that decision. 7. I am not a decision maker, but I would be knowledgeable about, or involved in, those decisions. 8. I would not be involved in that type of decision in a meaningful way. [ASK FOR REFERRAL TO SOMEONE WHO WOULD BE INVOLVED IN THESE DECISIONS – RESTART AS APPROPRIATE ABOVE] What type of facility does your organization occupy or operate at this location? [INTERVIEWER: ONLY READ CATEGORIES AS NECESSARY TO CLARIFY] 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. Office (finance, insurance, real estate, law, etc.) Retail (department stores, services, boutiques, etc.) Grocery (supermarkets, convenience store, market, etc.) Restaurant / food service (sit‐down, fast food, coffee shop, etc.) Warehouse School (day care, pre‐school, elementary, secondary) College, university or trade school Health Care (health practitioner office, hospital, urgent care center, etc.) Nursing home / assisted living facility / residential treatment facility Lodging / housing facility (hotel, motel, bed and breakfast, apartment building, etc.) Not‐for profit housing facility (shelter, prison, jail, etc.) Entertainment / recreation facility (movie theater, bowling alley, health club/gym, library, museum, etc.) Public assembly facility (convention / conference center, etc.) Worship (church, temple, etc.) Multi‐use or shopping mall (i.e., mixed use of space for offices, restaurants, stores, service, apartments, etc.) [INTERVIEWER NOTE: USE AS LITTLE AS POSSIBLE – TRY TO FOCUS ON PRIMARY USE; THAT WHICH ACCOUNTS FOR 75%+ OF SPACE] 16. Manufacturing, production, or processing facility (including for‐profit businesses and governmental facilities) 17. Agricultural (farms, ranches, dairies, greenhouses, nurseries, orchards, hatcheries, etc.) 990. Other [SPECIFY] [PROGRAMMER NOTE: NO MORE THAN 20 COMPLETES WITH “SCHOOLS” S4=6] 2016 – 2030 Upper Midwest Resource Plan
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[PRICES TESTED: A (LOWER) BLOCK] [Saver’s Switch: $20 / ton] [CPP: 6%, 8%, 11%] [CPP W/ TECH: 8%, 11%, 15%] [TOU: 4%, 6%, 10%] [INTERRUPTIBLE BASE: $2, $3.50, $5.50] [INTERRUPTIBLE MORE DAYS: $3.50, $5.00, $7.00] [DEMAND BIDDING: 10 cents/kWh, 30 cents/kWh, 50 cents/kWh] [PRICES TESTED: B (UPPER) BLOCK] [Saver’s Switch: $20 / ton] [CPP: 11%, 13%, 15%] [CPP W/ TECH: 15%, 17%, 20%] [TOU: 10%, 12%, 14%] [INTERRUPTIBLE BASE: $5.50, $7.00, $9.50] [INTERRUPTIBLE MORE DAYS: $7.00, $8.50, $11.00] [DEMAND BIDDING: 50 cents/kWh, 75 cents/kWh, $1/kWh] 2016 – 2030 Upper Midwest Resource Plan
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TERMINATE TEXT Thank you for your help but, at this point, we have reached the number of respondents we can accept from companies like yours. Again, we would like to thank you for your time and effort. Have a nice day! INVITATION LANGUAGE FOR QUALIFYING RESPONDENTS Thank you for your responses so far. You and your business have qualified to complete this survey, which should take about 20 minutes to complete. Once you complete the survey you will be eligible to receive the $50 ‘thank you’ payment. Of course, if your company’s policies require that you decline the payment you can do so, or you can direct us to donate it to Habitat for Humanity. Is this a good time for you to continue? 1. YES –CONTINUE 2. NO – SCHEDULE APPT. 2016 – 2030 Upper Midwest Resource Plan
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Please note that all of my questions will be about your company’s operations at [SERVICE_ADD] Q1. Does your business own or lease the building space at this location? [INTERVIEWER: IF RESPONDENTS SAYS THEY LEASE SOME SPACE AND OWN SOME SPACE AT THIS LOCATION, ASK WHICH ACCOUNTS FOR THE MAJORITY OF THE SPACE HERE] 1. Own (or in the process of buying it) 2. Lease / rent Q2. Approximately how many employees work at this location? [DO NOT READ CATEGORIES] 1. Less than 5 employees 2. 5 – 9 3. 10 – 19 4. 20 – 49 5. 50 – 99 6. 100 – 199 7. 200 – 299 8. 300 – 399 9. 400 – 499 10. 500 – 999 11. 1,000 – 2,499 12. 2,500 – 4,999 13. 5,000 – 9,999 14. 10,000 – 24,999 15. 25,000 or more employees Q3. What is the approximate square footage of all of the enclosed floor space at your business’s location, including all buildings and any heated or cooled space, including heated or cooled enclosed parking areas? [DO NOT READ CATEGORIES: IF RESPONDENT IS UNSURE; ASK FOR THEIR BEST ESTIMATE] 1. Less than 1,000 sq. ft. 2. 1,000 – 4,999 3. 5,000 – 9,999 4. 10,000 – 14,999 5. 15,000 – 24,999 6. 25,000 – 49,999 7. 50,000 – 99,999 8. 100,000 – 499,999 9. 500,000 – 1 million 10. 1 million sq. ft. or more 2016 – 2030 Upper Midwest Resource Plan
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Q4. Which of the following uses of electricity does your company pay for at this location? In other words, does your electric bill include the cost of…? [INTERVIEWER: READ OPTIONS AND SELECT ALL THAT APPLY] Q5. 1. Heating some or all of your space 2. Cooling some or all of your space 3. Providing hot water or steam for your use [IF Q4 =2, ASK Q5; OTHERWISE, GO TO Q6] What type of cooling system is your primary means to cool your space? [INTERVIEWER: READ OPTIONS IF NECESSARY TO CLARIFY] [IF NEEDED:] By primary, we mean the cooling system that is used for the largest amount of space. 9. Air cooled chiller 10. Water cooled chiller 11. Central air conditioner 12. Packaged air conditioner units (such as HVAC units) 13. Floor‐by‐floor packaged water cooled DX (Direct Expansion) units 14. Wall or window air conditioner units 15. Air‐source heat pump 16. Geothermal heat pump 9. [DO NOT READ] Other [SPECIFY] 10. [DO NOT READ] Not sure Q6. Does your operation at this address have any source of back‐up generation, such as diesel generators? 3. Yes 4. No / Not sure [IF Q6=1, ASK Q7; OTHERWISE GO TO Q9] Q7. About what percentage of your total energy needs at this address can be met with your back‐up generators? _________ [ENTER PRECENTAGE] Q8. For about how long can your back‐up generators maintain your operations? _________ [ENTER APPROXIMATE NUMBER OF HOURS] Q9. Some customers are able to take advantage of an arrangement called an “interruptible rate,” under which you agree to reduce your electricity load at certain times, and in return, you receive a credit on your bill for doing so when you are asked to do so. Does your company utilize an “interruptible rate” like this? 3. Yes 4. No / Not sure [IF Q9=2, ASK Q10; OTHERWISE, GO TO Q11] Q10. Why has your company not participated in an “interruptible rate”? 1. [DO NOT READ] Did not know about it / Not aware 2. OTHER [RECORD RESPONSE] Now, let’s turn specifically to your organization’s thoughts about Xcel Energy. Q11. On a 1‐10 scale where 1 means “not at all satisfied,” and “10” means “extremely satisfied”, overall, how satisfied would you say your organization is with Xcel Energy as your electric utility? [RECORD NUMBER; 1=NOT AT ALL SATISFIED, 10=EXTREMELY SATISFIED] 2016 – 2030 Upper Midwest Resource Plan
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Now we’d like to ask you about some new energy management programs that could be offered by Xcel Energy. As you may know, the demand for electricity tends to peak at certain times of the day and year. The rates that all customers pay could be better managed if it were possible to reduce electricity usage at those peak times. The energy management programs I will ask you about are designed to help manage those peaks in energy usage by rewarding customers who are able to change, or shift, their energy usage away from those peaks. [PROGRAMMER NOTE: THERE ARE TWO SECTIONS BELOW (P1‐P25 AND P27 – P50); EACH RESPONDENT RECEIVES EITHER SECTION A OR SECTION B; RANDOMLY ASSIGN RESPOPNDENTS TO SECTIONS] [PRICING SECTION A: P1 – P26 (PRICE POINTS 1, 2, AND 3)] [IF STRATA = MEDIUM AND Q4 = 2 AND Q5= 3, ASK P1; OTHERWISE SKIP TO P1b] P1. One program currently offered by Xcel Energy is called the Saver’s Switch Program. Under this plan, Xcel Energy installs a device on your central air conditioner that allows them to turn off the unit at 15‐20 minute intervals between the hours of 2pm and 7pm on 5‐10 of the hottest summer weekday afternoons. In return for participating in this program, customers receive savings on their summer electric bills. Are you currently participating in Xcel Energy’s Saver’s Switch Program? 3. Yes 4. No / Not sure [IF P1=2 AND Q4 = 2 AND Q5= 1 or 2, CONTINUE; OTHERWISE SKIP TO INTRO BEFORE P4] [IF Q4 = 2 AND Q5= 1 or 2, ASK P1b; OTHERWISE SKIP TO P4 – NOT INTRO BEFORE P4] P1b. [IF Q4 = 2 AND Q5= 1 or 2 AND STRATA = MEDIUM OR LARGE] The first program we’ll discuss that that could be offered to customers like you is a modified version of the “Saver’s Switch” program. Under this plan, Xcel Energy could install a device on your primary chiller unit that allows them to turn off the unit at 15‐20 minute intervals between the hours of 2pm and 7pm on 5‐10 of the hottest summer weekday afternoons. In return for participating in this program, customers receive a rebate on their electric bill. [IF P1 = 2 AND Q4 = 2 AND Q5= 1 or 2] Under another version of the Saver’s Switch Program, Xcel Energy installs a device on your primary chiller unit that allows them to turn off the unit at 15‐20 minute intervals between the hours of 2pm and 7pm on 5‐10 of the hottest summer weekday afternoons. In return for participating in this program, customers receive a rebate on their electric bill. [ALL ANSWERING] The amount of the rebate you would receive depends on the size of your primary chiller. Please assume that you were offered a rebate of $20 per ton of primary chiller size each summer for participating in this program. This would mean that if you had a 10‐ton chiller, your rebate would be $200 per summer, though this would obviously be higher or lower depending on the size of your primary chiller. With this amount of rebate, how likely would you be to participate? Please use a scale from 0‐10, where 0 means “not at all likely to participate and “10” means “very likely to participate.” [“0” = NOT AT ALL LIKELY TO PARTICIPATE, “10”=VERY LIKELY TO PARTICIPATE] 2016 – 2030 Upper Midwest Resource Plan
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Next, we’d like to ask how interested you would be in different rate options that could make it possible for you to lower your overall electricity bill. [P2‐P3 INTENTIONALLY SKIPPED] P4. First, consider an electricity rate in which the price you pay for electricity more closely connects to the price of producing that electricity. This rate is called a “critical peak pricing” rate. Under this rate, the price that you pay for electricity would vary during certain times of the day. Specifically: o During “off‐peak” hours – which account for most hours of the day and year – the price you pay for electricity would be less than you pay now o On approximately 10 days each summer – days when the demand for electricity is especially high – critical peak pricing would be in effect from 2pm to 7pm and the cost for electricity would be several times as much as it is during regular off‐peak periods With an electricity rate like this, you could lower your monthly electric bill by as much as 8% if you chose to reduce or move some of your electricity use away from peak hours on all of those 10 days each summer. If you did not, or were not able to, move your electricity use away from these peak hours, your savings would be lower, or you might actually see a slightly higher bill. Using a 0‐10 scale, with 0 being “Not at all interested” and 10 being “Extremely interested”, if this electricity rate was available to you, how interested would you be in signing up for it? Not At All Interested Extremely Interested In Signing Up In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P4=0‐5, ASK P5; OTHERWISE SKIP TO P6] P5. Now, consider the same basic rate that you just evaluated, but under this scenario, you could lower your monthly electric bill by as much as 11% if you reduced or moved some of your electricity use away from summer peak hours on the 10 summer days on which peak prices occurred. Again, if you did not move your electricity usage away from the peak periods of 2pm to 7pm on the 10 critical peak days, your savings would be lower, or you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P4=6‐10, ASK P6; OTHERWISE SKIP TO P7] P6. Now, consider the same basic rate that you just evaluated, but under this scenario, you could lower your monthly electric bill by as much as 6% if you reduced or moved some of your electricity use away from summer peak hours on the 10 summer days on which peak prices occurred. Again, if you did not move your electricity usage away from the peak periods of 2pm to 7pm on the 10 critical peak days, your savings would be lower, or you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely 2016 – 2030 Upper Midwest Resource Plan
