MARDALJEVIC, J., 2008. Sky model blends for predicting internal illuminance: a comparison founded on the BRE-IDMP dataset. Journal of Building Performance Simulation, 1 (3), pp.163-173.
The BRE-IDMP validation dataset contains simultaneous measurements of sky luminance patterns and internal illuminances in two full-size office spaces. This benchmark dataset has been applied previously to test
the illuminance predictions from a lighting simulation program under real
sky conditions. Sky luminance patterns were mapped into the lighting simulation so that the absolute accuracy of the program could be evaluated without the uncertainties that are introduced when sky models are used. For this
follow-on study, the BRE-IDMP dataset is now used to quantify the divergence between the sky model generated luminance patterns and the actually
occurring conditions based on the resulting internal daylight illuminances.
The internal illuminances were predicted using three 'narrow-range' models (CIE overcast, CIE clear and intermediate) and the Perez All-Weather
model. Predictions from the narrow-range models were used to investigate
formulations for sky model blends. The illuminance effect of arbitrary sky
model blends is reproduced in a post-process of the illuminance predictions
from the 'narrow-range' sky model types. The determination of an optimum
sky model blend is described. The findings show that relatively simple blends
of just two pure sky models (e.g. CIE overcast and intermediate) may be
adequate for the prediction of time-varying illuminances founded on climatic
test reference year data.