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Supply and Demand Forecasting
in Competitive Markets:
The Case of Alberta
LaRhonda Papworth
Manager, Forecasting
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Alberta Market - History
• The evolution to a deregulated market began in 1996. The goal of this
market was to encourage efficiencies by introducing competition in the
electricity generation sector. The market was set up for energy to be
dispatched through an economic merit order with a single equilibrium
price.
• The market evolved to full deregulation in 2001, following the auction of
Power Purchase Arrangements (PPAs) in 2000. This framework provided a
competitive landscape by immediately introducing new players into the
market.
• In 2003, the AESO (not-for profit, corporate entity) was created and
provides the function of the Independent System Operator, and is tasked
with providing for the safe, reliable and economic operation of the Alberta
Interconnected Electric System (AIES) and promoting a fair, efficient and
openly competitive market for electricity
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Alberta Market - Today
26,000 kms of transmission lines
235 generating units
11,139 MW peak demand
15,852 MW installed capacity
200+ active projects, including both transmission
system upgrades and customer connections
Over 100 new energizations in 2013
Over 1,200 MW of actual wind production
Industrial is 60% of total energy with 80% load factor
2013 Pool Price - $80.13
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Alberta Regulation - Forecasting
Transmission Regulation
• Must anticipate future demand for electricity, generation capacity . . . so
that transmission facilities can be planned to be available in a timely
manner to accommodate the forecast load and new generation capacity
• Must make assumptions about future load growth, the timing and location
of future generation additions, including areas of renewable or low
emission generation, and other related assumptions to support
transmission system planning
• Taking into consideration the characteristics and expected availability of
generating units, plan a transmission system that
– Is sufficiently robust so that 100% of the time, transmission of all anticipated in-merit
electric energy referred to in section 17 (c) of the Act can occur when all transmission
facilities are in series
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What does that mean?
anticipate, assumptions = forecast
characteristics, expected availability, anticipated inmerit = generator merit order or stack
forecast = to predict or estimate
AESO is required to defend assumptions,
methodologies and resulting forecast against industry
standard practices
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Forecast Methodologies & Tools
• Neural Network models - Itron’s MetrixND software
Model continually assessed against actual values and reviewed
periodically by third-party expert
• Econometric Models – Itron’s MetrixND software
Model assessed annually against actual values and reviewed every 2nd
year by third-part expert
• Hourly substation forecast – in-house built Java tool
20-year hourly forecast by substation (~600 points) incorporating utility
substation forecast information
• Capacity Generation Model – Excel based
VBA ‘tests’ for adequacy and fuel/technology mix
• Market evaluation tool – EPIS AURORAxmp  software
Probabilistic approach to assessing bidding behavior and generation
behavior
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Short Term Load Forecast
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Short-term load forecast
1 – 10 day out forecast
neural network model
using Itron’s MetrixND
software
Major inputs are historical
load patterns, weather,
daylight, etc.
Software can be used to
illustrate and understand
relationships between
load and weather, for
example
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Econometric Forecast
• Econometric model – the statistical relationship that is believed to hold
between an economic quantity and the particular phenomenon under
study
9,000
Average Alberta Internal Load (AIL) Load and Alberta
GDP
300,000
8,000
250,000
Average AIL (MW)
7,000
200,000
6,000
5,000
150,000
4,000
100,000
3,000
2,000
50,000
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
1,000
0
Alberta GDP ($2002 Millions)
10,000
Average AIL
GDP
0
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Econometric Forecast (cont’d)
Variable
CONST
Economic_Data.Service_Producing GDP
Annual.HDDPlusCDD
Annual.Year1983To2000
Coefficient
2958.309586
0.095562
0.000317
3008.525025
StdErr
350.113554
0.003175
0.000378
148.95922
T-Stat
8.450
30.102
0.841
20.197
P-Value
0.00%
0.00%
41.09%
0.00%
Statistics
Estimation
Degrees of Freedom
R2
Adj. R2
MAD
MAPE
DW
AESO Commercial
Energy Model
1990-2012
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0.983
0.980
107.77
0.90%
1.981
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Econometric Forecast (cont’d)
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Econometric model – statistical relationship between
