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Multiobjective Dynamic Multi-Swarm Particle Swarm Optimization for Environmental/Economic Dispatch Problem

  • Jane-Jing Liang
  • Wei-Xing Zhang
  • Bo-Yang Qu
  • Tie-Jun Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7389)

Abstract

This paper presents a new multiobjective particle swarm optimization (MOPSO) technique to solve environmental/economic dispatch (EED) problem. The EED problem is a non-linear constrained multiobjective optimization problem. The Multi-objective Dynamic Multi-Swarm Particle Swarm Optimizer (DMS-MO-PSO) proposed employs novel pbest and lbest updating criteria which are more suitable for solving multi-objective problems. In this work, the standard IEEE 30-bus six-generator test system is used and simulation results showed that the proposed approach is efficient and confirms its potential to solve the multiobjective EED problem.

Keywords

environmental/economic dispatch particle warm optimization multi-objective optimization evolutionary algorithm 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jane-Jing Liang
    • 1
  • Wei-Xing Zhang
    • 1
  • Bo-Yang Qu
    • 2
  • Tie-Jun Chen
    • 1
  1. 1.School of Electrical EngineeringZhengzhou UniverisityZhengzhouChina
  2. 2.School of Electric and Information EngineeringZhongyuan University of TechnologyZhengzhouChina

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