Evolutionary Game Based Bidding Strategy of Aggregated Generation Unit for Renewable Energy

Kaijia MO , Yingjing HE , Xunjun CHEN , Renshun WANG , Cenfeng WANG , Keping ZHU , Quanyuan JIANG

›› 2025, Vol. 19 ›› Issue (5) : 83 -92.

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›› 2025, Vol. 19 ›› Issue (5) : 83 -92. DOI: 10.13648/j.cnki.issn1674-0629.2025.05.008
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Evolutionary Game Based Bidding Strategy of Aggregated Generation Unit for Renewable Energy

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Abstract

Aggregating clean energy and energy storage access to the grid can effectively reduce the impact on the safe operation of power grids caused by decentralized access. However, the focus of future research on clean energy participating in market competition lies in improving the revenue of aggregated clean energy and energy storage. This paper aggregates clean energy and energy storage as an aggregated regulation generation unit (AGU), and studies its bidding strategy on day-ahead power market. Firstly, a power market clearance model using queuing clearing method is established, and then the optimization model of bidding strategy based on evolutionary game theory is constructed. Secondly, the cost-benefit model of AGU is constructed to determine final bidding strategy. Finally, the arithmetic examples are analyzed using relevant data from the electricity market in Zhejiang Province and then a comparison is made with traditional bidding strategies, which verifies that the proposed strategy can improve the revenue of AGU.

Keywords

power markets / evolutionary game / bidding strategies / aggregated generation unit

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Kaijia MO,Yingjing HE,Xunjun CHEN,Renshun WANG,Cenfeng WANG,Keping ZHU,Quanyuan JIANG. Evolutionary Game Based Bidding Strategy of Aggregated Generation Unit for Renewable Energy. 2025, 19(5): 83-92 DOI:10.13648/j.cnki.issn1674-0629.2025.05.008

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Funding

the National Key Research and Development Program of China(2022YFB2403000)

the Science and Technology Project of State Grid Zhejiang Electric Power Co., Ltd(5211JY230005)

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