the assumptions and electrical consumption
Residential- Statistically-adjusted end-use model includes assumptions on
real-disposable income, energy efficiency improvement and population
Commercial – Econometric model built on assumptions of Alberta serviceproduction GDP
Farm – Econometric model using assumptions on acres of irrigate land and
agricultural GDP
Industrial – Econometric model using assumptions on manufacturing GDP,
oilsands production, natural gas production and crude-oil production
Oilsands – Simple assessment of oilsands production times estimates of
electrical requirement of each oilsands barrel
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Hourly by Substation
Residential/Commercial Load Shape
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Hourly by Substation
Industrial Load Shape
Final Forecast –
Hourly by Substation
Energy
Outlook
Distribution
Facility
Owners (DFO)
and ProjectSpecific
Information
Load Shapes
by Point of
Delivery
(POD)
Hourly Load by Substation, Area, Region,
and Alberta over the next 20 years
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Future Generation Additions
• Expected future generation
capacity additions
• Announced generation
developments
• Policies that impact future
generation development
• Technology considerations
• Forecast Validation
• 10-year Outlook
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Alberta Generation – end of 2013
Coal
6,271 MW
Cogeneration 4,245 MW
Gas
1,647 MW
Hydro
894 MW
Wind
1,088 MW
Other
Renewables
423 MW
Capacity Addition Model
Generation Type
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Co-generation – Related to industrial activity and the associated need for steam in
the industrial process
Baseload
• Coal – No further additions of coal due to federal legislation requiring new plants
to meet a 420 kg/MWh emission level (roughly equivalent to a natural gas
combined-cycle unit)
• Combined cycle – Provides a flexible baseload generation and is expected to serve
as a replacement for coal plants
Peaking
• Simple cycle – Evaluated for providing short start-up, fast ramping up and down,
can provide operating reserves and take advantage of peak hours (high pool price)
Renewables
• Simple cycle – Evaluated for providing short start-up, fast ramping up and down,
can provide operating reserves and take advantage of peak hours (high pool price)
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Capacity Addition Model
Generation Type (cont’d)
Renewables and Other
• Wind – Evaluated for comparable costs against other generation types
taking into consideration economics, green attributes and policy
• Hydro – Future hydro possible. Potential of 10,000 MW but due to large
capital investment may need other support
• Biomass – Influenced by the ability to economically utilize any waste
material from processes. Policy could provide incentives
• Solar – Increases in other technologies or decrease in solar technology
could increase development of solar
• Energy Storage – Alberta has some interest in energy storage (pumped
hydro, battery and compressed air). Current project at the AESO to
understand the fit of energy storage in the market.
• Others – Nuclear and Geothermal
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Probabilistic Market Evaluation
• Objective of the Market Simulation Tool
– Given the economics and physical characteristics
of supply and demand
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Pool Price ($/MWh)
Probabilistic Market Evaluation
$160
$160
$140
$140
$120
$120
$100
$100
$80
$80
$60
$60
$40
$40
$20
$20
$0
1
2
3
4
5
6
7
8
9
10
Month
Monthly Prices
P05
Median
P95
Actual/Fwd Mkt
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12
$0
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Probabilistic Market Evaluation
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Final Result
• 20-year hourly load forecast by substation
based on models driven by historical
relationships between electricity and
economy
• 20-year forecast of generation additions based
on fundamentals of generation costs, demand
growth, policies and technology drivers
• Load and generation scenarios to address
uncertainty on largest drivers of change
• Next Step – Planning studies
Load and Forecast Dispatches
for PSEE
Dispatches must reflect approved forecast
• Load – Percentile approach using the ‘8760’ annual points produced by load
forecast to minimize high impact – low frequency events but capture
approximately 85 percentile load levels of all metering points
• Generation – In-merit generation dispatch from the capacity addition
model/market simulation to create particular stresses based on the region of the
province (high wind/low wind, high hydro/low hydro, import/export, regional inflow/out-flow, etc.)
• Scenarios – Integrated load and generation scenarios to study forecast-approved
uncertainty (environmental policy changes, low economic growth, etc.)
Engineering Sensitivities
• Sensitivities – Flexibility to test ‘extreme’ load and generation to understand
impacts on system but not used to support regulatory filings
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Questions?