Development of a novel strategy of CFD-based model predictive control

Abstract

With increasing energy consumption, growing attentions are given to reduce the carbon footprint in the world. The building sector is always one of the largest energy end user in many developed countries. Energy management of heating, ventilating and air-conditioning (HVAC) system is a key issue in building energy analysis, since the energy cost of HVAC system is the highest among those of all other building services installation and electrical appliances. The air-conditioned environment is an essential component for a HVAC system and the rationality of airflow pattern has significant influence on the energy use of air-conditioning. Therefore, it appeals to control temperature and air velocity distributions in an air-conditioned environment to achieve the optimized thermal comfort with the minimized energy consumption. In the present work, a novel model is developed by integrating a simplified Computational Fluid Dynamics (CFD) model into the model predictive control (MPC) algorithm for a CFD-based MPC (CFDbMPC) system. Firstly, based on the two dimensional Navier-Stokes equations, a CFD model is simplified for simulation of the air-conditioned indoor environment, in order to significantly reduce computational cost with desired numerical accuracy. The simplified CFD model is then integrated into the MPC algorithm with assistance of the successive linearization method. Finally, the preliminary case studies are conducted by the proposed CFDbMPC system.