DocumentCode :
3105788
Title :
Particle Swarm Optimization for next generation Smart Grid outage analyses
Author :
Chen, Zhe ; Chegu, Ashwini
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Tennessee, Knoxville, TN, USA
fYear :
2012
fDate :
7-10 May 2012
Firstpage :
1
Lastpage :
6
Abstract :
Smart Grid realization has been an ultimate goal for the power research community. The goal makes it necessary to incorporate the advanced algorithm and new technologies to make the power system more robust and secure. In order to reduce system-wide blackouts, high order contingency has to be analyzed and extensive work has been performed on N-k contingency studies. This paper proposes to use the Artificial Intelligence algorithm Particle Swarm Optimization (PSO) in solving cascading power outage failure problems, identifying potential risk, quantifying fitness results, and providing important guidance for system operators and business owners to make informed decisions.
Keywords :
artificial intelligence; failure analysis; particle swarm optimisation; power system faults; power system reliability; smart power grids; N-k contingency study; PSO algorithm; artificial intelligence algorithm; cascading power outage failure problems; next generation smart grid outage analysis; particle swarm optimization; power research community; system-wide blackouts; Generators; Load flow; Particle swarm optimization; Power system faults; Power system restoration; Silicon; N-k contingency; blackouts; high order contingency; particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Transmission and Distribution Conference and Exposition (T&D), 2012 IEEE PES
Conference_Location :
Orlando, FL
ISSN :
2160-8555
Print_ISBN :
978-1-4673-1934-8
Electronic_ISBN :
2160-8555
Type :
conf
DOI :
10.1109/TDC.2012.6281650
Filename :
6281650
Link To Document :
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