A statistical analysis of the relationship between domestic hot water consumption and mean outdoor temperature in Budapest

Abstract

This study analyzes how outdoor temperature influences domestic hot water consumption in multiapartment large-panel system buildings in Budapest, Hungary. The analysis is based on data from the validated invoicing system of the district heating provider, and from two weather stations of the Hungarian Meteorological Service. The official monthly hot water consumption data of 72 buildings for 7 consecutive years and the corresponding monthly mean temperatures were used in this study. Linear regression analysis and time series decomposition were carried out. The results prove that the outdoor temperature and the domestic hot water consumption are definitely related. The model based on regression analysis could account for 74% of values. The time series decomposition model is able to estimate hot water consumption per apartment per day for a future month with 94% probability. The study relies on data obtained from a projection of two regional climate models each, namely ALADIN-Climate and RegCM. Based on these data, the model forecasts how the effects of climate change will probably influence domestic hot water consumption in the near future. These results shed light on the factors influencing hot water consumption, and may help authorities and decision makers to form sustainability policies and to plan sustainable resource management.