Electricity consumption data of a student residence in Southern Africa

S. O. Masebinu; J. B. Holm-Nielsen; C. Mbohwa; S. Padmanaban; N. Nwulu

doi:10.1016/j.dib.2020.106150

Electricity consumption data of a student residence in Southern Africa

S. O. Masebinu^*, J. B. Holm-Nielsen, C. Mbohwa, S. Padmanaban, N. Nwulu

^*Kontaktforfatter

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

6 Citationer (Scopus)

Abstract

The time-series dataset presented in this article was captured using a real-time energy monitoring device from a distribution panel of a student residence in Johannesburg, South Africa. The data was captured from April 2016 to January 2018. The data from the three conductors supplying the student residence with electricity was automatically aggregated and presented as a single data point. The granularity was at resolution levels of watt-minute and kilowatt-hour. A total of 13,966 hrs of data points was captured. The data has not been processed further. Hence, data consists of 1,209-hour of missing data points. In addition to the energy consumption data, 16 months of hourly data for wind speed, temperature and humidity of the closest weather station has been provided. The data will be useful in the formulation of mathematical models of electricity consumption that is most suitable for a student residence. Furthermore, the data provided in this article will encourage the development of a data-driven electricity consumption management strategy and policy formulation for student residences.

Originalsprog	Engelsk
Artikelnummer	106150
Tidsskrift	Data in Brief
Vol/bind	32
ISSN	2352-3409
DOI	https://doi.org/10.1016/j.dib.2020.106150
Status	Udgivet - okt. 2020

Bibliografisk note

Funding Information:
This project was carried out under the Project No. 19-MG04AAU, Danida Mobility Grant, sponsored by the Ministry of Foreign Affairs of Denmark (MFA), under Act 7 on Denmark's International Development Cooperation. The authors acknowledge the Process, Energy and Environmental Technology Station at the University of Johannesburg, the South African Weather Service and the center for Bioenergy and Green Engineering, Department of Energy Technology, Aalborg University, Denmark, for supporting this research work.

Funding Information:
The authors acknowledge the Process, Energy and Environmental Technology Station at the University of Johannesburg, the South African Weather Service and the center for Bioenergy and Green Engineering, Department of Energy Technology, Aalborg University, Denmark, for supporting this research work.

Funding Information:
This project was carried out under the Project No. 19-MG04AAU, Danida Mobility Grant, sponsored by the Ministry of Foreign Affairs of Denmark (MFA), under Act 7 on Denmark's International Development Cooperation.

Publisher Copyright:
© 2020

Adgang til dokumentet

10.1016/j.dib.2020.106150

AUB Link

Søg efter materialet i Aalborg Universitetsbiblioteks søgemaskine

Andre filer og links

Link to publication in Scopus

Citationsformater

@article{07db4bf512454229bcbae264174cd5f0,

title = "Electricity consumption data of a student residence in Southern Africa",

abstract = "The time-series dataset presented in this article was captured using a real-time energy monitoring device from a distribution panel of a student residence in Johannesburg, South Africa. The data was captured from April 2016 to January 2018. The data from the three conductors supplying the student residence with electricity was automatically aggregated and presented as a single data point. The granularity was at resolution levels of watt-minute and kilowatt-hour. A total of 13,966 hrs of data points was captured. The data has not been processed further. Hence, data consists of 1,209-hour of missing data points. In addition to the energy consumption data, 16 months of hourly data for wind speed, temperature and humidity of the closest weather station has been provided. The data will be useful in the formulation of mathematical models of electricity consumption that is most suitable for a student residence. Furthermore, the data provided in this article will encourage the development of a data-driven electricity consumption management strategy and policy formulation for student residences.",

keywords = "Data analysis, Electricity consumption, Energy efficiency, Real-time data, Renewable energy",

author = "Masebinu, {S. O.} and Holm-Nielsen, {J. B.} and C. Mbohwa and S. Padmanaban and N. Nwulu",

