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Heuristic Optimization of Virtual Inertia Control in Grid-Connected Wind Energy Conversion Systems for Frequency Support in a Restructured Environment

Author

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  • Anuoluwapo Oluwatobiloba Aluko

    (Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4041, KwaZulu-Natal, South Africa)

  • David George Dorrell

    (Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4041, KwaZulu-Natal, South Africa)

  • Rudiren Pillay Carpanen

    (Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4041, KwaZulu-Natal, South Africa)

  • Evan E. Ojo

    (Department of Electrical Power Engineering, Durban University of Technology, Durban 4000, KwaZulu-Natal, South Africa)

Abstract

In the work reported in this paper, a novel application of the artificial bee colony algorithm is used to implement a virtual inertia control strategy for grid-connected wind energy conversion systems. The proposed control strategy introduces a new heuristic optimization technique that uses the artificial bee colony (ABC) algorithm to calculate the optimal gain value of an additional derivative control loop added to the control scheme of the machine side converter in a wind energy system to enable wind farms to participate in frequency control as specified by recent grid codes. This helps to minimize the frequency deviations, reduce active power deviation in the system, and increase the penetration level of wind energy in power systems. The study was performed in a restructured power system environment. The proposed control scheme and its robustness were evaluated using load–frequency analysis for three real-life transaction scenarios that can occur in an interconnected open-energy market and the validation was carried out using eigenvalue analysis. The results in this study show that the optimal gain of the proposed controller reduces the frequency deviations and improves stability and overall performance of the system.

Suggested Citation

  • Anuoluwapo Oluwatobiloba Aluko & David George Dorrell & Rudiren Pillay Carpanen & Evan E. Ojo, 2020. "Heuristic Optimization of Virtual Inertia Control in Grid-Connected Wind Energy Conversion Systems for Frequency Support in a Restructured Environment," Energies, MDPI, vol. 13(3), pages 1-28, January.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:3:p:564-:d:312642
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    References listed on IDEAS

    as
    1. Thongchart Kerdphol & Fathin Saifur Rahman & Yasunori Mitani, 2018. "Virtual Inertia Control Application to Enhance Frequency Stability of Interconnected Power Systems with High Renewable Energy Penetration," Energies, MDPI, vol. 11(4), pages 1-16, April.
    2. Ismi Rosyiana Fitri & Jung-Su Kim & Hwachang Song, 2017. "High-Gain Disturbance Observer-Based Robust Load Frequency Control of Power Systems with Multiple Areas," Energies, MDPI, vol. 10(5), pages 1-21, April.
    3. Hassan Haes Alhelou & Mohamad-Esmail Hamedani-Golshan & Reza Zamani & Ehsan Heydarian-Forushani & Pierluigi Siano, 2018. "Challenges and Opportunities of Load Frequency Control in Conventional, Modern and Future Smart Power Systems: A Comprehensive Review," Energies, MDPI, vol. 11(10), pages 1-35, September.
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    Cited by:

    1. Anuoluwapo Aluko & Andrew Swanson & Leigh Jarvis & David Dorrell, 2022. "Modeling and Stability Analysis of Distributed Secondary Control Scheme for Stand-Alone DC Microgrid Applications," Energies, MDPI, vol. 15(15), pages 1-18, July.
    2. Raquel Villena-Ruiz & Andrés Honrubia-Escribano & Emilio Gómez-Lázaro, 2023. "Solar PV and Wind Power as the Core of the Energy Transition: Joint Integration and Hybridization with Energy Storage Systems," Energies, MDPI, vol. 16(6), pages 1-5, March.
    3. Anuoluwapo Aluko & Elutunji Buraimoh & Oluwafemi Emmanuel Oni & Innocent Ewean Davidson, 2022. "Advanced Distributed Cooperative Secondary Control of Islanded DC Microgrids," Energies, MDPI, vol. 15(11), pages 1-17, May.

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