Artificial neural networks in power system restoration

Power system restoration (PSR) has been a subject of study for many 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....

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Published in:IEEE transactions on power delivery 2003-10, Vol.18 (4), p.1181-1186
Main Authors: Bretas, A.S., Phadke, A.G.
Format: Article
Language:English
Subjects:
Artificial neural networks
Circuit breakers
Guidelines
Intelligent networks
Medical services
Power system analysis computing
Power system protection
Power system restoration
Signal restoration
Switching circuits
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description Power system restoration (PSR) has been a subject of study for many 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 (ANNs). 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.
doi_str_mv 10.1109/TPWRD.2003.817500
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subjects Artificial neural networks
Circuit breakers
Guidelines
Intelligent networks
Medical services
Power system analysis computing
Power system protection
Power system restoration
Signal restoration
Switching circuits
title Artificial neural networks in power system restoration
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