摘要
基于变风量空调系统节能效果好,但存在相对湿度变化范围较大的问题,提出了一种变风量空调系统的变机器露点控制方案,建立了基于Elman神经网络模型的变机器露点送风温度预测方法的仿真系统。仿真结果表明,该方法可以明显提高变风量空调系统相对湿度变化精度,也说明了采用Elman神经网络是一种可靠的变机器露点送风温度预测途径。
To solve the wide change of relatively humidity of Variable Air Volume （VAV） system, which has the advantages of energy saving, a control scheme of changing machine dew point is brought forward, and the simulation system of supply air temperature forecast for changing machine dew point based on Elman Neural Network model is established. The result of simulation shows that this way can improve the precision of relatively humidity and the Elman neural network is a credible forecast way.
出处
《建筑热能通风空调》
2008年第4期29-32,共4页
Building Energy & Environment
关键词
变风量空调系统
变机器露点
送风温度
Elman神经网络模型
Variable Air Volume （VAV） system, change machine dew point, supply air temperature, Elman Neural Network
