中国照明电器

传统室内照明布局存在光照分布不均、能源浪费等问题。遗传算法、粒子群算法等优化算法因其在多目标、多约束问题中的高效求解能力，为照明布局与能效协同优化提供了新思路。文章探讨了基于优化算法的室内照明布局与能效提升策略，并验证：算法实现日常办公场景动态调光使能耗下降28%,照度波动控制在7%;会议核心区照度增强23%且眩光指数100%达标，证明基于算法优化的室内照明能够获得经济与环境效益。

Traditional indoor lighting layout has problems such as uneven light distribution and energy waste.Optimization algorithms such as genetic algorithm and particle swarm optimization provide new ideas for collaborative optimization of lighting layout and energy efficiency due to their efficient solution ability in multi-objective and multi-constraint problems.This paper discusses the indoor lighting layout and energy efficiency improvement strategy based on the optimization algorithm, and verifies that the dynamic dimming of the algorithm in daily office scenes reduces the energy consumption by 28%,and the illuminance fluctuation is controlled by 7%;The 23% increase in illumination and 100% glare index in the core area of the conference proved that algorithm-optimized indoor lighting can achieve economic and environmental benefits