Daylighting/Lighting in LEED

Transcription

1 4.430 Daylighting Christoph Visual Comfort & Occupant Behavior Massachusetts Institute of Technology Department of Architecture Building Technology Program Daylighting/Lighting in LEED Indoor Environmental Quality section: credits for: (a) glazing factor (daylight factor) of 2% (b) Between 250 and 5000 lux under equinox clear sky at 9AM and 3PM. view to the outside Compliance via spreadsheet method. 1 1

2 LEED 2.2 Glazing Factor Formula How many of you have used this formula? External obstructions are not considered. View to the Outside in LEED I Credit 8.2 Views for 90% of Spaces Achieve direct line of sight to vision glazing for building occupants in 90% of all regularly occupied spaces. Examples for exceptions copy rooms, storage areas, mechanical, laundry and other low occupancy support areas. 2 3

3 View to the Outside in LEED II Image by MIT OpenCourseWare. View to the Outside Size and content matter Information rich views with natural elements provide satisfaction and health benefits 3 4

4 Daylighting/Lighting in LEED Sustainable Sites: Light Pollution Credit eliminate light trespass from the building and site, improve night sky access and reduce development impact on nocturnal environments. Occupant Behavior 4 5

5 Occupant Behavior 100 blinds always up 80 daylight autonomy [%] USER BEHAVIOUR?! blinds always down, slats at 45 o 0 blinds always fully closed distance to facade [m] Monitoring User Behavior architecture: Meier-Weinbrenner-Single, Nürtingen Paper: C F, Voss K, Monitoring manual control of electric lighting and blinds. Lighting Research & Technology, 35:3 pp ,

6 Monitoring Setup in the Offices Illuminance Temperature occupancy HOBO data logger Monitoring Blind Usage video surveillance camera receiver MHz Blind setting EIB system data acquisition 6 7

7 Example Picture 7 8

8 Switch-On Probability (I) switch-on probability at arrival type 2 type minimum work plane illuminance [lux] Jim Love, University of Calgary Switch-On Probability (II) switch-on probability at arrival Hunt 1978 Lamparter minimum work plane illuminance [lux] 8 9

9 People are Consistent but Different 1 sw itc h-on proba bility at a rrival minimum work plane illuminance [lux] Switch-Off Probability switch-off probability when leaving no controls no controls dimmed no controls system occupancy sensor 00 <30 <30 minutes minutes hours hours hours hours hours hours hours hours minutes minutes hours hours hours hours hours Pigg et al. University of Wisconsin behavioral patterns change in the presence of automated controls 9 10

10 Intermediate Switch-On Probability intermediate switch-on probability minimum work plane illuminance [lux] Manual Lighting Control Algorithm 100 blinds occlusion [%] Lamparter Inoue solar penetration depth [m] Blinds get lowered to avoid direct sunlight falling on the work plane

11 Model Overview Lightswitch 2002 annual occupancy profiles annual illuminance profiles Lightswitch Algorithm (stochastic) el. lighting/blinds profile Paper: C F, " Lightswitch 2002: A model for manual control of electric lighting and blinds", Solar Energy, 77:1 pp , 2004 Lightswitch - Manual Lighting Control NO Is work place already occupied? YES NO Are lights switched on? YES NO Are lights switched on? YES NO Does occupant arrive? 1 Does occupant arri ve? YES Does occupan t l eave? YES NO Does occupant leave? NO YES stochastic process: switch on probability (Fi g. 7-5) switch-on probability NO NO Is there an occupancy sensor? YES Hunt Lamparter NO stochastic process: i ntermediate swi tch on probabili ty (Fi g. 7-7) NO YES stochastic process: Pigg s switch off probability with or without occupancy sensor (Fig. 7-5) YES 0 NO0 Has the 100 room been desert ed f or l onger minimum than sensor work plane illumiance [lux] delay time? NO YES YES YES Switch lights on Switch lights off Switch lights on Switch lights off 11 12

