Determining the shading correction factor using a smartphone camera with a fisheye lens

•A low-cost fisheye lens and a smartphone quantify the shading correction factor.•The method does not require 3D building design or angle measurements.•The model correctly predicts the real Sun’s position in the photos.•The model correctly predicts the expected window shading.•Standard tabulated values do not take into account overlapping shading. Quasi-steady-state methods to calculate monthly heating and cooling energy needs require the quantification of solar heat gains through windows. The presence of external obstacles, such as natural topography, other buildings, overhangs, or side fins, may significantly decrease solar gains. Simplified methods to evaluate shading on windows throughout the year use the shading correction factor concept, i.e., the ratio between the surface solar irradiation in the presence of external obstacles and in their absence. This paper presents a photographic method using a low-cost fisheye lens attached to a smartphone to quantify the shading correction factor. It is based on image processing, solar geometry, and climate databases and does not require 3D building design or angle measurement of external obstacles. Both beam and diffuse correction factors are calculated monthly. The model correctly predicts the real Sun’s position in the photos and the expected monthly shading of a South window with an overhang. For the diffuse correction factor, errors up to 11% are obtained when compared to the analytical solution of a window with a large overhang. Standard tabulated values for windows with multiple obstructions are conservative when compared to those of the photographic method. The tabulated approach considers the effect of various obstacles shading even when overlapping occurs, which possibly explains the difference between methods.