Voltage sag source location based on sag event amplitude information

Voltage sag source location provides a solution to improve the operation and maintenance efficiency and resolve disputes between power supply and consumption. The existing sag source locating methods are based on the fault recording system’s sampling value waveform data, which requires more storage...

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Main Authors: Zhu Liu, Shuai Zhang, Wenjing Li, Chen Zheng, Shuming Liu, Limin Wang
Format: Article
Language:English
Published: Elsevier 2023-09-01
Series:Energy Reports
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352484723004213
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author Zhu Liu
Shuai Zhang
Wenjing Li
Chen Zheng
Shuming Liu
Limin Wang
author_facet Zhu Liu
Shuai Zhang
Wenjing Li
Chen Zheng
Shuming Liu
Limin Wang
author_sort Zhu Liu
collection DOAJ
description Voltage sag source location provides a solution to improve the operation and maintenance efficiency and resolve disputes between power supply and consumption. The existing sag source locating methods are based on the fault recording system’s sampling value waveform data, which requires more storage space and transmission channels. Based on sag event list with easy access and high real-time performance and takes the line as the location result, this paper proposes a voltage sag source locating method based on sag event amplitude information. Firstly, Based on the voltage amplitude of the monitoring nodes recorded in the sag event list, a matrix of voltage amplitude of disturbed monitoring nodes is formed. Secondly, the voltage amplitude and fault type of the disturbed nodes are used as inputs, and the line number is used as a classification number. The multi-classifier model based on multi-layer perceptron is trained to locate the voltage sag source. Finally, the method in this paper is verified by IEEE39 node simulation model and the actual monitoring data of sag events in an area in East China. The results show that the method is effective and feasible. Compared with the existing commonly used multi classification algorithms, it is found that the accuracy of sag source location in this method is 10% ∼ 20% higher than other multi classification algorithms.
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spelling doaj.art-22473a88e5ef4eaa87b6b1fa08b083ac2023-09-06T04:51:35ZengElsevierEnergy Reports2352-48472023-09-01920042012Voltage sag source location based on sag event amplitude informationZhu Liu0Shuai Zhang1Wenjing Li2Chen Zheng3Shuming Liu4Limin Wang5State Grid Information & Telecommunication Group Co., Ltd., Beijing, 102211, China; Corresponding author.State Grid Information & Telecommunication Group Co., Ltd., Beijing, 102211, ChinaState Grid Information & Telecommunication Group Co., Ltd., Beijing, 102211, ChinaState Grid Henan Electric Power Research Institute, Zhengzhou, 450052, ChinaState Grid Henan Electric Power Research Institute, Zhengzhou, 450052, ChinaState Grid Information & Telecommunication Group Co., Ltd., Beijing, 102211, ChinaVoltage sag source location provides a solution to improve the operation and maintenance efficiency and resolve disputes between power supply and consumption. The existing sag source locating methods are based on the fault recording system’s sampling value waveform data, which requires more storage space and transmission channels. Based on sag event list with easy access and high real-time performance and takes the line as the location result, this paper proposes a voltage sag source locating method based on sag event amplitude information. Firstly, Based on the voltage amplitude of the monitoring nodes recorded in the sag event list, a matrix of voltage amplitude of disturbed monitoring nodes is formed. Secondly, the voltage amplitude and fault type of the disturbed nodes are used as inputs, and the line number is used as a classification number. The multi-classifier model based on multi-layer perceptron is trained to locate the voltage sag source. Finally, the method in this paper is verified by IEEE39 node simulation model and the actual monitoring data of sag events in an area in East China. The results show that the method is effective and feasible. Compared with the existing commonly used multi classification algorithms, it is found that the accuracy of sag source location in this method is 10% ∼ 20% higher than other multi classification algorithms.http://www.sciencedirect.com/science/article/pii/S2352484723004213Voltage sagVoltage sag source locationMulti-layer perceptron
spellingShingle Zhu Liu
Shuai Zhang
Wenjing Li
Chen Zheng
Shuming Liu
Limin Wang
Voltage sag source location based on sag event amplitude information
Energy Reports
Voltage sag
Voltage sag source location
Multi-layer perceptron
title Voltage sag source location based on sag event amplitude information
title_full Voltage sag source location based on sag event amplitude information
title_fullStr Voltage sag source location based on sag event amplitude information
title_full_unstemmed Voltage sag source location based on sag event amplitude information
title_short Voltage sag source location based on sag event amplitude information
title_sort voltage sag source location based on sag event amplitude information
topic Voltage sag
Voltage sag source location
Multi-layer perceptron
url http://www.sciencedirect.com/science/article/pii/S2352484723004213
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AT wenjingli voltagesagsourcelocationbasedonsageventamplitudeinformation
AT chenzheng voltagesagsourcelocationbasedonsageventamplitudeinformation
AT shumingliu voltagesagsourcelocationbasedonsageventamplitudeinformation
AT liminwang voltagesagsourcelocationbasedonsageventamplitudeinformation