12 Lightswitch - Manual Blind Control Lightswitch - Manual Blind Control ) ) ) ) ) ) ) ) ) ) ) ) window with blinds work plane sensors Define work plane sensors that define where the occupants are usually located. Associate sensors with shading groups. A shading group consists of a (set of) blinds that are opened and lowered at the same time. Check when direct sunlight (>50Wm -2 ) is incident on a work plan sensor. Close shading device if yes until occupant is away for more than an hour

13 Blind Use in New York City Classrooms Question 14: How often do you adjust the shading device(s)? MDesS thesis, Jennifer Sze % 5% 17% 31% 18% 21% Multiple times a day Once or twice a week Once or twice a month Never Other N/A Image by MIT OpenCourseWare. 183 teacher surveys, 9 participating schools DIVA Demo: Occupant Behavior 13 14

14 Modeling Occupant Behavior No Blinds With Blinds Detecting Glare 14 15

15 What is glare? Glare is a subjective human sensation that describes light within the field of vision that is brighter than the brightness to which the eyes are adapted (HarperCollins 2002). Illustration by ZStardust on Wikimedia Commons. Glare Indices A glare index is a numerical evaluation of high dynamic range images using a mathematical formula that has been derived from human subject studies. UGR 8log L b n i 1 L P 2 s s 2 CIE Unified Glare Rating Example indices include the unified glare rating (UGR) and the daylight glare index (DGI). All of these equations were derived from experiments with artificial glare sources none of them under real daylight conditions. The reason for this is that until recently it has been next to impossible to collect high dynamic range images of daylit scenes under continuously changing lighting levels

16 Daylight Glare Probability (DGP) Room 1: CCD Camera Room 2: Human Subject DGP is a recently proposed Courtesy discomfort of Elsevier. Used glare with permission. index that was derived by Wienold and Christoffersen from laboratory studies in daylit spaces using 72 test Weak subjects correlation in Denmarkbetween and Germany. DGI and CGI (cventional galre metrics) Two identical, and occupant side-by-sideevaluations. test rooms were used. In Room 1 a CCD camera based luminance mapping technology was installed at the exact position and orientation as the head of the human subject in Room 2. Paper: Wienold & Christoffersen, " Evaluation methods and development of a new glare prediction model for daylight environments with the use of CCD cameras ", Energy & Buildings Image-based Glare Source Detection using the Radiance evalglare Program Paper: Wienold & Christoffersen, " Evaluation methods and development of a new glare prediction model for daylight environments with the use of CCD cameras ", Energy & Buildings

17 In Search of a Glare Metric Courtesy of Elsevier. Used with permission. Weak correlation between DGI and CGI (conventional glare metrics) and occupant evaluations. Paper: Wienold & Christoffersen, " Evaluation methods and development of a new glare prediction model for daylight environments with the use of CCD cameras ", Energy & Buildings In Search of a Glare Metric 100% 100% Percentage of disturbed persons 80% 60% 40% 20% R 2 =0.12 0% Percentage of disturbed persons 80% 60% 40% 20% R 2 =0.56 0% Window Luminance [cd/m 2 ] Daylight glare index DGI Window Luminance + - Standard deviation of DGP DGI + - Standard deviation 100% 100% Percentage of disturbed persons 80% 60% 40% 20% R 2 =0.56 0% Percentage of disturbed persons Total responses: % Number of responses per illuminance- class:29 60% 40% 20% R 2 =0.77 0% CGI Vertical Eye Illuminance [lux] CGI + - Standard deviation Vertical Eye Illuminance + - Standard deviation Image by MIT OpenCourseWare. Vertical eye illuminance promising for the first term

18 Final Daylight Glare Probability Metric Probability of disturbed persons 100% Total responses: % Number of responses per DGP - class: 29 80% 70% 60% 50% 40% 30% 20% R 2 = % 0% Daylight glare probability DGP DGP +_ Standard deviation of DGP +_ Standard deviation of binomial deviation Image by MIT OpenCourseWare. Paper: Wienold & Christoffersen, " Evaluation methods and development of a new glare prediction model for daylight environments with the use of CCD cameras ", Energy & Buildings DGP allows users to go back and forth between simulation and reality through HDR photography HDR Image (Digital Camera) HDR Image (Radiance) evalglare program instantaneous daylight glare probability 18 19

