本文提出了 1种用于热泵蓄能系统的模型预测控制(Model Predictive Control,MPC)框架,并针对1个实际系统提出了相应的负荷预测、系统模型和MPC优化算法.通过建立的仿真平台对固定日程控制(Rule-Based Control,RBC)和MPC方式进行了模拟实验测试和分析,测试后的算法可以方便地移植到实际控制系统中.对比分析结果表明MPC控制方式可以提高系统运行期间的蓄能率,并计及了机组性能系数(Coefficient of Performance,COP)、蓄能速率、水泵能耗以及热损失差异,从而可以获得更好的运行效果和系统稳定性.
Case Study and Simulation of Model Predictive Control Method for Typical Heat Pump Thermal Energy Storage System
This paper proposed a model predictive control(MPC)framework for heat pump thermal energy storage systems,and presented load prediction,a system model,and an MPC optimization algorithm for a real system accordingly.On the established simulation platform,the rule-based control(RBC)and MPC methods were simulated and analyzed.The tested algorithm can be easily implemented in real control systems.The comparative analysis results showed that the MPC method can improve the energy storage efficiency during system operation by considering factors such as the coefficient of performance(COP),energy storage rate,pump energy consumption,and heat loss differences of the unit,thus achieving better operation performance and system stability.
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