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Application of model-based control strategy to hybrid free cooling system with latent heat thermal energy storage for TBSs

机译：基于模型的控制策略在TBS潜热蓄热混合自由冷却系统中的应用

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This paper explored the application of model predictive control (MPC) technology to the TBSs hybrid free cooling system with latent heat thermal energy storage (LHTES) unit for minimizing the building operational cost without sacrificing temperature requirements. First, the system was briefly introduced and the dynamic thermal process models of building structure and LHTES unit were developed. Then, a hierarchical control structure with dynamic multi-swarm particle swarm optimization was presented to address the dimensional challenge and discontinuities in control variables. Due to the considerable decrease of optimization variable space, the method presented in this paper enables long-term simulation and application in a real controller. Simulations were carried out based on a typical TBS building located in Beijing, China. The total energy consumption of the cooling system and the control quality of indoor air temperature were used as the criteria to evaluate the performance. Compared to a defined baseline case, the optimal control method can achieve significant energy saving, i.e. up to 18%. The impacts of the size of LHTES unit and the type of building structure were discussed, as well. The active and passive heat capacity both played a catalytic role in performance of MPC. Additionally, an uncertainty analysis demonstrated that the proposed approach has strong robustness and can handle quite high errors in forecasting building disturbances from energy consumption level. In summary, the knowledge and use of the plant system and future disturbances make MPC a powerful control tool for TBS buildings for maximizing the use of renewable energy sources. (C) 2018 Elsevier B.V. All rights reserved.
机译：本文探讨了模型预测控制（MPC）技术在带有潜热热能存储（LHTES）单元的TBS混合自由冷却系统中的应用，以在不牺牲温度要求的情况下最大程度地降低建筑物的运营成本。首先，简要介绍了该系统，并开发了建筑结构和LHTES单元的动态热过程模型。然后，提出了具有动态多群粒子群优化的分层控制结构，以解决控制变量的维数挑战和不连续性。由于优化变量空间的显着减少，本文提出的方法可以在实际控制器中进行长期仿真和应用。基于位于中国北京的典型TBS建筑物进行了仿真。冷却系统的总能耗和室内空气温度的控制质量被用作评估性能的标准。与定义的基准情况相比，最佳控制方法可实现显着的节能，即最多可节省18％。还讨论了LHTES单元的大小和建筑结构类型的影响。主动和被动热容量均对MPC的性能起催化作用。此外，不确定性分析表明，所提出的方法具有很强的鲁棒性，并且可以处理从能耗水平预测建筑物干扰方面的很高误差。总之，对电厂系统的了解和使用以及未来的干扰使MPC成为TBS建筑物的强大控制工具，可最大程度地利用可再生能源。 （C）2018 Elsevier B.V.保留所有权利。

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