考虑绿电交易的集群新能源场站与共享储能两阶段鲁棒优化运行策略

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  • 1. 上海交通大学 电力传输与功率变换控制教育部重点实验室,上海 200240

    2. 大唐云南发电有限公司,昆明 650506

归一凡(2000—),硕士生,从事电力市场、电力系统优化运行、共享储能等研究
王玲玲,助理研究员;E-mail:wanglingling1993@sjtu.edu.cn

网络出版日期: 2025-06-30

基金资助

上海市扬帆计划(24YF2721400)资助项目

Two-Stage Robust Optimization Operation Strategy for Clustered Renewable Energy Stations and Shared Energy Storage Considering Green Power Trading

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  • 1. Key Laboratory of Control of Power Transmission and Conversion of the Ministry of Education , Shanghai Jiao Tong University, Shanghai 200240, China; 

    2. Datang Yunnan Power Generation Co., Ltd., Kunming 650506, China

Online published: 2025-06-30

摘要

大型新能源基地的建设推动了电力系统的低碳转型,新能源场站和储能在电力调度和市场交易中扮演着愈加重要的角色。同时,共享经济模式因其能提高闲置资源利用率而受到学者青睐。本文对新能源基地中集群场站与共享储能联合优化运行模式进行了研究。首先,构建了新能源基地中集群场站与共享储能的联合优化运行框架。然后,建立考虑绿电交易的新能源场站与共享储能两阶段优化模型。针对新能源出力的不确定性,构建考虑风光误差时序特性的不确定性集,可以反映可再生能源输出的真实波动范围。在此基础上,构建日前-日内两阶段鲁棒模型。最后,利用共享储能的闲置容量参与电能量市场与备用市场,提升了储能的利用率,拓宽了储能的盈利渠道。算例分析验证了所提模型和方法的有效性。结果表明,所提的优化运行策略能够显著降低新能源场站偏差惩罚成本,并加速储能投资回收,最终提高新能源基地的净收益。

本文引用格式

归一凡1, 王继才2, 赵胤呈1, 王玲玲1, 蒋传文1 . 考虑绿电交易的集群新能源场站与共享储能两阶段鲁棒优化运行策略[J]. 上海交通大学学报, 0 : 1 . DOI: 10.16183/j.cnki.jsjtu.2025.075

Abstract

The construction of large-scale renewable energy bases has promoted the low-carbon transformation of the power system, with renewable energy stations and energy storage playing an increasingly important role in power dispatch and market transactions. At the same time, the sharing economy model has gained favor among scholars for its ability to improve the utilization of idle resources. This paper investigates the joint optimization operation mode of clustered renewable energy stations and shared energy storage in renewable energy bases. First, a joint optimization operation framework for clustered renewable energy stations and shared energy storage in renewable energy bases is established. Then, a two-stage optimization model for renewable energy stations and shared energy storage, considering green power trading, is developed. To address the uncertainty of renewable energy generation, an uncertainty set that accounts for the temporal characteristics of wind and solar power errors is constructed, which can reflect the true fluctuation range of renewable energy output. On this basis, a day-ahead and intraday two-stage robust model is built. Finally, the idle capacity of shared energy storage is utilized to participate in both the energy and reserve markets, improving energy storage utilization and expanding its profit channels. Case studies verify the effectiveness of the proposed model and method. The results show that the proposed optimization operation strategy can significantly reduce the penalty cost for renewable energy station deviations, accelerate the recovery of energy storage investment, and ultimately increase the net profit of the renewable energy base.

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