Climate, weather, socio-economic and electricity usage data for the residential and commercial sectors in FL, U.S

This paper presents the data that is used in the article entitled “Climate sensitivity of end-use electricity consumption in the built environment: An application to the state of Florida, United States” (Mukhopadhyay and Nateghi, 2017) [1]. The data described in this paper pertains to the state of F...

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Main Authors: Sayanti Mukherjee, Roshanak Nateghi
Format: Article
Language:English
Published: Elsevier 2017-08-01
Series:Data in Brief
Online Access:http://www.sciencedirect.com/science/article/pii/S2352340917302226
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spelling doaj-cb735ca82c0a41ed91d61862417755202020-11-25T02:29:24ZengElsevierData in Brief2352-34092017-08-0113192195Climate, weather, socio-economic and electricity usage data for the residential and commercial sectors in FL, U.SSayanti Mukherjee0Roshanak Nateghi1Lyles School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA; Corresponding author.School of Industrial Engineering, Division of Environmental and Ecological Engineering, Purdue University, West Lafayette, IN 47907, USAThis paper presents the data that is used in the article entitled “Climate sensitivity of end-use electricity consumption in the built environment: An application to the state of Florida, United States” (Mukhopadhyay and Nateghi, 2017) [1]. The data described in this paper pertains to the state of Florida (during the period of January 1990 to November 2015). It can be classified into four categories of (i) state-level electricity consumption data; (ii) climate data; (iii) weather data; and (iv) socio-economic data. While, electricity consumption data and climate data are obtained at monthly scale directly from the source, the weather data was initially obtained at daily-level, and then aggregated to monthly level for the purpose of analysis. The time scale of socio-economic data varies from monthly-level to yearly-level. This dataset can be used to analyze the influence of climate and weather on the electricity demand as described in Mukhopadhyay and Nateghi (2017) [1]. Keywords: Predictive energy analytics, Climate-energy nexus, Electricity consumption, Residential and commercial electricity sectorshttp://www.sciencedirect.com/science/article/pii/S2352340917302226
collection DOAJ
language English
format Article
sources DOAJ
author Sayanti Mukherjee
Roshanak Nateghi
spellingShingle Sayanti Mukherjee
Roshanak Nateghi
Climate, weather, socio-economic and electricity usage data for the residential and commercial sectors in FL, U.S
Data in Brief
author_facet Sayanti Mukherjee
Roshanak Nateghi
author_sort Sayanti Mukherjee
title Climate, weather, socio-economic and electricity usage data for the residential and commercial sectors in FL, U.S
title_short Climate, weather, socio-economic and electricity usage data for the residential and commercial sectors in FL, U.S
title_full Climate, weather, socio-economic and electricity usage data for the residential and commercial sectors in FL, U.S
title_fullStr Climate, weather, socio-economic and electricity usage data for the residential and commercial sectors in FL, U.S
title_full_unstemmed Climate, weather, socio-economic and electricity usage data for the residential and commercial sectors in FL, U.S
title_sort climate, weather, socio-economic and electricity usage data for the residential and commercial sectors in fl, u.s
publisher Elsevier
series Data in Brief
issn 2352-3409
publishDate 2017-08-01
description This paper presents the data that is used in the article entitled “Climate sensitivity of end-use electricity consumption in the built environment: An application to the state of Florida, United States” (Mukhopadhyay and Nateghi, 2017) [1]. The data described in this paper pertains to the state of Florida (during the period of January 1990 to November 2015). It can be classified into four categories of (i) state-level electricity consumption data; (ii) climate data; (iii) weather data; and (iv) socio-economic data. While, electricity consumption data and climate data are obtained at monthly scale directly from the source, the weather data was initially obtained at daily-level, and then aggregated to monthly level for the purpose of analysis. The time scale of socio-economic data varies from monthly-level to yearly-level. This dataset can be used to analyze the influence of climate and weather on the electricity demand as described in Mukhopadhyay and Nateghi (2017) [1]. Keywords: Predictive energy analytics, Climate-energy nexus, Electricity consumption, Residential and commercial electricity sectors
url http://www.sciencedirect.com/science/article/pii/S2352340917302226
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