19 DGP Comfort Ranges DGP < 35% imperceptible 35% < DPP < 40% perceptible 40% <DGP < 45% disturbing DGP > 45% intolerable Example DGP Calculation 19 20

20 DIVA Demo: DGP Point in Time Calculation Towards Annual Glare Calculations Generated visualizations for illuminance calculation removed due to copyright restrictions. Wienold developed a process through which the annual glare calculation is split into a regular Daysim illuminance calculation and an ab=0 contrast image. Paper: J Wienold, Dynamic Daylight Glare Evaluation, Building Simulation 2009, Glasgow Scotland

21 Comparison of Simplified DGP and hour -byhour method Graph of vertical illuminance removed due to copyright restrictions. Paper: J Wienold, Dynamic Daylight Glare Evaluation, Building Simulation 2009, Glasgow Scotland, Annual Glare Map 21 22

22 DGP Comfort Ranges Number of working hours above DGP hours DGP intolerable = 39% Daylight glare probability [%] Imperceptible Perceptible Disturbing Intolerable Image by MIT OpenCourseWare. Paper: C F, Simulation-based Daylight Performance Predictions", Book chapter in Building Performance Simulation for Design and Operation, Editors J Hensen and R Lamberts, Taylor & Francis, Expanded Blind Control Model: Close Blinds when DGP > 40% Number of working hours with DGP above Active blind use (avoid discomfort glare) Blinds always lowered No blinds Active blind use (avoid direct sunlight) Daylight glare probability [%] Daylight Autonomy [%] Blinds always lowered No blinds Distance to facade [m] Active blind use (avoid direct sunlight) Active blind use (avoid discomfort glare) Imperceptible Perceptible Disturbing Intolerable Image by MIT OpenCourseWare. 22

23 The formula makes sense. How plausible are DGP results compared to other glare indices? Multidirectional Time-Lapse Simulation The image shows a cylindrical 360 o view of a work space in Gund Hall. The color coded lines at the bottom show the predictions of different glare indices (DGP, DGI, UGI, CGI and VCP) whether discomfort glare will be experienced in a particular direction at different times of the day (Green=Imperceptible Glare; Yellow=Perceptible Glare; Orange=Disturbing Glare; Red=Intolerable Glare). Design: Jeff Niema Paper J A Jakubiec, C F, The Use of Glare Metrics in the Design of Daylit Spaces: Recommendations for Practice ", submitted sz to Lighting Research and Technology

24 Multidirectional Time-Lapse Simulation DGP yields most plausible results in these spaces. Design: Jeff Niema Paper sz J A Jakubiec, C F, The Use of Glare Metrics in the Design of Daylit Spaces: Recommendations for Practice ", submitted to Lighting Research and Technology How to analyze for visual discomfort? Paper: J A Jakubiec, C F, 2010, The Use of Glare Metrics in the Design of Daylit Spaces: Recommendations for Practice", Lighting Research and Technology,

25 Multidirectional Time-Lapse Simulation DGP yields most plausible results in these spaces. Design: Jeff Niema Paper sz J A Jakubiec, C F, The Use of Glare Metrics in the Design of Daylit Spaces: Recommendations for Practice ", submitted to Lighting Research and Technology Concept of the Adaptive Zone Annual DG Calculation: Fixed view looking forward AnnualDG Calculation: +/ 45 degrees rotational freedom The concept helps to quantify the benefits of flexible furniture settings etc. Design: Jeff Niema Paper sz J A Jakubiec, C F, The Use of Glare Metrics in the Design of Daylit Spaces: Recommendations for Practice ", submitted to Lighting Research and Technology

26 The Ultimate Adaptive Space Christoph Associate Professor

27 MIT OpenCourseWare Daylighting Spring 2012 For information about citing these materials or our Terms of Use, visit: