Improving Prediction of Daylighting Performance

Daylighting is an essential strategy to get to zero energy commercial buildings. However, simplistic metrics that cannot account for climate, location, orientation or advanced technologies have made it difficult to design programs that require daylighting, promote optimized design or technologies, ensure occupant comfort in daylit spaces, or estimate energy use. New climate-based performance metrics generated from annual simulation programs offer improved capability in assessing daylighting design, and thus will improve the prediction of the energy and comfort performance of resulting buildings. This paper discusses the variety of user needs that will help inform the choice of those metrics, such as code development, program design and post-occupancy verification, from simple to detailed modeling, from pessimistic to optimistic assumptions. It presents a Daylighting Analysis Framework that describes all the inputs and outputs of an idealized simulation tool. The Framework can also help to describe what information is needed for which purposes, and could help prioritize the development of analysis tools, metrics and methods for describing daylighting performance according to program needs. The paper goes on to describe a new simulation tool with advanced daylight modeling capabilities developed to support the needs of this project and the initial findings from analysis of its output on 61 field study spaces compared to occupant and expert assessments of daylight quality in those spaces.