Using a pattern recognition approach to disaggregate the total electricity consumption in a house into the major end-uses

The method presented in this paper shows a promising potential for application in residential buildings. The results prove that the whole-house electricity consumption can be disaggregated into its major end-uses, using a pattern recognition approach and only one sensor installed on the main electric entrance of the house. It also required a one-time submetering of the target appliances during the training period, of about a week, to find the electric characteristics of appliances. The results are provided in terms of daily load profiles, energy consumption and energy contribution of selected appliances. The proposed method was tested with monitored data from 3 weeks: (i) the training period of 1 week in October, (ii) the near-to-date testing period of 1 week in November and (iii) the far-to-date testing period of 1 week in January. For instance, the difference between monitored and estimated contribution is, for the month of October 1996, as follows: (i) 13 kW h or $0.85 for the DHW heater and (ii) 6 kW h or $0.36 for the refrigerator. The overall difference for both appliances does not exceed $1.25 for the month of October, for a total electricity bill of 912 kW h and $60.60, which appears to be acceptable for every homeowner. The errors in evaluating the daily energy consumption is between −10.5% and 15.9% for both the DWH heater and the refrigerator.