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Solution of Optimal Power Flow Using Non-Dominated Sorting Multi Objective Based Hybrid Firefly and Particle Swarm Optimization Algorithm

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  • Abdullah Khan

    (Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Malaysia
    Advanced Lightning, Power and Energy Research, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Malaysia)

  • Hashim Hizam

    (Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Malaysia
    Advanced Lightning, Power and Energy Research, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Malaysia)

  • Noor Izzri Abdul-Wahab

    (Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Malaysia
    Advanced Lightning, Power and Energy Research, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Malaysia)

  • Mohammad Lutfi Othman

    (Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Malaysia
    Advanced Lightning, Power and Energy Research, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Malaysia)

Abstract

In this paper, a multi-objective hybrid firefly and particle swarm optimization (MOHFPSO) was proposed for different multi-objective optimal power flow (MOOPF) problems. Optimal power flow (OPF) was formulated as a non-linear problem with various objectives and constraints. Pareto optimal front was obtained by using non-dominated sorting and crowding distance methods. Finally, an optimal compromised solution was selected from the Pareto optimal set by applying an ideal distance minimization method. The efficiency of the proposed MOHFPSO technique was tested on standard IEEE 30-bus and IEEE 57-bus test systems with various conflicting objectives. Simulation results were also compared with non-dominated sorting based multi-objective particle swarm optimization (MOPSO) and different optimization algorithms reported in the current literature. The achieved results revealed the potential of the proposed algorithm for MOOPF problems.

Suggested Citation

  • Abdullah Khan & Hashim Hizam & Noor Izzri Abdul-Wahab & Mohammad Lutfi Othman, 2020. "Solution of Optimal Power Flow Using Non-Dominated Sorting Multi Objective Based Hybrid Firefly and Particle Swarm Optimization Algorithm," Energies, MDPI, vol. 13(16), pages 1-24, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:16:p:4265-:d:400354
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    References listed on IDEAS

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