Jump model learning and filtering for energy end-use disaggregation. Issue 15 (2018)

• Record Type: Journal Article
• Authors: Breschi, V.; Piga, D.; Bemporad, A.
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 15(2018)
• Page Start: 275
• Page End: 280
• Publication Date: 2018
• Subjects: Jump models -- Filtering -- Energy disaggregation -- Non-intrusive appliance load monitoring -- Recursive estimate; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.09.147
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Energy disaggregation aims at reconstructing the power consumed by each electric appliance available in a household from the aggregate power readings collected by a single-point smart meter. With the ultimate goal of fully automatizing this procedure, we first estimate a set of jump models, each of them describing the consumption behaviour of each electric appliance. By representing the total power consumed at the household level as the sum of the outputs of the estimated jump models, a filtering algorithm, based on dynamic programming, is then employed to reconstruct, in an iterative way, the power consumption at an individual appliance level.