Mostafa Sahraei-ArdakaniSeth BlumsackAndrew Kleit

Department of Energy and Mineral EngineeringPenn State University

mostafa@psu.edu

Zonal Electricity Supply Curve Estimation with Fuzzy Fuel Switching Thresholds

North American power grid is “the largest and most complex machine in the world” Amin, (2004)

04/22/2023

MOTIVATION

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How to analyze supply and demand policies considering the transmission constraints ?– Pennsylvania’s Act 129: Energy conservation and

peak demand reduction in Pennsylvania.• What would happen to the prices in PA?• What would happen to the prices in other states?• What would happen to the emissions?

– Carbon tax:• What would happen to the prices?• What would happen to the emissions?

04/22/2023

DISPATCH CURVE MODEL

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• What would happen to electricity prices if a CO2 price was imposed?– Engineers• Very complex model• Data may not be publicly available

– Policy analysts• Collect marginal cost data from power plants• Collect fuel price data• Form a supply curve by sorting generators from cheap to

expensive• Ignore transmission network

Each point represents a single power plant

New

com

er e

t al.,

200

8

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DIFFERENT MODELS

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• Engineering models– Too complex– Data may not be available– Takes a long time to converge

• Econometric models– Estimate prices well– Do not do a good job in estimating

fuel mix and emission impacts of policies.• Dispatch curve

– Ignores transmission system and how congestion makes prices different.• Our model

– Needs no more data than a dispatch curve– Implicitly accounts for transmission constraints

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OTHER APPROACHES

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• Econometric models– Predict prices well.– Do not do a good job on estimating fuel utilization.

• Engineering models: Power Transfer Distribution Factor (PTDF)– Need detailed data which is not publicly available.– They are complex and take a lot of time to converge

for large power systems.

04/22/2023

OUR APPROACH

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For each zone we want to identify:

1. Thresholds where the marginal fuel changes (Coal, Gas, Oil) CMA-ESFixed and variable thresholds

2. The slope of each portion of the overall dispatch curve. OLS

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FUZZY THRESHOLDS

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GAS

COAL

Summer 2008DeterministicThresholds

Summer 2011

qi

qT

ΔC/G

100% Natural Gas100% Coal

50% Coal, 50% Natural Gas

Observations100%

Natural Gas100%

Oil

Fuzzy Gap

qT,C/G

qi,G/O

Fuzzy ThresholdsVariables to be estimated:1. Relative fuel price

threshold for having the fuzzy gap

2. Fuzzy gap width coefficient

04/22/2023

IMPLEMENTATION IN PJM

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• Seventeen PJM utility zones

• Data: (2006-2009)– Hourly zonal load– Hourly zonal prices– Fuel prices

• Insufficient data for nodal level modeling

• Robustness Check:– Linear and quadratic

curves– Fixed and Variable

Thresholds

04/22/2023

Marginal Fuels in PSEG

Load in PSEG (GW)

Tota

l Loa

d in

PJM

(GW

)

Price ($/MWh)

Gas

Coal

Oil

Gas-Oil Fuzzy Region

Coal – Gas Fuzzy Region

RESULTS: THRESHOLDS

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PSEG= Public Service Electric and Gas Company

$/MWhPSEG demand= 5.8 GWPJM demand= 118 GWAPS price=80 $/MWh

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RESULTS: SUPPLY CURVE PROJECTION

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Central Pennsylvania and West Virginia Philadelphia

• Zonal price differences are captured.•50 $/ton carbon tax

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RESULTS: MARGINAL FUEL SHARES

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• Another robustness check• Natural Gas often sets the prices.

•DUQ in western PA is a coal dominated zone.

•RECO in northern NJ is a natural gas dominated zone.

•Natural gas often sets the prices in PJM.

04/22/2023

RESULTS: PRICES

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•BGE is in eastern PJM (Baltimore).

•DUQ is in western PJM (Pittsburgh).

•Our model captures zonal price differences.

•50 $/ton carbon tax would increase prices by about 70%.

04/22/2023

APPLICATION: PENNSYLVANIA ACT 129

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• Act 129 is a wide-reaching energy policy initiative in Pennsylvania. Among other things, Act 129 requires all Pennsylvania utilities to:

1. Reduce annual electricity demand by 1%

2. Reduce “peak” demand (highest 100 hours) by 4.5%

• We will estimate the impacts of Act 129 on total electricity costs, fuels utilization and greenhouse gas emissions in the PJM territory, using our model and the “dispatch curve” model that I discussed earlier. We use 2009 as our “base” year.

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APPLICATION: PENNSYLVANIA ACT 129

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Electricity Cost Savings ($ million):

• Savings: 333 million dollars

•253 million dollars in PA

•Dispatch Curve: 150 million dollars

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APPLICATION: PENNSYLVANIA ACT 129

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Shifts in Marginal Fuel (% Increase with Act 129):

Emission decreases by 4 million metric tons.

Dispatch Curve: 2.3 million metric tons.

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CONCLUSIONS

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• We have developed an approach to estimating zonal supply curves in transmission constrained electricity markets:

- Requires no proprietary data

- Can be implemented by analysts without requiring complex engineering calculations

• Our approach captures regional effects of policies that “transmission-less” dispatch models do not. Regional impact differences may be important in policy evaluation.⁻ Zonal fuel utilization shift⁻ Zonal price differences

Mostafa Sahraei-Ardakani

Department of Energy and Mineral EngineeringPenn State University

mostafa@psu.edu

Comprehensive Exam

Thanks!

04/22/2023

PRICE INCREASE IN DC

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Rest of PJM

Virginia and Washington, DC

10 MW

MC1=P1

MC2=10+P2 50MW

1

2 3

35MW

25MW

50/325/325/3

50/3

25MW

25MW

λ1=MC1=35 ($/MWh)

λ2=MC2=35 ($/MWh)

Thermal Capacity =20 MW

20MW

40MW

20MW

30MW

10MW

λ1=MC1=20 ($/MWh)

λ2=MC1=50 ($/MWh)

45MW

25MW

30MW

25MW

5MW

25$/MWh

40$/MWh

MC1=MC2P1+P2=10+50 (MW)