A mathematical model for rapid estimation of solar radiation in urban canyons with trees and its applications

Abstract

Street-level solar radiation estimation can help to better understand the influence of solar radiation on urban microclimate, outdoor thermal comfort and health, solar energy utilization, and building energy savings. However, existing urban canyon radiation models based on Monte Carlo ray tracing are challenging to apply in real practice due to limited applicability and high computational efforts. A flexible and robust mathematical model for solar radiation in urban canyons is proposed in this study to estimate solar radiation potential at the street level quickly and can be applied to the urban scale. The newly developed model considers the effect of trees on street canyon radiative transfer based on some assumptions and simplifications. Using the matrix method to resolve the infinite number of multi-reflections, the model accurately predicts solar radiation inside the street canyon compared to experimental data. The maximum root mean square error (RMSE) in the model prediction is 52.7 W/m2 and 14.5 W/m2, respectively, for urban canyons without and with trees in the studied case. And the Pearson correlation coefficient (r) is above 0.987 for all scenarios. An open-source Python script module for the model application is provided and can be integrated with other models or software platforms. The model has been used to estimate solar potential on the street and urban scales taking Chongqing city, China as an example. It is proven that the model is helpful for rapid assessment of solar radiation at the street and urban scales, serving urban design and planning.