Paper Info
Title
Wide Area Power System Fault Detection Using Compressed Sensing to Reduce the WAN Data Traffic
Abstract
With the increasingly complex power system, wide area protection, using global data obtained from different substations through communications, has been a hot research topic for some time. However, the overall transmission of large amounts of data will cause communication network congestion, which will lead to delay and loss of data. Therefore building an algorithm which can make use of a reduced number of global data to identify the fault area is very useful. This paper proposes a down-sampling matrix to reduce the original data. For example, a protection system requiring 240 feature points of voltage data, if using the down-sampling matrix, will need only a minimum of 24 points, and still has a high probability to identify the fault zone. Simulation results show that when the data size M > 0.3, the result of classifying adjacent bus fault point is credible (greater than 60%), and when the data size M > 0.05, the result of classifying the non-adjacent bus fault point is credible (greater than 72%).
Year
DOI
Venue
2014
10.1109/PAAP.2014.28
PAAP
Keywords
Field
DocType
power system protection,fault zone,complex power system,wan data traffic,compressed sensing (cs),wide area protection,communication network congestion,power system faults,compressed sensing,wide area power system fault detection,substations,adjacent bus fault point,down-sampling matrix,data traffic,wide area networks,mathematical model,simulation,sparse matrices
Telecommunications network,Fault (geology),Matrix (mathematics),Fault detection and isolation,Computer science,Voltage,Computer network,Electric power system,Real-time computing,Compressed sensing,Fault indicator
Conference
ISSN
ISBN
Citations 
2168-3034
978-1-4799-3844-5
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Bei Li100.34
Jinghan He2147.47
Tony Yip301.01
Jiangchen Li400.34