Nonlinear system identification of thermal dynamics in buildings

Standard (black-box) linear regression models may not necessarily suffice for accurate identification of thermal dynamics in buildings. This is particularly apparent when either a radiant-heating (RH) system or a heating-ventilation-air-conditioning (HVAC) system is used for temperature control and the flow rate of the thermal medium varies significantly. For this reason, this paper analytically derives, using physical insight, and investigates nonlinear regression models for system identification of thermal dynamics in buildings. The performance of these models is compared with standard (black-box) linear regression models through simulations.

[1]  Dean Karnopp,et al.  System Dynamics: Modeling, Simulation, and Control of Mechatronic Systems , 1999 .

[2]  Michael Baldea,et al.  Model reduction and nonlinear MPC for energy management in buildings , 2013, 2013 American Control Conference.

[3]  Alex Simpkins,et al.  System Identification: Theory for the User, 2nd Edition (Ljung, L.; 1999) [On the Shelf] , 2012, IEEE Robotics & Automation Magazine.

[4]  Shengwei Wang,et al.  Multiple ARMAX modeling scheme for forecasting air conditioning system performance , 2007 .

[5]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[6]  Jie Chen,et al.  Prediction of room temperature and relative humidity by autoregressive linear and nonlinear neural n , 2011 .

[7]  S. Shankar Sastry,et al.  Energy management via pricing in LQ dynamic games , 2013, 2013 American Control Conference.

[8]  George J. Pappas,et al.  Event-based Green scheduling of radiant systems in buildings , 2013, 2013 American Control Conference.

[9]  George J. Pappas,et al.  Receding-horizon supervisory control of green buildings , 2011, Proceedings of the 2011 American Control Conference.

[10]  Nicolas Petit,et al.  Thermal building model identification using time-scaled identification methods , 2010, 49th IEEE Conference on Decision and Control (CDC).

[11]  Manfred Morari,et al.  Use of model predictive control and weather forecasts for energy efficient building climate control , 2012 .

[12]  Ali H. Sayed,et al.  Fundamentals Of Adaptive Filtering , 2003 .

[13]  Bo Wahlberg,et al.  Physics-based modeling and identification for HVAC systems? , 2013, 2013 European Control Conference (ECC).

[14]  A. Abdel-azim.  Fundamentals of Heat and Mass Transfer , 2011 .