中央空调冷冻水系统遗传蚁群算法优化控制研究  

Research on optimal central air-conditioning chilled water system control based on GA-ACO algorithm

作　　者：喻锴 张九根 朱元[1,2] YU Kai;ZHANG Jiugen;ZHU Yuan(College of Electrical Engineering and Control Science,Nanjing Tech University,Nanjing 211816,China;Institute of Intelligent Building,Nanjing Tech University,Nanjing 211800,China)

机构地区：[1]南京工业大学电气工程与控制科学学院,江苏南京211816 [2]南京工业大学建筑智能化研究所,江苏南京211800

出　　处：《现代电子技术》2019年第11期135-139,共5页Modern Electronics Technique

摘　　要：针对中央空调冷冻水系统控制存在的节能及稳定有效缺陷的问题,提出一种遗传蚁群算法综合优化控制策略。首先对冷冻水系统建模;然后利用遗传算法对蚁群算法的运行参数进行优化,使蚁群算法寻优能力更佳;最后采用改进蚁群算法优化冷冻水变流量PID控制器参数。通过仿真以及实验对比分析发现,在对蚁群算法的运行参数优化过后,系统的稳定性明显加强,具有较强的鲁棒性,在满足室内负荷的前提下,节能效果也有所改善。A new comprehensive optimization scheme based on genetic algorithm(GA)and ant colony optimization(ACO)algorithm is proposed to solve the problems of energy saving and effective stability existing in central air-conditioning chilled water system control.The mathematical model of central air-conditioning chilled water system is constructed,and then the running parameters of ACO algorithm are improved by GA,which makes the optimization ability of ACO algorithm better.The improved ACO algorithm is used to optimize the parameters of PID controller for chilled water variable flow.The contrastive analysis results of simulation and experiment show that the system stability after running parameters optimization of ACO algorithm has higher stability and stronger robust,and the energy saving effect is also improved while satisfying the indoor load.

关 键 词：中央空调 冷冻水系统 遗传算法 蚁群算法 PID控制器 参数优化 

分 类 号：TN876-34[电子电信—信息与通信工程] TP273[自动化与计算机技术—检测技术与自动化装置]