DocumentCode :
3219067
Title :
Reliability evaluation of composite power systems using parallel genetic algorithms: Some conceptual and simulation studies
Author :
Wang, Lingfeng ; Singh, Chanan
Author_Institution :
Electr. & Comput. Eng. Dept., Texas A&M Univ., College Station, TX
fYear :
2009
fDate :
15-18 March 2009
Firstpage :
1
Lastpage :
7
Abstract :
Genetic algorithm (GA) has shown its promise in dealing with reliability evaluation of complex power systems. However, it may be computationally expensive due to its stochastic search mechanism coupled with the problem complexity. Especially, when each system state needs a load flow calculation to determine its status, the reliability evaluation process may take a long time. Parallel computation is being more widely used because of the increasing computing capability. In this paper, the parallel computation mechanism is incorporated into the GA in order to increase its computational efficiency. Several parallel computation topologies are introduced, and conceptual comparisons with respect to parallel Monte Carlo simulation are detailed. Also some preliminary numerical studies are carried out to examine their performance in terms of computing cost and solution quality.
Keywords :
genetic algorithms; load flow; power system reliability; stochastic processes; Monte Carlo simulation; composite power system reliability evaluation; load flow calculation; parallel computation; parallel genetic algorithms; stochastic search mechanism; Computational efficiency; Computational modeling; Concurrent computing; Costs; Genetic algorithms; Load flow; Power system reliability; Power system simulation; Stochastic processes; Topology; Genetic algorithm; Monte Carlo simulation; computational efficiency; hash table; loss of load probability; master-slave parallelization; parallel computation; reliability evaluation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Systems Conference and Exposition, 2009. PSCE '09. IEEE/PES
Conference_Location :
Seattle, WA
Print_ISBN :
978-1-4244-3810-5
Electronic_ISBN :
978-1-4244-3811-2
Type :
conf
DOI :
10.1109/PSCE.2009.4840222
Filename :
4840222
Link To Document :
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