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P7. Interested In Signing Up 0 1 2 3 4 5 6 7 8 Interested In Signing Up 9 10 Now, please consider the same “critical peak pricing” rate you have been thinking about, only this time, you would be offered some new technology that would help you to respond automatically to changes in the price of electricity. Your utility could install a communicating thermostat, for example, that could be set up ahead of time to automatically change your air conditioner settings to the levels that you want to have whenever critical peak prices occur. With this kind of automated technology, and this type of rate, you might find it easier to lower your monthly electric bill by as much as 11% by reducing or moving some of your electricity use away from the peak hours of 2 pm to 8 pm on those 10 days each summer. Since the technology is automated, it would mean that it would be easier for you to respond as you want during these peak pricing days. Using a 0‐10 scale, with 0 being “Not at all interested” and 10 being “Extremely interested”, if this electricity rate was available to you, how interested would you be in signing up for it? Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P7=0‐5, ASK P8; OTHERWISE SKIP TO P9] P8. Now, think again about the same rate that you just evaluated, and assume that you would still be offered the technology that would help you respond to those prices in an automated way. Under this scenario, however, imagine that you could lower your monthly electric bill by as much as 15% if you reduced or moved some of your electricity use away from peak hours on those 10 days each summer. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Would Not Try For Would Try Very Hard The Rebates At All For The Rebates 0 1 2 3 4 5 6 7 8 9 10 [IF P7=6‐10, ASK P9; OTHERWISE SKIP TO P10] P9. Now, think again about the same rate that you just evaluated, and assume that you would still be offered the technology that would help you respond to those prices in an automated way. Under this scenario, however, imagine that you could lower your monthly electric bill by as much as 8% if you reduced or moved some of your electricity use away from peak hours on those 10 days each summer. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 P10. Now, consider another, similar rate that is called a “Time of Use” rate. Under this rate, during the “peak hours” hours of 2pm to 8pm, Monday through Friday, during the summer the price you pay for electricity would be 2016 – 2030 Upper Midwest Resource Plan
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higher than what you pay now (in fact, about twice what you pay now). At all other hours, however, the price you pay for electricity would be less than you pay now. Unlike the Critical Peak Pricing rate, this rate does not have any critical peak days, and you would not be offered any technology that would help to respond to any price changes. With an electricity rate like this, you could lower your monthly electric bill by as much as 6% if you chose to reduce or move some of your electricity use away from summer peak hours. If you did not, or were not able to, move your electricity use away from these peak hours, your savings would be lower, or you might actually see a slightly higher bill. Using the 0‐10 scale where 0 is “Not at all interested” and 10 is “Extremely interested”, please indicate how interested you would be in signing up, if this electricity rate was available to you. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P10=0‐5, ASK P11; OTHERWISE SKIP TO P12] P11. Now, thinking about this Time of Use rate again, imagine that you could lower your monthly electric bill by as much as 10% if you chose to reduce or move some of your electricity use away from summer peak hours. Remember that if you did not move your electricity usage away from the weekday peak periods of 2 pm to 8 pm, your savings would be lower, or you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Extremely Not At All Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P10=6‐10, ASK P12; OTHERWISE SKIP TO P12a] P12. Now, thinking about this Time of Use rate again, imagine that you could lower your monthly electric bill by as much as 4% if you chose to reduce or move some of your electricity use away from summer peak hours. Remember that if you did not move your electricity usage away from the weekday peak periods of 2 pm to 8 pm, your savings would be lower, or you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Extremely Not At All Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF Q9 NE 1, READ P12a; OTHERWISE SKIP TO P16] P12a. Another rate option we would like you to consider is what is called an "interruptible rate". Under this sort of an arrangement you would agree to participate in a program to reduce your electricity demand by a specified amount, given a one hour notice from your utility. In return, you would receive reductions off of your demand charges for each month of the year. 2016 – 2030 Upper Midwest Resource Plan
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In order to qualify for this rate, you would need to have a controllable load of at least 50 kilowatts at least once during the summer months of June thru September. Do you have a total controllable electricity load of 50 kW at least once during the summer months? 1. Yes 2. No 3. Not sure [IF P12A = 1, CONTINUE, OTHERWISE SKIP TO P22] P13. The key elements of this plan are that, during periods of peak energy demand, your business would:  Agree to reduce your demand for electricity to a predetermined level that you specify when a control period is called, and this will happen only a few times a year, during hot summer days.  Receive an average bill credit of $3.50 on your demand charges for each kilowatt that you agree to reduce your demand, and you would get this credit for every month of the year So, you would get a bill credit every month for peak energy reductions you would make only a few times a year during the summer. Again, we know that this would take further study, but based on what you heard, if this option was available to you, how likely would you be to consider signing your business up for it? Please use a scale from “0” to “10” where “0” means “not at all likely” and “10” means “extremely likely.” Not At All Likely Extremely Likely 0 1 2 3 4 5 6 7 8 9 10 [IF P13=0‐5, ASK P14; OTHERWISE SKIP TO P15] P14. Now, thinking about this Interruptible rate again, imagine that the average bill credit was $5.50 per kW for every month of the year for the number of kWs that you agreed to reduce your demand. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Extremely Not At All Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 2016 – 2030 Upper Midwest Resource Plan
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[IF P13=6‐10, ASK P15; OTHERWISE SKIP TO P16] P15. Now, thinking about this Interruptible rate again, imagine that the average bill credit was $2 per kW for every month of the year for the number of kWs that you agreed to reduce your demand. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 P16. [IF Q9=1, READ] I know that you said that your company already participates in an “Interruptible Rate Plan”, but we would like to ask you about another version of that plan. Under this sort of an arrangement you would agree to participate in a program to reduce your electricity demand by a specified amount, but such control periods could be called more frequently – up to 15 times per year – and you would receive an average bill credit of $5 on your demand charges for each kilowatt that you agree to reduce your demand, and you would get this credit for every month of the year. [IF Q9 NE 1, READ] Please think now about another version of the “Interruptible Rate Plan.” With this plan, the control periods could be called more frequently – up to 15 times per year – and you receive an average bill credit of $5 on your demand charges for each kilowatt that you agree to reduce your demand, and you would get this credit for every month of the year. Again, we know that this would take further study, but based on what you heard, if this option was available to you, how likely would you be to consider signing your business up for it? Please use a scale from “0” to “10” where “0” means “not at all likely” and “10” means “extremely likely.” Not At All Likely Extremely Likely 0 1 2 3 4 5 6 7 8 9 10 [IF P13 OR P16=7 OR HIGHER, ASK P17; OTHERWISE, SKIP TO P20] P17. About how many kilowatts of demand do you think you might be willing to reduce under this sort of interruptible rate option? __________________ kilowatts of demand [IF Q6=1 ASK P18; OTHERWISE, SKIP TO P20] P18. And would you expect to actually reduce your demand for electricity by that amount, or would you expect to use your backup generation capacity to replace the electricity that you would have received from the electricity utility? 1. Actually reduce demand 2. Use backup generation to replace that electricity 3. Not sure 2016 – 2030 Upper Midwest Resource Plan
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[IF P18 = 2, ASK P19; OTHERWISE SKIP TO P20] P19. Please assume that if your backup generation capacity was not available for some reason, then under this plan, you would still need to reduce your load by the agreed upon amount. If this was the case, how likely would you be to participate? Not At All Likely Extremely Likely 0 1 2 3 4 5 6 7 8 9 10 [IF P16=0‐5, ASK P20; OTHERWISE SKIP TO P21] P20. Now, thinking about this second version of the Interruptible rate again that would have more frequent interruptions, imagine that the average bill credit was $7 per kW for every month of the year for the number of kWs that you agreed to reduce your demand. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Extremely Not At All Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P16=6‐10, ASK P21; OTHERWISE SKIP TO P22] P21. Now, thinking about this second version of the Interruptible rate again that would have more frequent interruptions, imagine that the average bill credit was $3.50 per kW for every month of the year for the number of kWs that you agreed to reduce your demand. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Extremely Not At All Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 P22. Now the last program option we will ask you about is called “demand bidding.” Under this program, customers would offer to reduce their load and Xcel Energy would pay you for each kilowatt hour that you reduce your load during periods of critical peak electricity usage. More specifically,  Customers would provide a daily schedule to Xcel Energy indicating the amount of load they would be willing to reduce during the next day’s peak, and the price they want to receive for making that load reduction  Assume that the plan would be in effect during the summer, especially during hot summer afternoons and evenings  Customers who have their price agreed to by Xcel Energy would actually need to make those load reductions the next day or incur financial penalties Again, we know that this would take further study, but let’s assume that the price that Xcel Energy would agree to pay you would be 30 cents for each kilowatt hour that you agreed to reduce your load during the next day. Based on what you heard, if this option was available to you, how often – during the summer – do you think you would expect to participate in this program? Please use a scale from “0” to “10” where “0” means “never” and “10” means “as often as possible.” 2016 – 2030 Upper Midwest Resource Plan
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Never 0 As often as Possible 8 9 10 1 2 3 4 5 6 7 [IF P22=0‐5, ASK P23; OTHERWISE SKIP TO P24] P23. Now, if the payment for each kilowatt hour that you reduced your load was 50 cents, how often – during the summer – do you think you would participate in the program? Never As often as Possible 0 1 2 3 4 5 6 7 8 9 10 [IF P22=6‐10, ASK P24; OTHERWISE SKIP TO C0] P24. Now, if the payment for each kilowatt hour that you reduced your load was 10 cents, how often – during the summer – do you think you would participate in the program? Never As often as Possible 0 1 2 3 4 5 6 7 8 9 10 [IF ANY P22 – P24=7 OR HIGHER, ASK P25; OTHERWISE, SKIP TO C0] P25. About what percentage of your load do you think you would reduce – on average ‐ if Xcel Energy accepted your bid to participate in this program? __________________ [ENTER %] 2016 – 2030 Upper Midwest Resource Plan
