Title
Data-Driven Event Detection of Power Systems Based on Unequal-Interval Reduction of PMU Data and Local Outlier Factor
Abstract
With the deployment of phasor measurement units (PMU) and wide area measurement system (WAMS), it is feasible to have an insight into the events occurred in power systems based on measured data. Thus, a novel data-driven algorithm based on local outlier factor (LOF) is proposed in this work to detect and locate events in power systems using reduced PMU data. First, the unequal-interval reduction method is presented to reduce the scale of PMU data in sub-stations and reconstruct it in master station of WAMS, which can relieve the burden of communication systems. Then, principle component analysis (PCA)-based similarity search method is proposed to measure the differences of operation state between any two buses. Next, LOF is presented to detect the abnormal events in power systems, and employed to determine the region of the event source. Finally, six cases from the Western electricity coordinating council (WECC) 179-bus power system, a case from the South China power system (SCPS), and a case from the Guangdong power system (GDPS) are utilized to demonstrate the effectiveness of the proposed algorithm. The results show that proposed algorithm is effective and can be applied to event detection, event location, and online monitoring, which can enhance the situation awareness ability of power system operators.
Year
DOI
Venue
2020
10.1109/TSG.2019.2941565
IEEE Transactions on Smart Grid
Keywords
Field
DocType
Event detection,phasor measurement units (PMU),wide area measurement system (WAMS),similarity search method,local outlier factor (LOF)
Local outlier factor,Units of measurement,Data-driven,Situation awareness,Phasor,Communications system,Electric power system,Control engineering,Real-time computing,Engineering,Master station
Journal
Volume
Issue
ISSN
11
2
1949-3053
Citations 
PageRank 
References 
0
0.34
0
Authors
7
Name
Order
Citations
PageRank
Shengyuan Liu121.23
Yuxuan Zhao200.68
Zhenzhi Lin342.27
Yilu Liu417237.39
Yi Ding510037.68
Li Yang600.68
Shimin Yi700.34