摘要
在变风量空调系统中,为了减少系统能耗并对静压控制回路进行稳定而有效的控制,提出了一种静压优化控制方法,根据各末端风阀开度的变化确定空调系统所需的最小静压设定值,采用粒子群算法优化神经网络,调整PID控制器的3个参数,通过PID控制器调节变频风机的频率,把实际静压控制在设定值附近。通过仿真和实验对该控制方法的有效性和优越性进行了验证。结果表明,采用该方法在满足空调系统负荷需求的前提下能使末端阀门处于较大的开度,降低了风机的运行频率,改进了控制质量,提高了控制精度,不仅能够有效节能,还具有较强的鲁棒性。
In the variable air volume air conditioning system,proposes an optimization control method of static pressure to reduce energy consumption and effectively control.Determines the minimum static pressure set-point according to the opening of the terminal valve.Optimizes neural network using the particle swarm optimization algorithm,adjusts three parameters of PID controller and makes the static pressure close to the set value through the adjustment of frequency conversion fan by PID controller.Verifies this method by the simulation and experiments.The results show that the terminal valve is in a larger opening,which can reduce the fan operating frequency,and improve the control quality and precision when meeting the load demand.It not only effectively saves energy,but also has strong robustness.
出处
《暖通空调》
北大核心
2016年第3期84-88,共5页
Heating Ventilating & Air Conditioning
基金
甘肃省自然科学基金资助项目(编号:148RJZA022)
甘肃省工业过程先进控制重点实验室基金资助项目(编号:XJK201512)
国家自然科学基金资助项目(编号:61463029)
关键词
变风量空调
静压
优化控制
神经网络
PID控制器
节能
variable air volume air conditioning
static pressure
optimization control
neural network
PID controller
energy saving
