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Novel Techniques for the Detection of ON and OFF States of Appliances for Power Estimation in Non-Intrusive Load Monitoring
| Content Provider | Semantic Scholar |
|---|---|
| Author | Giri, Suman Lai, Po-Hsiang Berges, Mario |
| Copyright Year | 2013 |
| Abstract | 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. |
| Starting Page | 522 |
| Ending Page | 530 |
| Page Count | 9 |
| File Format | PDF HTM / HTML |
| DOI | 10.22260/ISARC2013/0056 |
| Alternate Webpage(s) | http://www.iaarc.org/publications/fulltext/isarc2013Paper184.pdf |
| Alternate Webpage(s) | https://doi.org/10.22260/ISARC2013%2F0056 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
