Improved urban canopy model for building energy simulation with ray tracing

The urban microclimate, and its specific heat island phenomenon, is both a cause and a consequence of increased building energy consumption and increased power demand peaks during summer period, due to air-conditioning , in the context of urban overheating. In this paper, we propose the combined use of urban canopy and building energy models, at neighborhood scale, to predict urban heat islands and the building energy demand, considering both heating and cooling consumptions. In usual urban canopy models, the urban morphology is typically considered as a simplified urban canyon, which results in an acceptable accuracy loss in solar calculations for common urban climate studies. In this article, we reconsider this simplification to study more precisely the potential benefits for building energy simulations of detailed solar calculations. We developed our model comparison with the urban canopy model of UWG (Urban Weather Generator), an urban canyon model. The detailed model uses ray tracing methods to calculate the solar irradiance on all sub-surfaces of the studied neighborhood, described in a BIM (Building Information Model). This approach significantly enhances the consideration of urban area geometry in the urban microclimate model. An automated process for transforming BIM into BEM (Building Energy Model) is then applied, and the air temperature generated by this improved canopy model is used as external boundary condition for the BEM.

The first part of the article presents the methodology for coupling UWG with the ray tracing calculation, detailing how geometric data from BIM are used as well as the solar calculation method. In the second part, the impact of this improved solar calculation is evaluated through two case studies. A first simple street canyon geometry allows us to validate the approach given the results of shortwave irradiances and air temperatures with both the standard and the enhanced UWG model. Then, we study the real impact of the detailed ray tracing model for an actual neighborhood in France. For both simplified and realistic neighborhood case studies, we quantify the impacts on heating and cooling demand for buildings.