DocumentCode :
2102718
Title :
Hybrid Differential Evolution Particle Swarm Optimization Algorithm for Reactive Power Optimization
Author :
Wang, Shouzheng ; Ma, Lixin ; Sun, Dashuai
Author_Institution :
Dept. of Electr. Eng., Univ. of Shanghai for Sci. & Tech., Shanghai, China
fYear :
2010
fDate :
28-31 March 2010
Firstpage :
1
Lastpage :
4
Abstract :
Reactive power optimization is a mixed integer nonlinear programming problem where metaheuristics techniques have proven suitable for providing optimal solutions. In this paper, swarm and evolutionary algorithm have been applied for reactive power optimization. The objective of this nonlinear optimization is minimization of system losses and improvement of voltage profiles in a power system. A hybrid differential evolution particle swarm optimization algorithm is presented to obtain the global optimum. The proposed algorithm is implemented on the IEEE 14-bus system. To validate the effectiveness of the algorithm, the simulation results are compared with other optimization algorithms´. It is shown that the approach developed is feasible and efficient.
Keywords :
evolutionary computation; minimisation; particle swarm optimisation; reactive power; IEEE 14-bus system; hybrid differential evolution particle swarm optimization algorithm; metaheuristic techniques; mixed integer nonlinear programming; nonlinear optimization; power system voltage; reactive power optimization; system loss minimization; Hybrid power systems; Linear programming; Niobium; Particle swarm optimization; Power generation; Power system simulation; Quadratic programming; Reactive power; Sun; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-4812-8
Electronic_ISBN :
978-1-4244-4813-5
Type :
conf
DOI :
10.1109/APPEEC.2010.5448803
Filename :
5448803
Link To Document :
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