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[PRICING SECTION B: P27 – P50 (PRICE POINTS 3, 4, and 5)] [IF STRATA = MEDIUM AND Q4 = 2 AND Q5= 3, ASK P27; OTHERWISE SKIP TO P27b] P27. One program currently offered by Xcel Energy is called the Saver’s Switch Program. Under this plan, Xcel Energy installs a device on your central air conditioner that allows them to turn off the unit at 15‐20 minute intervals between the hours of 2pm and 7pm on 5‐10 of the hottest summer weekday afternoons. In return for participating in this program, customers receive savings on their summer electric bills. Are you currently participating in Xcel Energy’s Saver’s Switch Program? 5. Yes 6. No / Not sure [IF P27=2 AND Q4 = 2 AND Q5= 1 or 2, CONTINUE; OTHERWISE SKIP TO INTRO BEFORE P28] [IF Q4 = 2 AND Q5= 1 or 2, ASK P27b; OTHERWISE SKIP TO P4 – NOT INTRO BEFORE P28] P27b. [IF Q4 = 2 AND Q5= 1 or 2 AND STRATA = MEDIUM OR LARGE] The first program we’ll discuss that that could be offered to customers like you is a modified version of the “Saver’s Switch” program. Under this plan, Xcel Energy could install a device on your primary chiller unit that allows them to turn off the unit at 15‐20 minute intervals between the hours of 2pm and 7pm on 5‐10 of the hottest summer weekday afternoons. In return for participating in this program, customers receive a rebate on their electric bill. [IF P1 = 2 AND Q4 = 2 AND Q5= 1 or 2] Under another version of the Saver’s Switch Program, Xcel Energy installs a device on your primary chiller unit that allows them to turn off the unit at 15‐20 minute intervals between the hours of 1pm and 7pm on 5‐10 of the hottest summer weekday afternoons. In return for participating in this program, customers receive a rebate on their electric bill. [ALL ANSWERING] The amount of the rebate you would receive depends on the size of your primary chiller. Please assume that you were offered a rebate of $20 per ton of primary chiller size each summer for participating in this program. This would mean that if you had a 10‐ton chiller, your rebate would be $200 per summer, though this would obviously be higher or lower depending on the size of your primary chiller. With this amount of rebate, how likely would you be to participate? Please use a scale from 0‐10, where 0 means “not at all likely to participate and “10” means “very likely to participate.” [“0” = NOT AT ALL LIKELY TO PARTICIPATE, “10”=VERY LIKELY TO PARTICIPATE] 2016 – 2030 Upper Midwest Resource Plan
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Next, we’d like to ask how interested you would be in different rate options that could make it possible for you to lower your overall electricity bill. P28. First, consider an electricity rate in which the price you pay for electricity more closely connects to the price of producing that electricity. This rate is called a “critical peak pricing” rate. Under this rate, the price that you pay for electricity would vary during certain times of the day. Specifically: o During “off‐peak” hours – which account for most hours of the day and year – the price you pay for electricity would be less than you pay now o On approximately 10 days each summer – days when the demand for electricity is especially high – critical peak pricing would be in effect from 2pm to 7pm and the cost for electricity would be several times as much as it is during regular off‐peak periods With an electricity rate like this, you could lower your monthly electric bill by as much as 13% if you chose to reduce or move some of your electricity use away from peak hours on all of those 10 days each summer. If you did not, or were not able to, move your electricity use away from these peak hours, your savings would be lower, or you might actually see a slightly higher bill. Using a 0‐10 scale, with 0 being “Not at all interested” and 10 being “Extremely interested”, if this electricity rate was available to you, how interested would you be in signing up for it? Not At All Interested Extremely Interested In Signing Up In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P28=0‐5, ASK P29; OTHERWISE SKIP TO P30] P29. Now, consider the same basic rate that you just evaluated, but under this scenario, you could lower your monthly electric bill by as much as 15% if you reduced or moved some of your electricity use away from summer peak hours on the 10 summer days on which peak prices occurred. Again, if you did not move your electricity usage away from the peak periods of 2pm to 7pm on the 10 critical peak days, your savings would be lower, or you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 2016 – 2030 Upper Midwest Resource Plan
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[IF P28=6‐10, ASK P30; OTHERWISE SKIP TO P31] P30. Now, consider the same basic rate that you just evaluated, but under this scenario, you could lower your monthly electric bill by as much as 11% if you reduced or moved some of your electricity use away from summer peak hours on the 10 summer days on which peak prices occurred. Again, if you did not move your electricity usage away from the peak periods of 2pm to 7pm on the 10 critical peak days, your savings would be lower, or you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 P31. Now, please consider the same “critical peak pricing” rate you have been thinking about, only this time, you would be offered some new technology that would help you to respond automatically to changes in the price of electricity. Your utility could install a communicating thermostat, for example, that could be set up ahead of time to automatically change your air conditioner settings to the levels that you want to have whenever critical peak prices occur. With this kind of automated technology, and this type of rate, you might find it easier to lower your monthly electric bill by as much as 17% by reducing or moving some of your electricity use away from the peak hours of 2 pm to 8 pm on those 10 days each summer. Since the technology is automated, it would mean that it would be easier for you to respond as you want during these peak pricing days. Using a 0‐10 scale, with 0 being “Not at all interested” and 10 being “Extremely interested”, if this electricity rate was available to you, how interested would you be in signing up for it? Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P31=0‐5, ASK P32; OTHERWISE SKIP TO P33] P32. Now, think again about the same rate that you just evaluated, and assume that you would still be offered the technology that would help you respond to those prices in an automated way. Under this scenario, however, imagine that you could lower your monthly electric bill by as much as 20% if you reduced or moved some of your electricity use away from peak hours on those 10 days each summer. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Would Not Try For Would Try Very Hard The Rebates At All For The Rebates 0 1 2 3 4 5 6 7 8 9 10 [IF P31=6‐10, ASK P33; OTHERWISE SKIP TO P34] P33. Now, think again about the same rate that you just evaluated, and assume that you would still be offered the technology that would help you respond to those prices in an automated way. Under this scenario, however, 2016 – 2030 Upper Midwest Resource Plan
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imagine that you could lower your monthly electric bill by as much as 15% if you reduced or moved some of your electricity use away from peak hours on those 10 days each summer. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 P34. Now, consider another, similar rate that is called a “Time of Use” rate. Under this rate, during the “peak hours” hours of 2pm to 8pm, Monday through Friday, during the summer the price you pay for electricity would be higher than what you pay now (in fact, about twice what you pay now). At all other hours, however, the price you pay for electricity would be less than you pay now. Unlike the Critical Peak Pricing rate, this rate does not have any critical peak days, and you would not be offered any technology that would help to respond to any price changes. With an electricity rate like this, you could lower your monthly electric bill by as much as 12% if you chose to reduce or move some of your electricity use away from summer peak hours. If you did not, or were not able to, move your electricity use away from these peak hours, your savings would be lower, or you might actually see a slightly higher bill. Using the 0‐10 scale where 0 is “Not at all interested” and 10 is “Extremely interested”, please indicate how interested you would be in signing up, if this electricity rate was available to you. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P34=0‐5, ASK P35; OTHERWISE SKIP TO LOGIC P36] P35. Now, thinking about this Time of Use rate again, imagine that you could lower your monthly electric bill by as much as 14% if you chose to reduce or move some of your electricity use away from summer peak hours. Remember that if you did not move your electricity usage away from the weekday peak periods of 2 pm to 8 pm, your savings would be lower, or you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Extremely Not At All Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 2016 – 2030 Upper Midwest Resource Plan
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[IF P34=6‐10, ASK P36; OTHERWISE SKIP TO LOGIC BEFORE P37] P36. Now, thinking about this Time of Use rate again, imagine that you could lower your monthly electric bill by as much as 10% if you chose to reduce or move some of your electricity use away from summer peak hours. Remember that if you did not move your electricity usage away from the weekday peak periods of 2 pm to 8 pm, your savings would be lower, or you might see a slightly higher bill. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Not At All Extremely Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF Q9 NE 1, READ P37; OTHERWISE SKIP TO P41] P37. Another rate option we would like you to consider is what is called an "interruptible rate". Under this sort of an arrangement you would agree to participate in a program to reduce your electricity demand by a specified amount, given a one hour notice from your utility. In return, you would receive reductions off of your demand charges for each month of the year. In order to qualify for this rate, you would need to have a controllable load of at least 50 kilowatts at least once during the summer months of June thru September. Do you have a total controllable electricity load of 50 kW at least once during the summer months? 4. Yes 5. No 6. Not sure [IF P37 = 1, CONTINUE, OTHERWISE SKIP TO P47] P38. The key elements of this plan are that, during periods of peak energy demand, your business would:  Agree to reduce your demand for electricity to a predetermined level that you specify when a control period is called, and this will happen only a few times a year, during hot summer days.  Receive an average bill credit of $7.00 on your demand charges for each kilowatt that you agree to reduce your demand, and you would get this credit for every month of the year So, you would get a bill credit every month for peak energy reductions you would make only a few times a year during the summer. Again, we know that this would take further study, but based on what you heard, if this option was available to you, how likely would you be to consider signing your business up for it? Please use a scale from “0” to “10” where “0” means “not at all likely” and “10” means “extremely likely.” Not At All Likely Extremely Likely 0 1 2 3 4 5 6 7 8 9 10 [IF P38=0‐5, ASK P39; OTHERWISE SKIP TO P40] 2016 – 2030 Upper Midwest Resource Plan
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P39. Now, thinking about this Interruptible rate again, imagine that the average bill credit was $9.50 per kW for every month of the year for the number of kWs that you agreed to reduce your demand. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Extremely Not At All Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P38=6‐10, ASK P40; OTHERWISE SKIP TO P41] P40. Now, thinking about this Interruptible rate again, imagine that the average bill credit was $5.50 per kW for every month of the year for the number of kWs that you agreed to reduce your demand. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Extremely Not At All Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 P41. [IF Q9=1, READ] I know that you said that your company already participates in an “Interruptible Rate Plan”, but we would like to ask you about another version of that plan. Under this sort of an arrangement you would agree to participate in a program to reduce your electricity demand by a specified amount, but such control periods could be called more frequently – up to 15 times per year – and you would receive an average bill credit of $8.50 on your demand charges for each kilowatt that you agree to reduce your demand, and you would get this credit for every month of the year. [IF Q9 NE 1, READ] Please think now about another version of the “Interruptible Rate Plan.” With this plan, the control periods could be called more frequently – up to 15 times per year – and you receive an average bill credit of $8.50 on your demand charges for each kilowatt that you agree to reduce your demand, and you would get this credit for every month of the year. Again, we know that this would take further study, but based on what you heard, if this option was available to you, how likely would you be to consider signing your business up for it? Please use a scale from “0” to “10” where “0” means “not at all likely” and “10” means “extremely likely.” Not At All Likely Extremely Likely 0 1 2 3 4 5 6 7 8 9 10 [IF P38 OR P41=7 OR HIGHER, ASK P42; OTHERWISE, SKIP TO P20] P42. About how many kilowatts of demand do you think you might be willing to reduce under this sort of interruptible rate option? __________________ kilowatts of demand [IF Q6=1 ASK P43; OTHERWISE, SKIP TO P45] 2016 – 2030 Upper Midwest Resource Plan
