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An Effective Passive Islanding Detection Algorithm for Distributed Generations

Author

Listed:
  • Arash Abyaz

    (School of Electrical and Computer Engineering, University of Tehran, Tehran 395515, Iran)

  • Habib Panahi

    (School of Electrical and Computer Engineering, University of Tehran, Tehran 395515, Iran)

  • Reza Zamani

    (Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran 115111, Iran)

  • Hassan Haes Alhelou

    (Department of Electrical Power Engineering, Faculty of Mechanical and Electrical Engineering, Tishreen University, Lattakia 2230, Syria)

  • Pierluigi Siano

    (Department of Management & Innovation Systems, University of Salerno, 84084 Salerno, Italy)

  • Miadreza Shafie-khah

    (School of Technology and Innovations, University of Vaasa, 65200 Vaasa, Finland)

  • Mimmo Parente

    (Department of Management & Innovation Systems, University of Salerno, 84084 Salerno, Italy)

Abstract

Different issues will be raised and highlighted by emerging distributed generations (DGs) into modern power systems in which the islanding detection is the most important. In the islanding situation, a part of the system which consists of at least one DG, passive grid, and local load, becomes fully separated from the main grid. Several detection methods of islanding have been proposed in recent researches based on measured electrical parameters of the system. However, islanding detection based on local measurements suffers from the non-detection zone (NDZ) and undesirable detection during grid-connected events. This paper proposes a passive islanding detection algorithm for all types of DGs by appropriate combining the measured frequency, voltage, current, and phase angle and their rate of changes at the point of common coupling (PCC). The proposed algorithm detects the islanding situation, even with the exact zero power mismatches. Proposed algorithm discriminates between the islanding situation and non-islanding disturbances, such as short circuit faults, capacitor faults, and load switching in a proper time and without mal-operation. In addition, the performance of the proposed algorithm has been evaluated under different scenarios by performing the algorithm on the IEEE 13-bus distribution system.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:16:p:3160-:d:258401
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    References listed on IDEAS

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    1. Reza Zamani & Mohamad-Esmail Hamedani-Golshan & Hassan Haes Alhelou & Pierluigi Siano & Hemanshu R. Pota, 2018. "Islanding Detection of Synchronous Distributed Generator Based on the Active and Reactive Power Control Loops," Energies, MDPI, vol. 11(10), pages 1-15, October.
    2. Yi Tang & Feng Li & Chenyi Zheng & Qi Wang & Yingjun Wu, 2018. "PMU Measurement-Based Intelligent Strategy for Power System Controlled Islanding," Energies, MDPI, vol. 11(1), pages 1-15, January.
    3. 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.
    4. Menghua Liu & Wei Zhao & Qing Wang & Songling Huang & Kunpeng Shi, 2019. "Compatibility Issues with Irregular Current Injection Islanding Detection Methods and a Solution," Energies, MDPI, vol. 12(8), pages 1-20, April.
    5. Kong, Xiangrui & Xu, Xiaoyuan & Yan, Zheng & Chen, Sijie & Yang, Huoming & Han, Dong, 2018. "Deep learning hybrid method for islanding detection in distributed generation," Applied Energy, Elsevier, vol. 210(C), pages 776-785.
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    Cited by:

    1. Pierluigi Siano & Miadreza Shafie-khah, 2020. "Special Issue on Advanced Approaches, Business Models, and Novel Techniques for Management and Control of Smart Grids," Energies, MDPI, vol. 13(11), pages 1-3, May.
    2. Danny Ochoa & Sergio Martinez, 2021. "Analytical Approach to Understanding the Effects of Implementing Fast-Frequency Response by Wind Turbines on the Short-Term Operation of Power Systems," Energies, MDPI, vol. 14(12), pages 1-22, June.
    3. 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.
    4. 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.
    5. Marino Coppola & Pierluigi Guerriero & Adolfo Dannier & Santolo Daliento & Davide Lauria & Andrea Del Pizzo, 2020. "Control of a Fault-Tolerant Photovoltaic Energy Converter in Island Operation," Energies, MDPI, vol. 13(12), pages 1-18, June.
    6. 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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