期刊
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
卷 32, 期 6, 页码 607-614出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ijepes.2009.11.017
关键词
Environmental/economic dispatch (EED); Multi-objective optimization; Particle swarm; Differential evolution; Equality constraint
To solve the highly constrained environmental/economic dispatch problem involving conflicting objectives, this paper presents a hybrid multi-objective optimization algorithm based on particle swarm optimization (PSO) and differential evolution (DE). In this algorithm, a PSO with time variant acceleration coefficients is designed to explore the entire search space, while a local version of DE is proposed to exploit the sub-space with sparse solutions. A crowing distance-based approach is introduced to assign the particles' leaders and to update the external archive. Moreover, a new technique for equality constraints is proposed to hurdle the unfeasible solutions directly. Finally, several optimization trials of the proposed algorithm are carried out on the IEEE 30-bus test system. Results demonstrate superiority of the proposed approach and confirm its potential to solve the multi-objective EED problem. (C) 2009 Elsevier Ltd. All rights reserved.
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