ELECTRICITY CONSUMPTION PATTERN DISAGGREGATION USING NON-INTRUSIVE APPLIANCE LOAD MONITORING METHOD
DOI:
https://doi.org/10.11113/jt.v78.8692Keywords:
Non-intrusive load monitoring, energy management, power consumption disaggregation, energy savingAbstract
In practice, a standard energy meter can only capture the overall electricity consumption and estimating electricity consumption pattern of various appliances from the overall consumption pattern is complicated. Therefore, the Non-Intrusive Appliance Load Monitoring (NIALM) technique can be applied to trace electricity consumption from each appliance in a monitored building. However, the method requires a detailed, second-by-second power consumption data which is commonly not available without the use of high specification energy meter. Hence, this paper analyzes the impact of different time sampling data in estimating the energy consumption pattern of various appliances through NIALM method. This is so that consumers will have an overview of time sampling data which is required in order to apply the NIALM technique. As for the analysis, air-conditioning systems and fluorescent lamps were used in the experimental setup. One minute sample rate was the minimum time interval required by NIALM carried out in this analysis. Through the study presented in this paper, it can be established that higher time sampling led to uncertain appliance detection and low accuracy.
References
Tsai M. S. and Lin Y. H. 2011. Development Of A Non-Intrusive Monitoring Technique For Appliance' Identification In Electricity Energy Management. in Advanced Power System Automation and Protection (APAP), 2011 International Conference on. 108-113.
Yao-Chung F., Xingjie L., Wang-Chien L. and Chen A. L. P. 2012. Efficient Time Series Disaggregation for Non-intrusive Appliance Load Monitoring. in Ubiquitous Intelligence & Computing and 9th International Conference on Autonomic & Trusted Computing (UIC/ATC), 2012 9th International Conference on. 248-255.
Leeb S. B., Shaw S. R., And Kirtley J. L., Jr. 1995. Transient Event Detection In Spectral Envelope Estimates For Nonintrusive Load Monitoring," Power Delivery, IEEE Transactions on. 10: 1200-1210,.
Hart G. W. 1992. Nonintrusive Appliance Load Monitoring. Proceedings of the IEEE. 80:1870-1891.
Cole A. I. and Albicki A. 1998. Data Extraction For Effective Non-Intrusive Identification Of Residential Power Loads. in Instrumentation and Measurement Technology Conference, 1998. IMTC/98. Conference Proceedings. IEEE. 2:812-815.
Zoha A., Gluhak A., Nati M., and Imran M. A. 2013. Low-Power Appliance Monitoring Using Factorial Hidden Markov Models. in Intelligent Sensors, Sensor Networks and Information Processing, 2013 IEEE Eighth International Conference on. 527-532.
Lei J., Jiaming L., Suhuai L., Jin J., and West S. 2011. Literature Review Of Power Disaggregation," in Modelling, Identification and Control (ICMIC), Proceedings of 2011 International Conference on.38-42.
Duarte C., Delmar P., Goossen K. W, Barner K., and Gomez-Luna E.. 2012. Non-Intrusive Load Monitoring Based On Switching Voltage Transients And Wavelet Transforms. in Future of Instrumentation International Workshop (FIIW).1-4.
Yi-Ching S., Kuo-Lung L., and Hsueh-Hsien C. 2011 .Feature Selection of Non-intrusive Load Monitoring System Using STFT and Wavelet Transform," in e-Business Engineering (ICEBE), 2011 IEEE 8th International Conference on,.293-298.
Hsueh-Hsien C., Kuo-Lung L., Yi-Ching S., and Wei-Jen L.. 2013. Energy Spectrum-Based Wavelet Transform For Non-Intrusive Demand Monitoring And Load Identification," in Industry Applications Society Annual Meeting, 2013 IEEE. 1-9.
Janani K. and Himavathi S. 2013. Non-Intrusive Harmonic Source Identification Using Neural Networks. in Computation of Power, Energy, Information and Communication (ICCPEIC), 2013 International Conference on. 59-64.
Hsueh-Hsien C., Ching-Lung L., And Hong-Tzer Y. 2008. Load Recognition For Different Loads With The Same Real Power And Reactive Power In A Non-Intrusive Load-Monitoring System. in Computer Supported Cooperative Work in Design, 2008. CSCWD 2008. 12th International Conference on.1122-1127.
Roos J. G., Lane I. E., Botha E. C., and Hancke G. P. 1994. Using Neural Networks For Non-Intrusive Monitoring Of Industrial Electrical Loads," In Instrumentation and Measurement Technology Conference, 1994. IMTC/94. Conference Proceedings. 10th Anniversary. Advanced Technologies in I & M., 1994 IEEE. 3:1115-1118.
Zoha A., Gluhak A., Imran M., and Rajasegarar S,. 2012. Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey," Sensors. 12: 16838-16866
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