Automated demand response system in lighting for optimization of electricity cost

Abstract

Daylighting is an important factor in improving visual comfort and energy efficiency. Lighting control using daylighting can reduce energy consumption in buildings. This thesis proposes an automatic demand response system for lighting based on wireless sensor networks (WSN) in order to reduce the peak electricity demand according to the stage of electricity rate with real-time pricing (RTP), time of use pricing (TOUP), and critical peak pricing (CPP). The proposed system automatically controls the slat angle of the venetian blind with a cut-off angle according to the altitude of the sun, automatically executing light dimming according to measured current luminance to remove an unpleasant glare caused by daylighting. The target illuminance of area at this time is set at a minimum illuminance required for the work execution in the office during the time zone where the electricity load is high to save the lighting energy cost, while a maximum illuminance is set during the time zone where the electricity load is low according to the real-time electricity pricing stages obtained through the advanced metering infrastructure (AMI) in order to improve the work efficiency of the occupants. In this study, two testbeds having the same environments, as well as a control system targeting a fixed illuminance per price system, were established. The illuminance energy consumption and cost were then measured and the effect of the proposed illuminance system was evaluated.