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Inaugural US-EU-China Thermophysics Conference-Renewable Energy 2009 (UECTC 2009 Proceedings)

Editor
Y. Tao
Y. Tao
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C. Ma
C. Ma
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ISBN:
9780791802908
No. of Pages:
1200
Publisher:
ASME Press
Publication date:
2009

This paper introduces a preliminary testing of the performance of a novel daylighting control strategy. Specifically, it introduces a set of control strategies to operate lighting fixtures in order to maintain a desired luminance level for one or more working zones in an office space while reducing the electrical energy use for lighting. These control strategies used the genetic algorithm approach to determine the optimal configuration of operating electrical lighting fixtures. An optimization algorithm has been implemented using measured data obtained for an office space. This algorithm can be incorporated in a controller or an energy management system to operate the lighting fixtures in an office room. The study indicates that the algorithm can save up to 50% of the annual total energy use of the building relative to conventional daylighting controls.

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