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P43. And would you expect to actually reduce your demand for electricity by that amount, or would you expect to use your backup generation capacity to replace the electricity that you would have received from the electricity utility? 4. Actually reduce demand 5. Use backup generation to replace that electricity 6. Not sure [IF P43 = 2, ASK P44; OTHERWISE SKIP TO P45] P44. Please assume that if your backup generation capacity was not available for some reason, then under this plan, you would still need to reduce your load by the agreed upon amount. If this was the case, how likely would you be to participate? Not At All Likely Extremely Likely 0 1 2 3 4 5 6 7 8 9 10 [IF P41=0‐5, ASK P45; OTHERWISE SKIP TO P46] P45. Now, thinking about this second version of the Interruptible rate again that would have more frequent interruptions, imagine that the average bill credit was $11 per kW for every month of the year for the number of kWs that you agreed to reduce your demand. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Extremely Not At All Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 [IF P41=6‐10, ASK P46; OTHERWISE SKIP TO P47] P46. Now, thinking about this second version of the Interruptible rate again that would have more frequent interruptions, imagine that the average bill credit was $7 per kW for every month of the year for the number of kWs that you agreed to reduce your demand. If this electricity rate was available to you, how interested would you be in signing up for this rate? Please note that we are using the 0‐10 scale. Extremely Not At All Interested In Signing Up Interested In Signing Up 0 1 2 3 4 5 6 7 8 9 10 2016 – 2030 Upper Midwest Resource Plan
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P47. Now the last program option we will ask you about is called “demand bidding.” Under this program, customers would offer to reduce their load and Xcel Energy would pay you for each kilowatt hour that you reduce your load during periods of critical peak electricity usage. More specifically,  Customers would provide a daily schedule to Xcel Energy indicating the amount of load they would be willing to reduce during the next day’s peak, and the price they want to receive for making that load reduction  Assume that the plan would be in effect during the summer, especially during hot summer afternoons and evenings  Customers who have their price agreed to by Xcel Energy would actually need to make those load reductions the next day or incur financial penalties Again, we know that this would take further study, but let’s assume that the price that Xcel Energy would agree to pay you would be 75 cents for each kilowatt hour that you agreed to reduce your load during the next day. Based on what you heard, if this option was available to you, how often – during the summer – do you think you would expect to participate in this program? Please use a scale from “0” to “10” where “0” means “never” and “10” means “as often as possible.” Never As often as Possible 0 1 2 3 4 5 6 7 8 9 10 [IF P47=0‐5, ASK P48; OTHERWISE SKIP TO P49] P48. Now, if the payment for each kilowatt hour that you reduced your load was $1.00 cents, how often – during the summer – do you think you would participate in the program? Never As often as Possible 0 1 2 3 4 5 6 7 8 9 10 [IF P47=6‐10, ASK P25; OTHERWISE SKIP TO C0] P49. Now, if the payment for each kilowatt hour that you reduced your load was 50 cents, how often – during the summer – do you think you would participate in the program? Never As often as Possible 0 1 2 3 4 5 6 7 8 9 10 [IF ANY P47 – P49=7 OR HIGHER, ASK P50; OTHERWISE, SKIP TO C0] P50. About what percentage of your load do you think you would reduce – on average ‐ if Xcel Energy accepted your bid to participate in this program? __________________ [ENTER %] 2016 – 2030 Upper Midwest Resource Plan
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CLOSE / INCENTIVE INFO We appreciate your time and effort in responding to our questions. In order to send you the compensation we promised for your help with this research, I will need your name and address information for the check. C0. [DO NOT READ] 1. RESPONDENT REFUSES INCENTIVE [GO TO C0_1] 2. GO TO PAYMENT INFO SCREEN (C1‐7) CO_1. You indicated that you do not wish to receive the $50 for completing the survey. Is that correct? [INTERVIEWER, DO NOT READ CHOICES; SELECT 1] 1. CORRECT – NO INCENTIVE AT ALL [GO TO NO INCENTIVE CLOSE] 2. DONATE INCENTIVE TO HABITAT FOR HUMANITY [GO TO NO INCENTIVE CLOSE] 3. INCORRECT, RESPONDENT DOES WANT INCENTIVE; GO TO C1 [IF CO_1=1 OR 2, READ ‘NO INCENTIVE CLOSE’; OTHERWISE, GOT TO INCENTIVE INFO CAPTURE SCREEN] [NO INCENTIVE CLOSE:] Thank you again for your participation. If you would like information on how your business can save money on energy bills, please visit Xcel Energy at www.xcelenergy.com. Have a nice day!” [END OF SURVEY] [INCENTIVE INFO CAPTURE SCREEN] C1. NAME: C2. COMPANY NAME (OPTIONAL): C3. ADDRESS 1: C4. ADDRESS 2: C5. CITY: C6: STATE: C7: ZIP: C8. {PROGRAMMER, RESTORE NAME & ADDRESS INFO FOR VERIFICATION} [INTERVIEWER, READ RESTORED INFO TO RESPONDENT AND ASK:] Is this information correct? 1. Yes 2. No [IF C8=2, RE‐ENTER INFO UNTIL CORRECT; WHEN CORRECT, READ:] Thank you for your participation. It will take 2‐4 weeks to process and mail your check. If you would like information on how your business can save money on energy bills, please visit Xcel Energy at www.xcelenergy.com Have a nice day. 2016 – 2030 Upper Midwest Resource Plan
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Appendix D:
Additional Methodological Notes on the
Market Research Study
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Additional Methodological Notes on the Market Research Study
Sampling and Weighting
In order to be as cost-effective as possible, the residential sample for this work was drawn
from online panel sources. Potential respondents were then screened to ensure that they
were NSP customers, reported living in a zip code served by NSP, paid an electric bill
directly to the utility, were primary or joint energy decision makers for their household, and
did not report that anyone in their household worked in a disqualifying industry
(Advertising, Broadcasting, Electric or natural gas utility, Environmental Protection, Public
Relations, or Government).
The zip codes of respondents were monitored and quotas were established to ensure that the
distribution of respondents across states was consistent with the actual distribution of
customers across those states, and that a minimum number of respondents from both singlefamily and multi-family homes were represented in the sample. Additionally, census data
was used to weight the sample on single-family / multi-family housing type, gender, and age,
so that the resulting weighted database was consistent with the underlying universe on those
variables.
Telephone surveys were used with business customers since there was no viable online panel
source for this population. NSP provided YouGov America with a sample of qualifying
business establishments (single business entities operating at a single, contiguous, physical
locations). These individual business establishments were sometimes served by multiple
physical meters. Telephone calls were used to qualify respondent facilities as ones that
included enclosed space, and qualified respondents as at least knowledgeable about energyrelated decisions.
The final business sample was disproportionately allocated by customer strata (smaller,
medium, larger), but weighting was not applied to the sample, since there was no intention
to conduct analysis on the business sample in total, but rather, only within strata. Separate
questionnaires were used for smaller vs. medium/larger businesses.
Adjusting for Say / Do Overstatement
For each of the DR options tested, respondents answered a question that asked how
interested they would be in signing up for (opting-in to) the option if it was offered as
described in the questionnaire. The team then needed to determine how to use those
responses to estimate an aggregate likely adoption rate for each DR option. Different research
agencies use different approaches to make this calculation, but all need to account for
something generally described as the “say / do” problem. This label applies to the widely
recognized finding that survey respondents in general tend to overstate the likelihood that
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they will take any future action they are asked about. This is particularly relevant to
questions about future purchases, or future likelihood to adopt a new service or sign-up for a
new program. The reality is that almost every respondent is overly optimistic in projecting
these future probabilities. YGA uses a proprietary approach to move from “say” to “do” based
on research the company conducted during 2010. This research captured stated likelihood to
adopt / purchase a variety of new products / services, at one point in time, and then tracked
actual product / service adoption / purchase over 6 -12 months. The research was conducted
with consumers, and with smaller and medium sized business customers over a broad range
of IT, telecom, and energy related products and services. As we expected, people were less
likely to actually purchase or adopt products / services than they estimated they would do at
an earlier time. We also found that the rate at which customer stated intentions needed to be
adjusted to make them similar to what they actually did had broad similarities across product
and customers classes. This is not to say that there were not differences. Indeed, we found
that:

Customers who were more knowledgeable about, or had more experience with, a
given product category made better estimates of their future behavior.

In particular, customers who made regular purchases within a given product or
service category were much better predictors of their future behavior.

While small and medium business customers were no better than consumers – in the
aggregate in predicting their future behavior – when businesses had a specialist who
was responsible for making decisions within a given category of purchase (so, an IT
person responsible for making IT purchases, for example), then those persons were
much better than the average business decision maker in predicting their behavior.
For the case at hand – since DR options, and especially the DR rate options tested – were
new to most of the residential and business populations in this sample, we chose to apply our
standard adjustment algorithm to the stated intent values we saw. Had we attempted to
generate quantitative estimates for the larger business customer population, a reasonable
argument could have been made that a different adjustment factor (one that adjusted
responses down less aggressively) would have been appropriate (since these customers are
more likely to have knowledgeable energy management specialists on staff, and more likely
to have experience with at least some of the tested rate options). We chose not to do so,
however, since only some of even the larger business customer group either had specialists
on staff, or had experience with some the rates.
Based on that the YouGov America proprietary research, then, we applied our “standard”
algorithm to customer responses as is indicated below. These values mean, for example, that
| brattle.com
2016 – 2030 Upper Midwest Resource Plan
Page 233 of 243
Appendix O
Demand Response Market Potential in Xcel Energys NSP Service Territory - Brattle
Draft - Confidential
if someone rates their response a “10” (extremely likely to participate), then the algorithm
treats that respondent case as having a 56% probability of adopting.
