Paper Info
Title
Rule-based data-driven analytics for Wide-Area fault detection using synchrophasor data.
Abstract
Synchrophasor technology, also known as Wide-Area Monitoring System (WAMS) technology, utilizes Phasor Measurement Unit (PMU) to monitor real-time system data, which can provide unique insights into the operation of a power grid. In this paper, a rule-based data-driven analytics method for wide-area fault detection in a power system using synchrophasor data is proposed. As a data-driven approach, this method relies on rules created using PMU measurement data, and does not require knowledge of the power system's topology and model. It can detect fault location (bus and line) and fault type for a particular fault event. Three common types of short circuit faults in a power grid, single-Iine-to-ground (SLG), line-to-Iine (LL), and three phase faults, can be identified using the proposed method. Fault thresholds used in rules are determined based on theoretical values and recorded PMU data during fault events in Bonneville Power Administration (BPA)'s large power grid. The proposed method is validated by comparing with the recorded field data for fault events provided by BPA. It is found that it can effectively detect most faults with a great accuracy. It has been developed into a software program, and can be readily used by utility companies.
Year
DOI
Venue
2016
10.1109/TIA.2016.2644621
IEEE Industry Applications Society Annual Meeting
Keywords
DocType
Volume
Data-Driven Analytics,Fault Detection,Phasor Measurement Unit (PMU),Smart Grid,Synchrophasor,Wide-Area Monitoring System (WAMS)
Conference
53
Issue
ISSN
Citations 
3
0197-2618
0
PageRank 
References 
Authors
0.34
2
3
Name
Order
Citations
PageRank
Xiaodong Liang13021.59
Scott A. Wallace2124.68
Duc Nguyen310.70