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| Title | Efficient time series disaggregation for non-intrusive appliance load monitoring |
| Creator | Fan, Y.-C.;Liu, X.;Lee, W.-C.;Chen, Arbee L. P. 陳良弼 |
| Contributor | 資科系 |
| Key Words | Computing technology; Disaggregation; Electrical appliances; Electrical circuit; Energy cost; Energy monitoring; Green Computing; Load forecasting; Load separation; Non-intrusive; Non-intrusive appliance load monitoring; Nonintrusive load monitoring; Novel techniques; Pattern recognition algorithms; Research studies; Search space pruning; Algorithms; Electric load forecasting; Electric load management; Environmental technology; Estimation; Global warming; Pattern recognition; Separation; Time series; Ubiquitous computing |
| Date | 2012 |
| Date Issued | 10-Apr-2015 17:26:17 (UTC+8) |
| Summary | 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. © 2012 IEEE. |
| Relation | Proceedings - IEEE 9th International Conference on Ubiquitous Intelligence and Computing and IEEE 9th International Conference on Autonomic and Trusted Computing, UIC-ATC 2012 10.1109/UIC-ATC.2012.122 |
| Type | conference |
| DOI | http://dx.doi.org/10.1109/UIC-ATC.2012.122 |
| dc.contributor | 資科系 | |
| dc.creator (作者) | Fan, Y.-C.;Liu, X.;Lee, W.-C.;Chen, Arbee L. P. | |
| dc.creator (作者) | 陳良弼 | zh_TW |
| dc.date (日期) | 2012 | |
| dc.date.accessioned | 10-Apr-2015 17:26:17 (UTC+8) | - |
| dc.date.available | 10-Apr-2015 17:26:17 (UTC+8) | - |
| dc.date.issued (上傳時間) | 10-Apr-2015 17:26:17 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/74489 | - |
| dc.description.abstract (摘要) | 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. © 2012 IEEE. | |
| dc.format.extent | 176 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | Proceedings - IEEE 9th International Conference on Ubiquitous Intelligence and Computing and IEEE 9th International Conference on Autonomic and Trusted Computing, UIC-ATC 2012 | |
| dc.relation (關聯) | 10.1109/UIC-ATC.2012.122 | |
| dc.subject (關鍵詞) | Computing technology; Disaggregation; Electrical appliances; Electrical circuit; Energy cost; Energy monitoring; Green Computing; Load forecasting; Load separation; Non-intrusive; Non-intrusive appliance load monitoring; Nonintrusive load monitoring; Novel techniques; Pattern recognition algorithms; Research studies; Search space pruning; Algorithms; Electric load forecasting; Electric load management; Environmental technology; Estimation; Global warming; Pattern recognition; Separation; Time series; Ubiquitous computing | |
| dc.title (題名) | Efficient time series disaggregation for non-intrusive appliance load monitoring | |
| dc.type (資料類型) | conference | en |
| dc.identifier.doi (DOI) | 10.1109/UIC-ATC.2012.122 | en_US |
| dc.doi.uri (DOI) | http://dx.doi.org/10.1109/UIC-ATC.2012.122 | en_US |