High resolution solar potential computation in large scale urban areas by means of semantic 3D city models
Longxiang Xu (Student TU Delft)
Camilo León-Sánchez (TU Delft - Urban Data Science)
G. Agugiaro (TU Delft - Urban Data Science)
J. Stoter (TU Delft - Urban Data Science)
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Abstract
Solar energy is becoming increasingly important with the transition towards green and sustainable energy. Predicting solar irradiance is one of the core steps to optimise solar energy utilisation when planning and scheduling power grids. Accurate solar irradiance prediction can also help forecast microclimate conditions, enabling the analysis of citizens and planning of optimal intervention strategies for heating or cooling behaviour. This paper discusses a novel approach to computing the solar potential of buildings at the city level with promising scalability using semantic 3D city models. Experiments are conducted at different locations in the Netherlands. We evaluate our results by comparing them to the statistical Dutch data, and CitySim shows huge discrepancies in summer.
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