| Multiple objective particle swarm optimization technique for economic load dispatch |
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| 作者姓名： | 赵波 曹一家 |
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| 作者单位： | School of Electrical Engineering，Zhejiang University，Hangzhou 310027，China，School of Electrical Engineering，Zhejiang University，Hangzhou 310027，China |
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| 摘 要： | INTRODUCTION The conventional economic load dispatch prob-lem of power generation involves allocation of power generation to different thermal units to minimize the operating cost subject to diverse equality and ine-quality constraints of the power system. This makes the economic load dispatch problem a large-scale highly non-linear constrained optimization problem. However, as a result of public awareness of envi-ronmental protection, diverse emission compliance strategies have emerged (…
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| 关 键 词： | 电力系统 经济载荷分配 多目标粒子集合 优化分配 |
Multiple objective particle swarm optimization technique for economic load dispatch |
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| Zhao Bo,Cao Yi-jia.Multiple objective particle swarm optimization technique for economic load dispatch[J].Journal of Zhejiang University Science,2005,6(5):420-427. |
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| Authors: | Zhao Bo Cao Yi-jia |
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| Institution: | (1) School of Electrical Engineering, Zhejiang University, 310027 Hangzhou, 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 "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. Com parison 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. |
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| Keywords: | Economic load dispatch Multi-objective optimization Multi-objective particle swarm optimization |
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