  This work presents a whole-year simulation study on nonlinear mixed-integer
Model Predictive Control (MPC) for a complex thermal energy supply system which
consists of a heat pump, stratified water storages, free cooling facilities,
and a large underground thermal storage. For solution of the arising
Mixed-Integer Non-Linear Programs (MINLPs) we apply an existing general and
optimal-control-suitable decomposition approach. To compensate deviation of
forecast inputs from measured disturbances, we introduce a moving horizon
estimation step within the MPC strategy. The MPC performance for this study,
which consists of more than 50,000 real time suitable MINLP solutions, is
compared to an elaborate conventional control strategy for the system. It is
shown that MPC can significantly reduce the yearly energy consumption while
providing a similar degree of constraint satisfaction, and autonomously
identify previously unknown, beneficial operation modes.
