Comparing Typical Meteorological Year Data with New Weather Data Sets in Building Energy Analysis Under Climate Change

초록

As the impacts of climate change become more apparent, the reliance on Typical Meteorological Year (TMY) data for dynamic energy simulations may no longer accurately reflect current conditions. This study examines the differences in energy consumption using TMY data sets constructed from different year ranges, incorporating recent weather data to improve the reliability of energy performance simulations. The study involves generating five distinct weather datasets using meteorological data from 2004 to 2023. Specifically, TMY datasets were created from the periods 2004-2023 and 2014-2023, MY (Multi-Year) sets from 2019-2023 and 2021-2023, and an AMY (Actual Meteorological Year) for the single year 2023. The study then calculates and compares heating and cooling degree days across these datasets. The degree-day method is used to compare the heating and cooling degree days, showing that the cooling degree days increase, and the heating degree days decrease as the TMY data sets include more recent years, reflecting a warming climate. Dynamic energy simulations were performed on two case study buildings using IES VE to compare energy consumption results across these TMY sets. The simulation results indicate that energy consumption values vary significantly depending on the year composition of the TMY data. Notably, when TMY sets are constructed with more recent meteorological data, cooling energy tends to be underestimated, and heating energy is overestimated in comparison to sets with older data. These findings underscore the importance of incorporating updated weather data and considering climate change effects when creating TMY data sets to ensure accurate and resilient building designs.