4.2 Article

Application of Biogeography-based Optimization for Solving Multi-objective Economic Emission Load Dispatch Problems

期刊

ELECTRIC POWER COMPONENTS AND SYSTEMS
卷 38, 期 3, 页码 340-365

出版社

TAYLOR & FRANCIS INC
DOI: 10.1080/15325000903273296

关键词

biogeography-based optimization; economic emission load dispatch; particle swarm optimization; non-dominated sorting genetic algorithm; valve-point loading

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This article presents a biogeography-based optimization algorithm to solve complex economic emission load dispatch problems of thermal generators of power systems. Different emission substances, such as NOX, SOX, and COX, are considered for case studies. The methodology considers the power demand equality constraint and the operating limit constraint during the time of solving economic emission load dispatch problems. Biogeography deals with the geographical distribution of biological organisms. Mathematical models of biogeography describe how species migrate from one habitat to another, how species arise, and how species become extinct. Here, it will be discussed how biogeography-based optimization can be used to solve economic emission load dispatch problems. This algorithm searches the global optimum mainly through two steps: migration and mutation. To show the advantages of the proposed algorithm, this algorithm has been applied for solving multi-objective economic emission load dispatch problems in a six-generator system considering NOX emission for different loading condition; in a three-generator system with NOX and SOX emission; in a six-generator system with SOX, NOX, and COX emissions; and in a six-generator system addressing both valve-point loading and NOX emission. Compared with the other existing techniques, the current proposal is found to be better in terms of quality of the compromising and individual solution obtained.

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