Dynamic Daylight Performance Metrics for Sustainable Building Design


C. Reinhart, J. Mardaljevic, and Z. Rogers. Leukos, v. 3, no. 1, 2006, pp. 1-25

Review by Scott Schuetter, Energy Center of Wisconsin: 

In this paper, Reinhart et al. investigates various dynamic daylight performance metrics and compares their advantages and disadvantages as opposed to static metrics.

Daylight factor is one such static metric that is defined as the ratio of internal illuminance at a given location in a space to the external horizontal illuminance under a CIE overcast sky. This metric is often utilized by the design community due to its simplicity to calculate and is advantageous in that it accounts for building geometry, surrounding conditions, and properties of the interior materials and glazings.

However, this metric does not account for facade orientations, season, and variable sky conditions. Dynamic daylight performance metrics are more difficult to calculate but include this variability. Recent developments in software have made the time-intensive calculations more tractable.

One such dynamic metric is daylight autonomy, which is the percentage of a building's occupied hours that a target illuminance value is provided by only daylight. Useful daylight illuminance is another metric that varies daylight autonomy by including an upper threshold of illuminance. Continuous daylight autonomy is a third metric that incorporates partial credit for times that the naturally provided illuminance is below the target.

The paper then goes on to calculate these static and dynamic metrics using Daysim for different design variations. Note that interior blind control was added to the analysis for three different types of controls: automated, active manual, and passive manual.

The first set of design variations studied how the performance metrics changed for four different glazing geometries: a reference geometry including a view window and a daylighting window, a design that included a lightshelf, a design that utilized translucent glazing for the daylighting window, and a punched window. The study showed that the static metrics ranked the designs in reverse order as the dynamic metrics.

A second set of design variations studied the impact of different types of shading control. In this study, an automated shading device ranked higher in terms of the dynamic metrics, while an active user did slightly better than a passive user. Note that the static metrics did not capture any change at all.

A third variation studied two different climates that were at similar latitudes: Boulder, CO and Arcata, CA. The metrics were similar for both as the higher direct sunlight received in Boulder was offset by the higher use of interior blinds. Note that the static metrics again did not capture any change at all.

Finally, varying target illuminance levels were studied. The paper concludes that dynamic daylight metrics are more useful for making design decisions and that the added time and expense associated with them has been greatly reduced. Absolute benchmarks for whether a given design is passable still need to be developed. Quantitative metrics, although important, are not all that needs to be considered in a daylight analysis, as daylight is as much an art as it is a science.