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An Islanding Detection Technique for Inverter-Based Distributed Generation in Microgrids

Author

Listed:
  • Mazaher Karimi

    (School of Technology and Innovations, University of Vaasa, Wolffintie 34, FI-65200 Vaasa, Finland)

  • Mohammad Farshad

    (Department of Electrical Engineering, Faculty of Basic Sciences and Engineering, Gonbad Kavous University, Gonbad Kavous 49717-99151, Iran)

  • Qiteng Hong

    (Department of Electronics and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK)

  • Hannu Laaksonen

    (School of Technology and Innovations, University of Vaasa, Wolffintie 34, FI-65200 Vaasa, Finland)

  • Kimmo Kauhaniemi

    (School of Technology and Innovations, University of Vaasa, Wolffintie 34, FI-65200 Vaasa, Finland)

Abstract

This article proposes a new passive islanding detection technique for inverter-based distributed generation (DG) in microgrids based on local synchrophasor measurements. The proposed method utilizes the voltage and current phasors measured at the DG connection point (point of connection, PoC). In this paper, the rate of change of voltages and the ratio of the voltage and current magnitudes (VoI index) at the PoC are monitored using micro-phasor measurement units. The developed local measurements based decentralized islanding detection technique is based on the VoI index in order to detect any kind of utility grid frequency fluctuations or oscillations and distinguishing them from islanding condition. The simulation studies confirm that the proposed scheme is accurate, robust, fast, and simple to implement for inverter-based DGs.

Suggested Citation

  • Mazaher Karimi & Mohammad Farshad & Qiteng Hong & Hannu Laaksonen & Kimmo Kauhaniemi, 2020. "An Islanding Detection Technique for Inverter-Based Distributed Generation in Microgrids," Energies, MDPI, vol. 14(1), pages 1-18, December.
    • Handle: RePEc:gam:jeners:v:14:y:2020:i:1:p:130-:d:469790
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    References listed on IDEAS

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    1. S. Ananda Kumar & M. S. P. Subathra & Nallapaneni Manoj Kumar & Maria Malvoni & N. J. Sairamya & S. Thomas George & Easter S. Suviseshamuthu & Shauhrat S. Chopra, 2020. "A Novel Islanding Detection Technique for a Resilient Photovoltaic-Based Distributed Power Generation System Using a Tunable-Q Wavelet Transform and an Artificial Neural Network," Energies, MDPI, vol. 13(16), pages 1-22, August.
    2. Mehdi Hosseinzadeh & Farzad Rajaei Salmasi, 2020. "Islanding Fault Detection in Microgrids—A Survey," Energies, MDPI, vol. 13(13), pages 1-28, July.
    3. Fatemeh Ghalavand & Behzad Asle Mohammadi Alizade & Hossam Gaber & Hadis Karimipour, 2018. "Microgrid Islanding Detection Based on Mathematical Morphology," Energies, MDPI, vol. 11(10), pages 1-18, October.
    4. Taiying Zheng & Huan Yang & Rongxiang Zhao & Yong Cheol Kang & Vladimir Terzija, 2018. "Design, Evaluation and Implementation of an Islanding Detection Method for a Micro-grid," Energies, MDPI, vol. 11(2), pages 1-24, February.
    5. Min-Sung Kim & Raza Haider & Gyu-Jung Cho & Chul-Hwan Kim & Chung-Yuen Won & Jong-Seo Chai, 2019. "Comprehensive Review of Islanding Detection Methods for Distributed Generation Systems," Energies, MDPI, vol. 12(5), pages 1-21, March.
    6. Xinxin Zheng & Rui Zhang & Xi Chen & Nong Sun, 2018. "Improved Three-Phase AFD Islanding Detection Based on Digital Control and Non-Detection Zone Elimination," Energies, MDPI, vol. 11(9), pages 1-15, September.
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    Cited by:

    1. Muhammed Y. Worku & Mohamed A. Hassan & Luqman S. Maraaba & Mohammad A. Abido, 2021. "Islanding Detection Methods for Microgrids: A Comprehensive Review," Mathematics, MDPI, vol. 9(24), pages 1-23, December.

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