Prioritizing urban planning factors on community energy performance based on GIS-informed building energy modeling.

• Model community-level energy by combining GIS, simulation, and data-driven approaches. • Propose a GIS-based urban building energy modeling method with low computational cost. • Generate various prototype buildings through two-stage clustering process to describe buildings' diversity. • Integrate urban building energy modeling with global sensitivity analysis to discovery urban planning factors. • Identify FAR and BCR as the most influential factors affecting communities' energy use. The residential sector accounts for an increasing amount of global energy use with continued urbanization. Residential energy-informed urban planning offers an economical and easy-to-operate approach to achieve more efficient urban energy utilization. However, quantifying the interactions between residential energy and urban planning remains an open challenge. This study proposes a holistic approach integrating GIS techniques, building energy modeling, and a global sensitivity analysis to prioritize eight key urban planning factors on the community energy performance based on a building energy dataset. The dataset, including urban planning and building information, was first established using GIS techniques and validated using survey data. The residential energy performance model at the community scale was developed using the clustering tree structure of residential building prototypes and building performance simulations. A combined data-driven and global sensitivity analysis approach was further applied to prioritize the impacts of eight vital urban planning factors on energy use intensity and peak load intensity. A case study of 1963 communities in Shanghai revealed that, for the energy performance of residential communities, the floor area ratio and building coverage ratio are the most influential factors, followed by the maximum height and high-rise proportion having a relatively low impact but higher than other factors. Overall, the proposed holistic approach generates robust insights into urban-scale residential energy performance, which can effectively inform urban planners to achieve more energy-efficient regulatory planning. [ABSTRACT FROM AUTHOR]