DocumentCode :
134701
Title :
A knowledge-based fault diagnosis platform in smart grid: A conceptual design
Author :
Zhao Wang ; Feng Gao ; Xinjie Lv ; Wenjun Yin ; Jin Dong
Author_Institution :
IBM Res. - China, Beijing, China
fYear :
2014
fDate :
27-31 July 2014
Firstpage :
1
Lastpage :
5
Abstract :
Ill-treated faults lead to power service interruptions for end customers, or even large scale outages, such as the case of 2003 North America blackout. In a smart grid environment, it is possible to detect and isolate faults in a timely manner. Fault detection and isolation (FDI) techniques based on measurement of traditional system states are well developed after decades of research efforts, mostly formulated as modules. In smart grids, more information sources are available, such as vision, acoustic, weather monitoring, and social media. A knowledge-based FDI platform is proposed to incorporate all these information sources and fault diagnosis modules. The proposed knowledge-based fault diagnosis architecture supplied well-reasoned results to support operator decision making, while expertise from operators help to improve its performance.
Keywords :
fault diagnosis; knowledge based systems; power engineering computing; power system faults; power system reliability; smart power grids; FDI technique; North America; blackout; conceptual design; fault detection and isolation technique; fault diagnosis module; information source; knowledge-based fault diagnosis platform; large scale outage; operator decision making; power service interruption; smart grid environment; Expert systems; Fault diagnosis; Sensors; Smart grids; Fault diagnosis; expert system; smart grid;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
PES General Meeting | Conference & Exposition, 2014 IEEE
Conference_Location :
National Harbor, MD
Type :
conf
DOI :
10.1109/PESGM.2014.6938834
Filename :
6938834
Link To Document :
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