Frontiers in Sustainable Cities (Aug 2023)

GreEn-ER–Electricity consumption data of a tertiary building

  • Gustavo Felipe Martin Nascimento,
  • Gustavo Felipe Martin Nascimento,
  • Frédéric Wurtz,
  • Patrick Kuo-Peng,
  • Benoit Delinchant,
  • Nelson Jhoe Batistela,
  • Tiansi Laranjeira

DOI
https://doi.org/10.3389/frsc.2023.1043657
Journal volume & issue
Vol. 5

Abstract

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The increased use of intermittent renewable energy sources makes the use of machine learning methods combined with demand-side management more and more frequent. Machine learning algorithms rely on data to identify patterns and learn insights. Hence, data availability is of utmost importance, and the more, the merrier. Therefore, this data report aims to present a dataset concerning the electricity consumption of a tertiary building located in the French Alps region (Grenoble) in 2017 and 2018. It is a massively monitored and controlled building with about 330 electricity meters, whose measurement data constitute the dataset. The data were collected directly from the building management system and correspond to raw data, without any pre-treatment. The dataset also includes Python notebooks that allow for understanding the system design, navigating the data, and performing some simple analyses. This is a publicly available dataset that tries to fill the gap of the availability of electricity consumption data, especially regarding tertiary buildings.

Keywords