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The Power of Big Data and Data Analytics for AMI Data: A Case Study

In recent years, there has been a transformation in the value chain of different industrial sectors, like the electricity networks, with the appearance of smart grids. Currently, the underlying knowledge in raw data coming from numerous devices can mark a significant competitive advantage for utilit...

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Autores principales: Guerrero-Prado, Jenniffer Sidney, Alfonso-Morales, Wilfredo, Caicedo-Bravo, Eduardo, Zayas-Pérez, Benjamín, Espinosa-Reza, Alfredo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309066/
https://www.ncbi.nlm.nih.gov/pubmed/32526976
http://dx.doi.org/10.3390/s20113289
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author Guerrero-Prado, Jenniffer Sidney
Alfonso-Morales, Wilfredo
Caicedo-Bravo, Eduardo
Zayas-Pérez, Benjamín
Espinosa-Reza, Alfredo
author_facet Guerrero-Prado, Jenniffer Sidney
Alfonso-Morales, Wilfredo
Caicedo-Bravo, Eduardo
Zayas-Pérez, Benjamín
Espinosa-Reza, Alfredo
author_sort Guerrero-Prado, Jenniffer Sidney
collection PubMed
description In recent years, there has been a transformation in the value chain of different industrial sectors, like the electricity networks, with the appearance of smart grids. Currently, the underlying knowledge in raw data coming from numerous devices can mark a significant competitive advantage for utilities. It is the case of the Advanced Metering Infrastructure (AMI). Such technology gets user consumption characteristics at levels of detail that were previously not possible. In this context, the terms big data and data analytics become relevant, which are tools that allow using large volumes of information and the generation of valuable knowledge from raw data that can support data-driven decisions for operating on the grid. This paper presents the results of the big data implementation and data analytics techniques in a case study with smart metering data from the city of London. Implemented big data and data analytic techniques to show how to understand user consumption patterns on a broader horizon, the relationships with seasonal variables identify behaviors related to specific events and atypical consumptions. This knowledge helps support decision making about improving demand response programs and, in general, the planning and operation of the Smart Grid.
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spelling pubmed-73090662020-06-25 The Power of Big Data and Data Analytics for AMI Data: A Case Study Guerrero-Prado, Jenniffer Sidney Alfonso-Morales, Wilfredo Caicedo-Bravo, Eduardo Zayas-Pérez, Benjamín Espinosa-Reza, Alfredo Sensors (Basel) Article In recent years, there has been a transformation in the value chain of different industrial sectors, like the electricity networks, with the appearance of smart grids. Currently, the underlying knowledge in raw data coming from numerous devices can mark a significant competitive advantage for utilities. It is the case of the Advanced Metering Infrastructure (AMI). Such technology gets user consumption characteristics at levels of detail that were previously not possible. In this context, the terms big data and data analytics become relevant, which are tools that allow using large volumes of information and the generation of valuable knowledge from raw data that can support data-driven decisions for operating on the grid. This paper presents the results of the big data implementation and data analytics techniques in a case study with smart metering data from the city of London. Implemented big data and data analytic techniques to show how to understand user consumption patterns on a broader horizon, the relationships with seasonal variables identify behaviors related to specific events and atypical consumptions. This knowledge helps support decision making about improving demand response programs and, in general, the planning and operation of the Smart Grid. MDPI 2020-06-09 /pmc/articles/PMC7309066/ /pubmed/32526976 http://dx.doi.org/10.3390/s20113289 Text en © 2020 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 (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Guerrero-Prado, Jenniffer Sidney
Alfonso-Morales, Wilfredo
Caicedo-Bravo, Eduardo
Zayas-Pérez, Benjamín
Espinosa-Reza, Alfredo
The Power of Big Data and Data Analytics for AMI Data: A Case Study
title The Power of Big Data and Data Analytics for AMI Data: A Case Study
title_full The Power of Big Data and Data Analytics for AMI Data: A Case Study
title_fullStr The Power of Big Data and Data Analytics for AMI Data: A Case Study
title_full_unstemmed The Power of Big Data and Data Analytics for AMI Data: A Case Study
title_short The Power of Big Data and Data Analytics for AMI Data: A Case Study
title_sort power of big data and data analytics for ami data: a case study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309066/
https://www.ncbi.nlm.nih.gov/pubmed/32526976
http://dx.doi.org/10.3390/s20113289
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