Minimizing the Energy and Demand Cost of Building Energy Systems Based On Economic MPC

A simulation-based control system was established in our previous work to show the effectiveness of model predictive control in reducing the energy and demand costs for HVAC systems of commercial buildings. An economic objective function was introduced in the MPC framework to account for the electricity cost under time-of-use rate and demand charges.

In this work, we improve the configuration and iterative procedure of optimization in MPC to achieve larger economic profits. Soft constraints are applied to handle the infeasibility problem and the relation between cost savings and constraint violations is investigated. In the perspective of modeling, we utilize variables from air handling units (AHU) such as sensible cooling rate and air mass flow rate in addition to zone temperature setpoints to enhance the accuracy of model prediction. Besides, the robustness of the control system is studied by carrying out sensitivity analysis on ambient temperatures.