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Using Group Predictive Voltage and Frequency Regulators of Distributed Generation Plants in Cyber-Physical Power Supply Systems

Author

Listed:
  • Yuri Bulatov

    (Department of Energy, Bratsk State University, 665730 Bratsk, Russia)

  • Andrey Kryukov

    (Department of Electric Power Engineering of Transport, Irkutsk State Transport University, 664074 Irkutsk, Russia
    Department of Power Supply and Electrical Engineering, Irkutsk National Research Technical University, 664074 Irkutsk, Russia)

  • Konstantin Suslov

    (Department of Power Supply and Electrical Engineering, Irkutsk National Research Technical University, 664074 Irkutsk, Russia
    Department of Energy, Transbaikal State University, 672039 Chita, Russia)

Abstract

The widespread use of distributed generation (DG) plants in cyber-physical power supply systems (CPPSS) requires solving the complex problem of setting their regulators. The presented study aimed to determine the performance of the group predictive voltage and frequency regulators of DG plants in CPPSS. These studies were conducted in the MatLab environment on the CPPSS models with gas turbine units and with a small-scale hydroelectric power plant. The proposed method for tuning group predictive regulators makes it possible to improve the quality control indices. The research has established that with an additional load connected, the maximum voltage dip is reduced by a factor of 3.5 compared to conventional control regulators. In addition, the time of a transient process for the generator rotor speed is decreased by a factor of 3. In the case of a short-term short circuit, predictive regulators can reduce the time of the transient process by a factor of 1.5 and the overshoot by more than 2 times. The simulation results have confirmed the efficiency of group predictive regulators when used in DG plants, i.e., improvement of the quality of control processes in various operating modes.

Suggested Citation

  • Yuri Bulatov & Andrey Kryukov & Konstantin Suslov, 2022. "Using Group Predictive Voltage and Frequency Regulators of Distributed Generation Plants in Cyber-Physical Power Supply Systems," Energies, MDPI, vol. 15(4), pages 1-20, February.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:4:p:1253-:d:745128
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    References listed on IDEAS

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    1. Ellabban, Omar & Abu-Rub, Haitham & Blaabjerg, Frede, 2014. "Renewable energy resources: Current status, future prospects and their enabling technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 748-764.
    2. Ehsan, Ali & Yang, Qiang, 2018. "Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques," Applied Energy, Elsevier, vol. 210(C), pages 44-59.
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    Cited by:

    1. Hiramani Shukla & Srete Nikolovski & More Raju & Ankur Singh Rana & Pawan Kumar, 2022. "A Particle Swarm Optimization Technique Tuned TID Controller for Frequency and Voltage Regulation with Penetration of Electric Vehicles and Distributed Generations," Energies, MDPI, vol. 15(21), pages 1-32, November.
    2. Andrey Kryukov & Konstantin Suslov & Pavel Ilyushin & Azat Akhmetshin, 2023. "Parameter Identification of Asynchronous Load Nodes," Energies, MDPI, vol. 16(4), pages 1-18, February.
    3. Bulatov, Yu N. & Kryukov, A.V. & Suslov, K.V., 2022. "Group predictive voltage and frequency regulators for small hydro power plant in the context of low power quality," Renewable Energy, Elsevier, vol. 200(C), pages 571-578.

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