City-scale residential energy consumption prediction with a multimodal approach
摘要
The key role of buildings in tackling climate change has gained global recognition. To avoid unnecessary costs and time wasted, it is important to understand the conditions and energy usage for existing housing stock to identify the most important features affecting energy consumption and to guide the relevant retrofit measures. This paper investigated how the spatial, morphological and thermal characteristics of residential houses contribute to housing energy consumption. Additionally, it presents a rapid assessment tool using minimum data input to answer two main questions: 1) What type of properties may need retrofit? 2) What building elements/features may be prioritised to be retrofitted? A case study was performed with around 143,000 residential properties in Sheffield. An automated machine approach was applied which successfully estimated the energy consumption of target buildings with an