Application of the k-means clustering method for the detection and analysis of areas of homogeneous residential electricity consumption
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 consum...
| Autores principales: | , , , |
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| Formato: | Articulo |
| Lenguaje: | inglés |
| Publicado: |
2017
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/109273 |
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| _version_ | 1858161836794314753 |
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| author | Chévez, Pedro Joaquín Barbero, Dante Andrés Martini, Irene Discoli, Carlos Alberto |
| author_facet | Chévez, Pedro Joaquín Barbero, Dante Andrés Martini, Irene Discoli, Carlos Alberto |
| author_sort | Chévez, Pedro Joaquín |
| collection | Repositorio Sedici - Comunidad |
| 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”. |
| format | Articulo |
| id | I89-R6-10915-109273 |
| institution | UNLP - Facultad de Arquitectura y Urbanismo |
| institution_str | I-89 |
| language | English |
| publishDate | 2017 |
| record_format | dspace |
| repository_str | R-6 |
| spellingShingle | Arquitectura electric consumption clustering method k-means homogeneous areas households socio-demographic information Chévez, Pedro Joaquín Barbero, Dante Andrés Martini, Irene Discoli, Carlos Alberto 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 |
| 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_short | 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 |
| topic | Arquitectura electric consumption clustering method k-means homogeneous areas households socio-demographic information |
| url | http://sedici.unlp.edu.ar/handle/10915/109273 |
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