Meeting Notes
Committee
Leader:
Jamie Austin
Committee:
Data Work Group
From Date
10:30 – 10:45
10:45 – 12:00
November 29, 2016
To Date
December 06, 2016

Welcome and Introductions

TEPPC 2026CC – Background

TEPPC 2026CC – Using CEMS to Develop FOR & Maintenance Rates

TEPPC 2026CC – Update on Wind & Solar Data Development
Meeting Objectives
Chris Hagman, American Transmission Company, has kindly agreed to share study results from
using CEMS Data to Estimate Coal-Fired Plant FORs and Scheduled Maintenance. This is similar
to the DWG’s state-of-the-art approach of using Continuous Emission Monitoring System (CEMS)
data to develop unit-specific heat rate curves, but instead focuses on Forced Outage Rates and
Scheduled Maintenance durations.
Kevin Harris will briefly discuss tweaks he’s made to the 2026CC to adjust the NW thermal
maintenance schedule to Spring based on his CEMS data review; Kevin also found that 75% of
CA maintenance occurs Mar-May and 25% occurs Oct-Nov.
Introductions\Background
After introductions, Bhavana covered the WECC Antitrust Statement. Jamie welcomed meeting
attendees and reviewed the agenda. Setting expectations, Jamie explained that Chris Hagman,
ATC, promoted using EPA Continuing Emission Monitoring Systems (CEMS) data to calculate
Plant Forced Outage & Maintenance rates a year ago when the idea was last introduced to DWG
on 12/12/15. Currently the methodology used to develop FOR and Maintenance Rates involves
using the most recent 5-year NERC - Generator Availability Data System (GADS), covering the
WECC; the NERC data is proprietary and requires averaging at least seven plants in each
category. Whereas using when using CEMS data that’s in the public domain the results will be
plant specific. The timing of this discussion is supported by the recent attempts made by Kevin
Harris to adjust GridView generated maintenance rates to what was deemed more practical.
A year ago, Stan Holland shared that the staff uses GridView to determine maintenance schedules
and that GridView allows for manual override, at the unit level, as necessary.
Jamie concluded by showing a summary of the APTECH-suggested EFOR rates that covers for
increased thermal plant cycling due to higher penetration of RPS resources and the GADS 2016
data, currently in the TEPPC 2026 CC – V1.5. (See enclosed presentation).
Microsoft
PowerPoint Presentation
1
Using CEMS Data to Develop FOR & Maintenance Rates
Chris Hagman, ATC, explained that Forced Outage Rates (FORs) on large coal-fired plants can
have a significant impact on Transmission congestion.
 Transmission constraints may prevent lower-cost power from getting to load when large
low-cost generation is forced off.
 FORs and scheduled maintenance can vary widely on coal-fired plants.
 GridView can better mimic actual congestion when this variability is captured, i.e. when
there is better granularity
Chris added that the GADS data is not plant specific whereas using CEMS data is better suited for
determining FOR and Maintenance rates for base loaded units; in addition, CEMS data is in the
public domain. CEMS hour’s zero output are considered either scheduled maintenance or forced
outages. Chris noted that using CEMS data may not apply to combined cycle as zero output
maybe driven by economics.
On rules used for applying the CEMS method, see slides 5 & 6 of the enclosed presentation:
Microsoft
PowerPoint Presentation
Chris attributed the benefits of coding Python to do the analysis to his colleague Ziqi Yang. Ziqi
explained that the Python analysis tool allows users to specify in dialog boxes:
 Maintenance exclusion periods
 Minimum number of days to be considered scheduled maintenance
Chris noted that the most challenging issue is to capture and code partial FOR; a FOR may turn
into maintenance schedule depending on the season, the size of the unit and other economic
considerations. Chris added that significant FORs are not surprising for large coal-fire plants.
These systems are complex, operate at very high temperatures and pressures using corrosive
fuel…a list of FOR causes is displayed on slide 9.
Tom Miller commented that the challenge of using CEMS to generate outage rates into the future
might be contested as coal will be dispatched to follow RPS.
Chris responded that it is possible to see more cycling going forward that will result in higher FOR,
e.g., the APTECH data shared by Jamie. Chris added that the operator incentive is to have the
lowest outage rate. Using the CEMS data will result in higher rates than using GADS.
Covering Analysis, Ziki explained that ATC investigated 62 coal-fired plants in WECC with
capacities ranging from 156 to 818 MW; to be conservative, 14 years of hourly CEMS data was
used (2002-2015). We’ve concluded that the 2026CC equivalent data needs to be raised by 1% to
2% for average annual FOR. In all, higher outage rates were associated with higher plant
capacity. Relative to average annual maintenance length of 14 days should be increased to 21
days.
2
Other than for plant capacity, Jamie asked if plant vintage was considered. The response was no.
