A new tool for predicting the total energy consumption and associated greenhouse gas (GHG) emissions of Australian households is developed by integrating the thermal efficiency of the building envelope, installed equipment and appliances, and different occupancy profiles with energy end-use modules for space heating, space cooling, water heating, lighting, and plug-in appliances. Space heating and cooling energy consumption are simulated by an enhanced version of a house energy rating tool - AccuRate, modified to account for specific heating, ventilation and air-conditioning (HVAC) system efficiency and occupancy profile. Individual modules for hot water, lighting and appliances are developed, calibrated and assessed against available published end-use data in Australia and New Zealand. The tool's integrated capability to predict the annual energy consumption of a tenant-occupied house in Melbourne is validated with actual data measured over a 12-month period.

This study proposed a method to construct urban hourly weather data by adopting the ‘morphing’ approach considering urban heat islands. The method starts with the surrounding rural weather as the ‘baseline climate’ and an Urban Canopy Model is used to provide the differences in the monthly average values of major climate parameters due to urban heat islands. The ‘baseline climate’ is then morphed to generate the urban hourly weather file for building simulations. It was demonstrated that the constructed hourly weather data agree well with the observations. When used for building thermal simulations, the differences between the proposed approach and the observation in the total energy requirement of space heating and cooling and heat stress risk index were within 5% and 1.0℃, respectively. Practical applications: The proposed approach will allow academics and building engineers to construct realistic urban hourly weather data to analyse the impacts of urban heat islands on energy requirements and thermal stress for different urban planning and design options.

This study presents an integrated air flow model for AccuRate, a benchmark housing energy star-rating tool widely used in Australia. The model was developed by implementing a network multi-zonal infiltration model into an existing large opening model. Case studies using 10 houses in Melbourne, Australia, showed that on average the predicted infiltration rates are within 12.6% of the blower-door test results with a standard deviation of 1.6%. The model study also showed that on average the infiltration rates of the 10 houses could be reduced around 52% by sealing major air leakage pathways, which can result in an average of 7% reduction in the annual space heating and cooling loads for the 10 houses. It was also found that an annual hourly energy performance simulation using the new air flow model requires around 15 min in comparison with around 1 min using the existing simple infiltration model in the AccuRate engine.

Thermal simulations of buildings play a critical role in optimizing energy efficiency, thermal comfort, and heating, ventilation and air conditioning (HVAC) systems design. Accurate weather data is essential for reliable simulations, as local weather and climate have a significant impact on energy requirements for space heating and cooling and thermal comfort. This study conducted a literature review regarding the sources, types, and uncertainties of weather data used for thermal simulations of buildings, including typical meteorological years (TMYs) and extreme weather files under current and future climates. Additionally, this paper evaluates methods for weather data processing, including interpolation, downscaling, and synthetic generation, to improve simulation accuracy. Finally, approaches are proposed for constructing weather files for the future and extreme conditions under a changing climate. This review aims to provide a guide for researchers and practitioners to enhance the reliability of thermal modeling through informed construction, selection, and application of weather data.