MPC-Based Efficient Energy Control and Cost Estimation of HVAC in Buildings

The resistor-capacitor network (RC models) is a common approach to model thermal systems in buildings that proves advantageous in improving a building's energy efficiency. This paper presents a framework for energy consumption cost estimation and power efficient control in buildings-based model predictive control. The proposed framework calculates the electricity cost for dwellings based on their sizes using RC models. Additionally, it ensures consistent thermal comfort within the controlled building even during performance issues. The calculation of the cost of energy consumption takes into account the electricity tariff provided by Hydro-Quebec, Montreal, Quebec, Canada. Model Predictive Control (MPC) along with two backup controllers (ON/OFF control and Proportional-Derivative-Integral (PID) control) optimize the thermal model in a building, ensuring the desired indoor temperature efficiently with low cost. The Simulation results conducted on the Matlab/Simulink platform demonstrated that MPC control outperforms the other controllers in terms of energy consumption minimization and cost.