Ziki continued in stating that the unit specific information makes a difference. See slide 11, CEMS
unit-specific For and Maintenance compared to GADS data.
Kevin asked about the source for the Canadian data? The response was Velocity Suites.
Nader asked relative to the price of gas, how about economic factors; different units owned by
multiple entities with different strategies…? If you compare 2010 with 2016 you’ll see a wide
gap…
Chris responded that this is precisely for why we’re recommending to use unit specific CEMS data.
Small units have lower rates; active units are dispatched most…gas price doesn’t seem to matter.
The scheduled maintenance is the range of what’s expected, using the 14 years of data. After
2011, natural gas prices started to drop, although we saw some change, but not much…
Kevin asked why the maintenance is so high… Are you just covering the summer period?
Chris responded the numbers are in days. The CEMS data produced average 21 days where
currently modeled is 13 days.
Steven asked, have you adjusted maintenance for seasonality by keeping plant on line?
Chris responded that these are base loaded units and operators like to keep them on line.
Ziki concluded that the smallest units have the lowest FORs while the opposite hold true for larger
units; units with higher FORs also have longer scheduled maintenance. The CEMS method
provides unit specific FOR and scheduled maintenance. This enhanced methodology offers more
accuracy as base loaded coal plants can have a significant impact on transmission congestion.
Modeling Outages
Kevin began his presentation with an overview, addressing maintenance cycle steam, noting:
 Maintenance does not have the same value every year
 Based on unit design and how it operates, a four to nine maintenance year cycle is created
 Emission equipment is included in cycle or may have unique requirements
 He mentioned units that required a 1-2 day maintenance every 3-4 months of operation
Microsoft
PowerPoint Presentation
3
Kevin added that at the start of maintenance you inspect the turbine blades, looking for cracks,
preventative action and also for deciding on mobilizing material and manpower…of course
economics are factored into the decision.
Kevin noted using five year average outage rates by generic supply and size leads to better
results; one year data may be anomalous and may have lots of volatility.
Kevin asked Chris if Net Availability data, the ration of EFOR/maintenance, was calculated using
the CEMS approach? Chris responded no.
Kevin summarized:
 It is reasonable to expect individual unit maintenance to average out over time
 Plant modification should not be included in long term maintenance planning
 Some FOR events are converted to maintenance
Kevin added, down time is a function for supply need; some forced outage get changed to
maintenance (e.g., do I pay extra for overtime and rush parts if not summer peak; the tendency
would be to schedule repairs during working hours).
Update on Wind & Solar Data Development
Nader reported that coding to determine which NREL wind site to select has been completed.
Further, he is currently running another code to add time series which will be ready in a couple of
days. The 2009 data will be available in 5 minutes and hourly profiles, in Mountain Time.
Steven has been working diligently on locating geo-coordinates for wind plants; in his report,
Steven noted that only few plants remain missing and it is hoped they will be found in few days.
Jamie commented that Ron Schellberg is working with NTTG technical work group members to
locate missing coordinates for plants in ID and MT.
Steven added that many of the missing coordinates are associated with Canadian plants in Alberta
and BC as seen in the spread sheet…Angela asked about receiving the spread sheet? Jamie
assured it will be posted in today’s meeting folder.
Steven noted that the NREL data is in local Pacific time… All agreed that data has to be shifted to
Mountain Time.
Angela asked how manageable will the data set be given the focus has shifted to plant level rather
than by zone?
Jamie clarified does the concern have to do with PCM run time?
4
Nader responded that PNNL applied that level of granularity to the 2020 dataset using Plexos and
had no issue; 30 versus 300 files of wind shapes will not make a difference. Steven added that it
shouldn’t impact run time.
Tom was curious about Yi’s definition of granularity vs what is being proposed; is the ISO OK with
using a different approach?
Steven responded that the ISO sites do not have exact coordinates…however he worked with Yi
on identifying specific sites for existing plants…Yi concurred.
Nader added that this is meant to be a onetime effort to get it right.
Steven warned that this is not perfected yet…the work thus far has covered existing plant. We still
need to work on incremental future wind and solar.
Colby agreed that we’ll also need to discuss the method for mapping future RPS…how much RPS
should be modeled?
Steven added that this may require us to iterate…E3 said the case is resource adequate; if so,
after running with what’s been mapped in V1.5, we’ll need to revisit to see if more incremental
RPS is still needed.
Colby concurred with Steven; we’ll issue what’s produced in this intermediate step and come back
to address the rest in a subsequent version of the 2026 CC.
Jamie summarized what’s been agreed to for next steps on wind and solar:
Wind
1. Nader, PNNL, will produce hourly wind profiles for plants in the 2026CC-V1.5 by midDecember
Solar
1. Colby will take the lead on sharing solar plant data
2. Yi has agreed to help Steven and Nader with solar plant mapping
3. Nader will use same method for developing the code for solar plants
4. In a follow up email, Nader wrote the following about timeline for solar profiles: it will be a
challenge to have the data produced by Christmas; NREL solar data has a different format
than that for wind. W would need at least two weeks to develop the time series from the
time we receive the coordinates for solar plants.
