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Journal of Zhejiang University SCIENCE A 2005 Vol.6 No.5 P.420~427


Multiple objective particle swarm optimization technique for economic load dispatch

Author(s):  ZHAO Bo, CAO Yi-jia

Affiliation(s):  School of Electrical Engineering, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   yijiacao@zju.edu.cn

Key Words:  Economic load dispatch, Multi-objective optimization, Multi-objective particle swarm optimization

ZHAO Bo, CAO Yi-jia. Multiple objective particle swarm optimization technique for economic load dispatch[J]. Journal of Zhejiang University Science A, 2005, 6(5): 420~427.

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journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

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T1 - Multiple objective particle swarm optimization technique for economic load dispatch
A1 - ZHAO Bo
A1 - CAO Yi-jia
J0 - Journal of Zhejiang University Science A
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SP - 420
EP - 427
%@ 1673-565X
Y1 - 2005
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2005.A0420

A multi-objective particle swarm optimization (MOPSO) approach for multi-objective economic load dispatch problem in power system is presented in this paper. The economic load dispatch problem is a non-linear constrained multi-objective optimization problem. The proposed MOPSO approach handles the problem as a multi-objective problem with competing and non-commensurable fuel cost, emission and system loss objectives and has a diversity-preserving mechanism using an external memory (call “repository”) and a geographically-based approach to find widely different Pareto-optimal solutions. In addition, fuzzy set theory is employed to extract the best compromise solution. Several optimization runs of the proposed MOPSO approach were carried out on the standard IEEE 30-bus test system. The results revealed the capabilities of the proposed MOPSO approach to generate well-distributed Pareto-optimal non-dominated solutions of multi-objective economic load dispatch. Comparison with Multi-objective Evolutionary Algorithm (MOEA) showed the superiority of the proposed MOPSO approach and confirmed its potential for solving multi-objective economic load dispatch.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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