Abstract
The integration of Distributed Energy Resources (DERs) introduces non-conventional two-way power flows which cannot be captured well by traditional model-based techniques. This brings great challenges to accurately localize faults and initiate correct actions of the protection system. In this paper, we propose a data-driven fault localization strategy based on multilevel system regionalization and probabilistic fault detections on all the subregions. The strategy combines the Support Vector Data Description (SVDD) and the Kernel Density Estimation (KDE) to provide the confidence level of fault detections in each subregion by p-values, and then accurately localize the fault by comparing the p-values. Our experiments show that the proposed data-driven fault localization can greatly increase the accuracy of fault localization for distribution systems with high integration of DERs.
Original language | English (US) |
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Title of host publication | iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference |
Subtitle of host publication | Grid Modernization for Energy Revolution, Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1021-1026 |
Number of pages | 6 |
ISBN (Electronic) | 9781728149301 |
DOIs | |
State | Published - Nov 2019 |
Externally published | Yes |
Event | 2019 IEEE Sustainable Power and Energy Conference, iSPEC 2019 - Beijing, China Duration: Nov 21 2019 → Nov 23 2019 |
Publication series
Name | iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference: Grid Modernization for Energy Revolution, Proceedings |
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Conference
Conference | 2019 IEEE Sustainable Power and Energy Conference, iSPEC 2019 |
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Country/Territory | China |
City | Beijing |
Period | 11/21/19 → 11/23/19 |
Bibliographical note
Publisher Copyright:© 2019 IEEE.
Keywords
- Distributed Energy Resources (DERs)
- Support Vector Data Description (SVDD)
- distribution systems
- fault localization
- probabilistic fault detection