Development of Regression Equations for a Daylighting Coefficient-of-Utilization Model

When hourly energy simulation models are used to predict the performance of multi-zone buildings, they may be required to perform more than 2,000 daylight analyses in a single simulation. The traditional approach is to use a very fast computational model, which of necessity must be a very simple model. Coefficient of utilization models have been widely used as simple design tools but have been severely limited in their applicability to complex and realistic fenestration systems and building designs. This paper present a new coefficient of utilization (CU) model for daylighting that combines the ease of use of CU models with the ability to predict illuminance under a wide range of conditions. The model consists of seven regression equations normalized to exterior vertical surface illuminance. These equations describe daylight illuminance as a function of position in a room and are sensitive to all of the significant design variables. The equations are derived from parametric analysis using a mainframe daylighting computer model (SUPERLITE). We describe how these equations were developed and their physical and theoretical background. Comparisons between direct calculation and CU results for sample rooms are demonstrated.