Kenneth H. Tiedemann
End-use consumption, conditional demand analysis, statistical modelling
Utilities require detailed end-use energy consumption for power system planning, load forecasting, marketing and demand side management. End-use consumption refers to the consumption of space heating, space cooling, water heating, lighting and other specific uses as opposed to total consumption. This report presents the methodology and results of a commercial electricity end-use study for British Columbia, Canada. The study used Conditional Demand Analysis (CDA) to estimate unit energy consumption (UEC) values for the main commercial establishment end-uses. Conditional demand analysis is a multivariate regression technique which combines utility billing data with weather information and customer survey data to produce robust end-use energy consumption estimates. Very few studies have used CDA to model commercial electricity consumption by end-use, and some attempts have found that gaining an adequate level of precision is difficult. The main contribution of this paper is to show that by using a carefully designed survey administered to a large number of commercial customers, CDA can be used to model robust and accurate estimates of commercial end-use electricity consumption.
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