基于分布鲁棒联合机会约束的光储充电站滚动优化调控模型  

Rolling Optimization Strategy for Photovoltaic Energy Storage-Charging Stations Based on Distributionally Robust Joint Chance Constraints

作　　者：孙舟[1] 王洪彪 肖万芳[1] 王立永[1] 袁小溪 胡泽春[2] SUN Zhou;WANG Hongbiao;XIAO Wanfang;WANG Liyong;YUAN Xiaoxi;HU Zechun(State Grid Beijing Electric Power Co.Ltd.,Beijing 100031,China;Department of Electrical Engineering,Tsinghua University,Beijing 100084,China)

机构地区：[1]国网北京市电力公司,北京100031 [2]清华大学电机系,北京100084

出　　处：《智慧电力》2024年第4期1-7,77,共8页Smart Power

基　　金：国家重点研发计划资助项目(2022YFB2403903);国家电网公司总部科技项目(5108-202218280A-2-391-XG)。

摘　　要：随着电动汽车的普及和清洁能源装机容量的日益增加,光储充电站展现出广阔的应用前景。针对电动汽车随机接入影响下光储充电站功率难以精准调控的问题,提出基于分布鲁棒联合机会约束(DRJCC)的光储充电站滚动优化调控模型。将基于混合整数规划(MIP)的精确DRJCC模型、基于CVaR-Slim凸松弛的DRJCC模型、基于Bonferroni不等式的DRJCC模型进行对比,通过算例分析验证了所提优化调控模型的有效性。算例分析表明,所提基于CVaR-Slim凸松弛的DRJCC模型能够同时满足更多电动汽车的充电需求。With the popularization of electric vehicles and the increasing installed capacity of clean energy,the photovoltaic energy storage-charging station has a good application prospect.Aiming at the problem that the power of photovoltaic energy storage-charging station is difficult to be accurately regulated under the influence of random access of electric vehicles,the rolling optimization strategy of photovoltaic energy storage-charging stations based on distributionally robust joint chance constraints(DRJCC)is proposed.The DRJCC model based on CVal-SLIM convex relaxation,the exact DRJCC model based on mixed integer programming and the DRJCC model based on Bonferroni inequality are compared,and the effectiveness of the proposed optimization strategy is verified by example analysis.It is shown that the DRJCC model based on CVaR-Slim convex relaxation can meet more EV charging requirements.

关 键 词：分布式鲁棒联合机会约束 光储充电站 调控策略 

分 类 号：TM911[电气工程—电力电子与电力传动]