Providing the users information on the energy consumed in the household at the appliance level is of major importance for increasing their awareness of their consumption behavior. In this paper, we propose a technique based on Kalman filters to estimate the devices’ consumption patterns from aggregate readings, i.e., to solve the so called disaggregation problem. The method is suited for on-line disaggregation and the proposed results show that it is robust against modelling errors and unmodelled appliances.

Kalman filtering for energy disaggregation

Breschi V.;
2018

Abstract

Providing the users information on the energy consumed in the household at the appliance level is of major importance for increasing their awareness of their consumption behavior. In this paper, we propose a technique based on Kalman filters to estimate the devices’ consumption patterns from aggregate readings, i.e., to solve the so called disaggregation problem. The method is suited for on-line disaggregation and the proposed results show that it is robust against modelling errors and unmodelled appliances.
Proceedings of the 1st IFAC Workshop on Integrated Assessment Modelling for Environmental Systems IAMES 2018
Energy disaggregation
Kalman filter
Markov jump models
recursive estimate
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1167012
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