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Empirical Wavelet Transform-Based Intelligent Protection Scheme for Microgrids

Author

Listed:
  • Syed Basit Ali Bukhari

    (Department of Electrical Engineering, The University of Azad Jammu and Kashmir, Muzaffarabad 13100, Pakistan
    These authors contributed equally to this work.)

  • Abdul Wadood

    (Department of Electrical Engineering, Air University Islamabad, Aerospace and Aviation Campus, Kamra 43570, Pakistan)

  • Tahir Khurshaid

    (Department of Electrical Engineering, Yeungnam University, 280 Daehak-ro, Gyeongsan 38541, Korea
    These authors contributed equally to this work.)

  • Khawaja Khalid Mehmood

    (Department of Electrical Engineering, The University of Azad Jammu and Kashmir, Muzaffarabad 13100, Pakistan)

  • Sang Bong Rhee

    (Department of Electrical Engineering, Yeungnam University, 280 Daehak-ro, Gyeongsan 38541, Korea)

  • Ki-Chai Kim

    (Department of Electrical Engineering, Yeungnam University, 280 Daehak-ro, Gyeongsan 38541, Korea)

Abstract

Recently, the concept of the microgrid (MG) has been developed to assist the penetration of large numbers of distributed energy resources (DERs) into distribution networks. However, the integration of DERs in the form of MGs disturbs the operating codes of traditional distribution networks. Consequently, traditional protection strategies cannot be applied to MG against short-circuit faults. This paper presents a novel intelligent protection strategy (NIPS) for MGs based on empirical wavelet transform (EWT) and long short-term memory (LSTM) networks. In the proposed NIPS, firstly, the three-phase current signals measured by protective relays are decomposed into empirical modes (EMs). Then, various statistical features are extracted from the obtained EMs. Afterwards, the extracted features along with the three-phase current measurement are input to three different LSTM network to obtain exact fault type, phase, and location information. Finally, a trip signal based on the obtained fault information is generated to disconnect the faulty portion from the rest of the MG. The significant feature of the proposed NIPS is that it does not need adaptive relaying and communication networks. Moreover, it is independent of the operating scenario and hence fault current magnitude. To evaluate the efficacy of the proposed NIPS, exhaustive simulations are performed on an international electro-technical commission (IEC) MG. The simulation results confirm the efficiency of the proposed NIPs in terms of accuracy, dependability, and security. Moreover, comparisons with existing intelligent protection schemes validate that the proposed NIPS is highly accurate, secure, and dependable.

Suggested Citation

  • Syed Basit Ali Bukhari & Abdul Wadood & Tahir Khurshaid & Khawaja Khalid Mehmood & Sang Bong Rhee & Ki-Chai Kim, 2022. "Empirical Wavelet Transform-Based Intelligent Protection Scheme for Microgrids," Energies, MDPI, vol. 15(21), pages 1-17, October.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:21:p:7995-:d:955446
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    References listed on IDEAS

    as
    1. Mishra, Manohar & Patnaik, Bhaskar & Biswal, Monalisa & Hasan, Shazia & Bansal, Ramesh C., 2022. "A systematic review on DC-microgrid protection and grounding techniques: Issues, challenges and future perspective," Applied Energy, Elsevier, vol. 313(C).
    2. Mirsaeidi, Sohrab & Said, Dalila Mat & Mustafa, Mohammad Wazir & Habibuddin, Mohammad Hafiz & Ghaffari, Kimia, 2016. "Fault location and isolation in micro-grids using a digital central protection unit," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1-17.
    3. Syed Basit Ali Bukhari & Khawaja Khalid Mehmood & Abdul Wadood & Herie Park, 2021. "Intelligent Islanding Detection of Microgrids Using Long Short-Term Memory Networks," Energies, MDPI, vol. 14(18), pages 1-16, September.
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    Cited by:

    1. Jorge De La Cruz & Eduardo Gómez-Luna & Majid Ali & Juan C. Vasquez & Josep M. Guerrero, 2023. "Fault Location for Distribution Smart Grids: Literature Overview, Challenges, Solutions, and Future Trends," Energies, MDPI, vol. 16(5), pages 1-37, February.

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