Copyright © 2018 The Brattle Group, Inc.
Estimation of the Market Equilibrium and Economically Optimal Reserve Margins FOR THE ERCOT REGION, 2018 UPDATE
PRESENTED TO SAWG PRESENTED BY Samuel A. Newell Rebecca Carroll Kevin Carden (Astrapé) October 19, 2018
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Disclaimer This presentation is based on a report the authors prepared for ERCOT. Neither this presentation nor the report were intended or should be read as either comprehensive or fully applicable to any specific opportunity in the ERCOT market. Interested parties are advised to seek independent expert advice, as all opportunities have idiosyncratic features that will be impacted by actual market conditions. Both this presentation and the report, which interested parties should read in full, are provided ‘as is.’ The Brattle Group, Astrapé Consulting, and ERCOT disclaim any and all express or implied representations or warranties of any kind relating to the accuracy, reliability, completeness, or currency of the data, conclusions, forecasts or any other information in this report. Interested parties are advised to independently verify such, as well as the suitability of the same for any particular purpose. Interested parties are solely responsibility for conclusions they draw from the review of the presentation and the report. To the fullest extent permitted by law, The Brattle Group, Astrapé Consulting, and ERCOT, along with their respective directors, officers, and employees, shall not be liable for any errors, omissions, defects, or misrepresentations in the information contained in these documents, whether intentional or unintentional, or for any loss or damage suffered by persons who use or rely on such information or any conclusions that could be drawn from them that turn out to be inaccurate (including by reason of negligence, negligent misstatement, or otherwise).
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Agenda
Problem Statement and Approach
Analytical Results – Market Equilibrium Reserve Margin – Economically Optimal Reserve Margin – Physical Reliability Metrics – Comparison to 2014 Study Results
Sensitivities
Appendix – Model Validation – Key Assumptions
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Problem Statement What are the MERM and EORM in ERCOT?
Market Equilibrium Reserve Margin Concept Economically Optimal Reserve Margin Concept
Estimating the MERM and EORM inform whether ERCOT’s market will support sufficient reserve margins from an economic perspective (the modeling also informs reliability implications)
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Modeling Approach
Simulation Period: 2022 (8760 hours) Simulations per Reserve Margin: 9,500
– 50 outage draws – 38 weather years – 5 non-weather load forecast errors
Topology – ERCOT, Mexico, SPP, and Entergy footprints – Connected through existing DC-Ties
Installed Capacity – Baseline capacity consistent with ERCOT’s
2018 LTRA submissions – Higher and Lower Reserve Margins
modeled by adding and subtracting generic CC/CT capacity from baseline
Baseline ERCOT Installed Capacity by Resource Type
Nuclear
Wind
Solar
Hydro
Coal
Gas
Biomass
Source: 2018 Report, Figure 2 Note: “2018 Report” references Newell et. al., Estimation of the Market Equilibrium and Economically Optimal Reserve Margins for the ERCOT Region—2018 Update, Final Draft. See http://www.ercot.com/content/wcm/lists/143980/10.12.2018_ERCOT_MERM_Report_Final_Draft.pdf
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Agenda
Problem Statement and Approach
Analytical Results – Market Equilibrium Reserve Margin – Economically Optimal Reserve Margin – Physical Reliability Metrics – Comparison to 2014 Study Results
Sensitivities
Appendix – Model Validation – Key Assumptions
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10.25%
$0
$50
$100
$150
$200
$250
$300
6% 8% 10% 12% 14% 16%
$/kW
-yr
Reserve Margin (% ICAP)
Cost of New Entry
Market Equilibrium Reserve Margin
Marginal Unit Net Energy Revenue
