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Bidding strategy for a prosumer aggregator with stochastic renewable energy production in energy and reserve markets

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  • Sun, Guoqiang
  • Shen, Sichen
  • Chen, Sheng
  • Zhou, Yizhou
  • Wei, Zhinong

Abstract

A growing body of electricity consumers with renewable energy and demand response resources have become active prosumers who can both produce and consume energy. However, the small size of most prosumers forbids their direct participation in electricity markets. This study addresses this issue by proposing a bidding strategy for the prosumer aggregator based on a bi-level model to enable multiple prosumers to participate in day-ahead energy and reserve markets as a single entity. Here, the prosumer aggregator profit and social welfare are maximized in the upper-level and lower-level models, respectively, where the heating, ventilation, and air-conditioning system loads, residential loads, energy outputs associated with photovoltaic power generators, and energy storage systems are included. The Karush–Kuhn–Tucker condition and strong duality equalities are used to transform the proposed bi-level model into a single-level model. The effectiveness and economy of the proposed approach are demonstrated based on the numerical results obtained for a realistic test system.

Suggested Citation

  • Sun, Guoqiang & Shen, Sichen & Chen, Sheng & Zhou, Yizhou & Wei, Zhinong, 2022. "Bidding strategy for a prosumer aggregator with stochastic renewable energy production in energy and reserve markets," Renewable Energy, Elsevier, vol. 191(C), pages 278-290.
    • Handle: RePEc:eee:renene:v:191:y:2022:i:c:p:278-290
    DOI: 10.1016/j.renene.2022.04.066
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    3. Seong-Hyeon Cha & Sun-Hyeok Kwak & Woong Ko, 2023. "A Robust Optimization Model of Aggregated Resources Considering Serving Ratio for Providing Reserve Power in the Joint Electricity Market," Energies, MDPI, vol. 16(20), pages 1-27, October.
    4. Li, Xiaozhu & Chen, Laijun & Sun, Fan & Hao, Yibo & Du, Xili & Mei, Shenwei, 2023. "Share or not share, the analysis of energy storage interaction of multiple renewable energy stations based on the evolution game," Renewable Energy, Elsevier, vol. 208(C), pages 679-692.
    5. Álvarez-Arroyo, César & Vergine, Salvatore & de la Nieta, Agustín Sánchez & Alvarado-Barrios, Lázaro & D’Amico, Guglielmo, 2024. "Optimising microgrid energy management: Leveraging flexible storage systems and full integration of renewable energy sources," Renewable Energy, Elsevier, vol. 229(C).
    6. Tang, Hong & Wang, Shengwei, 2022. "Multi-level optimal dispatch strategy and profit-sharing mechanism for unlocking energy flexibilities of non-residential building clusters in electricity markets of multiple flexibility services," Renewable Energy, Elsevier, vol. 201(P1), pages 35-45.

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