Evaluating urban form influence on solar exposure and corresponding building energy demands

Solar radiation is a key factor in the energy balance of urban areas, with urban form significantly affecting solar exposure. The design and arrangement of buildings determine how they interact with solar radiation, influencing factors such as the performance of building-integrated photovoltaic systems, solar heat gains, and heating and cooling demands. Urban form indicators, including orientation, roof slope, and shading from surrounding structures, are crucial for determining solar exposure, which has significant implications for optimizing energy efficiency and guiding sustainable urban planning decisions. This paper presents a new Python-based framework that analyzes urban geometry to enable shadow analysis and the calculation of solar radiation, solar heat gain, and the heating/cooling load for any selected building(s) given 3D models. The framework is developed using CityJSON, facilitating the processing of 3D city models within the Python environment. Its performance is demonstrated through a case study of a representative building in the city of Munich. The results show that it effectively evaluates the thermal behavior of buildings in response to solar radiation and analyzes how the urban form influences solar shading. This provides potential methods for optimizing urban form and improving the energy systems of buildings. This framework is the first to use CityJSON in a unified environment to jointly analyze publicly available 3D building models, incorporate windows, and perform solar radiation and shadow analysis, as well as heating and cooling demand calculations.