Scale Rating
Not at all Likely to
Participate
0
1
2
0%
5%
5%
3
6%
4
8%
5
18%
6
20%
7
31%
Extremely Likely to
Participate
8
9
10
38%
44%
56%
NB: It is extremely important to note two important caveats that accompany the aggregate
likely adoption rates that are calculated by the above process:

The calculation assumes that everyone in the marketplace is aware of the program
offer, and not simply aware of it in general concept, but aware of it in the same level
of detail that was provided to respondents in the survey

Any changes in the design of the DR program offer that is ultimately made to
customers may have a significant effect on the estimated take rate. If a CPP rate was
described as having a specific set of on-peak hours and a specific limit of possible
critical peak days, and the offer made to customers differs on these details, for
example, then the original estimated likely take rate is no longer applicable.
The team also used the same set of survey responses to estimate the proportion of the
population that would be likely to “opt-out” of programs onto which they were defaulted as
participants, rather than to opt-in to programs which they had the option to join. Note that
the questions that respondents saw only asked about their likelihood to adopt the DR
options, not about their likelihood to reject those options if they were defaulted onto them
initially. We obviously recognize that actual program experience would have a critical effect
on opt-out rates, but for purposes of estimation, the team chose to interpret strongly negative
reaction to the rates as an indication of the people who would be most likely to reject (optout of) those rates if they had the chance.
For this reason, the team used the opt-in questions, but inverted the adjustment values for
those responding 0-5 to estimate total likely opt-outs and adjusted those responses to
generate probabilities of opt-out on a case-by-case basis as is indicated below.
Scale Rating
Extremely Likely to
Participate
10
9
8
0%
0%
0%
7
0%
6
0%
5
18%
4
20%
3
31%
Not at all Likely to
Participate
2
1
0
38%
44%
56%
| brattle.com
2016 – 2030 Upper Midwest Resource Plan
Page 234 of 243
Appendix O
Demand Response Market Potential in Xcel Energys NSP Service Territory - Brattle
Appendix E:
Annual DR Impact Tables
| brattle.com
2016 – 2030 Upper Midwest Resource Plan
Page 235 of 243
Appendix O
Demand Response Market Potential in Xcel Energys NSP Service Territory - Brattle
Measure‐level Peak Reduction Potential (MW, grossed up for line losses)
Current portfolio of DR programs
Class
Residential
Residential
Residential
Residential
Residential
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Program
DLC ‐ SFH
DLC ‐ MDU
TOU
CPP
CPP w/Tech
DLC
Demand Bidding
TOU
CPP
CPP w/Tech
DLC
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
2014
266
0
0
0
0
20
0
0
0
0
27
329
0
0
0
0
0
360
0
0
0
0
0
2015
270
0
0
0
0
21
0
0
0
0
27
329
0
0
0
0
0
360
0
0
0
0
0
2016
275
0
0
0
0
22
0
0
0
0
27
329
0
0
0
0
0
360
0
0
0
0
0
2017
282
0
0
0
0
23
0
0
0
0
27
329
0
0
0
0
0
360
0
0
0
0
0
2018
288
0
0
0
0
24
0
0
0
0
27
329
0
0
0
0
0
360
0
0
0
0
0
2019
290
0
0
0
0
24
0
0
0
0
27
331
0
0
0
0
0
361
0
0
0
0
0
2020
291
0
0
0
0
24
0
0
0
0
27
333
0
0
0
0
0
362
0
0
0
0
0
2021
292
0
0
0
0
24
0
0
0
0
27
334
0
0
0
0
0
364
0
0
0
0
0
2022
293
0
0
0
0
24
0
0
0
0
27
336
0
0
0
0
0
365
0
0
0
0
0
2023
295
0
0
0
0
24
0
0
0
0
27
338
0
0
0
0
0
364
0
0
0
0
0
2024
296
0
0
0
0
25
0
0
0
0
27
340
0
0
0
0
0
362
0
0
0
0
0
2025
297
0
0
0
0
25
0
0
0
0
28
342
0
0
0
0
0
359
0
0
0
0
0
2026
299
0
0
0
0
25
0
0
0
0
28
344
0
0
0
0
0
356
0
0
0
0
0
2027
300
0
0
0
0
25
0
0
0
0
28
346
0
0
0
0
0
354
0
0
0
0
0
2028
302
0
0
0
0
25
0
0
0
0
28
347
0
0
0
0
0
351
0
0
0
0
0
2014
266
0
0
0
0
20
0
0
0
0
27
329
0
0
0
0
0
360
0
0
87
0
0
2015
303
6
0
0
0
34
0
0
0
0
30
601
553
7
0
0
0
391
214
3
87
13
20
2016
340
12
0
0
0
49
0
0
0
0
34
878
1004
14
0
0
0
414
425
5
88
27
41
2017
342
18
0
0
0
49
0
0
0
0
35
883
1010
21
0
0
0
419
431
8
89
41
62
2018
344
24
0
0
0
49
0
0
0
0
35
888
1016
28
0
0
0
420
432
11
89
41
63
2019
345
30
0
0
0
49
0
0
0
0
35
894
1023
35
0
0
0
422
433
14
90
41
63
2020
346
30
0
0
0
50
0
0
0
0
35
901
1031
35
0
0
0
423
435
14
91
42
64
2021
348
30
0
0
0
50
0
0
0
0
35
907
1038
36
0
0
0
425
436
14
92
42
64
2022
349
30
0
0
0
50
0
0
0
0
35
913
1045
36
0
0
0
426
437
14
92
42
65
2023
351
30
0
0
0
50
0
0
0
0
36
919
1051
36
0
0
0
425
436
14
93
42
65
2024
353
30
0
0
0
51
0
0
0
0
36
924
1057
36
0
0
0
423
434
14
93
43
66
2025
354
30
21
52
88
51
0
0
0
2
36
929
1062
37
9
24
32
419
431
14
94
43
66
2026
356
31
43
105
178
51
0
0
0
5
36
935
1069
37
18
48
63
416
427
14
95
43
66
2027
358
31
65
159
268
52
0
0
1
7
36
940
1075
37
27
72
96
413
424
14
95
43
67
2028
360
31
65
160
270
52
0
0
1
7
37
945
1081
37
27
73
96
410
421
14
96
44
67
2019
345
30
0
0
0
49
0
0
0
0
35
894
1023
35
0
0
0
422
433
14
90
149
254
2020
346
30
0
0
0
50
0
0
0
0
35
901
1031
35
0
0
0
423
435
14
91
150
256
2021
348
30
0
0
0
50
0
0
0
0
35
907
1038
36
0
0
0
425
436
14
92
151
259
2022
349
30
0
0
0
50
0
0
0
0
35
913
1045
36
0
0
0
426
437
14
92
152
261
2023
351
30
0
0
0
50
0
0
0
0
36
919
1051
36
0
0
0
425
436
14
93
153
262
2024
353
30
0
0
0
51
0
0
0
0
36
924
1057
36
0
0
0
423
434
14
93
154
264
2025
354
30
153
235
382
51
0
1
1
21
36
929
1062
37
96
153
423
419
431
14
94
155
265
2026
356
31
147
230
378
51
0
1
1
20
36
935
1069
37
85
141
393
416
427
14
95
156
267
2027
358
31
140
225
373
52
0
1
1
18
36
940
1075
37
74
129
361
413
424
14
95
157
268
2028
360
31
141
226
375
52
0
1
1
18
37
945
1081
37
74
129
363
410
421
14
96
158
270
With opt‐in deployment for all measures
Class
Residential
Residential
Residential
Residential
Residential
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Program
DLC ‐ SFH
DLC ‐ MDU
TOU
CPP
CPP w/Tech
DLC
Demand Bidding
TOU
CPP
CPP w/Tech
DLC
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
With opt‐in deployment for traditional measures and opt‐out deployment for AMI‐enabled measures
Class
Residential
Residential
Residential
Residential
Residential
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Program
DLC ‐ SFH
DLC ‐ MDU
TOU
CPP
CPP w/Tech
DLC
Demand Bidding
TOU
CPP
CPP w/Tech
DLC
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
2014
266
0
0
0
0
20
0
0
0
0
27
329
0
0
0
0
0
360
0
0
87
0
0
2015
303
6
0
0
0
34
0
0
0
0
30
601
553
7
0
0
0
391
214
3
87
169
274
2016
340
12
0
0
0
49
0
0
0
0
34
878
1004
14
0
0
0
414
425
5
88
158
262
2017
342
18
0
0
0
49
0
0
0
0
35
883
1010
21
0
0
0
419
431
8
89
146
250
2018
344
24
0
0
0
49
0
0
0
0
35
888
1016
28
0
0
0
420
432
11
89
147
252
2016 – 2030 Upper Midwest Resource Plan
Page 236 of 243
Appendix O
Demand Response Market Potential in Xcel Energys NSP Service Territory - Brattle
Portfolio‐level Peak Reduction Potential, Including All Measures Regardless of Cost‐Effectiveness (MW, grossed up for line losses) ‐ 1 of 2
Current portfolio of DR programs
Class
Residential
Residential
Residential
Residential
Residential
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Program
DLC ‐ SFH
DLC ‐ MDU
TOU
CPP
CPP w/Tech
DLC
Demand Bidding
TOU
CPP
CPP w/Tech
DLC
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
2014
266
0
0
0
0
20
0
0
0
0
27
329
0
0
0
0
0
360
0
0
0
0
0
2015
270
0
0
0
0
21
0
0
0
0
27
329
0
0
0
0
0
360
0
0
0
0
0
2016
275
0
0
0
0
22
0
0
0
0
27
329
0
0
0
0
0
360
0
0
0
0
0
2017
282
0
0
0
0
23
0
0
0
0
27
329
0
0
0
0
0
360
0
0
0
0
0
2018
288
0
0
0
0
24
0
0
0
0
27
329
0
0
0
0
0
360
0
0
0
0
0
2019
290
0
0
0
0
24
0
0
0
0
27
331
0
0
0
0
0
361
0
0
0
0
0
2020
291
0
0
0
0
24
0
0
0
0
27
333
0
0
0
0
0
362
0
0
0
0
0
2021
292
0
0
0
0
24
0
0
0
0
27
334
0
0
0
0
0
364
0
0
0
0
0
2022
293
0
0
0
0
24
0
0
0
0
27
336
0
0
0
0
0
365
0
0
0
0
0
2023
295
0
0
0
0
24
0
0
0
0
27
338
0
0
0
0
0
364
0
0
0
0
0
2024
296
0
0
0
0
25
0
0
0
0
27
340
0
0
0
0
0
362
0
0
0
0
0
2025
297
0
0
0
0
25
0
0
0
0
28
342
0
0
0
0
0
359
0
0
0
0
0
2026
299
0
0
0
0
25
0
0
0
0
28
344
0
0
0
0
0
356
0
0
0
0
0
2027
300
0
0
0
0
25
0
0
0
0
28
346
0
0
0
0
0
354
0
0
0
0
0
2028
302
0
0
0
0
25
0
0
0
0
28
347
0
0
0
0
0
351
0
0
0
0
0
2014
266
0
0
0
0
20
0
0
0
0
27
329
0
0
0
0
0
360
0
0
0
0
0
2015
303
6
0
0
0
33
0
0
0
0
26
350
0
7
0
0
0
363
0
3
0
0
0
2016
340
12
0
0
0
47
0
0
0
0
29
510
0
13
0
