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Islanding Detection Using a Micro-Synchrophasor for Distribution Systems with Distributed Generation

Author

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  • Karthikeyan Subramanian

    (Department of Electrical and Electronics Engineering, PSG College of Technology, Coimbatore 641004, Tamil Nadu, India)

  • Ashok Kumar Loganathan

    (Department of Electrical and Electronics Engineering, PSG College of Technology, Coimbatore 641004, Tamil Nadu, India)

Abstract

Distributed Generation (DG) has changed the power generation system to small-scale instead of large-scale generation. The demanding issue with the interconnection of DG is the detection of unintended islanding in a network. Several methods proposed in the literature show drawbacks such as high non-detection zones (NDZ) and higher tripping time. In this paper, the IEEE 13 bus distribution network with DGs like wind and solar power plants is integrated at two buses. Islanding is detected by utilizing data from a micro-synchrophasor located at the distribution grid and the DG. The micro-synchrophasor-based unintended islanding detection algorithm is based on parameters such as voltage, rate of change of voltage, frequency, rate of change of frequency, voltage phase angle difference and the rate of change of the voltage phase angle difference between the utility and the islanded grid. The proposed islanding detection algorithm discriminates between islanding and non-islanding conditions and is highly efficient under zero power mismatch conditions. The proposed method has null NDZ and satisfies the IEEE 1547 standard for DG tripping time. The effectiveness of the proposed IDM was verified when there are multiple DGs in the islanded grid. Also, the proposed method does not require additional hardware as it can be incorporated in digital relays with synchrophasor functionality.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:19:p:5180-:d:423910
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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. 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.
    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. Bayrak, Gökay & Kabalci, Ersan, 2016. "Implementation of a new remote islanding detection method for wind–solar hybrid power plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1-15.
    5. Mojgan Hojabri & Ulrich Dersch & Antonios Papaemmanouil & Peter Bosshart, 2019. "A Comprehensive Survey on Phasor Measurement Unit Applications in Distribution Systems," Energies, MDPI, vol. 12(23), pages 1-23, November.
    6. 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.
    7. 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.
    8. Masoud Ahmadipour & Hashim Hizam & Mohammad Lutfi Othman & Mohd Amran Mohd Radzi, 2018. "An Anti-Islanding Protection Technique Using a Wavelet Packet Transform and a Probabilistic Neural Network," Energies, MDPI, vol. 11(10), pages 1-31, October.
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    Cited by:

    1. Ênio Costa Resende & Henrique Tannús de Moura Carvalho & Luiz Carlos Gomes Freitas, 2022. "Implementation and Critical Analysis of the Active Phase Jump with Positive Feedback Anti-Islanding Algorithm," Energies, MDPI, vol. 15(13), pages 1-27, June.
    2. 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.
    3. Szymon Barczentewicz & Tomasz Lerch & Andrzej Bień & Krzysztof Duda, 2021. "Laboratory Evaluation of a Phasor-Based Islanding Detection Method," Energies, MDPI, vol. 14(7), pages 1-17, April.

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