信息与控制2013，Vol.42Issue(1)：100-110,11.DOI:10.3724/SP.J.1219.2013.00100
基于粒子群优化的室内动态热舒适度控制方法
Indoor Dynamic Thermal Comfort Control Method Based on Particle Swarm Optimization
摘要
Abstract
A PMV (predicted mean vote)-based dynamic thermal comfort (cool/hot) complaint event model and an energy consumption model are proposed for the control method in which PMV values change alternatively between comfortable and energy-saving zones. An improved multi-objective algorithm based on discrete PSO (particle swarm optimization) is applied to calculating optimal values of parameters in dynamic comfort control system according to the balance (specified by users) between comfort and energy conservation. This method only needs to measure data of thermal environment and occupant's thermal sensation, without building the physical analytic model. Experiment results demonstrate the effectiveness of the proposed control method. In addition, the realizability of the optimal control to dynamic comfort is also verified.关键词
预测平均投票数/动态热舒适度/多目标粒子群优化算法/基于数据的控制Key words
PMV (predicted mean vote)/ dynamic thermal comfort/ multi-objective particle swarm optimization algorithm/data-based control分类
信息技术与安全科学引用本文复制引用
段培永,刘聪聪,段晨旭,李慧..基于粒子群优化的室内动态热舒适度控制方法[J].信息与控制,2013,42(1):100-110,11.基金项目
国家自然科学基金资助项目(61074070,61004005) （61074070,61004005）
山东省自然科学基金资助项目(ZR2009GZ004) （ZR2009GZ004）
山东省科技攻关项目(2009GG10001029). （2009GG10001029）
