Dynamic Scheduling: A Comparison of High-Fidelity Models with Local Optimization versus Surrogate Models with Global Optimization

Industrial & Engineering Chemistry Research, vol. 64, pp. 21641–21657

Abstract

High Resolution Image Download MS PowerPoint Slide Flexible process operation supports demand-side management under fluctuating electricity prices, with integrated scheduling and control enabling coordinated, real-time decisions. This work investigates the trade-off between model fidelity and optimization complexity in dynamic scheduling under integrated dynamic scheduling, using an air separation process in a day-ahead electricity market. We explore mechanistic and typical surrogate dynamic models yielding established optimization formulations combined with standard global and local solution strategies. (Non)linear surrogates are used in full-discretization, formulating (mixed-integer) linear and nonlinear scheduling problems. Local dynamic scheduling with full-order mechanistic models yields superior performance. Conversely, deterministic global dynamic optimization incurs infeasibilities for linear surrogates, and computational intractability for nonlinear surrogates due to branch-and-bound limitations. Instead, stochastic local optimization (multistart) with nonlinear models offers an alternative, delivering high-quality solutions. We conclude that local dynamic scheduling with mechanistic models, and multistart with Hammerstein-Wiener models are preferable for available detailed process models or operational data, respectively.

Authors 3

1. Chrysanthi Papadimitriou Aachen

   RWTH Aachen University

   Affiliation as printed

   Process Systems Engineering (AVT.SVT)

   RWTH Aachen University

2. Michael Bâldea

   The University of Texas at Austin

   Affiliation as printed

   McKetta Department of Chemical Engineering

   Oden Institute for Computational Engineering and Sciences

   The University of Texas at Austin

3. Alexander Mitsos corresponding Aachen

   RWTH Aachen University · Forschungszentrum Jülich · Jülich Aachen Research Alliance

   Affiliation as printed

   Energy Systems Engineering (ICE-1)

   Forschungszentrum Jülich

   JARA-ENERGY

   Process Systems Engineering (AVT.SVT)

   RWTH Aachen University