A whole-year simulation study on nonlinear mixed-integer model predictive control for a thermal energy supply system with multi-use components. (15th January 2020) - Bürger, Adrian; Bohlayer, Markus; Hoffmann, Sarah; Altmann-Dieses, Angelika; Braun, Marco; Diehl, Moritz
Highlights: 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. Abstract: 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.