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Provision of Frequency Stability of an Islanded Microgrid Using a Novel Virtual Inertia Control and a Fractional Order Cascade Controller

Author

Listed:
  • Soroush Oshnoei

    (Department of Electrical Engineering, Shahid Abbaspour School of Engineering, Shahid Beheshti University, Tehran 19839-69411, Iran)

  • Mohammadreza Aghamohammadi

    (Department of Electrical Engineering, Shahid Abbaspour School of Engineering, Shahid Beheshti University, Tehran 19839-69411, Iran)

  • Siavash Oshnoei

    (Department of Electrical Engineering, Urmia Branch, Islamic Azad University, Urmia 57169-63896, Iran)

  • Arman Oshnoei

    (Department of Electrical Engineering, Shahid Abbaspour School of Engineering, Shahid Beheshti University, Tehran 19839-69411, Iran
    Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark)

  • Behnam Mohammadi-Ivatloo

    (Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark
    Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51666-16471, Iran)

Abstract

Nowadays, the renewable energy sources in microgrids (MGs) have high participation to supply the consumer’s demand. In such MGs, the problems such as the system frequency stability, inertia, and damping reduction are threatened. To overcome this challenge, employing the virtual inertia control (VIC) concept in the MG structure could be considered as a viable solution to improve the system frequency response. Hence, this work proposes a novel modeling for VIC in an islanded MG that provides simultaneous emulation of the primary frequency control, virtual inertia, and damping. To show the efficiency of the proposed technique, a comparison is made between the dynamic performance of the proposed VIC and conventional VIC under different scenarios. The results indicate that the proposed VIC presents superior frequency performance in comparison with conventional VIC. In addition to VIC modeling, a new cascade controller based on three-degrees of freedom and fractional-order controllers (FOCs) is proposed as an MG secondary controller. The effectiveness of the proposed controller is compared to tilt-integral-derivative and FO proportional-integral-derivative controllers. The Squirrel search algorithm is utilized to obtain the optimal coefficients of the controllers. The results demonstrate that the proposed controller improves the MG frequency performance over other controllers. Eventually, the sensitivity analysis is performed to investigate the robustness of the proposed controller in the face of the variations of the parameters.

Suggested Citation

  • Soroush Oshnoei & Mohammadreza Aghamohammadi & Siavash Oshnoei & Arman Oshnoei & Behnam Mohammadi-Ivatloo, 2021. "Provision of Frequency Stability of an Islanded Microgrid Using a Novel Virtual Inertia Control and a Fractional Order Cascade Controller," Energies, MDPI, vol. 14(14), pages 1-24, July.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:14:p:4152-:d:591597
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    References listed on IDEAS

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    1. Nastasi, Benedetto & Mazzoni, Stefano & Groppi, Daniele & Romagnoli, Alessandro & Astiaso Garcia, Davide, 2021. "Solar power-to-gas application to an island energy system," Renewable Energy, Elsevier, vol. 164(C), pages 1005-1016.
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    3. Iván Pazmiño & Sergio Martinez & Danny Ochoa, 2021. "Analysis of Control Strategies Based on Virtual Inertia for the Improvement of Frequency Stability in an Islanded Grid with Wind Generators and Battery Energy Storage Systems," Energies, MDPI, vol. 14(3), pages 1-18, January.
    4. Tefera Mekonnen & Ramchandra Bhandari & Venkata Ramayya, 2021. "Modeling, Analysis and Optimization of Grid-Integrated and Islanded Solar PV Systems for the Ethiopian Residential Sector: Considering an Emerging Utility Tariff Plan for 2021 and Beyond," Energies, MDPI, vol. 14(11), pages 1-24, June.
    5. Jie Xing & Peng Wu, 2021. "Optimal Planning of Electricity-Natural Gas Coupling System Considering Power to Gas Facilities," Energies, MDPI, vol. 14(12), pages 1-19, June.
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    Citations

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    Cited by:

    1. Mokhtar Aly & Emad A. Mohamed & Abdullah M. Noman & Emad M. Ahmed & Fayez F. M. El-Sousy & Masayuki Watanabe, 2023. "Optimized Non-Integer Load Frequency Control Scheme for Interconnected Microgrids in Remote Areas with High Renewable Energy and Electric Vehicle Penetrations," Mathematics, MDPI, vol. 11(9), pages 1-31, April.
    2. Asmaa Faragalla & Omar Abdel-Rahim & Mohamed Orabi & Esam H. Abdelhameed, 2022. "Enhanced Virtual Inertia Control for Microgrids with High-Penetration Renewables Based on Whale Optimization," Energies, MDPI, vol. 15(23), pages 1-18, December.
    3. Shreya Vishnoi & Srete Nikolovski & More Raju & Mukesh Kumar Kirar & Ankur Singh Rana & Pawan Kumar, 2023. "Frequency Stabilization in an Interconnected Micro-Grid Using Smell Agent Optimization Algorithm-Tuned Classical Controllers Considering Electric Vehicles and Wind Turbines," Energies, MDPI, vol. 16(6), pages 1-25, March.
    4. Oshnoei, Soroush & Aghamohammadi, Mohammad Reza & Oshnoei, Siavash & Sahoo, Subham & Fathollahi, Arman & Khooban, Mohammad Hasan, 2023. "A novel virtual inertia control strategy for frequency regulation of islanded microgrid using two-layer multiple model predictive control," Applied Energy, Elsevier, vol. 343(C).
    5. Hoda Sorouri & Arman Oshnoei & Mateja Novak & Frede Blaabjerg & Amjad Anvari-Moghaddam, 2022. "Learning-Based Model Predictive Control of DC-DC Buck Converters in DC Microgrids: A Multi-Agent Deep Reinforcement Learning Approach," Energies, MDPI, vol. 15(15), pages 1-21, July.
    6. 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.

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