Energy consumption prospective scenarios application on a land use mix - A case study of the Wallonia building stock in Belgium

Abstract

Cities are looking for sustainable ways to manage energy consumption in buildings. Many researchers have been focusing on assessing buildings' energy consumption without considering building categorization. In this study, Entropy and Herfindahl-Hirschman indices are used to create 12 land use mix (LUM) classes at the statistical sector (SS) scale for the Wallonia building stock, including nearly 1.7 million buildings. The categorization of the building stock into classes increases accuracy when applying forecast scenarios to choose the best energy strategies. The innovation consists in applying the concept of LUM to analyze the energy consumption of a large regional building stock and to compare the defined LUM classes with residential built density classes.Demography, degree days, heavy and light renovations, photovoltaic panels (PVs) and 3 mixed scenarios are applied to the created 12 LUM classes to forecast their energy evolution until 2050. Industrial buildings are playing an important role in PVs installation where energy reduction is the highest in the 7th LUM class (medium mix industrial with residential only) with -14.27%. Combining five scenarios results in -35%, -56% and -60% decrease in energy consumption in the 11th LUM class (high mix residential) for mixed scenarios 1, 2 and 3 respectively.