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Multi Criteria Frameworks Using New Meta-Heuristic Optimization Techniques for Solving Multi-Objective Optimal Power Flow Problems

Author

Listed:
  • Murtadha Al-Kaabi

    (Department of Electric Power Systems, Faculty of Energy, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania)

  • Virgil Dumbrava

    (Department of Electric Power Systems, Faculty of Energy, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania)

  • Mircea Eremia

    (Department of Electric Power Systems, Faculty of Energy, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania)

Abstract

This article develops two metaheuristics optimization techniques, Grey Wolf Optimizer (GWO) and Harris Hawks Optimization (HHO), to handle multi-objective optimal power flow (MOOPF) issues. Multi Objective GWO (MOGWO) and Multi Objective HHO (MOHHO) are the names of the developed techniques. By combining these optimization techniques with Pareto techniques, the non-dominated solution set can be obtained. These developed approaches are characterized by simplicity and have few control parameters. Fuel cost, emissions, real power losses, and voltage deviation were the four objective functions considered. The theories used to determine the best compromise solution and organize the Pareto front options are the fuzzy membership equation and the crowding distance approach, respectively. To validate and evaluate the performance of the presented techniques, two standard IEEE bus systems—30-bus and 57-bus power systems—were proposed. Bi, Tri, and Quad objective functions with 21 case studies are the types of objective functions and the scenarios that were applied in this paper. As compared to the results of the most recent optimization techniques documented in the literature, the comparative analysis results for the proposed methodologies demonstrated the superiority and robustness of MOGWO and MOHHO.

Suggested Citation

  • Murtadha Al-Kaabi & Virgil Dumbrava & Mircea Eremia, 2024. "Multi Criteria Frameworks Using New Meta-Heuristic Optimization Techniques for Solving Multi-Objective Optimal Power Flow Problems," Energies, MDPI, vol. 17(9), pages 1-39, May.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:9:p:2209-:d:1388528
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    References listed on IDEAS

    as
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    2. Zhang, Jingrui & Wang, Silu & Tang, Qinghui & Zhou, Yulu & Zeng, Tao, 2019. "An improved NSGA-III integrating adaptive elimination strategy to solution of many-objective optimal power flow problems," Energy, Elsevier, vol. 172(C), pages 945-957.
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    4. Niknam, Taher & Narimani, Mohammad rasoul & Jabbari, Masoud & Malekpour, Ahmad Reza, 2011. "A modified shuffle frog leaping algorithm for multi-objective optimal power flow," Energy, Elsevier, vol. 36(11), pages 6420-6432.
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