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Microgrid Islanding Detection Based on Mathematical Morphology

Author

Listed:
  • Fatemeh Ghalavand

    (Department of Electrical Engineering, Shahid Beheshti University, Tehran 1983969411, Iran)

  • Behzad Asle Mohammadi Alizade

    (Department of Electrical Engineering, Shahid Beheshti University, Tehran 1983969411, Iran)

  • Hossam Gaber

    (Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, Oshawa, ON L1H 7K4, Canada)

  • Hadis Karimipour

    (School of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada)

Abstract

Voltage and frequency stability are highly important for reliable performance of smart grids. In grid-connected mode, the utility controls these parameters, but when islanding occurs these parameters exceed their limits, which may result in irreparable damage to the system. This paper presents a time-domain approach which uses basic mathematical morphology (MM) operators, dilation and erosion filters, for microgrid islanding detection. The proposed method applies a dilation-erosion differential filter (DED) of the RMS signal (DEDFOR) at the point of common coupling (PCC) in a micro-grid connected to distributed generations (DGs). To evaluate the performance of the proposed approach, it is tested and compared with existing techniques in the literature under various conditions such as capacitor bank switching and motor starting. The results verify the accuracy and efficiency of the proposed technique for islanding detection under different operating conditions and various power mismatches.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:10:p:2696-:d:174683
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    References listed on IDEAS

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    1. Yaozhen Han & Ronglin Ma & Jinghan Cui, 2018. "Adaptive Higher-Order Sliding Mode Control for Islanding and Grid-Connected Operation of a Microgrid," Energies, MDPI, vol. 11(6), pages 1-17, June.
    2. Niloofar Ghanbari & Hossein Mokhtari & Subhashish Bhattacharya, 2018. "Optimizing Operation Indices Considering Different Types of Distributed Generation in Microgrid Applications," Energies, MDPI, vol. 11(4), pages 1-12, April.
    3. 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.
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    Cited by:

    1. Kuang-Hsiung Tan & Chien-Wu Lan, 2019. "DG System Using PFNN Controllers for Improving Islanding Detection and Power Control," Energies, MDPI, vol. 12(3), pages 1-19, February.
    2. Karthikeyan Subramanian & Ashok Kumar Loganathan, 2020. "Islanding Detection Using a Micro-Synchrophasor for Distribution Systems with Distributed Generation," Energies, MDPI, vol. 13(19), pages 1-31, October.
    3. 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.
    4. Abdullah Albaker & Mansoor Alturki & Rabeh Abbassi & Khalid Alqunun, 2022. "Zonal-Based Optimal Microgrids Identification," Energies, MDPI, vol. 15(7), pages 1-15, March.

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