One-class classifier based fault detection in distribution systems with distributed energy resources

Zhidi Lin; Dongliang Duan; Qi Yang; Xiang Cheng; Liuqing Yang; Shuguang Cui

doi:10.1109/GlobalSIP.2018.8646526

One-class classifier based fault detection in distribution systems with distributed energy resources

Zhidi Lin, Dongliang Duan, Qi Yang, Xiang Cheng, Liuqing Yang, Shuguang Cui

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

The integration of distributed energy resources (DERs) into distribution systems greatly increases the system complexity and introduces two-way power flows. Conventional protection schemes are based upon local measurements and simple linear system models, thus they cannot handle the new complexity and power flow patterns in systems with high DERs penetration. In this paper, we propose a data-driven protection framework to address the challenges induced by DERs. Considering the limited available data under fault conditions, we adopt the support vector data description (SVDD) method, a commonly used one-class classifier, for distribution system fault detection. The proposed method is tested under the IEEE 123-node test feeder and simulation results show that our proposed SVDD-based fault detection method significantly improves the robustness and resilience against DERs in comparison with conventional protection systems.

Original language	English (US)
Title of host publication	2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	932-936
Number of pages	5
ISBN (Electronic)	9781728112954
DOIs	https://doi.org/10.1109/GlobalSIP.2018.8646526
State	Published - Jul 2 2018
Externally published	Yes
Event	2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Anaheim, United States Duration: Nov 26 2018 → Nov 29 2018

Publication series

Name	2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings

Conference

Conference	2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018
Country/Territory	United States
City	Anaheim
Period	11/26/18 → 11/29/18

Bibliographical note

Funding Information:
This work was supported in part by Shenzhen Fundamental Research Fund under Grant No. JCYJ20170411102217994 and ZDSYS201707251409055, Shenzhen Peacock Plan under Grant KQTD2015033114415450 and Guangdong province “The Pearl River Talent Recruitment Program Innovative and Entrepreneurial Teams in 2017”-Data Driven Evolution of Future Intelligent Network Team under grant No. 2017ZT07X152.

Keywords

Distributed energy resources (DERs)
Distribution systems
Fault detection
Support vector data description (SVDD)

Publisher link

10.1109/GlobalSIP.2018.8646526

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Cite this

Lin, Z., Duan, D., Yang, Q., Cheng, X., Yang, L., & Cui, S. (2018). One-class classifier based fault detection in distribution systems with distributed energy resources. In 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings (pp. 932-936). Article 8646526 (2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2018.8646526

One-class classifier based fault detection in distribution systems with distributed energy resources. / Lin, Zhidi; Duan, Dongliang; Yang, Qi et al.
2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. p. 932-936 8646526 (2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lin, Z, Duan, D, Yang, Q, Cheng, X, Yang, L & Cui, S 2018, One-class classifier based fault detection in distribution systems with distributed energy resources. in 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings., 8646526, 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 932-936, 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018, Anaheim, United States, 11/26/18. https://doi.org/10.1109/GlobalSIP.2018.8646526

Lin Z, Duan D, Yang Q, Cheng X, Yang L, Cui S. One-class classifier based fault detection in distribution systems with distributed energy resources. In 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. p. 932-936. 8646526. (2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings). doi: 10.1109/GlobalSIP.2018.8646526

Lin, Zhidi ; Duan, Dongliang ; Yang, Qi et al. / One-class classifier based fault detection in distribution systems with distributed energy resources. 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 932-936 (2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings).

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N2 - The integration of distributed energy resources (DERs) into distribution systems greatly increases the system complexity and introduces two-way power flows. Conventional protection schemes are based upon local measurements and simple linear system models, thus they cannot handle the new complexity and power flow patterns in systems with high DERs penetration. In this paper, we propose a data-driven protection framework to address the challenges induced by DERs. Considering the limited available data under fault conditions, we adopt the support vector data description (SVDD) method, a commonly used one-class classifier, for distribution system fault detection. The proposed method is tested under the IEEE 123-node test feeder and simulation results show that our proposed SVDD-based fault detection method significantly improves the robustness and resilience against DERs in comparison with conventional protection systems.

AB - The integration of distributed energy resources (DERs) into distribution systems greatly increases the system complexity and introduces two-way power flows. Conventional protection schemes are based upon local measurements and simple linear system models, thus they cannot handle the new complexity and power flow patterns in systems with high DERs penetration. In this paper, we propose a data-driven protection framework to address the challenges induced by DERs. Considering the limited available data under fault conditions, we adopt the support vector data description (SVDD) method, a commonly used one-class classifier, for distribution system fault detection. The proposed method is tested under the IEEE 123-node test feeder and simulation results show that our proposed SVDD-based fault detection method significantly improves the robustness and resilience against DERs in comparison with conventional protection systems.

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One-class classifier based fault detection in distribution systems with distributed energy resources

Abstract

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Bibliographical note

Keywords

Publisher link

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