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Household electricity consumption in Greece: A dataset based on socio-economic features

The electricity consumption of a residence depends on many factors such as the habits and economical status of the occupants, the properties of the household and many more. To shed more light on the subject a data set for households was created. The data were collected in Greece through an anonymous...

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Autores principales: Mischos, Stavros, Gkalinikis, Nikolaos Virtsionis, Manolopoulou, Aikaterini, Dalagdi, Eleana, Zaikis, Dimitrios, Lazaridis, Aristotelis, Vlachava, Danai, Lagouvardos, Kostantinos, Vrakas, Dimitrios
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10293984/
https://www.ncbi.nlm.nih.gov/pubmed/37383765
http://dx.doi.org/10.1016/j.dib.2023.109232
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author Mischos, Stavros
Gkalinikis, Nikolaos Virtsionis
Manolopoulou, Aikaterini
Dalagdi, Eleana
Zaikis, Dimitrios
Lazaridis, Aristotelis
Vlachava, Danai
Lagouvardos, Kostantinos
Vrakas, Dimitrios
author_facet Mischos, Stavros
Gkalinikis, Nikolaos Virtsionis
Manolopoulou, Aikaterini
Dalagdi, Eleana
Zaikis, Dimitrios
Lazaridis, Aristotelis
Vlachava, Danai
Lagouvardos, Kostantinos
Vrakas, Dimitrios
author_sort Mischos, Stavros
collection PubMed
description The electricity consumption of a residence depends on many factors such as the habits and economical status of the occupants, the properties of the household and many more. To shed more light on the subject a data set for households was created. The data were collected in Greece through an anonymous survey that comprises 26 questions, resulting in 188 data points from 104 households from different time periods. Each data point contains attributes that are divided into four categories. In the first category, the information is about the household data such as the type and properties of the residence. Next, occupants’ socio-economic features are gathered. In this category information for the number and type of the occupants, the employment status and the total income of the residents is included. The third category of attributes is about the energy-related occupants’ behavior. Finally, the location of the household was provided from the users to estimate the weather conditions for the provided time. Data augmentation was performed to discover non-trivial relationships between the data points. Thus, a secondary set of features was computed based on the raw attributes and is also included. The provided data set can be used to extract insights that could be valuable during the imminent energy crisis.
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spelling pubmed-102939842023-06-28 Household electricity consumption in Greece: A dataset based on socio-economic features Mischos, Stavros Gkalinikis, Nikolaos Virtsionis Manolopoulou, Aikaterini Dalagdi, Eleana Zaikis, Dimitrios Lazaridis, Aristotelis Vlachava, Danai Lagouvardos, Kostantinos Vrakas, Dimitrios Data Brief Data Article The electricity consumption of a residence depends on many factors such as the habits and economical status of the occupants, the properties of the household and many more. To shed more light on the subject a data set for households was created. The data were collected in Greece through an anonymous survey that comprises 26 questions, resulting in 188 data points from 104 households from different time periods. Each data point contains attributes that are divided into four categories. In the first category, the information is about the household data such as the type and properties of the residence. Next, occupants’ socio-economic features are gathered. In this category information for the number and type of the occupants, the employment status and the total income of the residents is included. The third category of attributes is about the energy-related occupants’ behavior. Finally, the location of the household was provided from the users to estimate the weather conditions for the provided time. Data augmentation was performed to discover non-trivial relationships between the data points. Thus, a secondary set of features was computed based on the raw attributes and is also included. The provided data set can be used to extract insights that could be valuable during the imminent energy crisis. Elsevier 2023-05-12 /pmc/articles/PMC10293984/ /pubmed/37383765 http://dx.doi.org/10.1016/j.dib.2023.109232 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data Article
Mischos, Stavros
Gkalinikis, Nikolaos Virtsionis
Manolopoulou, Aikaterini
Dalagdi, Eleana
Zaikis, Dimitrios
Lazaridis, Aristotelis
Vlachava, Danai
Lagouvardos, Kostantinos
Vrakas, Dimitrios
Household electricity consumption in Greece: A dataset based on socio-economic features
title Household electricity consumption in Greece: A dataset based on socio-economic features
title_full Household electricity consumption in Greece: A dataset based on socio-economic features
title_fullStr Household electricity consumption in Greece: A dataset based on socio-economic features
title_full_unstemmed Household electricity consumption in Greece: A dataset based on socio-economic features
title_short Household electricity consumption in Greece: A dataset based on socio-economic features
title_sort household electricity consumption in greece: a dataset based on socio-economic features
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10293984/
https://www.ncbi.nlm.nih.gov/pubmed/37383765
http://dx.doi.org/10.1016/j.dib.2023.109232
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