Control of Indoor Environmental Conditions Based on the Model and Use of Predictive Control Method

In this paper, a model predictive control approach is presented to regulate indoor temperature. In recent years, the highest energy consumption in buildings is related to heating, ventilation, and air conditioning systems. Therefore, the control of heating, ventilation, and air conditioning systems in buildings has been taken into consideration to reduce energy consumption. At first, a construction model is designed in the Energy-plus software, then all input and output data is collected from this software to identify the state-space model. Then the Model-based predictive control algorithm is applied to control the indoor building temperature. The contribution of this paper is two-fold. Firstly, the data used in the system identification section is based on the assumption that the rooms are not isolated. There is a temperature relationship between the rooms, which provides a more realistic model of the system. Secondly, the external ambient temperature is considered as a disturbance, and its effect on controller design has been investigated. The simulation results for 24 hours show the good performance of the model predictive control approach over the optimal control method along with reducing energy consumption while maintaining the optimal temperature conditions.