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Optimal Model Predictive Control for Virtual Inertia Control of Autonomous Microgrids

Author

Listed:
  • Amr Saleh

    (Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt)

  • Hany M. Hasanien

    (Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt)

  • Rania A. Turky

    (Electrical Engineering Department, Faculty of Engineering and Technology, Future University in Egypt, Cairo 11835, Egypt)

  • Balgynbek Turdybek

    (Department of Electrical Engineering, Superior Polytechnic School of Linares, University of Jaén, 23700 Linares, Spain)

  • Mohammed Alharbi

    (Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia)

  • Francisco Jurado

    (Department of Electrical Engineering, Superior Polytechnic School of Linares, University of Jaén, 23700 Linares, Spain)

  • Walid A. Omran

    (Faculty of Engineering and Materials Science, German University in Cairo, Cairo 16482, Egypt)

Abstract

For the time being, renewable energy source (RES) penetration has significantly increased in power networks, particularly in microgrids. The overall system inertia is dramatically decreased by replacing traditional synchronous machines with RES. This negatively affects the microgrid dynamics under uncertainties, lowering the microgrid frequency stability, specifically in the islanded mode of operation. Therefore, this work aims to enhance the islanded microgrid frequency resilience using the virtual inertia frequency control concept. Additionally, optimal model predictive control (MPC) is employed in the virtual inertial control model. The optimum design of the MPC is attained using an optimization algorithm, the African Vultures Optimization Algorithm (AVOA). To certify the efficacy of the proposed controller, the AVOA-based MPC is compared with a conventional proportional–integral (PI) controller that is optimally designed using various optimization techniques. The actual data of RES is utilized, and a random load power pattern is applied to achieve practical simulation outcomes. Additionally, the microgrid paradigm contains battery energy storage (BES) units for enhancing the islanded microgrid transient stability. The simulation findings show the effectiveness of AVOA-based MPC in improving the microgrid frequency resilience. Furthermore, the results secure the role of BES in improving transient responses in the time domain simulations. The simulation outcomes are obtained using MATLAB software.

Suggested Citation

  • Amr Saleh & Hany M. Hasanien & Rania A. Turky & Balgynbek Turdybek & Mohammed Alharbi & Francisco Jurado & Walid A. Omran, 2023. "Optimal Model Predictive Control for Virtual Inertia Control of Autonomous Microgrids," Sustainability, MDPI, vol. 15(6), pages 1-25, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5009-:d:1094612
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    References listed on IDEAS

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    1. Thongchart Kerdphol & Masayuki Watanabe & Yasunori Mitani & Veena Phunpeng, 2019. "Applying Virtual Inertia Control Topology to SMES System for Frequency Stability Improvement of Low-Inertia Microgrids Driven by High Renewables," Energies, MDPI, vol. 12(20), pages 1-16, October.
    2. Nelson, James R. & Johnson, Nathan G., 2020. "Model predictive control of microgrids for real-time ancillary service market participation," Applied Energy, Elsevier, vol. 269(C).
    3. Basma Salah & Hany M. Hasanien & Fadia M. A. Ghali & Yasser M. Alsayed & Shady H. E. Abdel Aleem & Adel El-Shahat, 2022. "African Vulture Optimization-Based Optimal Control Strategy for Voltage Control of Islanded DC Microgrids," Sustainability, MDPI, vol. 14(19), pages 1-26, September.
    4. Amr Saleh & Walid A. Omran & Hany M. Hasanien & Marcos Tostado-Véliz & Abdulaziz Alkuhayli & Francisco Jurado, 2022. "Manta Ray Foraging Optimization for the Virtual Inertia Control of Islanded Microgrids Including Renewable Energy Sources," Sustainability, MDPI, vol. 14(7), pages 1-19, April.
    5. Ruiming Liu & Shengtie Wang & Guangchen Liu & Sufang Wen & Jianwei Zhang & Yuechao Ma, 2022. "An Improved Virtual Inertia Control Strategy for Low Voltage AC Microgrids with Hybrid Energy Storage Systems," Energies, MDPI, vol. 15(2), pages 1-21, January.
    6. Hyung-Joon Kim & Mun-Kyeom Kim, 2019. "Multi-Objective Based Optimal Energy Management of Grid-Connected Microgrid Considering Advanced Demand Response," Energies, MDPI, vol. 12(21), pages 1-28, October.
    7. Gaber Magdy & Abualkasim Bakeer & Morsy Nour & Eduard Petlenkov, 2020. "A New Virtual Synchronous Generator Design Based on the SMES System for Frequency Stability of Low-Inertia Power Grids," Energies, MDPI, vol. 13(21), pages 1-17, October.
    8. 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.
    9. Vjatseslav Skiparev & Ram Machlev & Nilanjan Roy Chowdhury & Yoash Levron & Eduard Petlenkov & Juri Belikov, 2021. "Virtual Inertia Control Methods in Islanded Microgrids," Energies, MDPI, vol. 14(6), pages 1-20, March.
    10. Reza Alayi & Farhad Zishan & Seyed Reza Seyednouri & Ravinder Kumar & Mohammad Hossein Ahmadi & Mohsen Sharifpur, 2021. "Optimal Load Frequency Control of Island Microgrids via a PID Controller in the Presence of Wind Turbine and PV," Sustainability, MDPI, vol. 13(19), pages 1-14, September.
    11. Thongchart Kerdphol & Fathin S. Rahman & Yasunori Mitani & Komsan Hongesombut & Sinan Küfeoğlu, 2017. "Virtual Inertia Control-Based Model Predictive Control for Microgrid Frequency Stabilization Considering High Renewable Energy Integration," Sustainability, MDPI, vol. 9(5), pages 1-21, May.
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    Cited by:

    1. Fauzan Hanif Jufri & Jaesung Jung & Budi Sudiarto & Iwa Garniwa, 2023. "Development of Virtual Inertia Control with State-of-Charge Recovery Strategy Using Coordinated Secondary Frequency Control for Optimized Battery Capacity in Isolated Low Inertia Grid," Energies, MDPI, vol. 16(14), pages 1-22, July.
    2. Farhad Amiri & Mohsen Eskandari & Mohammad Hassan Moradi, 2023. "Virtual Inertia Control in Autonomous Microgrids via a Cascaded Controller for Battery Energy Storage Optimized by Firefly Algorithm and a Comparison Study with GA, PSO, ABC, and GWO," Energies, MDPI, vol. 16(18), pages 1-22, September.
    3. Plamen Stanchev & Gergana Vacheva & Nikolay Hinov, 2023. "Evaluation of Voltage Stability in Microgrid-Tied Photovoltaic Systems," Energies, MDPI, vol. 16(13), pages 1-20, June.

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