Simplified building model for transient thermal performance estimation using GA-based parameter identification
Simplified building model for transient thermal performance estimation using GA-based parameter identification
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DOI：
10.1016/j.ijthermalsci.2005.06.009
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发表时间：
2006-04
影响因子：
4.5
通讯作者：
Shengwei Wang;Xin-hua Xu
中科院分区：
文献类型：
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作者：
Shengwei Wang;Xin-hua Xu
建立简单有效的模型对于建筑物性能诊断和最优控制等许多应用都是必不可少的。详细的物理模型非常耗时，而且往往不具有成本效益。黑箱模型需要大量的训练数据，并且可能并不总是反映物理行为。本文提出了一种简化建筑热模型和辨识简化模型参数的方法。对于建筑物围护结构，可以在频率特性分析的基础上，利用容易获得的物理细节来确定模型参数。由于建筑物内部质量涉及各种构件，很难获得其详细的物理性质。为了克服这个问题，建筑物的内部质量表示的热网络的集中热质量和参数识别使用的操作数据。遗传算法（GA）估计开发，以确定这些参数。以一座真实的商业办公建筑为例，在不同气象条件下对简化的动态建筑能耗模型进行了验证。
Building simple and effective models are essential to many applications, such as building performance diagnosis and optimal control. Detailed physical models are time consuming and often not cost-effective. Black box models require large amount of training data and may not always reflect the physical behaviors. In this study, a method is proposed to simplify the building thermal model and to identify the parameters of the simplified model. For building envelopes, the model parameters can be determined using the easily available physical details based on the frequency characteristic analysis. For the building internal mass involving various components, it is very difficult to obtain the detailed physical properties. To overcome this problem, the building internal mass is represented by a thermal network of lumped thermal mass and the parameters are identified using operation data. Genetic algorithm (GA) estimators are developed to identify these parameters. The simplified dynamic building energy model is validated on a real commercial office building in different weather conditions.