Colby and staff will issue V1.6 with new wind and solar by year end
Jamie thanked presenters and meeting participants for their contributions.
5
Name
Austin, Jamie
Amjadi, Amir
Alagappan, Lakshmi
Alvarado, Al
Anderson, Grace
Baack, Jim
Bailey, Mike
Barbose, Galen
Brathwaite, Leon
Brownlee, Ben
Beckstead, Dan
Belval, Ron
Beus, Anna
Brinkman, Gregory
Brooks, Donald
Butikofer, Tyler
Brush, Ray
Burner, Bob
Carr, Tom
Carvallo, Juan Pablo
Charles, Gillian
Colburn, Mitch
Coe, Scott
Cole, Brian
Crane, Donovan
Davies, Donald
Deaver, Paul
Decker, Megan
Denker, Brendan
Depenbrock, Fred
Delleney, Mike
Doll, Brue
Didsayabutra, Paul
Elkins, Mat
Evans, Mike
Ezequiel
Freeman, Bryce
Gazewood, Jim
Green, Irina
Griffin, Karen
In attendance at the 120616 Meeting:
Company
Name
PAC
x
Lau, Elaine
Larsen, Peter
Le, David
E3
Lee, Peter
CEC
Lehr, Ron
CEC
VoteSolar
Li, Jim
CEC
Energy Strategies
WECC
TEP
WECC
NREL
CPUC
x
Western
Duke Energy
WIEB
IID
NPCC
IPC
WECC
WECC
CEC
x
x
SRP
Nevada Hydro
CAISO
COGRID
WECC
Shell Energy
IID
WYOC
BLM
CAISO
CEC
IID
Hagman, Chris
ATC
Hagler, Justin
CPUC
IID
COGRID
Maracas, Kate
Martinez, Esteban
Marxen, Chris
McCann, Richard
McIntosh, Henry
Mejia, Roni
x
Gutierrez, Noe
Harner, Patrick
Harris, Kevin
Haskovic, Mensur
Linvill, Carl
Mariscal, Garry
LBNL
x
x
Ming, Zachary
Miller, Tom
Milligan, Michael
Moussa, Effat
Moyer, Keegan
Mudita, Suri
Nail, George
O’Neill Mariscal, Garry
Pacheco, Ezquiel
Pacini, Heidi
Papic, Milorad
Pascoe, Bill
Perez, Army
Piper, David
Prochnik, Julia
Pryor, Mark
Puglia, Peter
Rahman, Brian
Raub, Jenika
Slazar, Marco
Samaan, Nader
Sanford
Schanahan, Patrick
Schellberg, Ron
Simmons, Steve
Soorya, Radha
Company
CPUC
LBNL
CAISO
BPA
AWEA
BC Hydro
RAP
CEC
WWND
IID
CEC
SDG&E
SCE
E3
PG&E
NREL
SDG&E
Energy Strategies
x
x
x
PN&M
CEC
IID
ICF
IPC
TREL
WECC
SCE
NRDC
CEC
CEC
IID
SRP
PNNL
x
CPS
NWPCC
Navigant
x
Spears, Michael
Snelgrove, Steve
Strack, Jan
x
Stokes, Mark
Tanghetti, Angela
SDG&E
CEC
x
6
Hein, Jeff
Heutte, Fred
Hodge, Bri-Mathias
Holland, Stan
Hosie, Bill
Iversen, Katie
Jensen, Jon
Jenka, Raub
Jensen, Richard
Johnson, Anders
Johnson, Colby
Johnson, Mitchell
Jourabchi, Massoud
Katyal, Bhavana
Kates, David
Kelly, Nancy
Klapka, Paul
Knudsen, Steve
Kravchuck, Luba
Kujala, Ben
Xcel
NWEC
NREL
WECC
Duke Energy
WECC
WECC
SRP
CEC
BPA
WECC
NWPCC
WECC
Nevada Hydro
SCE
BPA
AISO
NWPCC
x
x
x
x
Tilghman, Henry
Turner, Brian
Vastag, Bela
Vinnakita, Rama
Voisin, Nathalie
Von Reis Baron, Kate
Wang, Xiaobo
Wallace, Jonathan
Wallace, Steven
Wiggs, Matt
Williams, Stan
White, Keith
White, Stephen
Weiss, Steve
Woertz, Byron
Wong, Lana
Zhang, Yi
Zhu, Jin
Zhang, Hui
Zichella, Carl
NWNL
PGE
CAISO
OSC
OSC
BPA
CPUC
BPA
BPA
WECC
CEC
CAISO
ABB
x
x
x
NRDC
7