TY  - EJOUR
AU  - Baader, Florian
AU  - Bardow, André
AU  - Dahmen, Manuel
TI  - Simultaneous mixed-integer dynamic scheduling of processes and their energy systems
M1  - FZJ-2022-00694
PY  - 2021
N1  - 25 pages, 14 figures, 3 tables
AB  - Increasingly volatile electricity prices make simultaneous scheduling optimization for production processes and their energy supply systems desirable. Simultaneous scheduling needs to account for both process dynamics and binary on/off-decisions in the energy system and thus leads to challenging mixed-integer dynamic optimization problems. In this contribution, we propose an efficient scheduling formulation that consists of three parts: a linear scale-bridging model for the closed-loop process output dynamics, a data-driven model for the process energy demand, and a mixed-integer linear model for the energy system. Process dynamics are discretized by collocation yielding a mixed-integer linear programming (MILP) formulation. We apply the scheduling method to a single-product reactor, with 5.6% economic improvement compared to steady-state operation, and a multi-product reactor, with 5.2% improvement compared to sequential scheduling. While capturing 85% and 96% of the improvement realized by a nonlinear optimization, the MILP formulation achieves optimization runtimes sufficiently fast for real-time scheduling.
LB  - PUB:(DE-HGF)25
UR  - https://juser.fz-juelich.de/record/905453
ER  -