DocumentCode :
2503469
Title :
A comparison study on particle swarm and Evolutionary Particle Swarm Optimization using capacitor placement problem
Author :
Oo, Naing Win
Author_Institution :
Dept. of Electr., Curtin Univ. of Technol., Miri
fYear :
2008
fDate :
1-3 Dec. 2008
Firstpage :
1208
Lastpage :
1211
Abstract :
This paper reports the comparison study of particle swarm optimization (PSO) and evolutionary particle swarm optimization (EPSO) algorithms and their application to the optimal capacitor placement in radial power distribution system. Using JAVA language, software programs have been developed with PSO and 2 variant EPSO algorithms. The comparison study is then carried-out on the various versions of EPSO and PSO algorithms to analyze the performance of each algorithm in solving the capacitor placement problem. A power distribution system from Melaka, Malaysia has been used in this study. The results clearly indicate that EPSO is superior to PSO in finding the optimal solution and handling more complex, nonlinear objective functions due to its self-adaptability. However, EPSO is more computationally intense, requiring more computational time per iteration.
Keywords :
Java; particle swarm optimisation; power capacitors; power distribution; power system analysis computing; JAVA language; capacitor placement problem; computational time per iteration; evolutionary particle swarm optimization; radial power distribution system; software programs; Artificial intelligence; Capacitors; DC generators; Distributed computing; Particle swarm optimization; Power distribution; Power engineering and energy; Power engineering computing; Power generation economics; Power system economics; Capacitor Placement Problem; Evolutionary Computation; Particle Swarm Optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Conference, 2008. PECon 2008. IEEE 2nd International
Conference_Location :
Johor Bahru
Print_ISBN :
978-1-4244-2404-7
Electronic_ISBN :
978-1-4244-2405-4
Type :
conf
DOI :
10.1109/PECON.2008.4762650
Filename :
4762650
Link To Document :
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