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Islanding Detection Methods for Microgrids: A Comprehensive Review

Author

Listed:
  • Muhammed Y. Worku

    (Interdisciplinary Research Center for Renewable Energy and Power Systems (IRC-REPS), Research Institute, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia)

  • Mohamed A. Hassan

    (Interdisciplinary Research Center for Renewable Energy and Power Systems (IRC-REPS), Research Institute, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia)

  • Luqman S. Maraaba

    (Applied Research Center for Metrology, Standards and Testing, Research Institute, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia)

  • Mohammad A. Abido

    (Interdisciplinary Research Center for Renewable Energy and Power Systems (IRC-REPS), Research Institute, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
    Electrical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
    K.A.CARE Energy Research & Innovation Center, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia)

Abstract

Microgrids that are integrated with distributed energy resources (DERs) provide many benefits, including high power quality, energy efficiency and low carbon emissions, to the power grid. Microgrids are operated either in grid-connected or island modes running on different strategies. However, one of the major technical issues in a microgrid is unintentional islanding, where failure to trip the microgrid may lead to serious consequences in terms of protection, security, voltage and frequency stability, and safety. Therefore, fast and efficient islanding detection is necessary for reliable microgrid operations. This paper provides an overview of microgrid islanding detection methods, which are classified as local and remote. Various detection methods in each class are studied, and the advantages and disadvantages of each method are discussed based on performance evaluation indices such as non-detection zone (NDZ), detection time, error detection ratio, power quality and effectiveness in multiple inverter cases. Recent modifications on islanding methods using signal processing techniques and intelligent classifiers are also discussed. Modified passive methods with signal processing and intelligent classifiers are addressing the drawbacks of passive methods and are getting more attention in the recently published works. This comprehensive review of islanding methods will provide power utilities and researchers a reference and guideline to select the best islanding detection method based on their effectiveness and economic feasibility.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:24:p:3174-:d:698623
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Li, Canbing & Cao, Chi & Cao, Yijia & Kuang, Yonghong & Zeng, Long & Fang, Baling, 2014. "A review of islanding detection methods for microgrid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 211-220.
    4. Mehdi Hosseinzadeh & Farzad Rajaei Salmasi, 2020. "Islanding Fault Detection in Microgrids—A Survey," Energies, MDPI, vol. 13(13), pages 1-28, July.
    5. Velasco, D. & Trujillo, C.L. & Garcerá, G. & Figueres, E., 2010. "Review of anti-islanding techniques in distributed generators," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(6), pages 1608-1614, August.
    6. Trujillo, C.L. & Velasco, D. & Figueres, E. & Garcerá, G., 2010. "Analysis of active islanding detection methods for grid-connected microinverters for renewable energy processing," Applied Energy, Elsevier, vol. 87(11), pages 3591-3605, November.
    7. Noor Hussain & Mashood Nasir & Juan Carlos Vasquez & Josep M. Guerrero, 2020. "Recent Developments and Challenges on AC Microgrids Fault Detection and Protection Systems–A Review," Energies, MDPI, vol. 13(9), pages 1-31, May.
    8. Ku Ahmad, Ku Nurul Edhura & Selvaraj, Jeyraj & Rahim, Nasrudin Abd, 2013. "A review of the islanding detection methods in grid-connected PV inverters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 756-766.
    9. Muhammed Y. Worku & Mohamed A. Hassan & Mohamed A. Abido, 2019. "Real Time Energy Management and Control of Renewable Energy based Microgrid in Grid Connected and Island Modes," Energies, MDPI, vol. 12(2), pages 1-18, January.
    10. 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.
    11. Khamis, Aziah & Shareef, Hussain & Bizkevelci, Erdal & Khatib, Tamer, 2013. "A review of islanding detection techniques for renewable distributed generation systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 483-493.
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    Cited by:

    1. Rafaela Nascimento & Felipe Ramos & Aline Pinheiro & Washington de Araujo Silva Junior & Ayrlw M. C. Arcanjo & Roberto F. Dias Filho & Mohamed A. Mohamed & Manoel H. N. Marinho, 2022. "Case Study of Backup Application with Energy Storage in Microgrids," Energies, MDPI, vol. 15(24), pages 1-12, December.
    2. Krzysztof Dmitruk & Andrzej Sikorski, 2022. "Implementation of the Improved Active Frequency Drift Anti-Islanding Method into the Three-Phase AC/DC Converter with the LCL Grid Filter," Energies, MDPI, vol. 15(4), pages 1-14, February.
    3. Thomas Price & Gordon Parker & Gail Vaucher & Robert Jane & Morris Berman, 2022. "Microgrid Energy Management during High-Stress Operation," Energies, MDPI, vol. 15(18), pages 1-11, September.

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