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Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2005, Vol. 6 Issue (5): 420-427    DOI: 10.1631/jzus.2005.A0420
Computer & Information Science     
Multiple objective particle swarm optimization technique for economic load dispatch
ZHAO Bo, CAO Yi-jia
School of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
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Abstract  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 鈥渞epository鈥? 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.

Key wordsEconomic load dispatch      Multi-objective optimization      Multi-objective particle swarm optimization     
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Cite this article:

ZHAO Bo, CAO Yi-jia. Multiple objective particle swarm optimization technique for economic load dispatch. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2005, 6(5): 420-427.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2005.A0420     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2005/V6/I5/420

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