Market Equilibrium Reserve Margin
Source: 2018 Report, Figure ES-1 and Figure 5
ERCOT Projected 2022 Market Equilibrium Reserve Margin
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Year-to-Year Volatility in Annual Average Price and Revenue
Source: 2018 Report, Figure 6 Note: Marginal Unit Net Energy Revenue represents the net revenue from a mix of added CCs and CTs (77:23 ratio)
Net Energy Revenues for New Capacity Distribution of Spot Energy Prices
$0
$20
$40
$60
$80
$100
$120
$140
$160
$180
$200
6% 7% 8% 9% 10% 11% 12% 13% 14% 15% 16%
Annu
al A
vera
ge E
nerg
y Pr
ice
($/M
Wh)
Reserve Margin (% ICAP)
Median
5th Percentile
75th Percentile
90th Percentile
95th Percentile
Average
$0
$50
$100
$150
$200
$250
$300
$350
$400
$450
$500
6% 7% 8% 9% 10% 11% 12% 13% 14% 15% 16%
Annu
al A
vera
ge E
nerg
y M
argi
n ($
/kW
-yr)
Reserve Margin (% ICAP)
Median
5th Percentile
75th Percentile
90th Percentile
95th Percentile
Average
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$25,700
$25,900
$26,100
$26,300
$26,500
$26,700
$26,9004% 5% 6% 7% 8% 9% 10
%
11%
12%
13%
14%
15%
16%
17%
18%
Tota
l Sys
tem
Cos
ts ($
M/y
ear)
ERCOT Reserve Margin
Firm Load SheddingRegulation ShortagesNon-Spinning Reserve ShortagesSpinning Reserve ShortagesPrice-Responsive DemandTDSP Load ManagementNon-Controllable LRs30-Minute ERS10-Minute ERSEmergency GenerationExternal System Costs (Above Baseline)Production Costs (Above Baseline)Marginal CC Capital Costs
Economically Optimal Reserve Margin
Source: 2018 Report, Figure 8
Economically Optimal Reserve Margin at 9.0%
Total System Costs across Planning Reserve Margins
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Physical Reliability Metrics
Source: 2018 Report, Figure 10
Reliability Metrics that Vary with Reserve Margins (a) LOLE (b) LOLH (c) Normalized EUE
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
2.2
2.4
6% 8% 10% 12% 14% 16%
LOLE
(Eve
nts/
Yr)
Reserve Margin (%)
0.5 LOLE
Base Case Market Equilibrium
0
1
2
3
4
5
6
7
8
9
6% 8% 10% 12% 14% 16%
LOLH
(Hou
rs/Y
r)
Reserve Margin (%)
Base Case MarketEquilibrium
1.5 LOLH
0.0000%
0.0005%
0.0010%
0.0015%
0.0020%
0.0025%
0.0030%
0.0035%
0.0040%
0.0045%
6% 8% 10% 12% 14% 16%
Nor
mal
ized
EUE
(%)
Reserve Margin (%)
Base Case Market Equilibrium
0.0006% Normalized EUE
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Emergency Event Frequencies
Source: 2018 Report, Figure 12
0
1
2
3
4
5
6
7
8
9
10
6% 8% 10% 12% 14%
Even
t Fre
quen
cy (e
vent
s/yr
)
Reserve Margin (% ICAP)
Market Equilibirum Reserve Margin
30-min ERS
LRs
TDSP
Emergency Generation
10-min ERS
Load Shed
0.1 LOLE
Average Annual Frequency of Emergency Events
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10.25%
0.6%0.5%
0.75%
1.0%
0.3%
11.5%0.9%
1.0%
0%
2%
4%
6%
8%
10%
12%
14%
2014 MERMBase
ReserveMargin
Accounting
Lower Costof
New Entry
Increasein
Renewables
LowerGas
Prices
Change inWeather Year
Weighting
Lower ForcedOutage Rate
Other 2018 MERMBase
Mar
ket E
quili
briu
m R
eser
ve M
argi
n
Comparison to 2014 EORM Study Results
Drivers of the MERM Change from 2016 to 2022 Model
Source: 2018 Report, Figure 7
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Agenda
Problem Statement and Approach
Analytical Results – Market Equilibrium Reserve Margin – Economically Optimal Reserve Margin – Physical Reliability Metrics – Comparison to 2014 Study Results
Sensitivities
Appendix – Model Validation – Key Assumptions
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Variable Base Case Assumption Sensitivity Range
Renewables Penetration 9.6 GW new renewables -10.7 GW/+29.6 GW of renewables*
High Gas Price Henry Hub: $3.26 Henry Hub: $6.25
Gross CONE CT: $89/kW-year CC: $95/kW-year -10% / +25%
VOLL $9,000/MWh $5,000 to $30,000/MWh
Weighting of Historical Weather Years
Equal probability (2.5%) on last 38 years
(1) 10% most last 10 years (2) Probabilities based on Pareto distribution fit
to weather years based on number of consecutive days with weather over 100 degrees
(3) Probabilities equal to 2014 EORM base case
