Development of an optimal daylighting controller

A new lighting and daylighting control strategy is modeled and evaluated against conventional lighting and daylighting controls. The new lighting and daylighting control strategy can be incorporated in an energy management and control system (EMCS) to operate and control lighting fixtures in any indoor space. The new daylighting control can also be modeled and integrated in detailed building energy simulation tools. Through a validation analysis, it was found that the new control strategy provides more energy savings than conventional daylighting controls. Moreover, the validation analysis has indicated that existing daylighting control simulation analysis tools could overestimate lighting energy savings associated with daylighting controls. Moreover, it was also found that if calculated solar and illuminance data are used instead of measured solar radiation data, the errors in predicting lighting energy use when daylighting controls are utilized can be significant.

[1]  G. N. Tiwari,et al.  A model for estimation of daylight factor for skylight: An experimental validation using pyramid shape skylight over vault roof mud-house in New Delhi (India) , 2009 .

[2]  J. Timmer,et al.  Dynamic annual daylight simulations based on one-hour and one-minute means of irradiance data , 2002 .

[3]  Moncef Krarti,et al.  A simplified method to estimate energy savings of artificial lighting use from daylighting , 2005 .

[4]  T. Inoue,et al.  The development of an optimal control system for window shading devices based on investigations in office buildings , 1988 .

[5]  Danny H.W. Li,et al.  Lighting and energy performance for an office using high frequency dimming controls , 2006 .

[6]  M. Atif,et al.  Energy performance of daylight-linked automatic lighting control systems in large atrium spaces: report on two field-monitored case studies , 2003 .

[7]  Christoph F. Reinhart,et al.  Findings from a survey on the current use of daylight simulations in building design , 2006 .

[8]  J. Michalsky,et al.  Modeling daylight availability and irradiance components from direct and global irradiance , 1990 .

[9]  Donghyun Seo Development of a universal model for predicting hourly solar radiation---Application: Evaluation of an optimal daylighting controller , 2010 .

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

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

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

[13]  Jonathan McHugh,et al.  The energy impact of daylighting , 1998 .

[14]  Stephen Selkowitz,et al.  Daylighting simulation in the DOE-2 building energy analysis program , 1985 .

[15]  Jon Hand,et al.  CONTRASTING THE CAPABILITIES OF BUILDING ENERGY PERFORMANCE SIMULATION PROGRAMS , 2008 .

[16]  G. Tiwari,et al.  A modified model for estimation of daylight factor for skylight integrated with dome roof structure of mud-house in New Delhi (India) , 2010 .

[17]  Stephen Selkowitz,et al.  The New York Times headquarters daylighting mockup: Monitored performance of the daylighting control system , 2006 .

[18]  E. Polak,et al.  A convergent optimization method using pattern search algorithms with adaptive precision simulation , 2004 .

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

[20]  Christoph F. Reinhart,et al.  Monitoring manual control of electric lighting and blinds , 2003 .

[21]  M. Kischkoweit-Lopin An overview of daylighting systems , 2002 .

[22]  Danny H.W. Li,et al.  Evaluation of lighting performance in office buildings with daylighting controls , 2001 .

[23]  Moncef Krarti,et al.  Energy Audit of Building Systems : An Engineering Approach , 2000 .