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Solving economic emission load dispatch problems using hybrid differential evolution
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DOI：10.1016/j.asoc.2010.09.008.png)
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摘要
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This paper presents the combination of differential evolution (DE) and Biogeography-based Optimization (BBO) algorithm to solve complex economic emission load dispatch (EELD) problems of thermal generators of power systems. Emission substances like NOX, SOX, COX, power demand equality constraint and operating limit constraint are considered here. Differential evolution (DE) is one of the very fast and robust, accurate evolutionary algorithms for global optimization and solution of EELD problems. Biogeography-based Optimization (BBO) is another new biogeography inspired algorithm. Biogeography deals with the geographical distribution of different biological species. This algorithm searches for the global optimum mainly through two steps: migration and mutation. In this paper the combination of DE and BBO (DE/BBO) is proposed to accelerate the convergence speed of both the algorithm and to improve solution quality. To show the advantages of the proposed algorithm, it has been applied for solving multiobjective EELD problems in a 3 generator system with NOX and SOX emission, in a 6 generators system considering NOX emission, in a 6 generator system addressing both valve-point loading and NOX emission. The current proposal is found better in terms of quality of the compromising and individual solution obtained. (C) 2010 Elsevier B.V. All rights reserved.
Keyword:
Biogeography-based Optimization
Differential evolution
Economic emission load dispatch
Particle swarm optimization
Valve-point loading
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6.6
论文数:
1.4W
被引数:
4.8W
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