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Power loss reduction in radial distribution system with multiple distributed energy resources through efficient islanding detection

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  • Choudhry, Mohammad A.
  • Khan, Hasham

Abstract

To provide electric utility service of desired quality at the lowest possible cost, voltage drop and power loss reduction is crucial for distribution network. Distribution systems with Distributed Energy Resources (DER) have shown an enormous potential for power loss and voltage drop reduction. This paper investigates existing islanding detection techniques for feeder performance and proposes a new islanding detection algorithm (NIDA) for node voltage profile improvement and power loss reduction in the distribution network.

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  • Choudhry, Mohammad A. & Khan, Hasham, 2010. "Power loss reduction in radial distribution system with multiple distributed energy resources through efficient islanding detection," Energy, Elsevier, vol. 35(12), pages 4843-4861.
    • Handle: RePEc:eee:energy:v:35:y:2010:i:12:p:4843-4861
    DOI: 10.1016/j.energy.2010.09.003
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    References listed on IDEAS

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    1. Chicco, Gianfranco & Mancarella, Pierluigi, 2009. "Distributed multi-generation: A comprehensive view," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(3), pages 535-551, April.
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    Cited by:

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    2. Monteiro, Raul V.A. & Guimarães, Geraldo C. & Silva, Fernando Bento & da Silva Teixeira, Raoni F. & Carvalho, Bismarck C. & Finazzi, Antônio de P. & de Vasconcellos, Arnulfo B., 2018. "A medium-term analysis of the reduction in technical losses on distribution systems with variable demand using artificial neural networks: An Electrical Energy Storage approach," Energy, Elsevier, vol. 164(C), pages 1216-1228.
    3. Pan, Yu & Liu, Liuchen & Zhu, Tong & Zhang, Tao & Zhang, Junying, 2017. "Feasibility analysis on distributed energy system of Chongming County based on RETScreen software," Energy, Elsevier, vol. 130(C), pages 298-306.
    4. Senthil Kumar, J. & Charles Raja, S. & Jeslin Drusila Nesamalar, J. & Venkatesh, P., 2018. "Optimizing renewable based generations in AC/DC microgrid system using hybrid Nelder-Mead – Cuckoo Search algorithm," Energy, Elsevier, vol. 158(C), pages 204-215.
    5. Ming, Zeng & Shaojie, Ouyang & Hui, Shi & Yujian, Ge & Qiqi, Qian, 2015. "Overall review of distributed energy development in China: Status quo, barriers and solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 1226-1238.
    6. Niknam, Taher & Golestaneh, Faranak & Shafiei, Mehdi, 2013. "Probabilistic energy management of a renewable microgrid with hydrogen storage using self-adaptive charge search algorithm," Energy, Elsevier, vol. 49(C), pages 252-267.
    7. Laghari, J.A. & Mokhlis, H. & Karimi, M. & Bakar, A.H.A. & Mohamad, Hasmaini, 2015. "An islanding detection strategy for distribution network connected with hybrid DG resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 662-676.
    8. Khan, Mohammed Ali & Haque, Ahteshamul & Kurukuru, V.S. Bharath & Saad, Mekhilef, 2022. "Islanding detection techniques for grid-connected photovoltaic systems-A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    9. Niknam, Taher & Golestaneh, Faranak & Malekpour, Ahmadreza, 2012. "Probabilistic energy and operation management of a microgrid containing wind/photovoltaic/fuel cell generation and energy storage devices based on point estimate method and self-adaptive gravitational," Energy, Elsevier, vol. 43(1), pages 427-437.

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