Operational energy performance assessment of high-rise office buildings in Hong Kong under shading and microclimatic uncertainties

Abstract

Office buildings are a major building type responsible for a large proportion of the total energy consumption worldwide. Due to the scarce land resources in Hong Kong, numerous buildings in the city are high-rises. However, high-rise office buildings face more limitations on the selection of energy-saving strategies than low- or medium-rises do, as high-rises are associated with more complex designs of the building fabric, envelope and services. Besides, shading effects from nearby buildings in Hong Kong are more significant than in other regions due to the super high-density of urban areas, and whether or not the shading effects show significant effects on building energy consumption is unclear in literature. Moreover, due to the urban morphology effect, building energy consumption performs difference in regions. Traditional methods fall short in addressing the microclimatic uncertainties on building energy consumption. The aim of this research is thus to quantify the impacts of shading effects and microclimatic conditions on the energy consumption of high-rise office buildings in Hong Kong, and develop and validate an integrated framework of assessing the operational energy performance of high-rise office buildings under shading and microclimatic uncertainties. Firstly, through literature review, the research provides a thorough understanding of the recent development of knowledge and uncovers research gaps. Secondly, the research explores the status quo research on the building energy performance of high-rise office buildings in HK through literature and detailed energy modeling. The results of energy modeling of 12 typical buildings show that the annual building energy consumption ranges from 194.9 kWh/m2 to 320 kWh/m2. The results of the sensitivity analysis show that the most sensitive factor is HVAC system. Thirdly, the research explores the shading effects on building energy consumption. Scenarios of buildings modeled in both isolated and real communities were compared and analyzed. The deviation on whole building energy consumption was up to 8.5%. Energy consumption regression models were established considering the distance between surrounding and target building, the heights and the orientations of the surrounding building. Totally, 230 energy simulation was conducted to generate the regression model, and 30 additional energy simulation was used to verification. Fourthly, the research assesses the microclimatic effects on building energy performance by applying different weather datasets into the energy model through eleven real-life offices. The annual weather datasets comprise five hourly factors, namely, wind speed, wind direction, air temperature, solar radiation, and relative humidity. The deviation on estimated annual building energy consumption ranges from 3.0% to 4.5%. Eventually, an integrated conceptual framework with the consideration of shading and microclimatic effects is established and demonstrated through a calibrated real-life case study. Onsite observation, onsite measurement, simulation, were included. This research should be worthwhile in providing insights into the uncertainty of shading and microclimatic effects on building energy modeling that exist but was overlooked in previous studies. The research contributes to a better theoretical understanding of operational energy performance assessment. The proposed framework expands the existing knowledge on the method of assessing building energy consumption and gives practical guidance to future energy modeling research.