标题:Detection and classification of short-circuit faults in distribution networks based on Fortescue approach and Softmax regression
作者:Zhang, Chao ;Wang, Jiandong ;Huang, Jian ;Cao, Pengfei
作者机构:[Zhang, Chao ;Wang, Jiandong ;Cao, Pengfei ] Shandong University of Science and Technology, Qingdao; 266590, China;[Huang, Jian ] The State Grid Weifa 更多
通讯作者:Wang, Jiandong
来源:International Journal of Electrical Power and Energy Systems
出版年:2020
卷:118
DOI:10.1016/j.ijepes.2019.105812
关键词:Distribution networks; Fault detection and classification; Fortescue approach; Short-circuit faults; Softmax regression
摘要:This paper proposes a method to detect and classify ten short-circuit faults in distribution networks, where the presence of distributed generators makes fault diagnosis a challenging problem. The main idea is to consider operating modes of distributed generators in analyzing fault characteristics via the Fortescue approach, and exploit the softmax regression to alleviate negative effects of transient data samples on the fault classification. The proposed method is developed in three main steps. First, the relationship between measurable currents and unavailable currents of the fault point is developed for the grid-connected mode or the islanding mode of distributed generators. Second, the Fortescue approach is used to formulate fault characteristics from the positive-, negative- and zero-sequence components of measurable currents. Third, the softmax regression is introduced to alleviate negative effects of transient data samples on the fault classification. The effectiveness of the proposed method is demonstrated via numerical examples on balanced and unbalanced distribution networks. © 2020 Elsevier Ltd
收录类别:EI;SCOPUS
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077681462&doi=10.1016%2fj.ijepes.2019.105812&partnerID=40&md5=e21cfbcdee20df42df4782721ee4c59d
TOP