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A Fault Location Method for Active Distribution Network with Renewable Sources Based on BP Neural Network
Zhang T(张彤); Li XH(李先宏); Yu HB(于海斌); Liu JC(刘建昌); Zeng P(曾鹏); Sun LX(孙兰香)
作者部门工业控制网络与系统研究室
会议名称2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)
会议日期Augest 26-27, 2015
会议地点Hangzhou, China
会议录名称2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)
出版者IEEE
出版地Piscataway, NJ, USA
2015
页码357-361
收录类别EI ; CPCI(ISTP)
EI收录号20160401837839
WOS记录号WOS:000377211600085
产权排序1
ISSN号2157-8982
ISBN号978-1-4799-8645-3
关键词Distribution Power System Bp Neural Network Short-circuit Fault Active Distribution Network Fault Location
摘要This paper presents a neural network method to locate common fault exactly in a distribution power system (DPS) with renewable sources. The back propagation (BP) neural network method is applied to identify patterns of voltage and current measured from distribution branches. The input matrix of BP network consists of the voltage and current values, which can identify the accurate fault position. The fault location of a common short-circuit fault is analyzed thoroughly in an active distribution network (ADN) with the renewable power sources. Simulation results prove the feasibility and usefulness of the fault location method based on the BP neural network, wherein the fault location accuracy can reach 0.09%.
语种英语
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被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/17383
专题工业控制网络与系统研究室
通讯作者Li XH(李先宏); Yu HB(于海斌); Liu JC(刘建昌)
作者单位1.Key Laboratory of Industrial Control Network and System, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.Department of Automation, College of Information, Science and Engineering of Northeastern University, Shenyang, China
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GB/T 7714
Zhang T,Li XH,Yu HB,et al. A Fault Location Method for Active Distribution Network with Renewable Sources Based on BP Neural Network[C]. Piscataway, NJ, USA:IEEE,2015:357-361.
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