0
0
385
0
6
0
0
0
2017
342
18
0
0
0
47
0
0
0
0
30
514
0
20
0
0
0
390
0
9
0
0
0
2018
344
24
0
0
0
47
0
0
0
0
30
517
0
27
0
0
0
391
0
11
0
0
0
2019
345
30
0
0
0
48
0
0
0
0
30
520
0
34
0
0
0
392
0
14
0
0
0
2020
346
30
0
0
0
48
0
0
0
0
30
524
0
34
0
0
0
394
0
15
0
0
0
2021
348
30
0
0
0
48
0
0
0
0
30
528
0
34
0
0
0
395
0
15
0
0
0
2022
349
30
0
0
0
48
0
0
0
0
30
531
0
34
0
0
0
396
0
15
0
0
0
2023
351
30
0
0
0
49
0
0
0
0
31
535
0
35
0
0
0
395
0
15
0
0
0
2024
353
30
0
0
0
49
0
0
0
0
31
538
0
35
0
0
0
393
0
15
0
0
0
2025
354
30
0
0
0
49
0
0
0
0
31
540
0
35
0
0
0
390
0
15
0
0
0
2026
356
31
0
0
0
49
0
0
0
0
31
544
0
35
0
0
0
387
0
15
0
0
0
2027
358
31
0
0
0
50
0
0
0
0
31
547
0
35
0
0
0
384
0
15
0
0
0
2028
360
31
0
0
0
50
0
0
0
0
31
550
0
36
0
0
0
382
0
15
0
0
0
2016
340
12
0
0
0
47
0
0
0
0
29
510
0
13
0
0
0
385
0
6
10
0
0
2017
342
18
0
0
0
47
0
0
0
0
30
514
0
20
0
0
0
390
0
9
10
0
0
2018
344
24
0
0
0
47
0
0
0
0
30
517
0
27
0
0
0
391
0
11
10
0
0
2019
345
30
0
0
0
48
0
0
0
0
30
520
0
34
0
0
0
392
0
14
10
0
0
2020
346
30
0
0
0
48
0
0
0
0
30
524
0
34
0
0
0
394
0
15
10
0
0
2021
348
30
0
0
0
48
0
0
0
0
30
528
0
34
0
0
0
395
0
15
10
0
0
2022
349
30
0
0
0
48
0
0
0
0
30
531
0
34
0
0
0
396
0
15
10
0
0
2023
351
30
0
0
0
49
0
0
0
0
31
535
0
35
0
0
0
395
0
15
10
0
0
2024
353
30
0
0
0
49
0
0
0
0
31
538
0
35
0
0
0
393
0
15
11
0
0
2025
338
28
15
0
0
45
0
0
0
0
31
482
0
27
6
0
0
381
0
10
11
0
0
2026
340
28
31
0
0
45
0
0
0
0
31
485
0
27
11
0
0
378
0
11
11
0
0
2027
342
28
46
0
0
46
0
0
0
0
31
488
0
27
17
0
0
375
0
11
11
0
0
2028
343
28
46
0
0
46
0
0
0
0
31
491
0
27
17
0
0
373
0
11
11
0
0
Portfolio #1 (traditional DR options only)
Class
Residential
Residential
Residential
Residential
Residential
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Program
DLC ‐ SFH
DLC ‐ MDU
TOU
CPP
CPP w/Tech
DLC
Demand Bidding
TOU
CPP
CPP w/Tech
DLC
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Portfolio #2 (traditional DR options plus opt‐in redesigned TOU)
Class
Residential
Residential
Residential
Residential
Residential
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Program
DLC ‐ SFH
DLC ‐ MDU
TOU
CPP
CPP w/Tech
DLC
Demand Bidding
TOU
CPP
CPP w/Tech
DLC
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
2014
266
0
0
0
0
20
0
0
0
0
27
329
0
0
0
0
0
360
0
0
0
0
0
2015
303
6
0
0
0
33
0
0
0
0
26
350
0
7
0
0
0
363
0
3
10
0
0
2016 – 2030 Upper Midwest Resource Plan
Page 237 of 243
Appendix O
Demand Response Market Potential in Xcel Energys NSP Service Territory - Brattle
Portfolio‐level Peak Reduction Potential, Including All Measures Regardless of Cost‐Effectiveness (MW, grossed up for line losses) ‐ 2 of 2
Portfolio #3 (traditional DR options plus opt‐out redesigned TOU)
Class
Residential
Residential
Residential
Residential
Residential
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Program
DLC ‐ SFH
DLC ‐ MDU
TOU
CPP
CPP w/Tech
DLC
Demand Bidding
TOU
CPP
CPP w/Tech
DLC
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
2014
266
0
0
0
0
20
0
0
0
0
27
329
0
0
0
0
0
360
0
0
0
0
0
2015
303
6
0
0
0
33
0
0
0
0
26
350
0
7
0
0
0
363
0
3
41
0
0
2016
340
12
0
0
0
47
0
0
0
0
29
510
0
13
0
0
0
385
0
6
41
0
0
2017
342
18
0
0
0
47
0
0
0
0
30
514
0
20
0
0
0
390
0
9
41
0
0
2018
344
24
0
0
0
47
0
0
0
0
30
517
0
27
0
0
0
391
0
11
42
0
0
2019
345
30
0
0
0
48
0
0
0
0
30
520
0
34
0
0
0
392
0
14
42
0
0
2020
346
30
0
0
0
48
0
0
0
0
30
524
0
34
0
0
0
394
0
15
42
0
0
2021
348
30
0
0
0
48
0
0
0
0
30
528
0
34
0
0
0
395
0
15
43
0
0
2022
349
30
0
0
0
48
0
0
0
0
30
531
0
34
0
0
0
396
0
15
43
0
0
2023
351
30
0
0
0
49
0
0
0
0
31
535
0
35
0
0
0
395
0
15
43
0
0
2024
353
30
0
0
0
49
0
0
0
0
31
538
0
35
0
0
0
393
0
15
44
0
0
2025
338
28
94
0
0
45
0
1
0
0
31
482
0
27
59
0
0
381
0
10
44
0
0
2026
340
28
90
0
0
45
0
1
0
0
31
485
0
27
52
0
0
378
0
11
44
0
0
2027
342
28
86
0
0
46
0
1
0
0
31
488
0
27
46
0
0
375
0
11
44
0
0
2028
343
28
86
0
0
46
0
1
0
0
31
491
0
27
46
0
0
373
0
11
45
0
0
2017
342
18
0
0
0
47
0
0
0
0
30
514
0
20
0
0
0
390
0
9
0
0
117
2018
344
24
0
0
0
47
0
0
0
0
30
517
0
27
0
0
0
391
0
11
0
0
118
2019
345
30
0
0
0
48
0
0
0
0
30
520
0
34
0
0
0
392
0
14
0
0
119
2020
346
30
0
0
0
48
0
0
0
0
30
524
0
34
0
0
0
394
0
15
0
0
120
2021
348
30
0
0
0
48
0
0
0
0
30
528
0
34
0
0
0
395
0
15
0
0
121
2022
349
30
0
0
0
48
0
0
0
0
30
531
0
34
0
0
0
396
0
15
0
0
121
2023
351
30
0
0
0
49
0
0
0
0
31
535
0
35
0
0
0
395
0
15
0
0
122
2024
353
30
0
0
0
49
0
0
0
0
31
538
0
35
0
0
0
393
0
15
0
0
123
2025
338
28
0
0
235
45
0
0
0
18
31
482
0
27
0
0
267
381
0
10
0
0
124
2026
340
28
0
0
232
45
0
0
0
17
31
485
0
27
0
0
248
378
0
11
0
0
124
2027
342
28
0
0
229
46
0
0
0
16
31
488
0
27
0
0
228
375
0
11
0
0
125
2028
343
28
0
0
231
46
0
0
0
16
31
491
0
27
0
0
229
373
0
11
0
0
126
Portfolio #3 (traditional DR options plus opt‐out CPP with enabling technology)
Class
Residential
Residential
Residential
Residential
Residential
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Program
DLC ‐ SFH
DLC ‐ MDU
TOU
CPP
CPP w/Tech
DLC
Demand Bidding
TOU
CPP
CPP w/Tech
DLC
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
Interruptible (Reliability)
Interruptible (Price)
Demand Bidding
TOU
CPP
CPP w/Tech
2014
266
0
0
0
0
20
0
0
0
0
27
329
0
0
0
0
0
360
0
0
0
0
0
2015
303
6
0
0
0
33
0
0
0
0
26
350
0
7
0
0
0
363
0
3
0
0
128
2016
340
12
0
0
0
47
0
0
0
0
29
510
0
13
0
0
0
385
0
6
0
0
122
2016 – 2030 Upper Midwest Resource Plan
Page 238 of 243
Appendix O
Demand Response Market Potential in Xcel Energys NSP Service Territory - Brattle
Appendix F:
DR Supply Curves
| brattle.com
2016 – 2030 Upper Midwest Resource Plan
Page 239 of 243
Appendix O
Demand Response Market Potential in Xcel Energys NSP Service Territory - Brattle
The DR Supply Curve
The following are costs and peak reductions associated with each individual DR measure at each of the five "price points" that were tested through primary market research (very low, low, medium, high, and very high)
Impacts below assume each measure is offered in isolation; see "Portfolio Participation" table for impacts if mutually exclusive measures were simultaneously offered
Impacts have been grossed up to account for line losses; they are generator‐level impacts rather than meter‐level impacts
Impacts represent maximum potential participation in each year and only account for a multi‐year ramp up/down period from current participation levels in the first few years of the forecast horizon
Impacts represent total peak reduction available at each price point, as opposed to incremental additional peak reduction at each price point
For DLC, the $/kW‐year estimate excludes equipment costs. Those are represented separately as a one‐time, up‐front cost and are expressed in $/kW
All costs are in real 2013 dollars
Class
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Program
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ MDU
DLC ‐ MDU
DLC ‐ MDU
DLC ‐ MDU
DLC ‐ MDU
DLC ‐ MDU
DLC ‐ MDU
DLC ‐ MDU
DLC ‐ MDU
DLC ‐ MDU
DLC ‐ MDU
DLC ‐ MDU
DLC ‐ MDU
DLC ‐ MDU
DLC ‐ MDU
DLC
DLC
DLC
DLC
DLC
DLC
DLC
DLC
DLC
DLC
DLC
DLC
DLC
DLC
DLC
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Price Point
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Variable
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW, one time)
Cost ($/kW, one time)
Cost ($/kW, one time)
Cost ($/kW, one time)
Cost ($/kW, one time)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MW)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW, one time)
Cost ($/kW, one time)
Cost ($/kW, one time)
Cost ($/kW, one time)
Cost ($/kW, one time)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MW)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW, one time)
Cost ($/kW, one time)
Cost ($/kW, one time)
Cost ($/kW, one time)
Cost ($/kW, one time)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MWh/hr)
Impact (MWh/hr)
Impact (MWh/hr)
Impact (MWh/hr)
Impact (MWh/hr)
Cost ($/MWh)
Cost ($/MWh)
Cost ($/MWh)
Cost ($/MWh)
Cost ($/MWh)
Cost ($/year)
Cost ($/year)
Cost ($/year)
Cost ($/year)
Cost ($/year)
2014
64
89
119
144
184
240
240
240
240
240
190
219
266
317
375
71
96
126
151
191
426
426
426
426
426
0
0
0
0
0
41
66
96
121
161
78
78
78
78
78
15
17
19
20
22
0.0
0.0
0.0
0.0
0.0
100
300
500
750
1,000
620,000
620,000
