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Research data . Dataset . 2022

A full-year data regarding a smart building

Gomes, Luis; Pinto, Tiago; Vale, Zita;
Open Access
English
Published: 29 Jun 2022
Publisher: Zenodo
Abstract

The smart building represented by the dataset is divided into five zones, where each zone has 2 to 3 offices. The building has photovoltaic panels with a generation peak of 7.5 kW, inside sensors, light intensity control, and all consumption measured by load type. The data was collected in 5 minutes periods. By zones, the buildings have a distribution of 6 researchers in Zone#1, 5 researchers in Zone#2, 5 researchers in Zone#3, 3 researchers in Zone#4, and 5 researchers in Zone#5. Zone#1 includes a meeting room, and Zone#2 includes a server room. Regarding the server room, its HVAC unit was measured in HVAC#2, however, near the end of the year, the unit was removed from the monitoring system. The light intensity values represent the current state of the lamps and have a linear correlation with the lamp’s consumption. The dataset represents raw data without any treatment, this means that it is possible to find errors. The data do not have missing reading periods, but they can have a fixed zero (0) value, indicating a failure in the system. You can assume that periods with zero voltage represent an error in that zone at that period.

This article is a result of the project RETINA (NORTE-01-0145-FEDER-000062), supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). The authors acknowledge the work facilities and equipment provided by GECAD research center (UIDB/00760/2020) to the project team.

Subjects

smart building, energy data, IoT data, consumption, generation

Funded by
FCT| UIDB/00760/2020
Project
UIDB/00760/2020
Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development
  • Funder: Fundação para a Ciência e a Tecnologia, I.P. (FCT)
  • Project Code: UIDB/00760/2020
  • Funding stream: 6817 - DCRRNI ID
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