The Plegma dataset : domestic appliance-level and aggregate electricity demand with metadata from Greece
Athanasoulias, Sotirios and Guasselli, Fernanda and Doulamis, Nikolaos and Doulamis, Anastasios and Ipiotis, Nikos and Katsari, Athina and Stankovic, Lina and Stankovic, Vladimir (2024) The Plegma dataset : domestic appliance-level and aggregate electricity demand with metadata from Greece. Scientific Data, 11 (1). 376. ISSN 2052-4463 (https://doi.org/10.1038/s41597-024-03208-0)
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Abstract
The growing availability of smart meter data has facilitated the development of energy-saving services like demand response, personalized energy feedback, and non-intrusive-load-monitoring applications, all of which heavily rely on advanced machine learning algorithms trained on energy consumption datasets. To ensure the accuracy and reliability of these services, real-world smart meter data collection is crucial. The Plegma dataset described in this paper addresses this need bfy providing whole- house aggregate loads and appliance-level consumption measurements at 10-second intervals from 13 different households over a period of one year. It also includes environmental data such as humidity and temperature, building characteristics, demographic information, and user practice routines to enable quantitative as well as qualitative analysis. Plegma is the first high-frequency electricity measurements dataset in Greece, capturing the consumption behavior of people in the Mediterranean area who use devices not commonly included in other datasets, such as AC and electric-water boilers. The dataset comprises 218 million readings from 88 installed meters and sensors. The collected data are available in CSV format.
ORCID iDs
Athanasoulias, Sotirios, Guasselli, Fernanda, Doulamis, Nikolaos, Doulamis, Anastasios, Ipiotis, Nikos, Katsari, Athina, Stankovic, Lina ORCID: https://orcid.org/0000-0002-8112-1976 and Stankovic, Vladimir ORCID: https://orcid.org/0000-0002-1075-2420;-
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Item type: Article ID code: 88767 Dates: DateEvent12 April 2024Published2 April 2024AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering > Production of electric energy or power Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 17 Apr 2024 13:55 Last modified: 20 Nov 2024 01:27 URI: https://strathprints.strath.ac.uk/id/eprint/88767