Combining geographic information and climate data to develop urban building energy prediction models in Taichung, Taiwan

Climate change in Taiwan has extended and intensified the summer season, leading to a notable surge in energy demand for cooling systems, especially in densely populated regions. Building energy usage is directly correlated with cooling degree hours (CDHs), representing the hourly temperature differential between indoors and outdoors. This study employed high-resolution Taiwan ReAnalysis Downscaling (TReAD) data to develop an urban energy prediction model focusing on localized cooling demand in central Taiwan's urban areas. Validated against actual electricity consumption data, the model achieved an R² value of 0.76. The study reveals that urban areas exhibit a high cooling demand during the hot season, exceeding 25,000 °C-h and with an annual energy consumption of 44–64 kWh/m². Conversely, rural areas have a lower cooling demand – that is, below 8,000 °C-h, with an annual energy consumption of <10 kWh/m².

Considering the IPCC's RCP8.5 warming scenario, October shows a 20–40 % increase in cooling demand compared to July and May. This underscores the need to address rising energy consumption especially during the early and late stages of the hot season in response to climate change.