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A Reliable Data Delivery Mechanism for Grid Power Quality Using Neural Networks in Wireless Sensor Networks

Power grids deal with the business of generation, transmission, and distribution of electric power. Current systems monitor basic electrical quantities such as voltage and current from major pole transformers using their temperature. We improve the current systems in order to gather and deliver the...

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Detalles Bibliográficos
Autores principales: Lim, Yujin, Kim, Hak-Man, Kang, Sanggil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3230980/
https://www.ncbi.nlm.nih.gov/pubmed/22163411
http://dx.doi.org/10.3390/s101009349
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author Lim, Yujin
Kim, Hak-Man
Kang, Sanggil
author_facet Lim, Yujin
Kim, Hak-Man
Kang, Sanggil
author_sort Lim, Yujin
collection PubMed
description Power grids deal with the business of generation, transmission, and distribution of electric power. Current systems monitor basic electrical quantities such as voltage and current from major pole transformers using their temperature. We improve the current systems in order to gather and deliver the information of power qualities such as harmonics, voltage sags, and voltage swells. In the system, data delivery is not guaranteed for the case that a node is lost or the network is congested, because the system has in-line and multi-hop architecture. In this paper, we propose a reliable data delivery mechanism by modeling an optimal data delivery function by employing the neural network concept.
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spelling pubmed-32309802011-12-07 A Reliable Data Delivery Mechanism for Grid Power Quality Using Neural Networks in Wireless Sensor Networks Lim, Yujin Kim, Hak-Man Kang, Sanggil Sensors (Basel) Article Power grids deal with the business of generation, transmission, and distribution of electric power. Current systems monitor basic electrical quantities such as voltage and current from major pole transformers using their temperature. We improve the current systems in order to gather and deliver the information of power qualities such as harmonics, voltage sags, and voltage swells. In the system, data delivery is not guaranteed for the case that a node is lost or the network is congested, because the system has in-line and multi-hop architecture. In this paper, we propose a reliable data delivery mechanism by modeling an optimal data delivery function by employing the neural network concept. Molecular Diversity Preservation International (MDPI) 2010-10-18 /pmc/articles/PMC3230980/ /pubmed/22163411 http://dx.doi.org/10.3390/s101009349 Text en © 2010 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Lim, Yujin
Kim, Hak-Man
Kang, Sanggil
A Reliable Data Delivery Mechanism for Grid Power Quality Using Neural Networks in Wireless Sensor Networks
title A Reliable Data Delivery Mechanism for Grid Power Quality Using Neural Networks in Wireless Sensor Networks
title_full A Reliable Data Delivery Mechanism for Grid Power Quality Using Neural Networks in Wireless Sensor Networks
title_fullStr A Reliable Data Delivery Mechanism for Grid Power Quality Using Neural Networks in Wireless Sensor Networks
title_full_unstemmed A Reliable Data Delivery Mechanism for Grid Power Quality Using Neural Networks in Wireless Sensor Networks
title_short A Reliable Data Delivery Mechanism for Grid Power Quality Using Neural Networks in Wireless Sensor Networks
title_sort reliable data delivery mechanism for grid power quality using neural networks in wireless sensor networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3230980/
https://www.ncbi.nlm.nih.gov/pubmed/22163411
http://dx.doi.org/10.3390/s101009349
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