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A Novel Fractional-Order Active Disturbance Rejection Load Frequency Control Based on An Improved Marine Predator Algorithm

Author

Listed:
  • Weichao He

    (School of Automation, Guangxi University of Science and Technology, Liuzhou 545616, China)

  • Yuemin Zheng

    (College of Artificial Intelligence, Nankai University, Tianjin 300350, China)

  • Jin Tao

    (College of Artificial Intelligence, Nankai University, Tianjin 300350, China)

  • Yujuan Zhou

    (School of Automation, Guangxi University of Science and Technology, Liuzhou 545616, China)

  • Jiayan Wen

    (School of Automation, Guangxi University of Science and Technology, Liuzhou 545616, China
    Research Center for Intelligent Cooperation and Cross-Application, Guangxi University of Science and Technology, Liuzhou 545616, China)

  • Qinglin Sun

    (College of Artificial Intelligence, Nankai University, Tianjin 300350, China)

Abstract

Load frequency control (LFC) serves as a crucial component of automatic generation control in renewable energy power systems. Its primary objective is to maintain a balance between the output power of generators and the load demand, thereby ensuring system frequency stability. However, integrating renewable energy sources into power systems brings forth several challenges, such as low power quality and poor system stability due to their uncontrollable nature. To enhance the response speed, stability, and disturbance rejection capabilities of LFC, a novel fractional-order active disturbance rejection controller (NFOADRC) based on an improved marine predator algorithm (IMPA) has been designed in this paper. By leveraging the wide frequency-response range and non-local memory of NFOADRC, a more precise prediction and compensation of rapid oscillations in the system can be achieved. Additionally, the IMPA can be utilized for efficient parameter tuning, enabling a more accurate adjustment of the controller. Subsequently, the combined application of these approaches can be applied to two-area interconnected power systems with a solar thermal power plant (STPP) and a five-area interconnected power system including a wind turbine generator (WTG), photovoltaic (PV) cells, hydro turbine, and gas turbine. The simulation results confirm that the proposed control strategy effectively minimizes the undershoot and overshoot of frequency deviation in the power system. It achieves a faster stabilization of the load frequency, leading to enhanced power quality.

Suggested Citation

  • Weichao He & Yuemin Zheng & Jin Tao & Yujuan Zhou & Jiayan Wen & Qinglin Sun, 2023. "A Novel Fractional-Order Active Disturbance Rejection Load Frequency Control Based on An Improved Marine Predator Algorithm," Sustainability, MDPI, vol. 15(13), pages 1-23, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:9853-:d:1175679
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    References listed on IDEAS

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    1. Tayyab Ali & Suheel Abdullah Malik & Amil Daraz & Muhammad Adeel & Sheraz Aslam & Herodotos Herodotou, 2023. "Load Frequency Control and Automatic Voltage Regulation in Four-Area Interconnected Power Systems Using a Gradient-Based Optimizer," Energies, MDPI, vol. 16(5), pages 1-27, February.
    2. Valle, João & Machicao, Jeaneth & Bruno, Odemir M., 2022. "Chaotical PRNG based on composition of logistic and tent maps using deep-zoom," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
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    4. Shuzheng Wang & Haiming Zhu & Shaowen Zhang, 2023. "Two-Stage Grid-Connected Frequency Regulation Control Strategy Based on Photovoltaic Power Prediction," Sustainability, MDPI, vol. 15(11), pages 1-21, June.
    5. Muhammad Majid Gulzar & Muhammad Iqbal & Sulman Shahzad & Hafiz Abdul Muqeet & Muhammad Shahzad & Muhammad Majid Hussain, 2022. "Load Frequency Control (LFC) Strategies in Renewable Energy-Based Hybrid Power Systems: A Review," Energies, MDPI, vol. 15(10), pages 1-23, May.
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