Data-Driven Fault Localization in Distribution Systems with Distributed Energy Resources

Zhidi Lin, Dongliang Duan, Qi Yang, Xuemin Hong, Xiang Cheng, Liuqing Yang and Shuguang Cui
Additional contact information
Zhidi Lin: Future Network of Intelligence Institute (FNii), The Chinese University of Hong Kong, Shenzhen 518172, China
Dongliang Duan: Shenzhen Research Institute of Big Data (SRIBD), Shenzhen 518172, China
Qi Yang: School of Informatics, Xiamen University, Xiamen 361005, China
Xuemin Hong: School of Informatics, Xiamen University, Xiamen 361005, China
Xiang Cheng: Shenzhen Research Institute of Big Data (SRIBD), Shenzhen 518172, China
Liuqing Yang: Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO 80523, USA
Shuguang Cui: Future Network of Intelligence Institute (FNii), The Chinese University of Hong Kong, Shenzhen 518172, China

Energies, 2020, vol. 13, issue 1, 1-16

Abstract: The integration of Distributed Energy Resources (DERs) introduces a non-conventional two-way power flow which cannot be captured well by traditional model-based techniques. This brings an unprecedented challenge in terms of the accurate localization of faults and proper actions of the protection system. In this paper, we propose a data-driven fault localization strategy based on multi-level system regionalization and the quantification of fault detection results in all subsystems/subregions. This strategy relies on the tree segmentation criterion to divide the entire system under study into several subregions, and then combines Support Vector Data Description (SVDD) and Kernel Density Estimation (KDE) to find the confidence level of fault detection in each subregion in terms of their corresponding p -values. By comparing the p -values, one can accurately localize the faults. Experiments demonstrate that the proposed data-driven fault localization can greatly improve the accuracy of fault localization for distribution systems with high DER penetration.

Keywords: Distributed Energy Resources (DERs); distribution systems; fault localization; kernel density estimation (KDE); Support Vector Data Description (SVDD) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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