The building sector is accountable for about one-third of the global energy consumption and contributes to 19% of greenhouse gas (GHG) emissions relating to energy processes. Given the changing climate and its impact on building heating and cooling demands, energy models based on historical weather data cannot accurately simulate the performance of a building in the future. Accordingly, this paper generated several future weather data sets and applied them to the energy simulation of 16 ASHRAE reference building models for Toronto, Canada. Both statistical and dynamical downscaling techniques were used for generating these future weather files. The results indicate an average decrease of 17.8-27.2% in heating loads and an average increase of 13.5-55.4% in cooling loads, depending on the building type, leading to an overall decrease in energy use intensity (EUI) for the majority of the 16 reference building models. It is concluded that the application of future weather files for building performance simulation leads to a more realistic quantification of building energy demand in the future. Furthermore, depending on the availability and accuracy of regional climate models (RCM), the weather files generated using dynamical downscaling provide a more reliable forecast of the local boundary conditions for building performance simulation.
Building energy demand within a climate change perspective: The need for future weather file / Pouriya, J.; Berardi, U.. - In: IOP CONFERENCE SERIES: MATERIALS SCIENCE AND ENGINEERING. - ISSN 1757-8981. - 609:7(2019). [10.1088/1757-899X/609/7/072037]
Building energy demand within a climate change perspective: The need for future weather file
Berardi U.
2019-01-01
Abstract
The building sector is accountable for about one-third of the global energy consumption and contributes to 19% of greenhouse gas (GHG) emissions relating to energy processes. Given the changing climate and its impact on building heating and cooling demands, energy models based on historical weather data cannot accurately simulate the performance of a building in the future. Accordingly, this paper generated several future weather data sets and applied them to the energy simulation of 16 ASHRAE reference building models for Toronto, Canada. Both statistical and dynamical downscaling techniques were used for generating these future weather files. The results indicate an average decrease of 17.8-27.2% in heating loads and an average increase of 13.5-55.4% in cooling loads, depending on the building type, leading to an overall decrease in energy use intensity (EUI) for the majority of the 16 reference building models. It is concluded that the application of future weather files for building performance simulation leads to a more realistic quantification of building energy demand in the future. Furthermore, depending on the availability and accuracy of regional climate models (RCM), the weather files generated using dynamical downscaling provide a more reliable forecast of the local boundary conditions for building performance simulation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.