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
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