The Plegma dataset: Domestic appliance-level and aggregate electricity demand with metadata from Greece.

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 e

SUBMITTER: Athanasoulias S 

PROVIDER: S-EPMC11014970 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature