Disaggregating categories of electrical energy end-use from whole-house hourly data
The residential sector uses nearly 30% of all electricity in Canada, and, it is important to know how this energy is being used, so that savings may be identified and realised. We propose a method that can be applied to hourly whole-house electrical energy data to partially disaggregate total household electricity use into five load categories/parameters (base load, activity load, heating season gradient, cooling season gradient and lowest external temperature at which air-conditioning is used). This paper develops the proposed method, and verifies it using high-resolution end-use data from twelve households with known characteristics. We then apply the method to hourly whole-house (smart meter) data from 327 households in Ontario. The roll-out of smart (advanced) metering infrastructure in many countries will make hourly whole-house data abundant, and we propose that this method could be widely applied by utilities to target their demand-side management programs towards households more likely to provide benefits, thus increasing the cost-effectiveness of such programs.
|Keywords||Canada, Electricity, Load disaggregation, Residential, Smart meter|
|Journal||Energy and Buildings|
Birt, B.J. (Benjamin J.), Newsham, G.R. (Guy R.), Beausoleil-Morrison, I, Armstrong, M.M. (Marianne M.), Saldanha, N. (Neil), & Rowlands, I.H. (Ian H.). (2012). Disaggregating categories of electrical energy end-use from whole-house hourly data. Energy and Buildings, 50, 93–102. doi:10.1016/j.enbuild.2012.03.025