Title :
Implementation of GCPSO for Multi-objective VAr Planning with SVC and Its Comparison with GA and PSO
Author :
Farsangi, Malihe M. ; Nezamabadi-Pour, Hossein ; Lee, Kwang Y.
Author_Institution :
Shahid Bahonar Univ. of Kerman, Kerman
Abstract :
In this paper, Guaranteed Convergence Particle Swarm Optimization (GCPSO) Algorithm is used for VAr planning with the Static Var Compensators (SVC) in a large-scale power system. To enhance voltage stability, the planning problem is formulated as a multiobjective optimization problem for maximizing fuzzy performance indices. The multi-objective VAr planning problem is solved by the fuzzy GCPSO and the results are compared with those obtained by the Particle Swarm Optimization (PSO) and Genetic Algorithm
Keywords :
fuzzy set theory; genetic algorithms; particle swarm optimisation; power system planning; power system stability; static VAr compensators; PSO; SVC; fuzzy performance indices; genetic algorithm; guaranteed convergence particle swarm optimization; large- scale power system; multiobjective optimization problem; multiobjective var planning; particle swarm optimization; static var compensators; voltage stability; Convergence; Cost function; Genetic algorithms; Optimization methods; Particle swarm optimization; Power system planning; Power system stability; Reactive power; Static VAr compensators; Voltage; SVC; fuzzy performance indices; genetic algorithm; guaranteed convergence particle swarm optimization; multiobjective optimization; particle swarm optimization;
Conference_Titel :
Intelligent Systems Applications to Power Systems, 2007. ISAP 2007. International Conference on
Conference_Location :
Toki Messe, Niigata
Print_ISBN :
978-986-01-2607-5
Electronic_ISBN :
978-986-01-2607-5
DOI :
10.1109/ISAP.2007.4441632
