Biogeography based optimization for multi-constraint optimal power flow with emission and non-smooth cost function

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摘要

This paper presents biogeography based optimization (BBO) technique for solving constrained optimal power flow problems in power systems, considering valve point nonlinearities of generators. In this paper, the proposed algorithm has been tested in 9-bus and IEEE 30-bus systems under various simulated conditions. A comparison of simulation results reveals optimization efficacy of the proposed scheme over evolutionary programming (EP), genetic algorithm (GA), particle swarm optimization (PSO), mixed-integer particle swarm optimization (MIPSO) and sequential quadratic programming (SQP) used in MATPOWER for the global optimization of multi-constraint OPF problems.

论文关键词:Biogeography,Optimal power flow,Particle swarm optimization,Genetic algorithm,Mutation,Migration

论文评审过程:Available online 2 June 2010.

论文官网地址:https://doi.org/10.1016/j.eswa.2010.05.064