Electrical load disambiguation for end-use recognition in the residential sector has become an area of study of its own right. Several works have shown that individual loads can be detected (and separated) from sampling of the power at a single point (e.g. the electrical service entrance for the house) using a non-intrusive load monitoring (NILM) approach. This work presents the development of an algorithm for electrical feature extraction and pattern recognition, capable of determining the individual consumption of each device from the aggregate electric signal of the home. Namely, the idea consists of analyzing the electrical signal and identifying the unique patterns that occur whenever a device is turned on or off by applying signal processing techniques. We further describe our technique for distinguishing loads by matching different signal parameters (step-changes in active and reactive powers and power factor) to known patterns. Computational experiments show the effectiveness of the proposed approach.
Keywords
feature extraction and classification, k-nearest neighbors, non-intrusive load monitoring, steady-state signatures, support vector machines
Subject
Non-Intrusive Load Monitoring Systems
Conference
Proc Intl Conf on Adaptive and Natural Computing Algorithms, pp 31-40, Part II, LNCS 6594, April 2011
Cited by
Year 2018 : 2 citations
Wang, Huijuan and Yang, Wenrong. "An Iterative Load Disaggregation Approach Based on Appliance Consumption Pattern", Applied Sciences, 8(4), 542, 2018
de Paiva Penha, D., Castro, A.R.G., HOME APPLIANCE IDENTIFICATION FOR NILM SYSTEMS BASED ON DEEP NEURAL NETWORKS, International Journal of Artificial Intelligence and Applications (IJAIA), Vol.9, No.2, 2018.
Year 2017 : 3 citations
N. Sadeghianpourhamami, , J. Ruyssinck , D. Deschrijver , T. Dhaene , C. Develder. "Comprehensive Feature Selection for Appliance Classification in NILM", Energy and Buildings, 10.1016/j.enbuild.2017.06.042 (In Press- Available online 23 June 2017)
Maher Azazaa, Fredrik Wallin."Evaluation of classification methodologies and Features selection from smart meter data", Energy Procedia, Volume 142,Pages 2250–2256. 2017.[DOI:10.1016/j.egypro.2017.12.626]
Yang, C. C., Soh, C. S., Yap, V. V. A systematic approach in appliance disaggregation using k-nearest neighbours and naive Bayes classifiers for energy efficiency. Energy Efficiency, (Online: 21 August 2017; doi: 10.1007/s12053-017-9561-0)
Year 2016 : 3 citations
Chinthaka D., Pramuditha P., Roshan .G, MervynE.1, Janaka E., Non-intrusive load monitoring based on low frequency active power measurements, AIMS Energy, 2016, 4(3): 414-443.
Paradiso, Francesca, et al. "Context-Based Energy Disaggregation in Smart Homes." Future Internet 8.1 (2016): 4.
I. Vassileva, J. Campillo. Consumers' Perspective on Full-Scale Adoption of Smart Meters: A Case Study in Västerås, Sweden. Resources 2016, 5(1), 3; doi:10.3390/resources5010003 [edit]
Year 2015 : 3 citations
Ding Li, Sawyer, K., Dick, S. Disaggregating household loads via semi-supervised multi-label classification IEEE Proc Annual Conference of the North American on Fuzzy Information Processing Society (NAFIPS) 17-19 Aug. 2015 DOI: 10.1109/NAFIPS-WConSC.2015.7284144
Adabi, A. ; Baskin ; Mantey, P. ; Holmegaard, E. ; Kjaergaard, M.B. Status and challenges of residential and industrial non-intrusive load monitoring. Technologies for Sustainability (SusTech), 2015 IEEE Conference on, pp. 181 - 188, 10.1109/SusTech.2015.7314344
Chuan Choong Yang, Chit Siang Soh, Vooi Voon Yap. A systematic approach to ON-OFF event detection and clustering analysis of non-intrusive appliance load monitoring. Frontiers in Energy, Springer. DOI 10.1007/s11708-015-0358-6
Year 2014 : 6 citations
Tabatabaei, Seyed Mostafa. Decomposition Techniques for Non-intrusive Home Appliance Load Monitoring. Master Diss. University of Alberta, Canada, (2014).
F. Koufogiannis, Shuo Han, and George J. Pappas. "Computation of privacy-preserving prices in smart grids." IEEE Conference on Decision and Control. Los Angeles, CA, USA. (2014)
V Debusschere, K Basu, S Bacha, Identification et prédiction non intrusive de l'état des charges dans les bâtiments résidentiels à partir de mesures compteur à échantillonnage réduit, Symposium de Génie Électrique 2014.
Naghibi, B., Deilami, S. "Non-intrusive load monitoring and supplementary techniques for home energy management ". IEEE Proc 2014 Australasian Universities Power Engineering Conference, pp. 1-5, (AUPEC), (2014)
H. S. Kolahi, K. R. Milani, " A Novel Power Tariff Model for the Future Smart Homes". CIRED Workshop, Rome, June 2014, Paper 0373 (6p)
Kolahi, H.S., Milani, K.R., Nasiri, A., A Novel Power Tariff Model for the Future Smart Homes in Iran, Proceedings of the 2nd Iranian Regional CIRED, Tehran, Iran, No. 14-E-AAA-000, 2014.
Year 2013 : 3 citations
Wong, Y. F.; Ahmet Sekercioglu, Y.; Drummond, T.; Wong, V. S., "Recent approaches to non-intrusive load monitoring techniques in residential settings," IEEE Symposium on Computational Intelligence Applications In Smart Grid, 2013, pp.73-79, 2013, doi: 10.1109/CIASG.2013.6611501
Chou, Po-An and Chang, Ray-I, "Unsupervised Adaptive Non-intrusive Load Monitoring System", Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on, (Oct) pp. 3180-3185, 2013. DOI: 10.1109/SMC.2013.542
Basu, K., Debusschere, V. ; Bacha, S., "Residential appliance identification and future usage prediction from smart meter", Proc. Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE, 4994-4999, 2013, doi: 10.1109/IECON.2013.6699944
Year 2012 : 3 citations
Po-An Chou; Chi-Cheng Chuang; Ray-I Chang, "Automatic appliance classification for non-intrusive load monitoring," Power System Technology (POWERCON), 2012 IEEE International Conference on , vol., no., pp.1,6, Oct. 30 2012-Nov. 2 2012
doi: 10.1109/PowerCon.2012.6401409
Ahmed Zoha; Alexander Gluhak; Muhammad A. Imran; Sutharshan Rajasegarar; "Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey." Sensors, vol. 12, no. 12, pp: 16838-16866, 2012.
Basu, K. ; Debusschere, V. ; Bacha, S.; " Load identification from power recordings at meter panel in residential households", IEEEXplore: Electrical Machines (ICEM), 2012 XXth International Conference on, 2098 - 2104, 2012.
Year 2011 : 1 citations
Oliver Parson, "Using Hidden Markov Models for Non-intrusive Appliance Load Monitoring".
Tech. Report, School of Electronics and Computer Science, Faculty of Physical and Applied Science, Univ. of Southampton, 2011.
