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风电-光伏发电-抽水蓄能联合优化调度方法

Wind power-photovoltaic power generation-pumped storage joint optimal scheduling method
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摘要 为解决电力市场环境下的风电、光伏发电、抽水蓄能协同互补问题,提出了一种同时参与日前市场和实时平衡市场的风电-光伏发电-抽水蓄能联合优化调度方法。该方法考虑风电和光伏发电出力的不确定性,基于生成对抗网络和峰值密度聚类算法生成风电、光伏发电联合出力典型场景;基于抽水蓄能的灵活调节特性,并考虑风电和光伏发电实时出力引起的平衡成本,构建了风电-光伏发电-抽水蓄能联合参与日前市场和实时平衡市场的两阶段随机联合优化调度模型,最大化风电-光伏发电-抽水蓄能联合发电系统的收益。算例仿真结果表明,该方法具有有效性和合理性。 In order to solve the problem of coordination and complementary operation of wind power,photovoltaic power generation and pumped storage in the electricity market,a joint optimal dispatching method of wind power-photovoltaic power generation-pumped storage is proposed,which participates in both the day-ahead market and real-time balanced market.The method considers the uncertainty of wind power and photovoltaic power generation,and generates a typical scenario of wind power and photovoltaic power generation combined output based on adversarial generation network and peak density clustering algorithm.Based on the flexible regulation characteristics of pumped storage,and considering the balance cost caused by real-time output deviation of wind power and photovoltaic power generation,a two-stage stochastic scheduling model of wind power-photovoltaic power generation-pumped storage joint participation in the day-ahead market and real-time balanced market is constructed to maximize the income of the combined power generation system.The effectiveness and reasonability of the proposed method are verified by numerical examples.
作者 王立平 马实一 郭旭 李清 汪梦军 李杨 叶超 WANG Liping;MA Shiyi;GUO Xu;LI Qing;WANG Mengjun;LI Yang;YE Chao(EHV Power Transmission Company,CSG,Guangzhou 510663,China;China Renewable Energy Engineering Institute,Beijing 100120,China;School of Electrical and Power Engineering,Hohai University,Nanjing 211100,China)
出处 《水利经济》 北大核心 2024年第6期58-63,共6页 Journal of Economics of Water Resources
关键词 风电-光伏发电-抽水蓄能联合发电系统 日前市场 实时平衡市场 场景生成 两阶段随机优化 协同调度 wind-photovoltaic-pumped storage combined power generation system day-ahead market real-time balanced market scenario generation two-stage stochastic optimization coordinated scheduling
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