| Title |
Room air Temperature Prediction Model using Genetic Programming and BEMS Data |
| Authors |
Suh, Won Jun ; Park, Cheol Soo |
| DOI |
http://dx.doi.org/10.5659/JAIK_PD.2016.32.6.105 |
| Keywords |
Model Predictive Control (MPC) ; Data-driven Model ; Genetic Programming ; BEMS |
| Abstract |
Recently, BEMS(Building Energy Management Systems) are widely adopted in large existing buildings and there is a growing interest in applying model-assisted optimal control based on the BEMS data. Unfortunately, current BEMS are used only for measurement, data collection and rule-based operation. It would be ideal if a building's data-driven energy model can be automatically generated out of BEMS data and is used for real-time optimal control. This paper presents such approach that a data-driven genetic programming can be beneficially utilized for automatic development of a room air temperature prediction model. In this study, the room air temperature prediction model was developed and successfully validated using the genetic programming and actual BEMS data. In the paper, pros and cons of the genetic programming approach is discussed. |