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Robust Load Frequency Control Schemes in Power System Using Optimized PID and Model Predictive Controllers

Author

Listed:
  • Komboigo Charles

    (Electrical and Electronics Engineering Department, University of the Ryukyus, Okinawa 903-0213, Japan)

  • Naomitsu Urasaki

    (Electrical and Electronics Engineering Department, University of the Ryukyus, Okinawa 903-0213, Japan)

  • Tomonobu Senjyu

    (Electrical and Electronics Engineering Department, University of the Ryukyus, Okinawa 903-0213, Japan)

  • Mohammed Elsayed Lotfy

    (Electrical and Electronics Engineering Department, University of the Ryukyus, Okinawa 903-0213, Japan
    Electrical Power and Machines Department, Zagazig University, Zagazig 44519, Egypt)

  • Lei Liu

    (Electrical and Electronics Engineering Department, University of the Ryukyus, Okinawa 903-0213, Japan)

Abstract

Robust control methodology for two-area load frequency control model is proposed in this paper. The paper presents a comparative study between the performance of model predictive controller (MPC) and optimized proportional–integral–derivative (PID) controller on different systems. An objective function derived from settling time, percentage overshoot and percentage undershoot is minimized to obtain the gains of the PID controller. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to tune the parameters of the PID controller through performance optimization of the system. System performance characteristics were compared to another controller designed based on MPC. Detailed comparison was performed between the performances of the MPC and optimized PID. The effectiveness and robustness of the proposed schemes were verified by the numerical simulation in MATLAB environment under different scenarios such as load and parameters variations. Moreover, the pole-zero map of each proposed approach is presented to investigate their stability.

Suggested Citation

  • Komboigo Charles & Naomitsu Urasaki & Tomonobu Senjyu & Mohammed Elsayed Lotfy & Lei Liu, 2018. "Robust Load Frequency Control Schemes in Power System Using Optimized PID and Model Predictive Controllers," Energies, MDPI, vol. 11(11), pages 1-18, November.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:11:p:3070-:d:181275
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    References listed on IDEAS

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    1. Mohammed Elsayed Lotfy & Tomonobu Senjyu & Mohammed Abdel-Fattah Farahat & Amal Farouq Abdel-Gawad & Atsuhi Yona, 2017. "A Frequency Control Approach for Hybrid Power System Using Multi-Objective Optimization," Energies, MDPI, vol. 10(1), pages 1-22, January.
    2. Jun Yang & Zhili Zeng & Yufei Tang & Jun Yan & Haibo He & Yunliang Wu, 2015. "Load Frequency Control in Isolated Micro-Grids with Electrical Vehicles Based on Multivariable Generalized Predictive Theory," Energies, MDPI, vol. 8(3), pages 1-20, March.
    3. Sa-ngawong, Nattapol & Ngamroo, Issarachai, 2015. "Intelligent photovoltaic farms for robust frequency stabilization in multi-area interconnected power system based on PSO-based optimal Sugeno fuzzy logic control," Renewable Energy, Elsevier, vol. 74(C), pages 555-567.
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    Cited by:

    1. Fei Zhao & Jinsha Yuan & Ning Wang & Zhang Zhang & Helong Wen, 2019. "Secure Load Frequency Control of Smart Grids under Deception Attack: A Piecewise Delay Approach," Energies, MDPI, vol. 12(12), pages 1-15, June.
    2. Jun Deng & Jun Suo & Jing Yang & Shutao Peng & Fangde Chi & Tong Wang, 2019. "Adaptive Damping Control Strategy of Wind Integrated Power System," Energies, MDPI, vol. 12(1), pages 1-18, January.
    3. Wadi, Mohammed & Shobole, Abdulfetah & Elmasry, Wisam & Kucuk, Ismail, 2024. "Load frequency control in smart grids: A review of recent developments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    4. Yukun Dong & Yu Zhang & Fubin Liu & Zhengjun Zhu, 2022. "Research on an Optimization Method for Injection-Production Parameters Based on an Improved Particle Swarm Optimization Algorithm," Energies, MDPI, vol. 15(8), pages 1-18, April.
    5. Min-Rong Chen & Guo-Qiang Zeng & Yu-Xing Dai & Kang-Di Lu & Da-Qiang Bi, 2018. "Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid," Energies, MDPI, vol. 12(1), pages 1-21, December.

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