A Distributed Robust Voltage Control Framework for Active Distribution Systems

被引:0
作者
Xu, Junjun [1 ,2 ]
Mu, Yu [1 ,2 ]
Cheng, Wei [3 ]
Gong, Guangjing [3 ]
Huang, Jungao [3 ]
Zhang, Tengfei [1 ,2 ]
Hu, Qinran [4 ]
Chen, Kang [3 ]
Wu, Andrew Yang [5 ]
机构
[1] Nanjing Univ Posts & Telecommun, Coll Automat, Nanjing 210023, Peoples R China
[2] Nanjing Univ Posts & Telecommun, Coll Artificial Intelligence, Nanjing 210023, Peoples R China
[3] State Grid Elect Power Res Inst, NARI Grp Corp, Nanjing 211106, Peoples R China
[4] Southeast Univ, Sch Elect Engn, Nanjing 210096, Peoples R China
[5] Hong Kong Polytech Univ, Sch Profess Educ & Execut Dev, Hong Kong 999077, Peoples R China
基金
中国国家自然科学基金;
关键词
Voltage control; Clustering algorithms; Data models; Power system stability; Sensitivity; Reactive power; Partitioning algorithms; Robust control; Regulation; Microgrids; Distributed generator; distribution system; robust voltage control; uncertainty; DG;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Voltage fluctuations in active distribution systems (ADS) have increased with the high penetration of uncertain energy resources, making unified governance more challenging. This paper proposes a novel distributed robust voltage control (DRVC) method for ADS based on coordinated clustering of photovoltaic and energy storage systems, aiming to aggregate decentralized resources into interrelated clusters to achieve distributed voltage regulation. Firstly, an improved Louvain algorithm based clustering method for ADS is introduced, further incorporating the voltage sensitivity and regulation capability of generators into the modularized function. After that, a local robust voltage regulation model for each cluster is constructed, and the global multi-objective optimization function is solved through a distributed robust solution method for integrating intelligent optimization to further enhance the robustness. Case studies and results demonstrate the performance of the proposed voltage control framework in resisting uncertainties by contrast with existing models.
引用
收藏
页码:1896 / 1906
页数:11
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