A true measure of the long-term daylighting performance of a building must account for the illumination that results from a wide range of sky and sun conditions. This paper describes how to predict hourly internal daylight illuminances for a period of a full year using sky and sun conditions derived from meteorological time-series data. The technique is based on a refined implementation of the daylight coefficient approach. The analysis and the reduction of the large datasets that result from a daylight coefficient based evaluation are described. The new approach was validated under real sky condition using the BRE-IDMP dataset and shown to be highly accurate.
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