DocumentCode
1179676
Title
Artificial Neural Networks in Power System Restoration
Author
Bretas, Arturo S. ; Phadke, Arun G.
Author_Institution
University of Sao Paulo, Sao Paulo, Brazil; Virginia Polytechnic Institute and State University, Blacksburg, Virginia
Volume
22
Issue
10
fYear
2002
Firstpage
61
Lastpage
61
Abstract
Power system restoration (PSR) has been a subject of study for many years. In recent years many techniques were proposed to solve the limitations of the predetermined restoration guidelines and procedures used by a majority of system operators to restore a system following the occurrence of a wide area disturbance. This paper discusses limitations encountered in some currently used PSR techniques and a proposed improvement based on artificial neural networks (ANN). The proposed scheme is tested on a 162 bus transmission system and compared with a breadth-search restoration scheme. The results indicate that the use of ANN in power system restoration is a feasible option that should be considered for real-time applications.
Keywords
Artificial neural networks; Electrodes; Grounding; Impedance; Load modeling; Power system modeling; Power system relaying; Power system restoration; Protection; Protective relaying; Artificial neural networks; artificial intelligence; power system restoration; wide-area disturbances;
fLanguage
English
Journal_Title
Power Engineering Review, IEEE
Publisher
ieee
ISSN
0272-1724
Type
jour
DOI
10.1109/MPER.2002.4311755
Filename
4311755
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