Hierarchical Model Predictive Control for Complex Building Energy Systems

In this paper, a hierarchical Modelica-based Model Predictive Control (MPC) is presented in order to control complex building energy systems with different dynamics. The hierarchical MPC concept tackles the problem of controlling buildings with slow dynamics such as thermally activated building systems (TABS) and fast actuators such as air handling units (AHUs). It further addresses prediction errors of system disturbances (e.g. weather, occupancy) and ensures anticipation, reactivity and real-time capability. The benefits compared to single MPC, Rule-Based-Control (RBC) and Proportional-Integrative-Derivative (PID) strategies are demonstrated in simulations on Modelica models including detailed models for solar shading and visual comfort