Stacked Auto-Encoder-Based Fault Location in Distribution Network
Accurate fault location is crucial for finding and clearing faults in distribution networks. It can help to reduce the loss of power failure and ensure safe and stable operation. Without efficient observation points and the lack of phase angle information, traditional fault location methods of distr...
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doaj-e31ff12ad38f4364932d1a317c42d34e2021-03-30T02:11:25ZengIEEEIEEE Access2169-35362020-01-018280432805310.1109/ACCESS.2020.29715828981997Stacked Auto-Encoder-Based Fault Location in Distribution NetworkGuomin Luo0https://orcid.org/0000-0003-2273-0787Yingjie Tan1Meng Li2Mengxiao Cheng3Yanmei Liu4Jinghan He5https://orcid.org/0000-0003-4210-955XSchool of Electrical Engineering, Beijing Jiaotong University, Beijing, ChinaSchool of Electrical Engineering, Beijing Jiaotong University, Beijing, ChinaSchool of Electrical Engineering, Beijing Jiaotong University, Beijing, ChinaSchool of Electrical Engineering, Beijing Jiaotong University, Beijing, ChinaSchool of Electrical Engineering, Beijing Jiaotong University, Beijing, ChinaSchool of Electrical Engineering, Beijing Jiaotong University, Beijing, ChinaAccurate fault location is crucial for finding and clearing faults in distribution networks. It can help to reduce the loss of power failure and ensure safe and stable operation. Without efficient observation points and the lack of phase angle information, traditional fault location methods of distribution networks usually have large errors. As the application of $\mu $ PMUs in the distribution network becomes more and more common, voltage and current waveforms, as well as phase angle can be recorded and provide more information for accurate fault location. In this paper, an intelligent location method is proposed to pinpoint the fault location based on the information of $\mu $ PMUs which are properly allocated. The fault section is firstly determined by comparing the zero-sequence current waveforms on both sides of the fault section. Then, a Stack Auto-Encoder (SAE) is modeled to provide an end-to-end solution to pinpoint fault point with the voltage and current phasors. Finally, the performance of the proposed method is tested by a simulated distribution network on the platform of PSCAD. The results show that the proposed method is effective in locating faults and can withstand the effects of transition resistance, fault type, and noise. Compared to another popular method, the proposed method shows better location accuracy.https://ieeexplore.ieee.org/document/8981997/Fault locationstacked auto-encoderdistribution network |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Guomin Luo Yingjie Tan Meng Li Mengxiao Cheng Yanmei Liu Jinghan He |
spellingShingle |
Guomin Luo Yingjie Tan Meng Li Mengxiao Cheng Yanmei Liu Jinghan He Stacked Auto-Encoder-Based Fault Location in Distribution Network IEEE Access Fault location stacked auto-encoder distribution network |
author_facet |
Guomin Luo Yingjie Tan Meng Li Mengxiao Cheng Yanmei Liu Jinghan He |
author_sort |
Guomin Luo |
title |
Stacked Auto-Encoder-Based Fault Location in Distribution Network |
title_short |
Stacked Auto-Encoder-Based Fault Location in Distribution Network |
title_full |
Stacked Auto-Encoder-Based Fault Location in Distribution Network |
title_fullStr |
Stacked Auto-Encoder-Based Fault Location in Distribution Network |
title_full_unstemmed |
Stacked Auto-Encoder-Based Fault Location in Distribution Network |
title_sort |
stacked auto-encoder-based fault location in distribution network |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
Accurate fault location is crucial for finding and clearing faults in distribution networks. It can help to reduce the loss of power failure and ensure safe and stable operation. Without efficient observation points and the lack of phase angle information, traditional fault location methods of distribution networks usually have large errors. As the application of $\mu $ PMUs in the distribution network becomes more and more common, voltage and current waveforms, as well as phase angle can be recorded and provide more information for accurate fault location. In this paper, an intelligent location method is proposed to pinpoint the fault location based on the information of $\mu $ PMUs which are properly allocated. The fault section is firstly determined by comparing the zero-sequence current waveforms on both sides of the fault section. Then, a Stack Auto-Encoder (SAE) is modeled to provide an end-to-end solution to pinpoint fault point with the voltage and current phasors. Finally, the performance of the proposed method is tested by a simulated distribution network on the platform of PSCAD. The results show that the proposed method is effective in locating faults and can withstand the effects of transition resistance, fault type, and noise. Compared to another popular method, the proposed method shows better location accuracy. |
topic |
Fault location stacked auto-encoder distribution network |
url |
https://ieeexplore.ieee.org/document/8981997/ |
work_keys_str_mv |
AT guominluo stackedautoencoderbasedfaultlocationindistributionnetwork AT yingjietan stackedautoencoderbasedfaultlocationindistributionnetwork AT mengli stackedautoencoderbasedfaultlocationindistributionnetwork AT mengxiaocheng stackedautoencoderbasedfaultlocationindistributionnetwork AT yanmeiliu stackedautoencoderbasedfaultlocationindistributionnetwork AT jinghanhe stackedautoencoderbasedfaultlocationindistributionnetwork |
_version_ |
1724185682775113728 |