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Performance improvement of an air-to-water heat pump through linear time-varying MPC with adaptive COP predictor
Journal of Process Control ( IF 3.3 ) Pub Date : 2021-02-03 , DOI: 10.1016/j.jprocont.2021.01.006
Soroush Rastegarpour , Riccardo Scattolini , Luca Ferrarini

Air-to-water heat pumps are one of the most common and energy efficient heating systems for buildings, particularly floor-heating plants. One way to further improve their effectiveness is to control the heat pump exploiting the dependence of its coefficient of performance (COP) on the external temperature and temperature of the return water from the load. In particular, it is possible to exploit the heat pump when its efficiency is higher, so optimizing its performance in a predictive manner, anticipating the impact of external conditions. For the case of an air-to-water heat pump, the optimization problem is nonlinear due to the load dependence of the heat pump COP and variable supply water flow rate. This may pose implementation problems. If we address a standard control hardware, simplified optimal control formulations are more effective. In this paper, we specifically address this issue, and a reduced-order, linear, but adaptive time-varying predictive model of the heat pump COP is designed. Our solution takes into account the variation of the heat pump efficiency based on the external temperature and the load profile, which are changing within the control horizon. The proposed COP model is then used within a linear time-varying model predictive controller formulation which provides a prediction of the heat pump dynamical behavior based on the load dependence of the heat pump COP, while tackling the nonlinearities of the system imposed by the variable water flow rate in the hot water tank and also by the load dependence of the heat pump COP. The proposed approach has been implemented and in detail tested on a reference model based on a real case study from the Denmark Technical University, Risø Campus, SYSLAB. An intensive simulation analysis and complements the testing, showing the accuracy and the potential of the method, also in the perspective of practical implementation.



中文翻译:

通过带有自适应COP预测器的线性时变MPC改进空气-水热泵的性能

空气到水的热泵是建筑物(尤其是地暖设备)最常见,最节能的供暖系统之一。一种进一步提高其效率的方法是利用热泵的性能系数(COP)对外部温度和负载回水温度的依赖性来控制热泵。特别是,可以在效率较高时使用热泵,从而以可预测的方式优化其性能,从而预见外部条件的影响。对于空气对水热泵而言,由于热泵COP的负载依赖性和可变的供水流量,优化问题是非线性的。这可能会带来实施问题。如果我们使用标准控制硬件,则简化的最佳控制公式将更为有效。在本文中,我们专门解决了这个问题,并设计了热泵COP的降阶,线性但自适应时变预测模型。我们的解决方案考虑了基于外部温度和负载曲线的热泵效率变化,这些变化在控制范围内变化。然后,将所提出的COP模型用于线性时变模型预测控制器公式中,该公式可根据热泵COP的负载依赖性提供对热泵动力学行为的预测,同时解决由可变水引起的系统非线性问题热水箱中的流量以及热泵COP的负载依赖性。所提出的方法已经实施,并在参考模型的基础上进行了详细测试,该模型基于来自SYSLAB丹麦技术大学RisøCampus的实际案例研究。深入的仿真分析和对测试的补充,也从实际实施的角度展示了该方法的准确性和潜力。

更新日期:2021-02-03
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