4.7 Article

Multiobjective scatter search approach with new combination scheme applied to solve environmental/economic dispatch problem

期刊

ENERGY
卷 53, 期 -, 页码 14-21

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2013.02.045

关键词

Environmental/economic dispatch; Evolutionary algorithms; Scatter search

资金

  1. National Council of Scientific and Technologic Development of Brazil - CNPq [303963/2009-3/PQ, 478158/2009-3]
  2. Fundacao Araucaria [14/2008-416/09-15149]
  3. Pontifical Catholic University of Parana - PUCPR through the Institutional Program for Scientific Initiation Scholarships - PIBIC
  4. National Council of Scientific and Technologic Development of Brazil- CNPq through the Institutional Program for Scientific Initiation Scholarships - PIBIC

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The environmental/economic dispatch (EED) is an important daily optimization task in the operation of many power systems. It involves the simultaneous optimization of fuel cost and emission objectives which are conflicting ones. The EED problem can be formulated as a large-scale highly constrained nonlinear multiobjective optimization problem. In recent years, many metaheuristic optimization approaches have been reported in the literature to solve the multiobjective EED. In terms of metaheuristics, recently, scatter search approaches are receiving increasing attention, because of their potential to effectively explore a wide range of complex optimization problems. This paper proposes an improved scatter search (ISS) to deal with multiobjective EED problems based on concepts of Pareto dominance and crowding distance and a new scheme for the combination method. In this paper, we have considered the standard IEEE (Institute of Electrical and Electronics Engineers) 30-bus system with 6-generators and the results obtained by proposed ISS algorithm are compared with the other recently reported results in the literature. Simulation results demonstrate that the proposed ISS algorithm is a capable candidate in solving the multiobjective EED problems. (C) 2013 Elsevier Ltd. All rights reserved.

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