| Energy requirements for heating and cooling of residential, commercial and industrial spaces constitute a major fraction of end-use energy consumption. In the United States, there are almost 81 million buildings, which consume 71% of the national electricity energy usage, 41% of the total national energy usage, and are responsible for 38% of national CO2 emissions. Heating, Ventilation, and Air Conditioning (HVAC) uses almost 50% of the energy in these buildings. Modern Control schemes are becoming increasingly popular to meet the energy savings requirements for buildings.;This thesis presents a ventilation control strategy for multi-zone VAV air-conditioning systems based on Model Predictive Control (MPC). MPC is one of the most suitable modern control solutions for keeping thermal comfort, in buildings, with minimal energy consumption. This is due, in part, to the fact that it can handle multi-input and multi-output system and constraints as well as added in input or output.;Due to the fact that MPC relies on a dynamic model, the first step in the process is obtaining a thermal dynamic model for the to-be-controlled building. The model is based on three heat transfer processes: conduction, convection and radiation. The model also captures the heat generation inside the building. Finally, the model is written in form, which is more convenient for control design.;The proposed model is then used to design predictive control strategies. MPC can handle a multiple control objective, inherent complexity due to the coupled and multivariable nature of the problem, and the presence of constraints. In MPC, the control input signal is calculated by solving an optimal control problem, where a cost function is minimized over a given horizon. At last, we can compare the energy consumption of the MPC HVAC control scheme with the traditional two position on/off HVAC control scheme. |
