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Primary Voltage and Frequency Regulation in Inverter Based Islanded Microgrids through a Model Predictive Control Approach

Author

Listed:
  • Daniele Mestriner

    (Naval, Electrical, Electronics and Telecommunication Engineering and Naval Architecture Department (DITEN), University of Genoa, Via All’Opera Pia 11a, 16145 Genoa, Italy)

  • Alessandro Rosini

    (Naval, Electrical, Electronics and Telecommunication Engineering and Naval Architecture Department (DITEN), University of Genoa, Via All’Opera Pia 11a, 16145 Genoa, Italy)

  • Iris Xhani

    (RINA Consulting S.p.A., Via A. Cecchi, 6-16129 Genoa, Italy)

  • Andrea Bonfiglio

    (Naval, Electrical, Electronics and Telecommunication Engineering and Naval Architecture Department (DITEN), University of Genoa, Via All’Opera Pia 11a, 16145 Genoa, Italy)

  • Renato Procopio

    (Naval, Electrical, Electronics and Telecommunication Engineering and Naval Architecture Department (DITEN), University of Genoa, Via All’Opera Pia 11a, 16145 Genoa, Italy)

Abstract

A frequency and voltage control strategy based on a decentralized and communication-less approach is proposed in this work and applied to Photovoltaic-Storage-Microturbine islanded Microgrids (MGs). The approach is based on the Model Predictive Control (MPC) technique. Thanks to the use of local measurements, each source can nullify the steady-state voltage and frequency errors by means of a dedicated MPC controller. Consequently, the proposed approach unifies the advantages of classic droop and master/slave controllers due to the absence of communication links among devices and due to the absence of a secondary centralized control loop.

Suggested Citation

  • Daniele Mestriner & Alessandro Rosini & Iris Xhani & Andrea Bonfiglio & Renato Procopio, 2022. "Primary Voltage and Frequency Regulation in Inverter Based Islanded Microgrids through a Model Predictive Control Approach," Energies, MDPI, vol. 15(14), pages 1-19, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:14:p:5077-:d:860923
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    References listed on IDEAS

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    4. Zhang, Yan & Meng, Fanlin & Wang, Rui & Kazemtabrizi, Behzad & Shi, Jianmai, 2019. "Uncertainty-resistant stochastic MPC approach for optimal operation of CHP microgrid," Energy, Elsevier, vol. 179(C), pages 1265-1278.
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    Citations

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    Cited by:

    1. Yan Yang & Yeqin Wang & Weixing Zhang & Zhenghao Li & Rui Liang, 2022. "Design of Adaptive Fuzzy Sliding-Mode Control for High-Performance Islanded Inverter in Micro-Grid," Energies, MDPI, vol. 15(23), pages 1-25, December.
    2. Eros D. Escobar & Tatiana Manrique & Idi A. Isaac, 2022. "Campus Microgrid Data-Driven Model Identification and Secondary Voltage Control," Energies, MDPI, vol. 15(21), pages 1-19, October.
    3. La Fata, Alice & Brignone, Massimo & Procopio, Renato & Bracco, Stefano & Delfino, Federico & Barilli, Riccardo & Ravasi, Martina & Zanellini, Fabio, 2022. "An efficient Energy Management System for long term planning and real time scheduling of flexible polygeneration systems," Renewable Energy, Elsevier, vol. 200(C), pages 1180-1201.
    4. Juan Moreno-Castro & Victor Samuel Ocaña Guevara & Lesyani Teresa León Viltre & Yandi Gallego Landera & Oscar Cuaresma Zevallos & Miguel Aybar-Mejía, 2023. "Microgrid Management Strategies for Economic Dispatch of Electricity Using Model Predictive Control Techniques: A Review," Energies, MDPI, vol. 16(16), pages 1-24, August.

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