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Solving OPF Problems using Biogeography Based and Grey Wolf Optimization Techniques

Author

Listed:
  • Kingsuk Majumdar

    (Dr. B. C. Roy Engineering College, Durgapur, India)

  • Puja Das

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

  • Provas Kumar Roy

    (Kalyani Government Engineering College, Kalyani, India)

  • Subrata Banerjee

    (Department of Electrical Engineering, National Institute of Technology, Durgapur, India)

Abstract

This paper presents biogeography-based optimization (BBO) and grey wolf Optimization(GWO) for solving the multi-constrained optimal power flow (OPF) problems in the power system. In this paper, the proposed algorithms have been tested in 9-bus system under various conditions along with IEEE 30 bus test system. A comparison of simulation results reveals optimization efficacy of the proposed scheme over evolutionary programming (EP), genetic algorithm (GA), mixed-integer particle swarm optimization (MIPSO) for the global optimization of multi-constraint OPF problems. It is observed that GWO is far better in comparison to other listed optimization techniques and can be used for aforesaid problems with high efficiency.

Suggested Citation

  • Kingsuk Majumdar & Puja Das & Provas Kumar Roy & Subrata Banerjee, 2017. "Solving OPF Problems using Biogeography Based and Grey Wolf Optimization Techniques," International Journal of Energy Optimization and Engineering (IJEOE), IGI Global, vol. 6(3), pages 55-77, July.
    • Handle: RePEc:igg:jeoe00:v:6:y:2017:i:3:p:55-77
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    Cited by:

    1. Mengqi Zhao & Xiaoling Wang & Jia Yu & Lei Bi & Yao Xiao & Jun Zhang, 2020. "Optimization of Construction Duration and Schedule Robustness Based on Hybrid Grey Wolf Optimizer with Sine Cosine Algorithm," Energies, MDPI, vol. 13(1), pages 1-17, January.
    2. Mohammed Hamouda Ali & Ali M. El-Rifaie & Ahmed A. F. Youssef & Vladimir N. Tulsky & Mohamed A. Tolba, 2023. "Techno-Economic Strategy for the Load Dispatch and Power Flow in Power Grids Using Peafowl Optimization Algorithm," Energies, MDPI, vol. 16(2), pages 1-29, January.

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