A whole-year simulation study on nonlinear mixed-integer model predictive control for a thermal energy supply system with multi-use components.

• Whole-year nonlinear mixed-integer MPC simulation study for a thermal energy system. • General approximate MINLP solution method and measurement-based forecast correction. • Performance comparison of MPC to an elaborate conventional control strategy. • Energy consumption of the system is significantly reduced using MPC. • MPC autonomously identifies previously unconsidered, beneficial operation modes. 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. [ABSTRACT FROM AUTHOR]