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Hybrid Islanding Detection Method of Photovoltaic-Based Microgrid Using Reference Current Disturbance

Author

Listed:
  • Reza Bakhshi-Jafarabadi

    (Department of Electrical Engineering, Engineering Faculty, Ferdowsi University of Mashhad, Mashhad 91775-1111, Iran)

  • Marjan Popov

    (Faculty of EEMCS, Delft University of Technology, 2628CD Delft, The Netherlands)

Abstract

This paper proposes a new hybrid islanding detection method for grid-connected photovoltaic system (GCPVS)-based microgrid. In the presented technique, the suspicious islanding event is initially recognized whilst the absolute deviation of the point of common coupling (PCC) voltage surpasses a threshold. After an intentional delay, a transient disturbance is injected into the voltage source inverter’s d -axis reference current to decline the active power output. As a result, the PCC voltage reduces in islanding operating mode whilst its variation is negligible in the grid presence. Therefore, the simultaneous drop of PCC voltage and active power output is used as an islanding detection criterion. The effectiveness of the proposed algorithm is investigated for various islanding and non-islanding scenarios for a practical distribution network with three GCPVSs. The simulation results in MATLAB/Simulink show successful islanding detection with a small non-detection zone within 300 ms without false tripping during non-islanding incidents. In addition to the precise and fast islanding classification, the presented scheme is realized inexpensively; its thresholds are determined self-standing, and its output power quality degradation is eminently small. Moreover, the active power output is restored to the nominal set after islanding recognition, enhancing the chance of GCPVS generation at its highest possible level in the autonomous microgrid.

Suggested Citation

  • Reza Bakhshi-Jafarabadi & Marjan Popov, 2021. "Hybrid Islanding Detection Method of Photovoltaic-Based Microgrid Using Reference Current Disturbance," Energies, MDPI, vol. 14(5), pages 1-15, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:5:p:1390-:d:509790
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    References listed on IDEAS

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    1. Arash Abyaz & Habib Panahi & Reza Zamani & Hassan Haes Alhelou & Pierluigi Siano & Miadreza Shafie-khah & Mimmo Parente, 2019. "An Effective Passive Islanding Detection Algorithm for Distributed Generations," Energies, MDPI, vol. 12(16), pages 1-19, August.
    2. Hassaine, L. & OLias, E. & Quintero, J. & Salas, V., 2014. "Overview of power inverter topologies and control structures for grid connected photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 796-807.
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    Cited by:

    1. Juan Roberto Lopez & Luis Ibarra & Pedro Ponce & Arturo Molina, 2021. "A Decentralized Passive Islanding Detection Method Based on the Variations of Estimated Droop Characteristics," Energies, MDPI, vol. 14(22), pages 1-19, November.
    2. Varaha Satra Bharath Kurukuru & Ahteshamul Haque & Mohammed Ali Khan & Subham Sahoo & Azra Malik & Frede Blaabjerg, 2021. "A Review on Artificial Intelligence Applications for Grid-Connected Solar Photovoltaic Systems," Energies, MDPI, vol. 14(15), pages 1-35, August.

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