Hierachical Fuzzy MPC Concept for Building Heating Control

Abstract

This paper presents a hierachical model predictive control (MPC) structure with decoupled MPCs for building heating control using weather forcasts and occupancy information. The two level control structure embeds a fuzzy MPC (FMPC) for user comfort optimization and a mixed-integer MPC (MI-MPC) for energy optimization at minimal costs. As FMPC uses a set of local linear models classical linear MPC theory is applicable, though the underlying system dynamics is non-linear. The supply level in a large modern office building always features switching states of aggregates, hence an MI-MPC is used for energy supply optimization. Additionally, both FMPC and MI-MPC consider all relevant constraints. The innovation in this study, beside the usage of FMPC for building control, is the decoupling of the energy supply level and the user comfort with a single coupling node. Although a global optimum is not guaranteed, a decoupled control system often is more attractive for industrial applications and building operators. The perfomance of the proposed control structure is demonstrated in a simulation with a validated building model, and two different disturbance scenarios are presented.