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Published in:
2007 | OriginalPaper | Chapter
An Improved Particle Swarm Optimization Algorithm Applied to Economic Dispatch
Authors : Yuzeng Li, Long Long, Shaohua Zhang
Published in: Bio-Inspired Computational Intelligence and Applications
Publisher: Springer Berlin Heidelberg
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This paper proposes a new practical optimization method applied to the economic dispatch (ED) in a power system. The proposed method is based on an improved particle swarm optimization algorithm and considers some restrict conditions of ED in a practical power system. By reinitializing them with some currently optimal values during every cycle of iteration, this proposed method can make some inactivity particles to be always within a very small area having an optimal solution. The proposed method can avoid effectively the “premature” of the classic particle swarm optimization (PSO) algorithm due to improve the cognized capacity of the classic PSO, thereby it is beneficial to obtain some optimal global solutions. The simulation results show that proposed method has some excellent characteristics of higher quality calculation precision and better computation efficiency, compared with some other PSO methods.