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Exergy-based optimal control of a vapor compression system

机译：基于火用的蒸气压缩系统的最优控制

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摘要

Exergy-based analysis and optimization has been successfully used to design a variety of thermal systems to achieve greater efficiency. However, the advantages afforded by exergy destruction minimization (EDM) at the design stage have not been translated to closed-loop operation of thermal systems such as vapor compression systems (VCSs). Through online optimization and control, VCSs can effectively respond to disturbances, such as weather or varying loads that cannot be accounted for at the design stage, while simultaneously maximizing system efficiency. Furthermore, in applications where VCSs encounter high frequency disturbances, such as in refrigerated transport applications or passenger vehicles, optimizing efficiency at steady-state conditions alone may not lead to significant reductions in energy consumption. In this paper we design the first exergetic, or second law, optimal controller for a canonical four-component vapor compression system (VCS). A lumped parameter moving boundary modeling framework is used to model the two heat exchangers in the VCS. A model predictive controller is then designed and implemented in simulation using a dynamic exergy-based objective function to determine the optimal control actions for the VCS to maximize exergetic efficiency while achieving a desired cooling capacity. Simulation results show that an exergy-based model predictive controller minimizing exergy destruction achieves over 40% greater exergetic efficiency during operation than a comparable first law MPC. Moreover, the distribution of exergy destruction across individual components offers new insight into the effect of variable-speed actuators on system efficiency in VCSs.
机译：基于火用的分析和优化已成功用于设计各种热系统，以实现更高的效率。但是，在设计阶段由“火用破坏最小化”（EDM）提供的优势尚未转化为热力系统（如蒸气压缩系统（VCS））的闭环运行。通过在线优化和控制，VCS可以有效响应各种干扰，例如在设计阶段无法解决的天气或变化的负载，同时最大程度地提高系统效率。此外，在VCS遇到高频干扰的应用中（例如在冷藏运输应用或乘用车中），仅在稳态条件下优化效率可能不会显着降低能耗。在本文中，我们设计了规范的四分量蒸气压缩系统（VCS）的第一个泛能或第二定律最优控制器。集总参数移动边界建模框架用于对VCS中的两个热交换器进行建模。然后，使用基于动态能值的目标函数在仿真中设计和实现模型预测控制器，以确定VCS的最佳控制动作，以在达到所需冷却能力的同时最大化能效。仿真结果表明，与可比的第一定律MPC相比，基于火用的模型预测控制器将火用破坏最小化，其运行效率高出40％以上。此外，本能破坏在各个组件之间的分布为VCS中变速执行器对系统效率的影响提供了新的见解。

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