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Intelligent decision support algorithm for distribution system restoration

Distribution system is the means of revenue for electric utility. It needs to be restored at the earliest if any feeder or complete system is tripped out due to fault or any other cause. Further, uncertainty of the loads, result in variations in the distribution network’s parameters. Thus, an intell...

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Detalles Bibliográficos
Autores principales: Singh, Reetu, Mehfuz, Shabana, Kumar, Parmod
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4960103/
https://www.ncbi.nlm.nih.gov/pubmed/27512634
http://dx.doi.org/10.1186/s40064-016-2810-4
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author Singh, Reetu
Mehfuz, Shabana
Kumar, Parmod
author_facet Singh, Reetu
Mehfuz, Shabana
Kumar, Parmod
author_sort Singh, Reetu
collection PubMed
description Distribution system is the means of revenue for electric utility. It needs to be restored at the earliest if any feeder or complete system is tripped out due to fault or any other cause. Further, uncertainty of the loads, result in variations in the distribution network’s parameters. Thus, an intelligent algorithm incorporating hybrid fuzzy-grey relation, which can take into account the uncertainties and compare the sequences is discussed to analyse and restore the distribution system. The simulation studies are carried out to show the utility of the method by ranking the restoration plans for a typical distribution system. This algorithm also meets the smart grid requirements in terms of an automated restoration plan for the partial/full blackout of network.
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spelling pubmed-49601032016-08-10 Intelligent decision support algorithm for distribution system restoration Singh, Reetu Mehfuz, Shabana Kumar, Parmod Springerplus Research Distribution system is the means of revenue for electric utility. It needs to be restored at the earliest if any feeder or complete system is tripped out due to fault or any other cause. Further, uncertainty of the loads, result in variations in the distribution network’s parameters. Thus, an intelligent algorithm incorporating hybrid fuzzy-grey relation, which can take into account the uncertainties and compare the sequences is discussed to analyse and restore the distribution system. The simulation studies are carried out to show the utility of the method by ranking the restoration plans for a typical distribution system. This algorithm also meets the smart grid requirements in terms of an automated restoration plan for the partial/full blackout of network. Springer International Publishing 2016-07-26 /pmc/articles/PMC4960103/ /pubmed/27512634 http://dx.doi.org/10.1186/s40064-016-2810-4 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Singh, Reetu
Mehfuz, Shabana
Kumar, Parmod
Intelligent decision support algorithm for distribution system restoration
title Intelligent decision support algorithm for distribution system restoration
title_full Intelligent decision support algorithm for distribution system restoration
title_fullStr Intelligent decision support algorithm for distribution system restoration
title_full_unstemmed Intelligent decision support algorithm for distribution system restoration
title_short Intelligent decision support algorithm for distribution system restoration
title_sort intelligent decision support algorithm for distribution system restoration
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4960103/
https://www.ncbi.nlm.nih.gov/pubmed/27512634
http://dx.doi.org/10.1186/s40064-016-2810-4
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