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Title: Analysis of trends in seasonal electrical energy consumption via non-negative tensor factorization
Authors: Figueiredo, M.
Ribeiro, B.
de Almeida, A.
Keywords: Non-negative tensor factorization
Electrical signal disaggregation
Non-intrusive load monitoring (NILM)
Energy efficiency
Issue Date: 2015
Publisher: Elsevier
Abstract: This paper looks at the extraction of trends of household electrical seasonal consumption via load disaggregation. With the proviso that data for several home devices can be embedded in a tensor, non-negative multi-way array factorization is performed in order to extract the most relevant components. In the initial decomposition step the decomposed signals are incorporated in the test signal consisting of the whole-home measured consumption. After this the disaggregated data corresponding to each electrical device is obtained by factorizing the associated matrix through the learned model. Finally, we evaluate the performance of load disaggregation by the supervised method, and study the trends along several years and across seasons. Towards this end, computational experiments were yielded using real-world data from household electrical consumption measurements along several years. While breaking down the whole house energy consumption into appliance level gives less accurate estimates in the late years, we empirically show the adequacy of this method for handling the earlier years and the estimates of the underlying seasonal trend-cycle.
Peer reviewed: yes
DOI: 10.1016/j.neucom.2015.03.088
ISSN: 0925-2312
Accession number: WOS:000361256000032
Appears in Collections:CTI-RI - Artigos em revistas científicas internacionais com arbitragem científica

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