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Simultaneous identification of dynamic model and occupant-induced disturbance for commercial buildings

机译：同时识别商业建筑的动力学模型和人为干扰

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A model of a building's thermal dynamics is needed for prediction-based control. The task of identifying a thermal dynamic model is made challenging by the presence of large unmeasured disturbances, especially the heat gain due to the occupants. In fact, identification of this "occupant-induced load" is also valuable for predictive control especially in commercial buildings. We propose a method to identify both a model (of resistance-capacitance network type) and the unmeasured disturbances from measured input-output data. The method is based on the insight that the main contributor to the unmeasured disturbance, the occupant-induced load, is piecewise constant, especially in commercial buildings. This can be used to construct an augmented dynamic model so that disturbance estimation is converted to a state estimation problem. An outer-loop optimization identifies the best-fit parameter values. The effectiveness of the method is evaluated using data from a simulation model (under both open and closed-loop operations) and a real building.
机译：基于预测的控制需要建筑物的热动力学模型。由于存在大量无法测量的扰动，尤其是由于乘员引起的热量增加，因此识别热力学模型的任务变得具有挑战性。实际上，这种“乘员引起的负荷”的识别对于预测控制尤其是在商业建筑中也很有价值。我们提出一种从测量的输入输出数据中识别模型（电阻-电容网络类型）和未测量的干扰的方法。该方法基于这样的见解，尤其是在商业建筑中，未测干扰的主要贡献者，乘员感应的载荷是分段恒定的。这可以用于构建增强的动态模型，以便将干扰估计转换为状态估计问题。外环优化可确定最适合的参数值。使用模拟模型（在开环和闭环操作下）和实际建筑物中的数据评估该方法的有效性。

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