Optimal temperature control of intermittently heated buildings using Model Predictive Control: Part I – Building modeling

2012 ◽  
Vol 51 ◽  
pp. 379-387 ◽  
Author(s):  
Ion Hazyuk ◽  
Christian Ghiaus ◽  
David Penhouet
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Temperature Control ◽  
Optimal Temperature ◽  
Building Modeling ◽  
Control Part

Model Predictive Control (MPC) for Building Optimal Temperature Control

2018 ◽  
Author(s):  
Jarrou Abderrahmane ◽  
Domenic Sauter ◽  
Karim Alami ◽  
Chouri Brahim ◽  
Ailane Abdellah
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Temperature Control ◽  
Optimal Temperature

Model Predictive Control (MPC) for Building Optimal Temperature Control

2018 ◽  
Author(s):  
Jarrou Abderrahmane ◽  
Domenic Sauter ◽  
Karim Alami ◽  
Chouri Brahim ◽  
Ailane Abdellah
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Temperature Control ◽  
Optimal Temperature

Ultra-Supercritical Power Unit Steam Temperature Control Based on Model Predictive Control

2013 ◽  
Vol 291-294 ◽  
pp. 2240-2243
Author(s):  
Guo Liang Wang ◽  
Wei Wu Yan ◽  
Shi He Chen ◽  
Xi Zhang ◽  
Heng Feng Tian ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Temperature Control ◽  
Step Response ◽  
Outlet Temperature ◽  
Temperature Step ◽  
Steam Temperature ◽  
Efficient Operation ◽  
Response Models ◽  
Simulation Results

The steam temperature control is important to Ultra-supercritical (USC) unit for safe and efficient operation under load tracking. In this paper, a model predictive control (MPC) method is introduced for reheated steam temperature control of USC unit. Two inputs (i.e. damper, spray attemperator) are employed to control two outputs (i.e. primary reheater outlet temperature and finish reheater outlet temperature). Step response models of the reheater temperature are achieved using the two inputs by two outputs model. In simulation, the reheated steam temperature can be controlled around the setpoint closely in load tracking. The simulation results show the effectiveness of the proposed methods.

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