Forward Period and Load Forecast Uncertainty 3 years 0 years to 2 years
Sensitivity to Key Uncertainties
Source: 2018 Report, Table 4 & Table 5 Note: * -20.3 GW/ + 20 GW from the Base Case assumption
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Summary of Sensitivity Results
Sensitivity of the MERM to Study Assumptions
Source: 2018 Report, Figure 15
-1
-1
-0.25
-1
1
0.5
1.5
0.25
-1.5 -1 -0.5 0 0.5 1 1.5 2
Gas Price
Renewable Penetration
Forward Years
Weather Year Weighting
CONE
MERM (%)
Curve Fit Probabilities
-10% CONE+25% CONE
0 Year 3 Year
10 Most Recent Years
+20 GW Renewables
2014 Study Weighting
2014 EORM Study
8.75% 9.25% 9.75% 10.25% 10.75% 11.25 11.75% 12.25%
0.75
+$3/MMBtu
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Agenda
Problem Statement and Approach
Analytical Results – Market Equilibrium Reserve Margin – Economically Optimal Reserve Margin – Physical Reliability Metrics – Comparison to 2014 Study Results
Sensitivities
Appendix – Model Validation – Key Assumptions
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Model Validation (1 of 2)
Modeled vs. Actual Combined-Cycle Net Energy Revenues
$0
$20
$40
$60
$80
$100
$120
$140
$160
$180
2011 2012 2013 2014 2015 2016 2017
$/kW
-yr
ModeledHistorical
Source: 2018 Report, Figure 3
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Model Validation (2 of 2)
Average Modeled vs. Historical Expected Net Energy Revenues by Reserve Margin
Source: 2018 Report, Figure 4
$0
$50
$100
$150
$200
$250
$300
6% 8% 10% 12% 14% 16% 18% 20% 22%
$/kW
-yr
Reserve Margin (%)
Modeled Average CC Net Energy Revenues
2018
2014
2013
2015
2016
2012
2017
Historical Expected Net Energy Revenues at
Planning Reserve Margins
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Reference Technology Assumptions
Higher reserve margin cases add reference technology that represents a mix of H-Class combined cycles and combustion turbines consistent with recent additions and announced new builds (77:23)
Reference Technology Cost and Summer Performance Characteristics
Simple Cycle Combined Cycle
Plant ConfigurationTurbine GE 7HA.02 GE 7HA.02Configuration 1 x 0 2 x 1
Heat Rate (HHV)Base Load (Btu/kWh) 9,274 6,312Max Load w/ Duct Firing (Btu/kWh) n/a 6,553
Installed CapacityBase Load (MW) 352 1,023Max Load (MW) n/a 1,152
Gross CONE ($/kW-yr) $89 $95
Source: 2018 Report, Table 2
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10.25%9.25%
$0
$50
$100
$150
$200
$250
$300
6% 8% 10% 12% 14% 16%
$/kW
-yr
Reserve Margin (% ICAP)
10.5%
Marginal Unit Net Energy Revenue
Base CONE
Market Equilibrium Reserve Margin
Low CONE: -10%
High CONE: +25%
MERM Sensitivity to Cost of New Entry
CONE Sensitivity Results
Source: 2018 Report, Figure 14
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Samuel A. Newell Principal, Boston MA
+1.617.234.5725
Rebecca Carroll Associate, Boston MA
+1.617.234.5605
Kevin Carden Director, Astrapé Consulting
+1.205.988.4404
Dr. Newell is the co-leader of the firm’s electricity practice, with 20 years of experience in electricity wholesale markets, the transmission system, and RTO/ISO rules. He supports clients throughout North America in matters involving wholesale market design, generation asset valuation, transmission development, integrated resource planning, and demand response programs.
Rebecca Carroll has nearly ten years of experience in energy economics and electricity market modeling. She has supported a broad range of clients on system planning, market rules development, retail gas and electric choice, power plant and transmission line valuations, regulatory hearings, and arbitration proceedings.
Mr. Carden has over 18 years of experience in production cost simulations for risk analysis and reliability planning for power supply options, coupled with diverse utility management experience. Under Kevin's leadership, Astrapé Consulting has provided consulting services to utilities nationwide.
Presented By
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