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A platform for research: civil engineering, architecture and urbanism
Personal lighting control with occupancy and daylight adaptation
Highlights Personal lighting control with daylight and occupancy adaptation. Multi-variable optimization method for personal lighting control design. Simulation performance analysis with open-office lighting model.
Abstract Personal control with occupancy and daylight adaptation is considered in a lighting system with multiple luminaires. Each luminaire is equipped with a co-located occupancy sensor and light sensor that respectively provide local occupancy and illumination information to a central controller. Users may also provide control inputs to indicate a desired illuminance value. Using sensor feedback and user input, the central controller determines dimming values of the luminaires using an optimization framework. The cost function consists of a weighted sum of illumination errors at light sensors and the power consumption of the system. The optimum dimming values are determined with the constraints that the illuminance value at the light sensors are above the reference set-point at the light sensors and the dimming levels are within physical allowable limits. Different approaches to determine the set-points at light sensors associated with multiple user illumination requests are considered. The performance of the proposed constrained optimization problem is compared with a reference stand-alone controller under different simulation scenarios in an open-plan office lighting system.
Personal lighting control with occupancy and daylight adaptation
Highlights Personal lighting control with daylight and occupancy adaptation. Multi-variable optimization method for personal lighting control design. Simulation performance analysis with open-office lighting model.
Abstract Personal control with occupancy and daylight adaptation is considered in a lighting system with multiple luminaires. Each luminaire is equipped with a co-located occupancy sensor and light sensor that respectively provide local occupancy and illumination information to a central controller. Users may also provide control inputs to indicate a desired illuminance value. Using sensor feedback and user input, the central controller determines dimming values of the luminaires using an optimization framework. The cost function consists of a weighted sum of illumination errors at light sensors and the power consumption of the system. The optimum dimming values are determined with the constraints that the illuminance value at the light sensors are above the reference set-point at the light sensors and the dimming levels are within physical allowable limits. Different approaches to determine the set-points at light sensors associated with multiple user illumination requests are considered. The performance of the proposed constrained optimization problem is compared with a reference stand-alone controller under different simulation scenarios in an open-plan office lighting system.
Personal lighting control with occupancy and daylight adaptation
Rossi, Marco (author) / Pandharipande, Ashish (author) / Caicedo, David (author) / Schenato, Luca (author) / Cenedese, Angelo (author)
Energy and Buildings ; 105 ; 263-272
2015-07-22
10 pages
Article (Journal)
Electronic Resource
English
Personal lighting control with occupancy and daylight adaptation
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Distributed lighting control with daylight and occupancy adaptation
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