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基于广义线性多面体的有源配电网仿射可调鲁棒优化方法 被引量:2

Affinely Adjustable Robust Optimization Method for Active Distribution Network Based on Generalized Linear Polyhedral
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摘要 针对传统的多面体集合对分布式光伏出力相关性缺乏考虑,提出了基于广义线性多面体集合的有源配电网仿射可调鲁棒优化方法,以量化相关性对优化结果的影响。首先,采用多面体集合来描述分布式光伏出力的不确定性,利用分布式光伏出力的历史数据得到不确定性出力相关性的分布包络图;然后,结合相关性分布包络图重构了多面体集合的边界,并针对重构后的相关性多面体集合存在的保守性偏大的问题,进一步建立了描述分布式光伏出力相关性的广义多面体集合;最后,通过算例对比分析了广义多面体集合对有源配电网仿射可调鲁棒优化结果的影响。 In view of lacking consideration of distributed photovoltaic output correlation in the traditional polyhedral set,an affinely adjustable robust optimization method for active distribution networks based on the generalized linear polyhedral set is proposed to quantify the impact of correlation on optimization results.First,the polyhedral set is used to describe the uncertainty of distributed photovoltaic output,and the correlation distribution envelope of uncertain output is obtained by using the historical data of distributed photovoltaic output.Then,the boundary of the polyhedral set is reconstructed by combining the correlation distribution envelope.In response to the problem of the large conservativeness in the reconstructed correlation polyhedral set,a generalized polyhedral set is further established to describe the correlation of distributed photovoltaic output.Finally,the impact of the generalized polyhedral set on the affinely adjustable robust optimization results of the active distribution network is analyzed through the comparison of cases.
作者 乐健 郎红科 廖小兵 王靖 毛涛 LE Jian;LANG Hongke;LIAO Xiaobing;WANG Jing;MAO Tao(School of Electrical Engineering and Automation,Wuhan University,Wuhan 430072,China;School of Electrical and Information Engineering,Wuhan Institute of Technology,Wuhan 430205,China;Wuhan YICIYUAN Power Technology Co.,Ltd.,Wuhan 430223,China)
出处 《电力系统自动化》 EI CSCD 北大核心 2023年第22期138-148,共11页 Automation of Electric Power Systems
基金 国家自然科学基金资助项目(52107122)。
关键词 分布式光伏 广义多面体集合 有源配电网 混合整数二阶锥规划 鲁棒优化 distributed photovoltaic generalized polyhedral set active distribution network mixed-integer second-order cone programming robust optimization
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