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Virtual Inertia Control-Based Model Predictive Control for Microgrid Frequency Stabilization Considering High Renewable Energy Integration

Author

Listed:
  • Thongchart Kerdphol

    (Department of Electrical and Electronics Engineering, Kyushu Institute of Technology, Fukuoka 804-0093, Japan)

  • Fathin S. Rahman

    (Department of Electrical and Electronics Engineering, Kyushu Institute of Technology, Fukuoka 804-0093, Japan)

  • Yasunori Mitani

    (Department of Electrical and Electronics Engineering, Kyushu Institute of Technology, Fukuoka 804-0093, Japan)

  • Komsan Hongesombut

    (Department of Electrical Engineering, Kasetsart University, Bangkok 10900, Thailand)

  • Sinan Küfeoğlu

    (Department of Electrical Engineering, Aalto University, Espoo 02150, Finland)

Abstract

Renewable energy sources (RESs), such as wind and solar generations, equip inverters to connect to the microgrids. These inverters do not have any rotating mass, thus lowering the overall system inertia. This low system inertia issue could affect the microgrid stability and resiliency in the situation of uncertainties. Today’s microgrids will become unstable if the capacity of RESs become larger and larger, leading to the weakening of microgrid stability and resilience. This paper addresses a new concept of a microgrid control incorporating a virtual inertia system based on the model predictive control (MPC) to emulate virtual inertia into the microgrid control loop, thus stabilizing microgrid frequency during high penetration of RESs. The additional controller of virtual inertia is applied to the microgrid, employing MPC with virtual inertia response. System modeling and simulations are carried out using MATLAB/Simulink ® software. The simulation results confirm the superior robustness and frequency stabilization effect of the proposed MPC-based virtual inertia control in comparison to the fuzzy logic system and conventional virtual inertia control in a system with high integration of RESs. The proposed MPC-based virtual inertia control is able to improve the robustness and frequency stabilization of the microgrid effectively.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:5:p:773-:d:97925
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    References listed on IDEAS

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    1. Barbara Mayer & Michaela Killian & Martin Kozek, 2017. "Hierarchical Model Predictive Control for Sustainable Building Automation," Sustainability, MDPI, vol. 9(2), pages 1-20, February.
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