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Economic and environmental implications of different approaches to hedge against wind production uncertainty in two-settlement electricity markets: A PJM case study

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  • Daraeepour, Ali
  • Patino-Echeverri, Dalia
  • Conejo, Antonio J.

Abstract

This paper examines the economic and environmental outcomes of four two-settlement electricity market clearing designs. The first design corresponds to a Deterministic Market Clearing (DMC) similar to the mechanism currently used in organized wholesale electricity markets in the United States. The other three designs account for the day-ahead (DA) wind power production uncertainty into the DA market mechanisms either implicitly or explicitly. An Augmented Deterministic Market Clearing (ADMC) design introduces DA ramp-capability products. These products ensure adequate and ramp-feasible electricity generation capacity commitments in the DA stage to cope with the real-time realization of wind power generation. A Hybrid Deterministic Market clearing (HDMC) design augments ADMC by explicitly integrating a characterization of wind power production uncertainty into the residual unit commitment (RUC) process, which is run after the DA market is closed, using stochastic programming. The last design, referred to as stochastic market clearing (SMC), uses stochastic optimization to explicitly account for wind power production uncertainty in the DA market clearing mechanisms (i.e. DA unit commitment and economic dispatch).

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  • Daraeepour, Ali & Patino-Echeverri, Dalia & Conejo, Antonio J., 2019. "Economic and environmental implications of different approaches to hedge against wind production uncertainty in two-settlement electricity markets: A PJM case study," Energy Economics, Elsevier, vol. 80(C), pages 336-354.
    • Handle: RePEc:eee:eneeco:v:80:y:2019:i:c:p:336-354
    DOI: 10.1016/j.eneco.2019.01.015
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    3. Godoy-González, Diego & Gil, Esteban & Gutiérrez-Alcaraz, Guillermo, 2020. "Ramping ancillary service for cost-based electricity markets with high penetration of variable renewable energy," Energy Economics, Elsevier, vol. 85(C).
    4. Li, Mingquan & Gao, Huiwen & Abdulla, Ahmed & Shan, Rui & Gao, Shuo, 2022. "Combined effects of carbon pricing and power market reform on CO2 emissions reduction in China's electricity sector," Energy, Elsevier, vol. 257(C).
    5. Ruhang, Xu & Jia, Jia, 2023. "Towards reliability competition: Non-cooperative market mechanism under high variable renewable energy penetration," Applied Energy, Elsevier, vol. 331(C).
    6. Wu, Zhaoyuan & Zhou, Ming & Li, Gengyin & Zhao, Tong & Zhang, Yan & Liu, Xiaojuan, 2020. "Interaction between balancing market design and market behaviour of wind power producers in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    7. Deng, Xu & Lv, Tao & Meng, Xiangyun & Li, Cong & Hou, Xiaoran & Xu, Jie & Wang, Yinhao & Liu, Feng, 2024. "Assessing the carbon emission reduction effect of flexibility option for integrating variable renewable energy," Energy Economics, Elsevier, vol. 132(C).
    8. Virguez, Edgar & Wang, Xianxun & Patiño-Echeverri, Dalia, 2021. "Utility-scale photovoltaics and storage: Decarbonizing and reducing greenhouse gases abatement costs," Applied Energy, Elsevier, vol. 282(PA).
    9. Anna Schwele & Christos Ordoudis & Pierre Pinson & Jalal Kazempour, 2021. "Coordination of power and natural gas markets via financial instruments," Computational Management Science, Springer, vol. 18(4), pages 505-538, October.
    10. Stover, Oliver & Nath, Paromita & Karve, Pranav & Mahadevan, Sankaran & Baroud, Hiba, 2024. "Dependence structure learning and joint probabilistic forecasting of stochastic power grid variables," Applied Energy, Elsevier, vol. 357(C).
    11. Li, Mingquan & Shan, Rui & Virguez, Edgar & Patiño-Echeverri, Dalia & Gao, Shuo & Ma, Haichao, 2022. "Energy storage reduces costs and emissions even without large penetration of renewable energy: The case of China Southern Power Grid," Energy Policy, Elsevier, vol. 161(C).

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    More about this item

    Keywords

    Two-settlement markets; Market clearing design; Wind energy; Hidden uncertainty costs; Price formation;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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