Daylight metrics and energy savings

The drive towards sustainable, low-energy buildings has increased the need for simple, yet accurate methods to evaluate whether a ‘daylit’ building meets minimum standards for energy and human comfort performance. Current metrics do not account for the temporal and spatial aspects of daylight, nor of occupants comfort or interventions. This paper reviews the historical basis of current compliance methods for achieving daylit buildings, proposes a technical basis for development of better metrics, and provides two case study examples to stimulate dialogue on how metrics can be applied in a practical, real-world context.

[1]  P. Tregenza,et al.  Daylight coefficients , 1983 .

[2]  John Mardaljevic,et al.  Dynamic Daylight Performance Metrics for Sustainable Building Design , 2006 .

[3]  J. Rosenfeld,et al.  Optical and thermal performance of glazing with integral venetian blinds , 2001 .

[4]  John Mardaljevic,et al.  Sky model blends for predicting internal illuminance: a comparison founded on the BRE-IDMP dataset , 2008 .

[5]  L Roche Summertime performance of an automated lighting and blinds control system , 2002 .

[6]  John Mardaljevic,et al.  Electrochromic glazing and facade photovoltaic panels: a strategic assessment of the potential energy benefits , 2008 .

[7]  V.H.C. Crisp Preliminary study of automatic daylight control of artificial lighting , 1977 .

[8]  Ann R. Webb,et al.  Considerations for lighting in the built environment: Non-visual effects of light , 2006 .

[9]  Adrian Leaman,et al.  Assessing building performance in use 3: energy performance of the Probe buildings , 2001 .

[10]  D.R.G. Hunt Simple expressions for predicting energy savings from photo-electric control of lighting , 1977 .

[11]  Robert Clear,et al.  Office Worker Response to an Automated Venetian Blind and Electric Lighting System: A Pilot Study , 1998 .

[12]  Vice President,et al.  AMERICAN SOCIETY OF HEATING, REFRIGERATION AND AIR CONDITIONING ENGINEERS INC. , 2007 .

[13]  V.H.C. Crisp,et al.  The light switch in buildings , 1978 .

[14]  Marilyne Andersen,et al.  Experimental assessment of bi-directional transmission distribution functions using digital imaging techniques , 2001 .

[15]  John Mardaljevic,et al.  Minimally intrusive evaluation of visual comfort in the normal workplace. , 2008 .

[16]  Werner Osterhaus,et al.  Discomfort glare assessment and prevention for daylight applications in office environments , 2005 .

[17]  Peter Apian-Bennewitz,et al.  Enhancing and calibrating a goniophotometer , 1998 .

[18]  Christoph F. Reinhart,et al.  Lightswitch-2002: a model for manual and automated control of electric lighting and blinds , 2004 .

[19]  D.R.G. Hunt Improved daylight data for predicting energy savings from photoelectric controls , 1979 .

[20]  Christoph F. Reinhart,et al.  Adding advanced behavioural models in whole building energy simulation: A study on the total energy impact of manual and automated lighting control , 2006 .

[21]  P. Littlefair The luminous efficacy of daylight: a review , 1985 .

[22]  L. Roche,et al.  Occupant reactions to daylight in offices , 2000 .

[23]  R. G. Hopkinson Architectural physics lighting , 1963 .

[24]  J. Michalsky,et al.  All-weather model for sky luminance distribution—Preliminary configuration and validation , 1993 .

[25]  Robert J. Hitchcock,et al.  Delight2 Daylighting Analysis in Energy Plus: Integration and Preliminary User Results , 2005 .

[26]  Jan Wienold,et al.  Evaluation methods and development of a new glare prediction model for daylight environments with the use of CCD cameras , 2006 .

[27]  Standard Ashrae Thermal Environmental Conditions for Human Occupancy , 1992 .

[28]  David N Reid,et al.  The role of hospital design in the recruitment, retention and performance of NHS nurses in England , 2004 .

[29]  Christoph F. Reinhart,et al.  Validation of dynamic RADIANCE-based daylight simulations for a test office with external blinds , 2001 .

[30]  J. Mardaljevic Daylight simulation : validation, sky models and daylight coefficients. , 1999 .

[31]  Dj Carter The measured and predicted performance of passive solar light pipe systems , 2002 .

[32]  Marilyne Andersen,et al.  Bi-directional transmission properties of Venetian blinds: experimental assessment compared to ray-tracing calculations , 2005 .

[33]  Eleanor S. Lee,et al.  Subject Responses to Electrochromic Windows , 2006 .

[34]  Jan Wienold,et al.  DYNAMIC SIMULATION OF BLIND CONTROL STRATEGIES FOR VISUAL COMFORT AND ENERGY BALANCE ANALYSIS , 2007 .

[35]  I. R. Edmonds,et al.  RADIANCE algorithm to simulate laser-cut panel light-redirecting elements , 2000 .

[36]  Christoph F. Reinhart,et al.  The simulation of annual daylight illuminance distributions — a state-of-the-art comparison of six RADIANCE-based methods , 2000 .

[37]  D.R.G. Hunt,et al.  Predicting artificial lighting use - a method based upon observed patterns of behaviour , 1980 .

[38]  John Mardaljevic,et al.  Useful daylight illuminances: A replacement for daylight factors , 2006 .

[39]  John Mardaljevic,et al.  Simulation of annual daylighting profiles for internal illuminance , 2000 .

[40]  Daniel E. Fisher,et al.  EnergyPlus: creating a new-generation building energy simulation program , 2001 .

[41]  Paul J. Littlefair,et al.  Predicting lighting energy use under daylight linked lighting controls , 1998 .

[42]  M. E. Aiziewood Innovative daylighting systems: An experimental evaluation , 1993 .

[43]  G. W. Larson,et al.  Rendering with radiance - the art and science of lighting visualization , 2004, Morgan Kaufmann series in computer graphics and geometric modeling.

[44]  J. Mardaljevic Examples of Climate-Based Daylight Modelling , 2006 .

[45]  David Jenkins,et al.  A design tool for predicting the performances of light pipes , 2005 .

[46]  C. Reinhart,et al.  Development and validation of a Radiance model for a translucent panel , 2006 .