Modeling urban energy dynamics under clustered urban heat island effect with local-weather extended distributed adjacency blocks

Buildings are the major energy consumers in cities. To promote building energy efficiency and urban sustainability, researchers developed comprehensive digital simulation tools, such as CitySim, CityBES, and Autozoner, efforts to investigate, understand, and predict energy dynamics of urban buildings. However, different from independent buildings in rural areas, urban buildings have complicated interactions with surrounding buildings and the environment. Owing to the computational complexity of large building numbers, these models chose top-down or regression methods with universal weather conditions. However, a reliable prediction of building energy dynamics needs a comprehensive understanding of the thermal process of building physical elements, which is often weld by the bottom-up methods. Therefore, this study proposed a novel local-weather extended distributed adjacency blocks (LW-DAB) model that incorporates bottom-up distributed adjacency blocks (DAB) simulation and allows customizable local micro-climate clusters. This study also deployed a city building digital model with 1175 buildings and compared the results with the conventional typical morphological year weather-based simulation in three different climate regions. By introducing the impacts of urban island effects (UHI) based on building the morphological relationship, the results suggest that the proposed LW-DAB model not only allows independent micro-climate assignment for each building but also half the simulation time with 5% accuracy loss compared with the conventional whole city simulation model.