Identification of Network Dynamics and Disturbance for a Multizone Building
Identification of Network Dynamics and Disturbance for a Multizone Building
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DOI：
10.1109/tcst.2019.2949546
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发表时间：
2020-09
影响因子：
4.8
通讯作者：
Tingting Zeng;P. Barooah
中科院分区：
文献类型：
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作者：
Tingting Zeng;P. Barooah
我们提出了一种方法，可以根据输入和输出的测量同时识别多区域建筑温度动态的稀疏传输矩阵和扰动信号。所提出的方法基于解决凸优化问题，其成本函数涉及 $\ell _{1}$ 惩罚以促进稀疏解决方案。该方法确保传递矩阵是稀疏的，以便模型中仅保留区域之间的主要相互作用。干扰主要是由乘员引起的，假设为分段常数信号，这有助于识别，因为分段常数信号的导数是稀疏信号。我们使用来自虚拟建筑（模拟模型）和真实建筑的数据测试我们的方法。虚拟建筑的结果表明，该方法可以准确识别稀疏网络模型和变换后的扰动。真实建筑数据的结果（没有基本事实）表明该方法产生了合理的结果。
We propose a method that simultaneously identifies a sparse transfer matrix and a disturbance signal for a multizone building’s temperature dynamics from the measurements of inputs and outputs. The proposed method is based on solving a convex optimization problem whose cost function involves an $\ell _{1}$ -penalty to promote a sparse solution. The method ensures that the transfer matrix is sparse, so that only dominant interactions among zones are retained in the model. The disturbance, which is mostly occupant-induced, is assumed to be a piecewise-constant signal, which aids in identification, since the derivative of a piecewise-constant signal is a sparse signal. We test our method on data from a virtual building (a simulation model) and a real building. Results from the virtual building show that the proposed method can accurately identify a sparse network model and a transformed disturbance. Results from the real building data—that does not have a ground truth—show that the method produces sensible results.