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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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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