Abstract : Non-Intrusive Load Monitoring (Nilm) deals with the disaggregation of in- dividual appliances from the total load at the smart meter level. This work proposes a generic methodology using temporal sequence classification algo- rithms. It is based on a low sampling rate unlike other approaches in this domain. An innovative time series distance-based approach in the temporal classification domain is compared with a standard Nilm application based on the Hidden Markov Model algorithm (Hmm). The method is validated over a data-set of 100 houses for a duration of one year (with a 10 minutes sampling rate). A qualitative analysis of the database is also conducted, allowing to segment it into four major clusters based on discussed features.
https://hal.archives-ouvertes.fr/hal-01208468
Contributeur : Ahlame Douzal <>
Soumis le : vendredi 2 octobre 2015 - 15:57:43
Dernière modification le : jeudi 6 avril 2017 - 01:02:23
Kaustav Basu, Vincent Debusschere, Ahlame Douzal-Chouakria, Seddik Bacha. Time series distance-based methods for non-intrusive load monitoring in residential buildings. Energy and Buildings, Elsevier, 2015, 96 (109–117). <hal-01208468>
