Modelling the Electricity Consumption of Small to Medium Enterprises

Abstract

Estimating the demand on the low voltage network is essential for the distribution network operator (DNO), who is interested in managing and planning the network. Such concerns are particularly relevant as the UK moves towards a low carbon economy, and the electrification of heating and transport. Furthermore, small to medium enterprises (SMEs) contribute a significant proportion to network demand but are often overlooked. The smart meter roll out will provide greater visibility of the network, but such data may not be readily available to the DNOs. The question arises whether useful information about customer demand can be discerned from limited access to smart meter data? We analyse smart meter data from 196 SMEs so that one may create an energy demand profile based on information which is available without a smart meter. The profile itself comprises of simply two estimates, one for operational power and another for non-operational power. We further improve the profile by clustering the SMEs using a simple Gaussian mixture model. In both cases, the average difference between the actual and predicted operational/non-operational power is less than 0.15 kWh, and clustering reduces the range around this difference. The methods presented here out perform the flat profile (akin to current methods).