The daylighting dashboard e A simulation-based design analysis for daylit spaces Christoph F. Reinhart a, * , Jan Wienold b a Harvard University, Graduate School of Design, 48 Quincy Street, Cambridge, MA 02138, USA b Fraunhofer Institute for Solar Energy Systems, Heidenhofstraße 2, 79110 Freiburg, Germany article info Article history: Received 14 June 2010 Received in revised form 3 August 2010 Accepted 3 August 2010 Keywords: Daylight simulations Daylight metrics Radiance EnergyPlus Glare abstract This paper presents a vision of how state-of-the-art computer-based analysis techniques can be effec- tively used during the design of daylit spaces. Following a review of recent advances in dynamic daylight computation capabilities, climate-based daylighting metrics, occupant behavior and glare analysis, a fully integrated design analysis method is introduced that simultaneously considers annual daylight avail- ability, visual comfort and energy use: Annual daylight glare probability profiles are combined with an occupant behavior model in order to determine annual shading profiles and visual comfort conditions throughout a space. The shading profiles are then used to calculate daylight autonomy plots, energy loads, operational energy costs and green house gas emissions. The paper then shows how simulation results for a sidelit space can be visually presented to simulation non-experts using the concept of a daylighting dashboard. The paper ends with a discussion of how the daylighting dashboard could be practically implemented using technologies that are available today. Ó 2010 Elsevier Ltd. All rights reserved. 1. Introduction The last decade has seen multiple advances of how to numeri- cally analyze the overall performance of daylit spaces. These advances include a trend away from static and towards dynamic, climate-based daylight simulations [22,27], more refined glare prediction and simulation methods [40,41,43], occupancy behavior models that mimic occupant use of shading and lighting controls [28,10] and new evaluation methods to model the thermal and optical properties of complex fenestration systems such as light redirecting devices [8,15,17] 1 . These innovations stand in harsh contrast to current daylighting design practice that still favors the use of rules of thumb during schematic design and largely relies on the daylight factor and illuminance distributions under clear sky conditions during solstice and equinox days [9]. One is left wondering why the design community at large is not picking up the above mentioned advanced design analysis schemes? Several barriers towards the adoption of these technologies come to mind: 1. No single simulation environment: Part of the problem may be that different technical advances have been realized in different simulation environments and without appropriate graphical user interfaces which makes them difficult and time-consuming to learn and whose use is therefore hard to justify for design teams. 2. Simulation time: Another practical concern is that some of the advanced daylight simulation techniques e especially those that rely on the Radiance raytracer [38] e tend to require prohibitively long computation times. 3. Too complicated simulation process: A recent study on modeling errors made by simulation novices of sixty-nine models of the same sidelit space found that the beginners’ models had so many shortcomings that their relevance for the design process was questionable altogether [12]. If non- experts cannot even model the mean daylight factor in a standard sidelit space, what are the odds that they are going to get a fully integrated daylight/glare/thermal simulation right? 4. Outdated rating schemes: A missing driver for change is that building standards and rating schemes have generally remained rather static as far as daylight metrics are concerned, i.e., there is no immediate pressure for practitioners to move towards more advanced daylighting analysis. 5. Inability to interpret simulation results: An additional barrier is that casual software users e even if they happen to get the simulations right e oftentimes lack the expertise to interpret the simulation results as well as the know-how to fix the design problems raised by the simulation. * Corresponding author. Harvard University, Graduate School of Design, 48 Quincy Street, Cambridge, MA 02138, USA. E-mail address: reinhart@gsd.harvard.edu (C.F. Reinhart). 1 A detailed review of these techniques is provided under Ref. [30]. Contents lists available at ScienceDirect Building and Environment journal homepage: www.elsevier.com/locate/buildenv 0360-1323/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.buildenv.2010.08.001 Building and Environment 46 (2011) 386e396