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Load Frequency Control Based on Gray Wolf Optimizer Algorithm for Modern Power Systems

Author

Listed:
  • Dao Huy Tuan

    (Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam)

  • Dao Trong Tran

    (Modeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam)

  • Van Nguyen Ngoc Thanh

    (Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam)

  • Van Van Huynh

    (Modeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam)

Abstract

The increasing complexity of modern power systems (MPSs), driven by the integration of renewable energy sources and multi-area configurations, demands robust and adaptive load frequency control (LFC) strategies. This paper proposes a novel approach to the LFC of the MPS by integrating a proportional–integral–derivative (PID) controller optimized using the gray wolf optimizer (GWO) algorithm. The effectiveness of the GWO-PID method is evaluated on multi-area power systems, including systems integrated with wind energy. The GWO-PID controller shows superior frequency stability, achieving deviations of 49.67 Hz, 49.68 Hz, 49.87 Hz, 49.87 Hz and 49.88 Hz for area 1 and area 2 of the two-area multisource MPS, as well as for area 1, area 2 and area 3 in the three-area multisource MPS. The results demonstrate significant improvements in frequency stabilization, reduced oscillations and enhanced steady-state accuracy compared to traditional optimization techniques. This study emphasizes the scalability and adaptability of the proposed method to changing load conditions and complexity of the MPSs, providing a potential solution to ensure stability and reliability for the MPSs.

Suggested Citation

  • Dao Huy Tuan & Dao Trong Tran & Van Nguyen Ngoc Thanh & Van Van Huynh, 2025. "Load Frequency Control Based on Gray Wolf Optimizer Algorithm for Modern Power Systems," Energies, MDPI, vol. 18(4), pages 1-17, February.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:4:p:815-:d:1587546
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    References listed on IDEAS

    as
    1. Ahmed Fathy & Ahmed Kassem & Zaki A. Zaki, 2022. "A Robust Artificial Bee Colony-Based Load Frequency Control for Hydro-Thermal Interconnected Power System," Sustainability, MDPI, vol. 14(20), pages 1-13, October.
    2. Désiré D. Rasolomampionona & Michał Połecki & Krzysztof Zagrajek & Wiktor Wróblewski & Marcin Januszewski, 2024. "A Comprehensive Review of Load Frequency Control Technologies," Energies, MDPI, vol. 17(12), pages 1-74, June.
    3. Vincent N. Ogar & Sajjad Hussain & Kelum A. A. Gamage, 2023. "Load Frequency Control Using the Particle Swarm Optimisation Algorithm and PID Controller for Effective Monitoring of Transmission Line," Energies, MDPI, vol. 16(15), pages 1-17, August.
    4. Xinghua Liu & Siwei Qiao & Zhiwei Liu, 2023. "A Survey on Load Frequency Control of Multi-Area Power Systems: Recent Challenges and Strategies," Energies, MDPI, vol. 16(5), pages 1-22, February.
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