620,000
620,000
620,000
2015
64
89
119
144
184
240
240
240
240
240
216
250
303
361
427
71
96
126
151
191
426
426
426
426
426
4
5
6
6
7
41
66
96
121
161
78
78
78
78
78
25
30
33
34
38
0.0
0.0
0.0
0.1
0.1
100
300
500
750
1,000
620,000
620,000
620,000
620,000
620,000
2016
64
89
119
144
184
240
240
240
240
240
243
280
340
405
479
71
96
126
151
191
426
426
426
426
426
9
10
12
12
13
41
66
96
121
161
78
78
78
78
78
35
42
47
49
54
0.1
0.1
0.1
0.1
0.1
100
300
500
750
1,000
620,000
620,000
620,000
620,000
620,000
2017
64
89
119
144
184
240
240
240
240
240
244
282
342
408
482
71
96
126
151
191
426
426
426
426
426
13
16
18
19
20
41
66
96
121
161
78
78
78
78
78
36
42
47
49
54
0.1
0.1
0.1
0.2
0.2
100
300
500
750
1,000
620,000
620,000
620,000
620,000
620,000
2018
64
89
119
144
184
240
240
240
240
240
245
283
344
409
484
71
96
126
151
191
426
426
426
426
426
18
21
24
25
27
41
66
96
121
161
78
78
78
78
78
36
42
47
49
54
0.2
0.2
0.2
0.3
0.3
100
300
500
750
1,000
620,000
620,000
620,000
620,000
620,000
2019
64
89
119
144
184
240
240
240
240
240
246
284
345
411
486
71
96
126
151
191
426
426
426
426
426
22
27
30
32
34
41
66
96
121
161
78
78
78
78
78
36
43
48
49
55
0.2
0.2
0.2
0.3
0.4
100
300
500
750
1,000
620,000
620,000
620,000
620,000
620,000
2020
64
89
119
144
184
240
240
240
240
240
247
285
346
413
488
71
96
126
151
191
426
426
426
426
426
22
27
30
32
34
41
66
96
121
161
78
78
78
78
78
36
43
48
50
55
0.2
0.2
0.2
0.3
0.4
100
300
500
750
1,000
620,000
620,000
620,000
620,000
620,000
2021
64
89
119
144
184
240
240
240
240
240
248
286
348
414
490
71
96
126
151
191
426
426
426
426
426
23
27
30
32
34
41
66
96
121
161
78
78
78
78
78
36
43
48
50
55
0.2
0.2
0.2
0.3
0.4
100
300
500
750
1,000
620,000
620,000
620,000
620,000
620,000
2022
64
89
119
144
184
240
240
240
240
240
249
287
349
416
492
71
96
126
151
191
426
426
426
426
426
23
27
30
32
34
41
66
96
121
161
78
78
78
78
78
37
43
48
50
55
0.2
0.2
0.3
0.3
0.4
100
300
500
750
1,000
620,000
620,000
620,000
620,000
620,000
2023
64
89
119
144
184
240
240
240
240
240
250
289
351
418
494
71
96
126
151
191
426
426
426
426
426
23
27
30
32
35
41
66
96
121
161
78
78
78
78
78
37
44
48
50
56
0.2
0.2
0.3
0.3
0.4
100
300
500
750
1,000
620,000
620,000
620,000
620,000
620,000
2024
64
89
119
144
184
240
240
240
240
240
251
290
353
420
496
71
96
126
151
191
426
426
426
426
426
23
27
30
32
35
41
66
96
121
161
78
78
78
78
78
37
44
49
51
56
0.2
0.2
0.3
0.3
0.4
100
300
500
750
1,000
620,000
620,000
620,000
620,000
620,000
2025
64
89
119
144
184
240
240
240
240
240
252
292
354
422
499
71
96
126
151
191
426
426
426
426
426
23
27
30
33
35
41
66
96
121
161
78
78
78
78
78
37
44
49
51
56
0.2
0.2
0.3
0.3
0.4
100
300
500
750
1,000
620,000
620,000
620,000
620,000
620,000
2026
64
89
119
144
184
240
240
240
240
240
254
293
356
424
501
71
96
126
151
191
426
426
426
426
426
23
27
31
33
35
41
66
96
121
161
78
78
78
78
78
37
44
49
51
57
0.2
0.2
0.3
0.3
0.4
100
300
500
750
1,000
620,000
620,000
620,000
620,000
620,000
2027
64
89
119
144
184
240
240
240
240
240
255
295
358
426
504
71
96
126
151
191
426
426
426
426
426
23
27
31
33
35
41
66
96
121
161
78
78
78
78
78
38
45
50
52
57
0.2
0.2
0.3
0.3
0.4
100
300
500
750
1,000
620,000
620,000
620,000
620,000
620,000
2028
64
89
119
144
184
240
240
240
240
240
256
296
360
428
506
71
96
126
151
191
426
426
426
426
426
23
28
31
33
35
41
66
96
121
161
78
78
78
78
78
38
45
50
52
57
0.2
0.2
0.3
0.3
0.4
100
300
500
750
1,000
620,000
620,000
620,000
620,000
620,000
2016 – 2030 Upper Midwest Resource Plan
Page 240 of 243
Appendix O
Demand Response Market Potential in Xcel Energys NSP Service Territory - Brattle
The DR Supply Curve (continued)
Class
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Program
DLC
DLC
DLC
DLC
DLC
DLC
DLC
DLC
DLC
DLC
DLC
DLC
DLC
DLC
DLC
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Price Point
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Variable
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW, one time)
Cost ($/kW, one time)
Cost ($/kW, one time)
Cost ($/kW, one time)
Cost ($/kW, one time)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MW)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MW)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MW)
Cost ($/year)
Cost ($/year)
Cost ($/year)
Cost ($/year)
Cost ($/year)
Cost ($/MWh)
Cost ($/MWh)
Cost ($/MWh)
Cost ($/MWh)
Cost ($/MWh)
Impact (MWh/hr)
Impact (MWh/hr)
Impact (MWh/hr)
Impact (MWh/hr)
Impact (MWh/hr)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MW)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Cost ($/kW‐year)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MW)
Impact (MW)
Cost ($/year)
Cost ($/year)
Cost ($/year)
Cost ($/year)
Cost ($/year)
Cost ($/MWh)
Cost ($/MWh)
Cost ($/MWh)
Cost ($/MWh)
Cost ($/MWh)
Impact (MWh/hr)
Impact (MWh/hr)
Impact (MWh/hr)
Impact (MWh/hr)
Impact (MWh/hr)
2014
35
60
90
115
155
78
78
78
78
78
23
24
25
27
28
30
55
85
110
150
296
306
329
376
442
55
80
110
135
175
0
0
0
0
0
240,000
240,000
240,000
240,000
240,000
100
300
500
750
1,000
0
0
0
0
0
31
56
86
111
151
324
335
360
412
484
56
81
111
136
176
0
0
0
0
0
270,000
270,000
270,000
270,000
270,000
100
300
500
750
1,000
0
0
0
0
0
2015
35
60
90
115
155
78
78
78
78
78
26
28
28
30
32
30
55
85
110
150
541
560
601
688
809
55
80
110
135
175
461
507
553
600
656
240,000
240,000
240,000
240,000
240,000
100
300
500
750
1,000
5
6
7
8
10
31
56
86
111
151
351
364
391
447
525
56
81
111
136
176
178
196
214
232
254
270,000
270,000
270,000
270,000
270,000
100
300
500
750
1,000
2
2
3
3
4
2016
35
60
90
115
155
78
78
78
78
78
30
31
32
34
37
30
55
85
110
150
789
817
878
1004
1180
55
80
110
135
175
838
921
1004
1089
1192
240,000
240,000
240,000
240,000
240,000
100
300
500
750
1,000
10
12
14
17
20
31
56
86
111
151
372
385
414
473
556
56
81
111
136
176
355
390
425
461
504
270,000
270,000
270,000
270,000
270,000
100
300
500
750
1,000
4
4
5
6
8
2017
35
60
90
115
155
78
78
78
78
78
30
31
32
35
37
30
55
85
110
150
794
822
883
1010
1187
55
80
110
135
175
843
927
1010
1096
1199
240,000
240,000
240,000
240,000
240,000
100
300
500
750
1,000
16
17
21
26
30
31
56
86
111
151
377
390
419
479
564
56
81
111
136
176
359
395
431
467
511
270,000
270,000
270,000
270,000
270,000
100
300
500
750
1,000
6
7
8
10
11
2018
35
60
90
115
155
78
78
78
78
78
30
32
32
35
37
30
55
85
110
150
799
827
888
1016
1195
55
80
110
135
175
848
932
1016
1103
1206
240,000
240,000
240,000
240,000
240,000
100
300
500
750
1,000
21
23
28
34
40
31
56
86
111
151
378
391
420
481
565
56
81
111
136
176
360
396
432
469
513
270,000
270,000
270,000
270,000
270,000
100
300
500
750
1,000
8
9
11
13
15
2019
35
60
90
115
155
78
78
78
78
78
30
32
32
35
37
30
55
85
110
150
805
832
894
1023
1203
55
80
110
135
175
854
938
1023
1110
1214
240,000
240,000
240,000
240,000
240,000
100
300
500
750
1,000
26
30
35
43
51
31
56
86
111
151
379
393
422
483
567
56
81
111
136
176
361
397
433
470
514
270,000
270,000
270,000
270,000
270,000
100
300
500
750
1,000
10
11
14
17
19
2020
35
60
90
115
155
78
78
78
78
78
30
32
33
35
37
30
55
85
110
150
810
838
901
1030
1211
55
80
110
135
175
860
945
1031
1118
1223
240,000
240,000
240,000
240,000
240,000
100
300
500
750
1,000
27
30
35
44
51
31
56
86
111
151
381
394
423
484
569
56
81
111
136
176
363
399
435
472
516
270,000
270,000
270,000
270,000
270,000
100
300
500
750
1,000
10
11
14
17
20
2021
35
60
90
115
155
78
78
78
78
78
30
32
33
35
38
30
55
85
110
150
816
844
907
1037
1219
55
80
110
135
175
866
952
1038
1126
1231
240,000
240,000
240,000
240,000
240,000
100
300
500
750
1,000
27
30
36
44
51
31
56
86
111
151
382
395
425
486
571
56
81
111
136
176
364
400
436
473
518
270,000
270,000
270,000
270,000
270,000
100
300
500
750
1,000
10
12
14
17
20
2022
35
60
90
115
155
78
78
78
78
78
31
32
33
35
38
30
55
85
110
150
821
850
913
1044
1228
55
80
110
135
175
871
958
1045
1133
1240
240,000
240,000
240,000
240,000
240,000
100
300
500
750
1,000
27
30
36
44
52
31
56
86
111
151
383
396
426
487
573
56
81
111
136
176
365
401
437
475
519
270,000
270,000
270,000
270,000
270,000
100
300
500
750
1,000
10
12
14
17
20
2023
35
60
90
115
155
78
78
78
78
78
31
32
33
36
38
30
55
85
110
150
827
855
919
1051
1236
55
80
110
135
175
877
964
1051
1140
1248
240,000
240,000
240,000
240,000
