The energy and water demand is growing at an increasing rate on a global scale. This trend is especially pronounced in urban areas, which expand rapidly in size and population. At the same time, there is strong evidence to suggest that urban buildings are a major contributor to the resource and emissions footprint of human activity. For this reason, there are a number of initiatives, on a global and national level, to assess and improve the energy efficiency of buildings. This paper presents the development of a fast method for modelling the electricity, water consumption and indoor air temperature of a municipal kindergarten building in Sofia, Bulgaria. The models utilise a hybrid approach to analysing the data and successfully represents its trend. The use of statistical methods results in highly interpretable results, which can be built upon with more sophisticated techniques to achieve increased accuracy.

The 7th IEEE International Conference on Smart and Sustainable Technologies (SpliTech 2022). July 5-8, 2022, Bol and Split, Croatia