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中央空调系统节能的蚁群优化控制方法
引用本文:邝小磊,聂玉强,李安桂.中央空调系统节能的蚁群优化控制方法[J].哈尔滨工业大学学报,2009(8):217-220.
作者姓名:邝小磊  聂玉强  李安桂
作者单位:佛山建筑规划设计院;佛山建筑设计研究院;西安建筑科技大学市政与环境学院
基金项目:建设部科学技术项目计划资助项目(06-K5-30);广东省自然科学基金资助项目(05011006)
摘    要:针对中央空调系统运行时变性、非线性、多变量、大滞后等特性,提出了采用启发式全局寻优的蚁群优化算法对整个系统进行能耗寻优.通过建立空调系统能耗数学模型,采取蚁群算法对模型能耗最小化寻优,分析了信息素变挥发系数算法的收敛性,指出了算法以概率1收敛到最优解.同时对系统进行了控制结构改造及运行测试,结果表明,新的控制方法使空调系统能根据负荷变化进行参数动态调整,实现各设备运行匹配良好及工况较佳的目的,平均节能率达22.3%,获得较好的节能效果,对现有中央空调控制系统的节能改造具有借鉴作用.

关 键 词:空调系统  节能  优化  蚁群算法

Energy saving performances of central air-conditioning system and its optimal tactics
KUANG Xiao-lei,NIE Yu-qiang,LI An-gui.Energy saving performances of central air-conditioning system and its optimal tactics[J].Journal of Harbin Institute of Technology,2009(8):217-220.
Authors:KUANG Xiao-lei  NIE Yu-qiang  LI An-gui
Affiliation:1.Foshan Construction Project Institute,Foshan 528000,China;2.Foshan Architectural Design Institute,Foshan 528000,China;3.Municipal Administration and Environment College of Xi’an Construction Science and technique University,Xi’an 710072,China)
Abstract:In order to deal with the time-varying property,nonlinearity,multi-variables and large time delay characteristics of central air-conditioning system,ant colony optimization for power consumption of the whole system optimization was proposed. First a mathematical model of air-conditioning system energy consumption was established,and an ant colony algorithm for the model to minimize the power consumption optimization was adopted,then a variable pheromone coefficient algorithm and its convergence was analyzed. It is pointed out that the probability of 1 of the algorithm is converged to the optimal solution. At the same time,the the system control structure was transformated. The test results show that the self-adjustment of parameters of the new control method with dynamic load can be realized,and operation of all equipment in good working condition match better,and the average energy saving rate is up to 22.3%.
Keywords:air-conditioning system  energy saving  optimization  ant-colony algorithm
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