期刊
ENERGY AND BUILDINGS
卷 96, 期 -, 页码 109-117出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2015.03.021
关键词
Load monitoring; Time series; Dynamic time warping; Data mining; Smart meter; Smart buildings
资金
- project SuperBat
- project Paradise
- National Research Agency (ANR), France [ANR-10-HABI-0011]
- Agence Nationale de la Recherche (ANR) [ANR-10-HABI-0011] Funding Source: Agence Nationale de la Recherche (ANR)
Non-intrusive load monitoring (NILM) deals with the disaggregation of individual appliances from the total load at the smart meter level. This work proposes a generic methodology using temporal sequence classification algorithms. 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 (HMM) algorithm. The method is validated over a data-set of 100 houses for a duration of 1 year (with a 10 min sampling rate). A qualitative analysis of the database is also conducted, allowing to segment it into four major clusters based on discussed features. (C) 2015 Elsevier B.V. All rights reserved.
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