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首页> 外文会议>International High Performance Buildings Conference at Purdue >Comparison of Model Predictive Control Performance Using Grey-Box and White-Box Controller Models of a Multi-zone Office Building
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Comparison of Model Predictive Control Performance Using Grey-Box and White-Box Controller Models of a Multi-zone Office Building

机译：使用多区域办公楼的灰盒和白盒控制器模型模型预测控制性能的比较

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摘要

Model Predictive Control (MPC) is a promising control method to reduce the energy use of buildings. Its commercialization is, however, hampered by the difficulty of obtaining a reliable controller model. This paper compares two approaches to obtain such controller model: (1) a white-box model approach for which a detailed first-principles building model is linearized, and (2) a system identification method using a grey-box model approach. The MPC performance using both model approaches is evaluated on a validated 12 zones model of an existing office building. The results indicate that the MPC performance is very sensitive to the prediction accuracy of the controller model. This paper shows that both approaches can lead to an efficient MPC as long as very accurate identification data sets are available. For the considered simulation case, the white-box MPC resulted in a better thermal comfort and used only 50% of the energy used by the best grey-box MPC.
机译：模型预测控制（MPC）是一种有望的控制方法，以减少建筑物的能量使用。然而，它的商业化因获得可靠的控制器模型而受到阻碍。本文比较了两种方法来获得此类控制器型号：（1）一种白色盒式模型方法，其中详细的第一原理建筑模型是线性化的，并且（2）使用灰度盒式模型方法的系统识别方法。使用两种模型方法的MPC性能在现有办公楼的验证的12区模型上进行评估。结果表明，MPC性能对控制器模型的预测精度非常敏感。本文表明，只要可用非常准确的识别数据集，两种方法都可以导致高效的MPC。对于考虑的仿真情况，白盒MPC导致更好的热舒适性，仅使用最佳灰度箱MPC使用的50％的能量。

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