Multi-stage regression linear parametric models of room temperature in office buildings
- 作者：Siyu Wu swu8@ucmerced.edu ; Jian-Qiao Sun ; jqsun@ucmerced.edu
- 关键词：HVAC system ; Temperature model ; Multi-stage regression ; Autoregressive model
- 刊名：Building and Environment
- 出版年：2012
- 期刊代码：21_03601323
- 类别：et
- 出版时间：October, 2012
- 卷：56
- 期：Complete
- 页码：69-77
- 文件大小：505 K
摘要
Mathematical models of the heating, ventilation, and air conditioning (HVAC) components play an important role in control design and fault detection of the system. The work in this paper incorporates architectural parameters in linear parametric models of room temperature in office buildings. Specifically, we allow the physics-based autoregression moving average (pbARMAX) model to have a multi-stage structure in order to explicitly include the architectural parameters of the room in the model. Extensive measurements of the room temperature are used to develop and validate the multi-stage model. The resulting model can predict the temperature in different rooms accurately in both short-term and long-term. Over a period of four weeks, the predictions have a root mean squared error less than 0.10 with a coefficient of determination larger than 0.99.