Assessing the impacts of urban morphology factors on the energy performance for building stocks based on a novel automatic generation framework

Abstract

The building sector accounts for an increasing amount of energy and emissions with continued urbanization, and improving the energy performance of building stocks at the early planning stage is cost-efficient and easy to operate. This study presents an automatic generation framework to quantify the impacts of urban morphology factors on the energy performance of neighborhood-scale building stocks. The typical office building shape is firstly determined by a field survey and clustering analysis. Then the building modular cells-based method is introduced to establish a comprehensive energy performance database for building stocks. The impacts of urban morphology factors on energy performance are further prioritized via global sensitivity analysis. A case study in Shanghai, China demonstrated the proposed automatic generation framework which can act as a generalized paradigm to model building stocks and be widely applicable to other climate zones. The urban morphology factors representing buildings’ geometric characteristics tend to have greater impacts on energy performance, among which the top influencing factors are relative compactness, building coverage ratio, and building height distribution. The proposed framework and the findings are expected to generate valuable insights into energy-efficient urban design.