Abstract
Designers of commercial building's heating, ventilation and air-conditioning (HVAC) systems use typical weather data adjusted with global climate models (known as “morphing”) to obtain data reflecting climate change. Previous studies have found that climate change will increase annual cooling energy by 27–47% and peak cooling demand between 28 and 59% by 2070, but have not explored 2050 timeframes, extreme weather scenarios, nor examined thermal comfort beyond degree-day assessments. This study investigates the use of extreme weather datasets in HVAC building simulation to assess traditional HVAC system sizing methods under extreme conditions, as climate change will lead to more severe and frequent extreme weather events. This study also aims to quantify the impact of climate change on energy use, peak demand, and thermal comfort for a typical commercial building in the four most-populated Köppen-Geiger climates. A typical commercial office building was modelled in OpenStudio using Energy-Plus Weather (EPW) datasets using eight extreme weather scenarios constructed from historic weather data for each climate. Two downscaling morphing methodologies were used to prepare future weather datasets for 2050. The results show datasets with higher variability increase peak cooling demand up to 35% and unmet cooling hours up to 189%, a significant increase over a shorter timeframe than previously reported. A methodology to include extreme hot and cold weather conditions and datasets, in addition to typical conditions, is proposed to future-proof HVAC system design against the impacts of climate change across the most populated global climates.
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