DyOS - A Framework for Optimization of Large-Scale Differential Algebraic Equation Systems - Caspari, A.; Bremen, A.M.; Faust, J.M.M.; Jung, F.; Kappatou, C.D.; Sass, S.; Vaupel, Y.; Hannemann-Tamás, R.; Mhamdi, A.; Mitsos, A. (Computer Aided Chemical Engineering, 2019)
Dynamic optimization problems arise in many fields of engineering. Typically, they are subject to models of differential-algebraic equations and further process constraints. To promote and investigate the application of methods based on dynamic optimization, an efficient and modular implementation of numerical algorithms for their solution is essential. We present the current status of the open-source software DyOS for the solution of large-scale dynamic optimization problems. DyOS has been applied to optimal operation, model-predictive control and process design problems in various case studies. DyOS is based on direct adaptive shooting algorithms and it allows for multi-stage problem formulations including binary decision making. Models can either be imported as standardized functional mock-up units, flat Modelica models, or C++ models. The modular implementation of DyOS enables the use of various open-source and commercial integrators and nonlinear programming solvers based on various numerical methods. DyOS can be accessed via Matlab or Python interfaces. As an illustrative large-scale application, we present the results of optimal operation of an air separation process under fluctuating electricity prices. An open-source version of DyOS including several parts of the framework presented is available at http://permalink.avt.rwth-aachen.de/?id=295232.