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Greedy Sine-Cosine Non-Hierarchical Grey Wolf Optimizer for Solving Non-Convex Economic Load Dispatch Problems

Author

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  • Ali S. Alghamdi

    (Department of Electrical Engineering, College of Engineering, Majmaah University, Al-Majmaah 11952, Saudi Arabia)

Abstract

Economic load dispatch (ELD) provides significant benefits to the operation of the power system. It appears to be a complex nonconvex optimization problem subject to several equal and unequal constraints. The greedy sine-cosine nonhierarchical gray wolf optimizer (G-SCNHGWO) is introduced in this study to solve complex nonconvex ELD optimization problems efficiently and robustly. The sine and cosine functions assist the search agents of the grey wolf optimizer (GWO) algorithm in avoiding trapping in a local optimum. In addition, the greedy nonhierarchical concept is integrated into GWO to enrich the optimization power of the conventional GWO algorithm. Simulations are implemented to validate the capability of the suggested algorithm in solving the different ELD problems. According to the results, the algorithm demonstrates very suitable performance compared to other state-of-the-art methods.

Suggested Citation

  • Ali S. Alghamdi, 2022. "Greedy Sine-Cosine Non-Hierarchical Grey Wolf Optimizer for Solving Non-Convex Economic Load Dispatch Problems," Energies, MDPI, vol. 15(11), pages 1-19, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:11:p:3904-:d:823810
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    References listed on IDEAS

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    Cited by:

    1. Aokang Pang & Huijun Liang & Chenhao Lin & Lei Yao, 2023. "A Surrogate-Assisted Adaptive Bat Algorithm for Large-Scale Economic Dispatch," Energies, MDPI, vol. 16(2), pages 1-23, January.
    2. Taha Selim Ustun, 2022. "Power Systems Imitate Nature for Improved Performance Use of Nature-Inspired Optimization Techniques," Energies, MDPI, vol. 15(17), pages 1-2, August.

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