240,000
100
300
500
750
1,000
27
31
36
45
52
31
56
86
111
151
382
395
425
486
571
56
81
111
136
176
364
400
436
473
518
270,000
270,000
270,000
270,000
270,000
100
300
500
750
1,000
10
12
14
17
20
2024
35
60
90
115
155
78
78
78
78
78
31
33
33
36
38
30
55
85
110
150
831
860
924
1057
1243
55
80
110
135
175
882
970
1057
1147
1255
240,000
240,000
240,000
240,000
240,000
100
300
500
750
1,000
27
31
36
45
52
31
56
86
111
151
380
393
423
483
568
56
81
111
136
176
362
398
434
471
515
270,000
270,000
270,000
270,000
270,000
100
300
500
750
1,000
10
12
14
17
20
2025
35
60
90
115
155
78
78
78
78
78
31
33
33
36
38
30
55
85
110
150
835
864
929
1062
1249
55
80
110
135
175
886
974
1062
1152
1261
240,000
240,000
240,000
240,000
240,000
100
300
500
750
1,000
27
31
37
45
53
31
56
86
111
151
377
390
419
479
564
56
81
111
136
176
359
395
431
467
511
270,000
270,000
270,000
270,000
270,000
100
300
500
750
1,000
11
12
14
17
20
2026
35
60
90
115
155
78
78
78
78
78
31
33
34
36
39
30
55
85
110
150
841
870
935
1069
1257
55
80
110
135
175
892
981
1069
1160
1269
240,000
240,000
240,000
240,000
240,000
100
300
500
750
1,000
28
31
37
45
53
31
56
86
111
151
374
387
416
476
559
56
81
111
136
176
356
392
427
463
507
270,000
270,000
270,000
270,000
270,000
100
300
500
750
1,000
11
12
14
17
20
2027
35
60
90
115
155
78
78
78
78
78
32
33
34
36
39
30
55
85
110
150
845
875
940
1075
1264
55
80
110
135
175
897
986
1075
1166
1276
240,000
240,000
240,000
240,000
240,000
100
300
500
750
1,000
28
31
37
46
53
31
56
86
111
151
372
384
413
472
555
56
81
111
136
176
354
389
424
460
503
270,000
270,000
270,000
270,000
270,000
100
300
500
750
1,000
11
12
14
18
20
2028
35
60
90
115
155
78
78
78
78
78
32
33
34
37
39
30
55
85
110
150
850
880
945
1081
1271
55
80
110
135
175
902
992
1081
1173
1283
240,000
240,000
240,000
240,000
240,000
100
300
500
750
1,000
28
31
37
46
54
31
56
86
111
151
369
382
410
469
552
56
81
111
136
176
352
387
421
457
500
270,000
270,000
270,000
270,000
270,000
100
300
500
750
1,000
11
12
14
18
21
2016 – 2030 Upper Midwest Resource Plan
Page 241 of 243
Appendix O
Demand Response Market Potential in Xcel Energys NSP Service Territory - Brattle
Portfolio Participation ‐ Accounting for Overlap
The following are potential estimates (MW) if the DR options were offered simultaneously as part of a portfolio at each price point ‐ a single customer could not choose to participate in two DR measures at the same tim
The "Interruptible (reliability)" option and the "Interruptible (price)" option cannot both be simultaneously offered. In the estimates below, Interruptible (reliability) is assumed to be the option that is offered
Only one measure is being modeled for residential, so impacts for that customer class are the same as in the "Supply Curves" table
Class
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Residential
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Small C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Medium C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Large C&I
Program
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ SFH
DLC ‐ MDU
DLC ‐ MDU
DLC ‐ MDU
DLC ‐ MDU
DLC ‐ MDU
DLC
DLC
DLC
DLC
DLC
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
DLC
DLC
DLC
DLC
DLC
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (reliability)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Interruptible (price)
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Demand bidding
Price Point
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
Very low
Low
Medium
High
Very high
2014
190
219
266
317
375
0
0
0
0
0
14
17
19
20
21
0
0
0
0
0
20
21
21
27
27
172
178
329
329
329
0
0
0
0
0
0
0
0
0
0
301
312
360
383
450
0
0
0
0
0
0
0
0
0
0
2015
216
250
303
361
427
4
5
6
6
7
24
29
32
33
36
0
0
0
0
0
23
24
24
27
28
315
326
350
400
470
0
0
0
0
0
5
5
7
8
9
327
338
363
416
489
0
0
0
0
0
2
2
3
3
4
2016
243
280
340
405
479
9
10
12
12
13
34
40
45
47
52
0
0
0
0
0
25
27
27
29
31
459
475
510
584
686
0
0
0
0
0
10
11
13
16
19
346
358
385
440
517
0
0
0
0
0
4
5
6
7
8
2017
244
282
342
408
482
13
16
18
19
20
34
41
45
47
52
0
0
0
0
0
26
27
28
30
32
462
478
514
588
691
0
0
0
0
0
15
17
20
24
28
351
363
390
446
524
0
0
0
0
0
6
7
9
11
12
2018
245
283
344
409
484
18
21
24
25
27
35
41
46
47
52
0
0
0
0
0
26
27
28
30
32
465
481
517
591
695
0
0
0
0
0
20
22
27
33
38
352
364
391
447
526
0
0
0
0
0
9
10
11
14
16
2019
246
284
345
411
486
22
27
30
32
34
35
41
46
48
53
0
0
0
0
0
26
27
28
30
32
468
484
520
595
700
0
0
0
0
0
25
28
34
41
48
353
365
392
449
528
0
0
0
0
0
11
12
14
18
21
2020
247
285
346
413
488
22
27
30
32
34
35
41
46
48
53
0
0
0
0
0
26
27
28
30
32
471
488
524
599
705
0
0
0
0
0
25
28
34
42
49
354
366
394
450
529
0
0
0
0
0
11
12
15
18
21
2021
248
286
348
414
490
23
27
30
32
34
35
41
46
48
53
0
0
0
0
0
26
28
28
30
32
475
491
528
603
709
0
0
0
0
0
26
29
34
42
49
355
368
395
452
531
0
0
0
0
0
11
12
15
18
21
2022
249
287
349
416
492
23
27
30
32
34
35
42
46
48
53
0
0
0
0
0
26
28
28
30
32
478
494
531
608
714
0
0
0
0
0
26
29
34
42
49
356
369
396
453
533
0
0
0
0
0
11
12
15
18
21
2023
250
289
351
418
494
23
27
30
32
35
35
42
47
49
54
0
0
0
0
0
26
28
28
31
33
481
498
535
611
719
0
0
0
0
0
26
29
35
43
50
355
368
395
452
531
0
0
0
0
0
11
13
15
18
21
2024
251
290
353
420
496
23
27
30
32
35
36
42
47
49
54
0
0
0
0
0
27
28
29
31
33
484
500
538
615
723
0
0
0
0
0
26
29
35
43
50
354
366
393
450
528
0
0
0
0
0
11
13
15
18
22
2025
252
292
354
422
499
23
27
30
33
35
36
42
47
49
54
0
0
0
0
0
27
28
29
31
33
486
503
540
618
726
0
0
0
0
0
26
29
35
43
50
351
363
390
446
524
0
0
0
0
0
11
13
15
19
22
2026
254
293
356
424
501
23
27
31
33
35
36
43
48
49
55
0
0
0
0
0
27
28
29
31
33
489
506
544
622
731
0
0
0
0
0
26
30
35
43
51
348
360
387
442
520
0
0
0
0
0
11
13
15
19
22
2027
255
295
358
426
504
23
27
31
33
35
36
43
48
50
55
0
0
0
0
0
27
28
29
31
33
492
509
547
625
735
0
0
0
0
0
26
30
35
44
51
346
358
384
439
517
0
0
0
0
0
11
13
15
19
22
2016 – 2030 Upper Midwest Resource Plan
Page 242 of 243
2028
256
296
360
428
506
23
28
31
33
35
36
43
48
50
55
0
0
0
0
0
27
29
29
31
33
495
512
550
629
739
0
0
0
0
0
27
30
36
44
51
343
355
382
437
513
0
0
0
0
0
11
13
15
19
22
Appendix O
Demand Response Market Potential in Xcel Energys NSP Service Territory - Brattle
Operating Characteristics of the DR Options
The following are suggested operating characteristics for each DR option
The demand bidding option is always available; it effectively operates as a generating unit with a $/MWh dispatch price above which it would sell its energy into the market
Post‐event load building is the "snapback effect" in which load ramps up after a DR event to levels higher than it would have been in the absence of a DR event
Snapback estimates are based on a review of the 2012 DR program impact evaluations for the California utilities
Snapback was only observed for DLC programs and there was no significant pre‐event load building in any of the programs
Post‐event load building is expressed as a % of the average demand reduction during the DR event
For example, if NSP's residential DLC program reduced peak demand by 100 MW, 40% post‐event load building would result in 40 MW of load increase following the event
Class
Option
Typical event window
Typical event duration
Event season
Residential
Residential
Small C&I
Medium C&I
Medium C&I
Medium C&I
Large C&I
Large C&I
Large C&I
DLC ‐ SFH
DLC ‐ MDU
DLC
DLC
Interruptible (reliability)
Interruptible (price)
Interruptible (reliability)
Interruptible (price)
Demand bidding
2 pm to 7 pm
2 pm to 7 pm
2 pm to 7 pm
2 pm to 7 pm
Noon to 8 pm
Noon to 8 pm
Noon to 8 pm
Noon to 8 pm
Any time
5 hours
5 hours
5 hours
5 hours
4 to 8 hours
4 to 8 hours
4 to 8 hours
4 to 8 hours
Any duration
June ‐ Sept
June ‐ Sept
June ‐ Sept
June ‐ Sept
Year‐round
Year‐round
Year‐round
Year‐round
Year‐round
Max hours of Max number interruption per of events
year
15
300
15
300
15
300
15
300
5
80
15
120
5
80
15
120
No limit
No limit
Post‐event load building (expressed as % of event period demand reduction)
40%
40%
10%
10%
0%
0%
0%
0%
0%
Duration of post‐
event load building
3 hours
3 hours
3 hours
3 hours
N/A
N/A
N/A
N/A
N/A
2016 – 2030 Upper Midwest Resource Plan
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