22-24 September 2021
Alpen-Adria-Universität Klagenfurt
Europe/Vienna timezone

iPALM-based unsupervised energy disaggregation

22 Sep 2021, 15:30
20m
HS 1 (Alpen-Adria-Universität Klagenfurt)

HS 1

Alpen-Adria-Universität Klagenfurt

Speaker

Christian Aarset (University of Graz)

Description

With smart energy meters increasingly available to private households, new applications arise, such as identifying main power consuming devices and predicting human activity. One major obstacle is that smart energy meters typically provide aggregated data, where each source of energy consumption is summed. Further, obtaining training data can be intrusive. To counteract this, we propose an unsupervised minimization approach based on the Inertial Proximal Alternating Linearized Minimization (iPALM) algorithm, utilising convolutional sparse coding to represent individual device energy signatures as atoms convolved with sparse coefficient vectors.

Primary author

Christian Aarset (University of Graz)

Co-authors

Prof. Martin Holler (University of Graz) Andreas Habring (University of Graz)

Presentation Materials

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