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Black Widow Optimization-Based Optimal PI-Controlled Wind Turbine Emulator

Author

Listed:
  • K. Premkumar

    (Department of EEE, Rajalakshmi Engineering College, Tamilnadu 602105, India)

  • M. Vishnupriya

    (Department of ECE, Saveetha School of Engineering, Tamilnadu 602105, India)

  • Thanikanti Sudhakar Babu

    (Institute of Power Engineering, Department of Electrical Power Engineering, Universiti Tenaga National, Selangor 43000, Malaysia)

  • B. V. Manikandan

    (Department of EEE, Mepco Schlenk Engineering College, Tamilnadu 626005, India)

  • T. Thamizhselvan

    (Department of EEE, Rajalakshmi Engineering College, Tamilnadu 602105, India)

  • A. Nazar Ali

    (Department of EEE, Rajalakshmi Engineering College, Tamilnadu 602105, India)

  • Md. Rabiul Islam

    (School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, Australia)

  • Abbas Z. Kouzani

    (School of Engineering, Deakin University, Geelong, VIC 3216, Australia)

  • M. A. Parvez Mahmud

    (School of Engineering, Deakin University, Geelong, VIC 3216, Australia)

Abstract

In this article, the parameters of the proportional-integral (PI) controller of the wind turbine (WT) emulator, i.e., proportional and integral gain of the PI controller, are optimized using a black widow optimization algorithm (BWOA). The proposed system is developed and analyzed using MATLAB/Simulink environment. The performance of the BWOA optimized PI controller is compared with a BAT algorithm, particle swarm optimization, and genetic algorithm optimized PI controller to measure the effectiveness of the proposed control system. The developed system is tested for different operating conditions such as static wind speed settings, static pitch angle conditions, step-change in wind speed settings, and step-change in pitch angle settings. Finally, the proposed system is realized in real-time by hardware experimentations. The results of the experimentation are compared with simulation results as well. The presented simulation and hardware result shows good agreement, which confirms the effectiveness of the proposed method. Thereby, the proposed optimization-based PI-controlled wind emulator can be recommended for emulating the characteristics of any type of WT with a low-cost system.

Suggested Citation

  • K. Premkumar & M. Vishnupriya & Thanikanti Sudhakar Babu & B. V. Manikandan & T. Thamizhselvan & A. Nazar Ali & Md. Rabiul Islam & Abbas Z. Kouzani & M. A. Parvez Mahmud, 2020. "Black Widow Optimization-Based Optimal PI-Controlled Wind Turbine Emulator," Sustainability, MDPI, vol. 12(24), pages 1-19, December.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:24:p:10357-:d:460452
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    References listed on IDEAS

    as
    1. Martinez, Fernando & Herrero, L. Carlos & de Pablo, Santiago, 2014. "Open loop wind turbine emulator," Renewable Energy, Elsevier, vol. 63(C), pages 212-221.
    2. Kan, Cihangir & Devrim, Yilser & Eryilmaz, Serkan, 2020. "On the theoretical distribution of the wind farm power when there is a correlation between wind speed and wind turbine availability," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    3. Wollz, Danilo Henrique & da Silva, Sergio Augusto Oliveira & Sampaio, Leonardo Poltronieri, 2020. "Real-time monitoring of an electronic wind turbine emulator based on the dynamic PMSG model using a graphical interface," Renewable Energy, Elsevier, vol. 155(C), pages 296-308.
    4. Aravind Chellachi Kathiresan & Jeyaraj PandiaRajan & Asokan Sivaprakash & Thanikanti Sudhakar Babu & Md. Rabiul Islam, 2020. "An Adaptive Feed-Forward Phase Locked Loop for Grid Synchronization of Renewable Energy Systems under Wide Frequency Deviations," Sustainability, MDPI, vol. 12(17), pages 1-15, August.
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    Cited by:

    1. Maheshwari, Zeel & Kengne, Kamgang & Bhat, Omkar, 2023. "A comprehensive review on wind turbine emulators," Renewable and Sustainable Energy Reviews, Elsevier, vol. 180(C).
    2. Thirunavukkarasu, M. & Sawle, Yashwant & Lala, Himadri, 2023. "A comprehensive review on optimization of hybrid renewable energy systems using various optimization techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).

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