基于退火算法的医院中央空调优化控制研究

Research on Hospital Central Air Conditioning Optimization Control Based on Annealing Algorithm

为了使得高耗能的中央空调在大型建筑物内的使用更加节能环保,该研究以医院建筑物载体为例,将医院的中央空调优化控制分为采集、优化和控制三个阶段。利用AI/DI传感器对医院室内参数进行实时的搜集并转化为数据信号传输到优化系统中,并建立各空调设备费用开销与总能耗的目标函数,通过退火算法对样本测量值与预测值之间进行实时的偏差计算以调节最优设定值操作,最后将控制信号传输到DDC控制器中以完成对各空调设备的优化控制。经过实验测试的结果表明:优化后的医院中央空调可节省能耗最大值为86kW,节能率为16.24%,2h内的平均节能率为9.12%,可有效地减少电能的开销。

In order to make energy-efficient central air-conditioning in the use of large buildings more energy saving and environmental protection,this study takes the hospital building carrier as an example,the hospital central air conditioning optimization control is divided into three stages of acquisition,optimization and control. Using AI/DI sensor to real-time collection of hospital indoor parameters and converted into data signals to optimize the system,and the establishment of the cost of air conditioning equipment and the total energy consumption of the objective function of the sample by annealing the measured value and the predicted value real-time deviation calculation to adjust the optimal setpoint operation,and finally the control signal to the DDC controller to complete the optimization of the air conditioning equipment control. The experimental results show that the maximum energy saving is 86 kW,the energy saving rate is 16.24%,and the average energy saving rate is 9.12% within 2 h,which can effectively reduce the energy cost.