note = "Funding Information: This project was carried out under the Project No. 19-MG04AAU, Danida Mobility Grant, sponsored by the Ministry of Foreign Affairs of Denmark (MFA), under Act 7 on Denmark's International Development Cooperation. The authors acknowledge the Process, Energy and Environmental Technology Station at the University of Johannesburg, the South African Weather Service and the center for Bioenergy and Green Engineering, Department of Energy Technology, Aalborg University, Denmark, for supporting this research work. Funding Information: The authors acknowledge the Process, Energy and Environmental Technology Station at the University of Johannesburg, the South African Weather Service and the center for Bioenergy and Green Engineering, Department of Energy Technology, Aalborg University, Denmark, for supporting this research work. Funding Information: This project was carried out under the Project No. 19-MG04AAU, Danida Mobility Grant, sponsored by the Ministry of Foreign Affairs of Denmark (MFA), under Act 7 on Denmark's International Development Cooperation. Publisher Copyright: {\textcopyright} 2020",

year = "2020",

month = oct,

doi = "10.1016/j.dib.2020.106150",

language = "English",

volume = "32",

journal = "Data in Brief",

issn = "2352-3409",

publisher = "Elsevier",

}

TY - JOUR

T1 - Electricity consumption data of a student residence in Southern Africa

AU - Masebinu, S. O.

AU - Holm-Nielsen, J. B.

AU - Mbohwa, C.

AU - Padmanaban, S.

AU - Nwulu, N.

N1 - Funding Information: This project was carried out under the Project No. 19-MG04AAU, Danida Mobility Grant, sponsored by the Ministry of Foreign Affairs of Denmark (MFA), under Act 7 on Denmark's International Development Cooperation. The authors acknowledge the Process, Energy and Environmental Technology Station at the University of Johannesburg, the South African Weather Service and the center for Bioenergy and Green Engineering, Department of Energy Technology, Aalborg University, Denmark, for supporting this research work. Funding Information: The authors acknowledge the Process, Energy and Environmental Technology Station at the University of Johannesburg, the South African Weather Service and the center for Bioenergy and Green Engineering, Department of Energy Technology, Aalborg University, Denmark, for supporting this research work. Funding Information: This project was carried out under the Project No. 19-MG04AAU, Danida Mobility Grant, sponsored by the Ministry of Foreign Affairs of Denmark (MFA), under Act 7 on Denmark's International Development Cooperation. Publisher Copyright: © 2020

PY - 2020/10

Y1 - 2020/10

N2 - The time-series dataset presented in this article was captured using a real-time energy monitoring device from a distribution panel of a student residence in Johannesburg, South Africa. The data was captured from April 2016 to January 2018. The data from the three conductors supplying the student residence with electricity was automatically aggregated and presented as a single data point. The granularity was at resolution levels of watt-minute and kilowatt-hour. A total of 13,966 hrs of data points was captured. The data has not been processed further. Hence, data consists of 1,209-hour of missing data points. In addition to the energy consumption data, 16 months of hourly data for wind speed, temperature and humidity of the closest weather station has been provided. The data will be useful in the formulation of mathematical models of electricity consumption that is most suitable for a student residence. Furthermore, the data provided in this article will encourage the development of a data-driven electricity consumption management strategy and policy formulation for student residences.

AB - The time-series dataset presented in this article was captured using a real-time energy monitoring device from a distribution panel of a student residence in Johannesburg, South Africa. The data was captured from April 2016 to January 2018. The data from the three conductors supplying the student residence with electricity was automatically aggregated and presented as a single data point. The granularity was at resolution levels of watt-minute and kilowatt-hour. A total of 13,966 hrs of data points was captured. The data has not been processed further. Hence, data consists of 1,209-hour of missing data points. In addition to the energy consumption data, 16 months of hourly data for wind speed, temperature and humidity of the closest weather station has been provided. The data will be useful in the formulation of mathematical models of electricity consumption that is most suitable for a student residence. Furthermore, the data provided in this article will encourage the development of a data-driven electricity consumption management strategy and policy formulation for student residences.

KW - Data analysis

KW - Electricity consumption

KW - Energy efficiency

KW - Real-time data

KW - Renewable energy

UR - http://www.scopus.com/inward/record.url?scp=85089532850&partnerID=8YFLogxK

U2 - 10.1016/j.dib.2020.106150

DO - 10.1016/j.dib.2020.106150

M3 - Journal article

AN - SCOPUS:85089532850

SN - 2352-3409

VL - 32

JO - Data in Brief

JF - Data in Brief

M1 - 106150

ER -

Electricity consumption data of a student residence in Southern Africa

Abstract

Bibliografisk note

Adgang til dokumentet

AUB Link

Andre filer og links

Fingeraftryk

Citationsformater