Publications / 2013 Proceedings of the 30th ISARC, Montréal, Canada

Novel Techniques for the Detection of ON and OFF States of Appliances for Power Estimation in Non-Intrusive Load Monitoring

Suman Giri, Po-Hsiang Lai, Mario Bergés
Pages 522-530 (2013 Proceedings of the 30th ISARC, Montréal, Canada, ISBN 978-1-62993-294-1, ISSN 2413-5844)

Non-Intrusive Load Monitoring (NILM) is a method of extracting appliance-level power consumption information from aggregate circuit-level data with the goal of giving users feedback regarding their energy consumption so they can take control of their consumption habits. In this paper, we present a novel algorithm for classification of on and off states of appliances. We compare the performance of our algorithm in on state detection with a pervious paper that evaluated the same dataset and show that it performs up to 13% better. We also present the results of a case study where we collected data for different modes of a cooktop, microwave and dishwasher and used our algorithms to perform power estimation. The error on ten different setups in the test bed ranges from 1% to 32%. We discuss our results and lay out ideas for future work.

Keywords: Non-Intrusive Load Monitoring, Energy Disaggregation, Energy Efficiency, Machine Learning, Power Estimation, Normalization.