Large-scale prediction of solar irradiation, shading impacts, and energy generation on building Façade through urban morphological indicators: A machine learning approach

Abstract

Incorporating Building-integrated Photovoltaics (BIPVs) into urban environments offers a sustainable approach by transforming building exteriors into renewable energy sources, especially by utilizing the extensive vertical surfaces in cities. While individual building applications have been extensively studied, there is a lack of research on BIPV potential at the urban scale due to the complexity of urban fabrics. Therefore, this study presents a novel method for predicting large-scale solar irradiation and energy generation on building surfaces using urban morphological indicators through machine learning models. Using an Australian city as a case study, a hierarchical two-level machine lea..