A hydraulic balance regulation and return water temperature prediction model for the secondary network of centralized heating system is designed to address the issue of hydraulic imbalance,and an intelligent control strategy is implemented to achieve precise control of return water temperature in the secondary network.Firstly,a BP neural net-work prediction model is constructed,which treats the output of this model as the given value of the secondary network return water temperature.Secondly,in the entire system control,a strategy combining BP neural network and PID con-troller is implemented to control the return water temperature of the secondary network.Based on the data of a heat exchange station in a residential area of Gaoyi County,a mathematical model of the secondary network return water tem-perature control system is established using the step response curve method,and simulation experiments are conducted using BP-PID control.The experimental results show BP-PID controllers have the advantages of short adjustment time and small overshoot,and can quickly reach a stable state compared with traditional PID controllers.
关键词
BP神经网络/预测模型/BP-PID控制器/二次网回水温度/水力平衡
Key words
BP neural network/prediction model/BP-PID controller/secondary network return water tempera-ture/hydronic balance
维普
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