Development of an energy saving lighting control system based on an inverse problem solving for light diming

Shinji Kitagami, Yosuke Kaneko, Toru Abe, Hisao Koizumi, Takuo Suganuma

Research output: Contribution to journalArticlepeer-review

Abstract

In a typical office building, the energy-saving of lighting is an important problem because the lighting accounts for 40% of the total electric power consumption in the entire building. However, the lighting affects the amenity of an office space, and inappropriate energy-saving of the lighting decreases the productivity of office workers. Therefore, a lighting control system for the office building must achieve the appropriate energy-saving based on careful and accurate control of light dimming. This paper proposes a lighting control method, which saves the power consumption of lighting with keeping the accuracy in light dimming. In the proposed method, to control the lighting optimally, the lighting influence matrix, which associates the dimming rate pattern of light sources with the illuminance distribution on desks in an office space, is introduced, and a dimming inverse problem is solved by using this matrix. The dimming rate pattern obtained by the proposed method can minimize the power consumption of lighting while maintaining the target illuminance in the area where the office workers seat themselves at their desks. We implemented an energy saving lighting control system based on the proposed method and carried out evaluation experiments by applying this system to an actual office space. Experimental results show that the proposed method increases the evaluation index, which combines energy-saving ratio and dimming accuracy, by 9% compared to conventional energy-saving operations.

Original languageEnglish
Pages (from-to)642-651
Number of pages10
JournalIEEJ Transactions on Electronics, Information and Systems
Volume133
Issue number3
DOIs
Publication statusPublished - 2013

Keywords

  • Electric power minimization
  • Illuminance optimization
  • Lighting influence matrix
  • Linear programming
  • Point-by-point method

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