基于数据挖掘模型的冷却水温度监督控制

Supervisor Control for Condenser Water Temperature Based on Data Mining

为降低冷却水系统与冷水机组运行能耗,通过改变冷却塔风量控制来保持温度恒定。采用数据挖掘技术分析历史运行数据,建立了冷水机组运行能耗预测模型和冷却塔运行状态预测模型;以冷却水系统能耗最小为目标,构建了约束条件与优化目标函数,采用模式搜索算法优化求解,并编制监督控制程序对冷却水供水温度设定点进行优化。用能耗模拟软件TRNSYS与MATLAB联合仿真测试监督控制程序,结果表明,与定温度及定逼近度控制法相比,基于数据挖掘模型的监督控制法能够有效降低系统能耗。

In order to save energy of condenser water loop and chiller,the data mining technology was employed to analyze operation parameters of condenser water loop with constant degree of approximation control. The predicted energy consumption model and limitations of condenser water loop were constructed. Based on the predicted models,the optimization objective function and constraint condition for the system were set up. A pattern search algorithm was used to obtain the optimal set point of cooling water supply temperature. Programming the online optimization program code with MATLAB,the performance was tested with TRNSYS. The results of simulation were contrast with constant set point method and constant degree of approximation control method. It is indicated that the supervisor control method is effective to decrease the energy consumption of condenser water system.