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An Online Archimedes Optimization Algorithm Identifier-Controlled Adaptive Modified Virtual Inertia Control for Microgrids

Author

Listed:
  • Asmaa Fawzy

    (Department of Electrical Engineering, Faculty of Energy Engineering, Aswan University, Aswan 81528, Egypt)

  • Youssef Mobarak

    (Department of Electrical Engineering, Faculty of Energy Engineering, Aswan University, Aswan 81528, Egypt
    Faculty of Engineering, King Abdulaziz University, Rabigh 21911, Saudi Arabia)

  • Dina S. Osheba

    (Department of Electrical Engineering, Faculty of Engineering, Menoufia University, Shebin El Kom 32511, Egypt)

  • Mahmoud G. Hemeida

    (Minia Higher Institute of Engineering, Minya 61111, Egypt)

  • Tomonobu Senjyu

    (Department of Electrical and Electronics Engineering, Faculty of Engineering, University of the Ryukyus, Nishihara 903-0213, Japan)

  • Mohamed Roshdy

    (Department of Electrical Engineering, Faculty of Energy Engineering, Aswan University, Aswan 81528, Egypt)

Abstract

Single widespread employment of renewable energy sources (RESs) contributes to the shortage in the inertia of the microgrid (MG). After this, frequency stability may regress as a result of power imbalance or minor load fluctuations. This paper proposes an explicit adaptive modified virtual inertia control (VIC) based on an online Archimedes optimization algorithm (AOA) identifier for MG containing thermal, wind, and solar photovoltaic power plants. The Rung Kutta approach is used to construct the proposed online identifier, which acts as a model of the MG. AOA predicts the coefficients of the online identifier based on the input and output of MG to mimic the frequency deviation of the MG online. AOA estimates online the inertia and damping coefficients of the VIC system with an energy storage device based on online AOA identifier coefficients. The frequency deviation of the MG based on the proposed explicit adaptive modified VIC is compared with the conventional VIC based on fixed parameters and the VIC system based on optimal parameters using AOA offline under mutation in loads, weather-dependent input, and MG parameters using MATLAB/Simulink software. Furthermore, the proposed explicit adaptive modified VIC based on an online AOA identifier is evaluated with the adaptive VIC system based on fuzzy logic control, which adjusts only the inertial gain online. The simulation results demonstrate the capabilities of the proposed explicit adaptive modified VIC to improve the frequency stability and enhance low-inertia islanded MGs with RESs.

Suggested Citation

  • Asmaa Fawzy & Youssef Mobarak & Dina S. Osheba & Mahmoud G. Hemeida & Tomonobu Senjyu & Mohamed Roshdy, 2022. "An Online Archimedes Optimization Algorithm Identifier-Controlled Adaptive Modified Virtual Inertia Control for Microgrids," Energies, MDPI, vol. 15(23), pages 1-27, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:8884-:d:982977
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    References listed on IDEAS

    as
    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. Fernández-Guillamón, Ana & Gómez-Lázaro, Emilio & Muljadi, Eduard & Molina-García, Ángel, 2019. "Power systems with high renewable energy sources: A review of inertia and frequency control strategies over time," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
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    4. 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.
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