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Hybridization of Biogeography-Based: Optimization with Differential Evolution for Solving Optimal Power Flow Problems

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  • Provas Kumar Roy

    (Department of Electrical Engineering, Dr. B. C. Roy Engineering College, Durgapur, West Bengal, India)

  • Dharmadas Mandal

    (Department of Electrical Engineering, Birbhum Institute of Engineering and Technology, Suri, West Bengal, India)

Abstract

The aim of this paper is to evaluate a hybrid biogeography-based optimization approach based on the hybridization of biogeography-based optimization with differential evolution to solve the optimal power flow problem. The proposed method combines the exploration of differential evolution with the exploitation of biogeography-based optimization effectively to generate the promising candidate solutions. Simulation experiments are carried on standard 26-bus and IEEE 30-bus systems to illustrate the efficacy of the proposed approach. Results demonstrated that the proposed approach converged to promising solutions in terms of quality and convergence rate when compared with the original biogeography-based optimization and other population based optimization techniques like simple genetic algorithm, mixed integer genetic algorithm, particle swarm optimization and craziness based particle swarm optimization.

Suggested Citation

  • Provas Kumar Roy & Dharmadas Mandal, 2013. "Hybridization of Biogeography-Based: Optimization with Differential Evolution for Solving Optimal Power Flow Problems," International Journal of Energy Optimization and Engineering (IJEOE), IGI Global, vol. 2(3), pages 86-101, July.
    • Handle: RePEc:igg:jeoe00:v:2:y:2013:i:3:p:86-101
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