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Influence of Data Sampling Frequency on Household Consumption Load Profile Features: A Case Study in Spain

Smart meter (SM) deployment in the residential context provides a vast amount of data of high granularity at the individual household level. In this context, the choice of temporal resolution for describing household load profile features has a crucial impact on the results of any action or assessme...

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Autores principales: Hernandez, J. C., Sanchez-Sutil, F., Cano-Ortega, A., Baier, C. R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660333/
https://www.ncbi.nlm.nih.gov/pubmed/33114096
http://dx.doi.org/10.3390/s20216034
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author Hernandez, J. C.
Sanchez-Sutil, F.
Cano-Ortega, A.
Baier, C. R.
author_facet Hernandez, J. C.
Sanchez-Sutil, F.
Cano-Ortega, A.
Baier, C. R.
author_sort Hernandez, J. C.
collection PubMed
description Smart meter (SM) deployment in the residential context provides a vast amount of data of high granularity at the individual household level. In this context, the choice of temporal resolution for describing household load profile features has a crucial impact on the results of any action or assessment. This study presents a methodology that makes two new contributions. Firstly, it proposes periodograms along with autocorrelation and partial autocorrelation analyses and an empirical distribution-based statistical analysis, which are able to describe household consumption profile features with greater accuracy. Secondly, it proposes a framework for data collection in households at a high sampling frequency. This methodology is able to analyze the influence of data granularity on the description of household consumption profile features. Its effectiveness was confirmed in a case study of four households in Spain. The results indicate that high-resolution data should be used to consider the full range of consumption load fluctuations. Nonetheless, the accuracy of these features was found to largely depend on the load profile analyzed. Indeed, in some households, accurate descriptions were obtained with coarse-grained data. In any case, an intermediate data-resolution of 5 s showed feature characterization closer to those of 0.5 s.
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spelling pubmed-76603332020-11-13 Influence of Data Sampling Frequency on Household Consumption Load Profile Features: A Case Study in Spain Hernandez, J. C. Sanchez-Sutil, F. Cano-Ortega, A. Baier, C. R. Sensors (Basel) Article Smart meter (SM) deployment in the residential context provides a vast amount of data of high granularity at the individual household level. In this context, the choice of temporal resolution for describing household load profile features has a crucial impact on the results of any action or assessment. This study presents a methodology that makes two new contributions. Firstly, it proposes periodograms along with autocorrelation and partial autocorrelation analyses and an empirical distribution-based statistical analysis, which are able to describe household consumption profile features with greater accuracy. Secondly, it proposes a framework for data collection in households at a high sampling frequency. This methodology is able to analyze the influence of data granularity on the description of household consumption profile features. Its effectiveness was confirmed in a case study of four households in Spain. The results indicate that high-resolution data should be used to consider the full range of consumption load fluctuations. Nonetheless, the accuracy of these features was found to largely depend on the load profile analyzed. Indeed, in some households, accurate descriptions were obtained with coarse-grained data. In any case, an intermediate data-resolution of 5 s showed feature characterization closer to those of 0.5 s. MDPI 2020-10-23 /pmc/articles/PMC7660333/ /pubmed/33114096 http://dx.doi.org/10.3390/s20216034 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
Hernandez, J. C.
Sanchez-Sutil, F.
Cano-Ortega, A.
Baier, C. R.
Influence of Data Sampling Frequency on Household Consumption Load Profile Features: A Case Study in Spain
title Influence of Data Sampling Frequency on Household Consumption Load Profile Features: A Case Study in Spain
title_full Influence of Data Sampling Frequency on Household Consumption Load Profile Features: A Case Study in Spain
title_fullStr Influence of Data Sampling Frequency on Household Consumption Load Profile Features: A Case Study in Spain
title_full_unstemmed Influence of Data Sampling Frequency on Household Consumption Load Profile Features: A Case Study in Spain
title_short Influence of Data Sampling Frequency on Household Consumption Load Profile Features: A Case Study in Spain
title_sort influence of data sampling frequency on household consumption load profile features: a case study in spain
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660333/
https://www.ncbi.nlm.nih.gov/pubmed/33114096
http://dx.doi.org/10.3390/s20216034
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