Viability and accessibility of the Great Lakes microclimate data over current TMY weather data for accurate energy demand predictions

Abstract

As climate change continues to evolve with alarming increases in extreme weather conditions, its impact on building cooling and heating energy needs, in order to maintain acceptable occupant comfort becomes increasingly beyond the design constraints. To reduce such mismatch, it is important to improve the accuracy of weather files used for building energy simulations (BES). The widely used simulation software, EnergyPlus (EP) provides Typical Meteorological Year (TMY) weather data, which are not designed to detect extreme conditions and have limited data locations. There is a greater number of Microclimate (MC) stations that can be incorporated into BES for higher resolution data. The challenge is the time-consuming data preparation process to match the EP format. To address this issue, the co-authors developed a program, Virtual Information Fabric Infrastructure (VIFI), which automatically prepares MC data for more accurate BES. To demonstrate the need for higher resolution data, this study analyzed locations in the Great Lakes region and found that July's cooling demand for Rogers City MI and Alpena MI, which are located 35 mi (56 km) apart, differed by 19%. The results emphasize the importance of considering MC data in BES and provide a solution for their efficient integration into BES.