In most existing centralized lighting control systems, the lighting control problem (LCP) is reformulated as a constrained minimization problem and solved by linear programming (LP). However, in realworld applications, LCP is actually discrete and non-linear, which means that more accurate algorithm may be applied to achieve improvements in energy saving. In this paper, particle swarm optimization (PSO) is successfully applied for office lighting control and a linear programming guided particle swarm optimization (LPPSO) algorithm is developed to achieve considerable energy saving while satisfying users' lighting preference. Simulations in DIALux office models (one with small number of lamps and one with large number of lamps) are made and analyzed using the proposed control algorithms. Comparison with other widely used methods including LP shows that LPPSO can always achieve higher energy saving than other lighting control methods.
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Artificial Intelligence
- Hardware and Architecture
- Computer Vision and Pattern Recognition