Efficient time series disaggregation for non-intrusive appliance load monitoring

Yao Chung Fan, Xingjie Liu, Wang-chien Lee, Arbee L.P. Chen

Research output: Contribution to conferencePaper

5 Citations (Scopus)

Abstract

The growing concerns on urgent environmental and economical issues, such as global warming and rising energy cost, have motivated research studies on various green computing technologies. For example, Non-Intrusive Appliance Load Monitor (NIALM) techniques, aiming at energy monitoring, load forecasting and improved control of residential electrical appliances, have been developed by monitoring one electrical circuit that contains a number of electrical appliances without using separate sub-meters. By employing pattern recognition algorithms, the NIALM techniques estimate the consumption of individual appliances. While the basic ideas behind the NIALM techniques are valid, existing proposals suffer from the issue of poor estimation accuracy. In this paper, we model the process of load separation in NIALM as a time series disaggregation problem. Aiming at achieving high estimation accuracy and alleviating excessive computation, we develop a time-series disaggregation algorithm which incorporates two novel techniques, namely, DE-pruning and monotonic enumeration, for search space pruning. A comprehensive set of experiments are conducted to validate our proposals and to evaluate the effectiveness and the efficiency of the proposed methods. The result shows that our proposal is effective and efficient.

Original languageEnglish (US)
Pages248-255
Number of pages8
DOIs
StatePublished - Nov 28 2012
Event9th IEEE International Conference on Ubiquitous Intelligence and Computing, UIC 2012 and 9th IEEE International Conference on Autonomic and Trusted Computing, ATC 2012 - Fukuoka, Japan
Duration: Sep 4 2012Sep 7 2012

Other

Other9th IEEE International Conference on Ubiquitous Intelligence and Computing, UIC 2012 and 9th IEEE International Conference on Autonomic and Trusted Computing, ATC 2012
CountryJapan
CityFukuoka
Period9/4/129/7/12

Fingerprint

Time series
Monitoring
Global warming
Pattern recognition
Networks (circuits)
Costs
Experiments
Green computing

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications

Cite this

Fan, Y. C., Liu, X., Lee, W., & Chen, A. L. P. (2012). Efficient time series disaggregation for non-intrusive appliance load monitoring. 248-255. Paper presented at 9th IEEE International Conference on Ubiquitous Intelligence and Computing, UIC 2012 and 9th IEEE International Conference on Autonomic and Trusted Computing, ATC 2012, Fukuoka, Japan. https://doi.org/10.1109/UIC-ATC.2012.122
Fan, Yao Chung ; Liu, Xingjie ; Lee, Wang-chien ; Chen, Arbee L.P. / Efficient time series disaggregation for non-intrusive appliance load monitoring. Paper presented at 9th IEEE International Conference on Ubiquitous Intelligence and Computing, UIC 2012 and 9th IEEE International Conference on Autonomic and Trusted Computing, ATC 2012, Fukuoka, Japan.8 p.
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Fan, YC, Liu, X, Lee, W & Chen, ALP 2012, 'Efficient time series disaggregation for non-intrusive appliance load monitoring' Paper presented at 9th IEEE International Conference on Ubiquitous Intelligence and Computing, UIC 2012 and 9th IEEE International Conference on Autonomic and Trusted Computing, ATC 2012, Fukuoka, Japan, 9/4/12 - 9/7/12, pp. 248-255. https://doi.org/10.1109/UIC-ATC.2012.122

Efficient time series disaggregation for non-intrusive appliance load monitoring. / Fan, Yao Chung; Liu, Xingjie; Lee, Wang-chien; Chen, Arbee L.P.

2012. 248-255 Paper presented at 9th IEEE International Conference on Ubiquitous Intelligence and Computing, UIC 2012 and 9th IEEE International Conference on Autonomic and Trusted Computing, ATC 2012, Fukuoka, Japan.

Research output: Contribution to conferencePaper

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Fan YC, Liu X, Lee W, Chen ALP. Efficient time series disaggregation for non-intrusive appliance load monitoring. 2012. Paper presented at 9th IEEE International Conference on Ubiquitous Intelligence and Computing, UIC 2012 and 9th IEEE International Conference on Autonomic and Trusted Computing, ATC 2012, Fukuoka, Japan. https://doi.org/10.1109/UIC-ATC.2012.122