Application of the k-means clustering method for the detection and analysis of areas of homogeneous residential electricity consumption

Autores
Chévez, Pedro Joaquín; Barbero, Dante Andrés; Martini, Irene; Discoli, Carlos Alberto
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This research aims to detect areas of homogeneous residential electric consumption in the Great La Plata, Buenos Aires, Argentina. This study will identify main socio-demographic factors that impact on the electricity demand and the geographical location of these areas of homogeneous electric consumption. Results were analyzed from groups obtained from the six bimestrial electric average consumption of each of the 1010 census radius which constitutes the Great La Plata, using the K-means clustering method. The present methodology becomes a plausible mechanism to use in the construction of urban energy scenarios, more precisely to determine areas with homogeneous consumption that can be described based on certain socio-demographic characteristics in what is called the “base year”. This study allowed to identify eight homogeneous areas of electricity consumption and their associated characteristics such as rooms per home, people per home, percentage of homes with unsatisfied basic needs, gas network coverage, housing typologies and quality of construction. In this way, we were able to obtain valuable information that allows to propose energy efficiency strategies and to incorporate renewable energy alternatives using appropriate criteria for each area in different “policy scenarios”.
Facultad de Arquitectura y Urbanismo
Materia
Arquitectura
electric consumption
clustering method
k-means
homogeneous areas
households
socio-demographic information
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/109273

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network_name_str SEDICI (UNLP)
spelling Application of the k-means clustering method for the detection and analysis of areas of homogeneous residential electricity consumptionChévez, Pedro JoaquínBarbero, Dante AndrésMartini, IreneDiscoli, Carlos AlbertoArquitecturaelectric consumptionclustering methodk-meanshomogeneous areashouseholdssocio-demographic informationThis research aims to detect areas of homogeneous residential electric consumption in the Great La Plata, Buenos Aires, Argentina. This study will identify main socio-demographic factors that impact on the electricity demand and the geographical location of these areas of homogeneous electric consumption. Results were analyzed from groups obtained from the six bimestrial electric average consumption of each of the 1010 census radius which constitutes the Great La Plata, using the K-means clustering method. The present methodology becomes a plausible mechanism to use in the construction of urban energy scenarios, more precisely to determine areas with homogeneous consumption that can be described based on certain socio-demographic characteristics in what is called the “base year”. This study allowed to identify eight homogeneous areas of electricity consumption and their associated characteristics such as rooms per home, people per home, percentage of homes with unsatisfied basic needs, gas network coverage, housing typologies and quality of construction. In this way, we were able to obtain valuable information that allows to propose energy efficiency strategies and to incorporate renewable energy alternatives using appropriate criteria for each area in different “policy scenarios”.Facultad de Arquitectura y Urbanismo2017info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf115-129http://sedici.unlp.edu.ar/handle/10915/109273enginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S2210670716307636info:eu-repo/semantics/altIdentifier/issn/2210-6707info:eu-repo/semantics/altIdentifier/doi/10.1016/j.scs.2017.03.019info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-11-12T10:49:05Zoai:sedici.unlp.edu.ar:10915/109273Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-11-12 10:49:05.727SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Application of the k-means clustering method for the detection and analysis of areas of homogeneous residential electricity consumption
title Application of the k-means clustering method for the detection and analysis of areas of homogeneous residential electricity consumption
spellingShingle Application of the k-means clustering method for the detection and analysis of areas of homogeneous residential electricity consumption
Chévez, Pedro Joaquín
Arquitectura
electric consumption
clustering method
k-means
homogeneous areas
households
socio-demographic information
title_short Application of the k-means clustering method for the detection and analysis of areas of homogeneous residential electricity consumption
title_full Application of the k-means clustering method for the detection and analysis of areas of homogeneous residential electricity consumption
title_fullStr Application of the k-means clustering method for the detection and analysis of areas of homogeneous residential electricity consumption
title_full_unstemmed Application of the k-means clustering method for the detection and analysis of areas of homogeneous residential electricity consumption
title_sort Application of the k-means clustering method for the detection and analysis of areas of homogeneous residential electricity consumption
dc.creator.none.fl_str_mv Chévez, Pedro Joaquín
Barbero, Dante Andrés
Martini, Irene
Discoli, Carlos Alberto
author Chévez, Pedro Joaquín
author_facet Chévez, Pedro Joaquín
Barbero, Dante Andrés
Martini, Irene
Discoli, Carlos Alberto
author_role author
author2 Barbero, Dante Andrés
Martini, Irene
Discoli, Carlos Alberto
author2_role author
author
author
dc.subject.none.fl_str_mv Arquitectura
electric consumption
clustering method
k-means
homogeneous areas
households
socio-demographic information
topic Arquitectura
electric consumption
clustering method
k-means
homogeneous areas
households
socio-demographic information
dc.description.none.fl_txt_mv This research aims to detect areas of homogeneous residential electric consumption in the Great La Plata, Buenos Aires, Argentina. This study will identify main socio-demographic factors that impact on the electricity demand and the geographical location of these areas of homogeneous electric consumption. Results were analyzed from groups obtained from the six bimestrial electric average consumption of each of the 1010 census radius which constitutes the Great La Plata, using the K-means clustering method. The present methodology becomes a plausible mechanism to use in the construction of urban energy scenarios, more precisely to determine areas with homogeneous consumption that can be described based on certain socio-demographic characteristics in what is called the “base year”. This study allowed to identify eight homogeneous areas of electricity consumption and their associated characteristics such as rooms per home, people per home, percentage of homes with unsatisfied basic needs, gas network coverage, housing typologies and quality of construction. In this way, we were able to obtain valuable information that allows to propose energy efficiency strategies and to incorporate renewable energy alternatives using appropriate criteria for each area in different “policy scenarios”.
Facultad de Arquitectura y Urbanismo
description This research aims to detect areas of homogeneous residential electric consumption in the Great La Plata, Buenos Aires, Argentina. This study will identify main socio-demographic factors that impact on the electricity demand and the geographical location of these areas of homogeneous electric consumption. Results were analyzed from groups obtained from the six bimestrial electric average consumption of each of the 1010 census radius which constitutes the Great La Plata, using the K-means clustering method. The present methodology becomes a plausible mechanism to use in the construction of urban energy scenarios, more precisely to determine areas with homogeneous consumption that can be described based on certain socio-demographic characteristics in what is called the “base year”. This study allowed to identify eight homogeneous areas of electricity consumption and their associated characteristics such as rooms per home, people per home, percentage of homes with unsatisfied basic needs, gas network coverage, housing typologies and quality of construction. In this way, we were able to obtain valuable information that allows to propose energy efficiency strategies and to incorporate renewable energy alternatives using appropriate criteria for each area in different “policy scenarios”.
publishDate 2017
dc.date.none.fl_str_mv 2017
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/109273
url http://sedici.unlp.edu.ar/handle/10915/109273
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S2210670716307636
info:eu-repo/semantics/altIdentifier/issn/2210-6707
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.scs.2017.03.019
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
115-129
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
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instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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