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Data analytics and computational methods for anti-islanding of renewable energy based Distributed Generators in power grids

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  • Vyas, Shashank
  • Kumar, Rajesh
  • Kavasseri, Rajesh

Abstract

The centralized generation based model of power delivery remains inefficient due to unavoidable losses and limited reach of the related infrastructure to penetrate into inaccessible areas. Distributed generation based on cleaner sources like wind, solar, biomass etc. can provide energy access to all in a standalone configuration called microgrid. However such distributed generators can also be interfaced with the utility grid and support power flow and ensure supply to connected consumers during utility outages. Grid availability impacted by its vulnerability to extreme events is a major issue affecting wide-spread deployment of such systems. The paper gives an account of major computational intelligence based techniques addressing the problem of islanding in power grids having renewable energy based distributed generators connected to them. The various methods reported have been analyzed in terms of their working methodologies, tools used, accuracy, speed and other relevant aspects. In light of the current state of the art and a need to add more resiliency to the operation of grid-connected distributed generation systems, a new prospect, with preliminary results, will be discussed to address the issue of islanding that can be applied as an effective strategy by utilities to ensure smoother operation of the power grid.

Suggested Citation

  • Vyas, Shashank & Kumar, Rajesh & Kavasseri, Rajesh, 2017. "Data analytics and computational methods for anti-islanding of renewable energy based Distributed Generators in power grids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 493-502.
    • Handle: RePEc:eee:rensus:v:69:y:2017:i:c:p:493-502
    DOI: 10.1016/j.rser.2016.11.116
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    References listed on IDEAS

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    1. Heidari, Mehrdad & Seifossadat, Ghodratollah & Razaz, Morteza, 2013. "Application of decision tree and discrete wavelet transform for an optimized intelligent-based islanding detection method in distributed systems with distributed generations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 525-532.
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    Cited by:

    1. Kakran, Sandeep & Chanana, Saurabh, 2018. "Smart operations of smart grids integrated with distributed generation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 524-535.
    2. Sellak, Hamza & Ouhbi, Brahim & Frikh, Bouchra & Palomares, Iván, 2017. "Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1544-1577.
    3. S. Ananda Kumar & M. S. P. Subathra & Nallapaneni Manoj Kumar & Maria Malvoni & N. J. Sairamya & S. Thomas George & Easter S. Suviseshamuthu & Shauhrat S. Chopra, 2020. "A Novel Islanding Detection Technique for a Resilient Photovoltaic-Based Distributed Power Generation System Using a Tunable-Q Wavelet Transform and an Artificial Neural Network," Energies, MDPI, vol. 13(16), pages 1-22, August.
    4. Ahmadipour, Masoud & Hizam, Hashim & Othman, Mohammad Lutfi & Radzi, Mohd Amran Mohd & Murthy, Avinash Srikanta, 2018. "Islanding detection technique using Slantlet Transform and Ridgelet Probabilistic Neural Network in grid-connected photovoltaic system," Applied Energy, Elsevier, vol. 231(C), pages 645-659.
    5. Peng Tian & Zetao Li & Zhenghang Hao, 2019. "A Doubly-Fed Induction Generator Adaptive Control Strategy and Coordination Technology Compatible with Feeder Automation," Energies, MDPI, vol. 12(23), pages 1-21, November.
    6. 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.
    7. Villanueva-Rosario, Junior Alexis & Santos-García, Félix & Aybar-Mejía, Miguel Euclides & Mendoza-Araya, Patricio & Molina-García, Angel, 2022. "Coordinated ancillary services, market participation and communication of multi-microgrids: A review," Applied Energy, Elsevier, vol. 308(C).

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