Estimation, analysis and mapping of electricity consumption of a regional building stock in a temperate climate in Europe

Abstract

This study financed by ERDF and the Wallonia Region estimates the annual electricity consumption (EC) of building stock, including the 3 building sectors namely residential, tertiary and industrial building. The estimation takes into account appliances, electrical heating, cooling, lighting, cooking and EC by m2 on a building level. The results are spatialized on different territorial scales. Using cadastral data of more than 1,700,000 Walloon buildings and annual EC data from a sample collected in 2012 from the energy reports, the paper assesses the EC of the whole building stock and tests to what extent different types of variables (building factors and socio-demographics) explain annual EC. It then shows which individual variables have the highest explanatory power. In contrast to many other studies, the research recognizes the problem of multicollinearity between predictors in regression analysis and uses Lasso regression to address this issue. Three separate regression models were used to study the predictors of annual EC of residential, tertiary and industrial buildings. EC building factors (appliances, auxiliary and main heating, domestic hot water and cooking) explained the largest share which is 66.46% of the variability in EC for residential buildings whereas the EC usages share for tertiary buildings (lighting, heating and domestic hot water, air conditioning, cooling, etc.) is about 50.53% and 38.55% for industrial buildings. Socio-demographic variables on their own explained about 61.59%, 26.34% and 3.41% of the annual EC, respectively for residential, tertiary and industrial buildings. Hence, the building variables present the highest explanatory power for EC, presumably because heating and cooling EC are included in this study. The study highlights that when attempting to explain EC related to Walloon households, including heating and cooling EC, appliances usage has the strongest predictive power in residential buildings. On the other hand, the projected decrease in EC use for heating in existing residential buildings is −8.82% and −10% for existing tertiary buildings while the projected increase in EC use for cooling in existing tertiary buildings is + 11.94% from 2012 to 2050 on a regional scale. These trends follow the predicted regional heating degree-days (HDD) of −11.76% and cooling degree-days (CDD) of 14.04% for the same period based on the gated recurrent unit (GRU) an implemented deep learning (DL) model. In addition, the produced EC maps on different territorial scales show that the highest EC is seen in large and main cities in general.