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author:

Zhang, Y. (Zhang, Y..) [1] | Lin, Y. (Lin, Y..) [2] | Shao, Z. (Shao, Z..) [3]

Indexed by:

Scopus PKU CSCD

Abstract:

A multi-objective optimal method of monitors for voltage sag location under observability constraint is proposed. It uses positive sequence voltage variation as sag pattern and defines the distance of pattern to find the most likely fault location. Then the uncertainty region index is defined to measure the locating accuracy of the measuring set. Finally the multi-objective monitoring optimization model is established which takes the observability of voltage sag as the constraint condition and takes the minimum number of monitoring points and the minimum uncertainty index as the objective function. The multi-objective discrete particle swarm optimization algorithm is used to get the non-inferior solution set. The feasibility and validity of the method are verified by IEEE 39 and IEEE 118 node system. © 2019, Electrical Technology Press Co. Ltd. All right reserved.

Keyword:

Multi-objective optimization; Observability; Optimal allocation; Voltage sag location

Community:

  • [ 1 ] [Zhang, Y.]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, 350116, China
  • [ 2 ] [Zhang, Y.]Fujian Smart Electrical Engineering Technology Research Center, Fuzhou, 350116, China
  • [ 3 ] [Lin, Y.]Quanzhou Electric Power Supply Company of State Grid Fujian Electric Power Company, Quanzhou, 362000, China
  • [ 4 ] [Shao, Z.]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, 350116, China
  • [ 5 ] [Shao, Z.]Fujian Smart Electrical Engineering Technology Research Center, Fuzhou, 350116, China

Reprint 's Address:

  • [Shao, Z.]College of Electrical Engineering and Automation, Fuzhou UniversityChina

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Source :

Transactions of China Electrotechnical Society

ISSN: 1000-6753

Year: 2019

Issue: 11

Volume: 34

Page: 2375-2383

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 23

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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