LAUSR

Abstract As buildings consume substantial amounts of energy, researchers and decision makers are giving more attention to urban-scale energy assessment and design. In fact, researchers have developed many building-energy modeling and simulation tools that are regarded as effective for building designers and facility managers. However, few models have been found suitable for urban-scale efficient building design and planning. Indeed, to carry out urban-scale energy modeling and simulation, it is necessary to possess a comprehensive understanding of interactions among building groups as well as huge computational resources. To develop a more efficient and reliable simulation model, this study proposes a parallel computational building-chain (PCBC) model. This PCBC model aims to simplify building interactions and implement efficient multi-thread computations. It can decompose large-scale building groups into inter-connected building units by defining the thermal and shading boundary conditions of buildings in a neighborhood. By coupling individual buildings’ simulated energy consumption, the urban energy dynamics can be reconstructed. To validate the proposed method, researchers examined a sample urban-building group with 410 buildings. Compared with the conventional integrated Whole City model, the proposed method achieved nearly the same outputs with reduced computation time. With an increase in the simulation scale, computational efficiency can be improved in the future.