Impact of urban heat island on high-rise residential building cooling energy demand in Hong Kong

•Conducted multiple year-by-year simulations with actual weather data (1999–2018).•UHII in HK is positive during 17:00–10:00 and higher in colder seasons (up to 2.88 °C).•UHI increases cooling demand by 6.0% (whole year), 3.5% (summer), & 28.3% (winter).•UHI impacts fluctuate inter-annually (up to 7.1%) and decrease by 1.7%/decade.•Each 1 °C increase in UHII causes + 35.8% in UHI-driven cooling demand difference. This study aims to investigate the impact of urban heat island (UHI) on cooling energy demand in high-rise residential buildings, with a primary focus on cooling-dominated regions. We take Hong Kong, a typical highly urbanised city with a humid subtropical climate, as a representative case. Multiple year-by-year EnergyPlus simulations were conducted using 20 years of actual meteorological data (1999–2018) from one urban site and one rural site for a typical 40-storey residential building. Cross-sectional analyses were performed in inter-annual, seasonal, and diurnal scales to comprehensively examine the temporal dynamics of cooling-relevant energy impacts of UHI. Regression analyses were conducted to reveal the relationship between UHI’s energy impact and UHI intensity (UHII). Results show that UHI causes an increase of 6.0% in cooling energy demand for high-rise residential buildings in Hong Kong. Such impact reaches a daily (intra-annual) minimum/maximum of −1.4%/+21.8% (+3.5%/+28.3%) at 5 pm/6 am (in summer/winter) and diminishes by an average rate of 1.7% per decade likely due to the urbanisation in rural regions. Each 1 °C increase in UHII causes an increase of 7.9%/16.1%/36.9% in seasonal cooling energy demand for summer/transitional seasons/winter, respectively. This study reveals that UHI's intricate temporal dynamics can lead to heterogeneous effects on building energy performance. Besides, distinct patterns of UHI-driven cooling energy profiles between high-rise and low-/medium-rise buildings are identified. Moreover, this study underscores the importance of employing multiple year-by-year meteorological data and addressing season-specific nonlinearity in building energy research to ensure the reliability of findings against the backdrop of climate change.