Статья

Evaluation Method of Distribution Network Resilience Focusing on Critical Loads

Diansheng LuoCollege of Electrical and Information Engineering, Hunan University, Changsha, ChinaYongwei XiaHunan Key Laboratory of Intelligent Information Analysis and Integrated Optimization for Energy Internet, Hunan University, Changsha, ChinaYuanyuan ZengHunan Key Laboratory of Intelligent Information Analysis and Integrated Optimization for Energy Internet, Hunan University, Changsha, ChinaCanbing LiHunan Key Laboratory of Intelligent Information Analysis and Integrated Optimization for Energy Internet, Hunan University, Changsha, ChinaXian ZhangHunan Key Laboratory of Intelligent Information Analysis and Integrated Optimization for Energy Internet, Hunan University, Changsha, ChinaHao YuGrid Planning and Research Center, Guangdong Power Grid Co., Ltd, Guangzhou, ChinaQiuwei WuCenter for Electric Power and Energy, Technical University of Denmark, Kongens Lyngby, Denmark

2018en

ABI

Аннотация

With the frequent occurrence of extreme weather events in the world, the ability of power system to resist disasters has attracted more attention. In this paper, a method to evaluate the resilience of distribution networks by focusing on the impact of critical loads under extreme weather events is proposed, and typhoon is taken as the representative to formulate a vulnerability curve of components. Furthermore, the Monte Carlo method is used to simulate the whole process of extreme weather disaster and to generate the fault scenario. Different weights are assigned to different levels of load according to the importance of load, and the weighted loss of load is selected as the evaluation index of resilience. Finally, the method is verified by the IEEE-33 bus system. The results demonstrate that this method is effective to quantify the resilience of distribution networks under extreme weather events.

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Идентификаторы

DOI: 10.1109/access.2018.2872941

Цитирования и источники

Цитирований: 2Использованных источников: 0

Показатели — AkademScholar