261: Implications of varying weather data sets for predictions of thermal performance of buildings

This paper explores the implications of different input assumptions pertaining to local weather conditions (as represented in weather files) for computational predictions of buildings' thermal performance. As a case in point, we used twenty two distinctive weather files (based on meteorological data from different weather stations, different years) for the city of Vienna to compute heating and cooling energy demands of three different buildings. The results demonstrate the significant fluctuations in the buildings' predicted heating and cooling energy demand due to differences in micro-climatic assumptions. We explored the possibility to assess the impact of projected changes in standard micro-climatic indicators such as heating degree days and cooling degree hours on the buildings' heating and cooling loads.