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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)
Department工业控制网络与系统研究室
Conference Name2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)
Conference DateAugest 26-27, 2015
Conference PlaceHangzhou, China
Source Publication2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)
PublisherIEEE
Publication PlacePiscataway, NJ, USA
2015
Pages357-361
Indexed ByEI ; CPCI(ISTP)
EI Accession number20160401837839
WOS IDWOS:000377211600085
Contribution Rank1
ISSN2157-8982
ISBN978-1-4799-8645-3
KeywordDistribution Power System Bp Neural Network Short-circuit Fault Active Distribution Network Fault Location
AbstractThis 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%.
Language英语
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/17383
Collection工业控制网络与系统研究室
Corresponding AuthorLi XH(李先宏); Yu HB(于海斌); Liu JC(刘建昌)
Affiliation1.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
Recommended Citation
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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