A novel energy saving system for office lighting control by using RBFNN and PSO

This paper represents a novel energy saving system for office lighting control which consists of LED lamps, one illumination sensor for measuring the natural illumination condition, and one control module for the integrated control. The control module embeds an intelligent algorithm for generating the optimized dimming pattern according to the natural illumination and occupancy condition. The intelligent algorithm contains 1) Radial Basis Function Neural Networks (RBFNN) which are used to calculate the illuminance contribution from each luminaire to different positions in the office 2) a PSO algorithm which is used to optimize dimming ratio for luminaires according to the target illuminance in occupied areas thus provide optimized control strategy for the office. Simulations are made to prove the feasibility and effectiveness of the illumination simulator.