基于演化博弈的清洁能源聚合发电单元竞价策略
莫凯佳 , 何英静 , 陈浔俊 , 王仁顺 , 王岑峰 , 朱克平 , 江全元
南方电网技术 ›› 2025, Vol. 19 ›› Issue (5) : 83 -92.
基于演化博弈的清洁能源聚合发电单元竞价策略
Evolutionary Game Based Bidding Strategy of Aggregated Generation Unit for Renewable Energy
将清洁能源与储能聚合接入电网可有效降低分散接入对电网安全运行的影响,在清洁能源通过市场化竞争获取收益的背景下,如何提高清洁能源与储能聚合参与电力市场的收益是未来清洁能源参与市场竞争的研究重点。将风光水储汇集得到可实现聚合调控的聚合发电单元,针对其参与日前电能量市场的竞价策略展开研究。首先,以排队出清法建立电力市场出清模型,基于演化博弈理论构建竞价策略优化模型。其次,构建聚合发电单元成本收益模型,基于收益值确定最终竞价方案。最后,采用浙江省电力市场相关数据进行算例分析,并与传统竞价策略对比,验证了所提策略能够提高聚合发电单元的收益能力。
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.
power markets / evolutionary game / bidding strategies / aggregated generation unit
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