Residential end-use electricity demand: Results from a designed experiment

Being able to disaggregate total energy demand into components attributable to specific end uses provides useful information and represents a primary input into any attempt to simulate the impact of policies aimed at encourag ing households to use less energy or shift load. Conceptually the estimatio n problem can be solved by directly metering individual appliances. Not sur prisingly, this has not been widely practised and by far the most common es timation procedure has been the indirect statistical approach known as cond itional demand analysis. More recently, with access to limited direct meter ing, both approaches have been used in combination. This paper reports on a substantial modelling exercise that represents a unique example of combini ng data of this type. The distinctive aspects are the extent and richness o f the metering data and the fact that optimal design techniques were used t o decide on the pattern of metering. As such, the empirical results are abl e to provide a very detailed and accurate picture of how total residential load is disaggregated by end uses. Significantly, the consumption of high p enetration end uses such as lighting, which cannot be estimated by conventi onal conditional demand analysis, has been successfully estimated. Also, by matching our estimates of end-use load curves with some recent prices paid by distributors to purchase electricity from an electricity market pool, w e have been able to determine the costs to distributors associated with ser vicing individual end uses.