Name
Abstract | ||
|---|---|---|
Current methods for nonintrusive load monitoring (NILM) problems assume that the number of appliances in the target location is known, however, this may not be realistic. In real-world situations, the initial setup of the site can be known but new appliances may be added by users after a period of time, especially in a household or nonrestrictive scenarios. In this sense, current methods without detecting new appliances may not accurately monitor loads of different appliances and scenarios. In this paper, a novel new appliance detection method is proposed for NILM with imbalance classification for appliances switching
<sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ON</sc>
or
<sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">OFF</sc>
. The prediction of appliances being switched
<sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ON</sc>
or
<sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">OFF</sc>
is an important step in load monitoring and the switching on frequencies for coffee machine and air conditioning in a household are different, making the problem inherently imbalanced. Experimental results show that the proposed method yields outstanding performance against the well-known oversampling method, synthetic minority oversampling technique, on real NILM applications in scenarios with new appliances emerging. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/tii.2019.2916213 | IEEE Transactions on Industrial Informatics |
Keywords | Field | DocType |
Monitoring,Home appliances,Noise measurement,Switches,Training,Hidden Markov models,Sensors | Nonintrusive load monitoring,Air conditioning,Noise measurement,Oversampling,Computer science,Real-time computing,Control engineering,Hidden Markov model | Journal |
Volume | Issue | ISSN |
15 | 8 | 1551-3203 |
Citations | PageRank | References |
1 | 0.36 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianjun Zhang | 1 | 9 | 3.48 |
| Xuanqun Chen | 2 | 1 | 0.36 |
| Wing W. Y. Ng | 3 | 528 | 56.12 |
| Chun Sing Lai | 4 | 41 | 15.62 |
| Loi Lei Lai | 5 | 135 | 38.72 |