Modelica Based Grade Change Optimization for a Polyethylene Reactor

This paper presents a dynamic optimization procedure of grade changes of polyethylene production. The optimization is built upon a novel modular Modelica library containing e.g., non-linear DAE models for polyethylene reactors based on models currently used in nonlinear MPC of industrial reactors at Borealis AB. Using Optimica, which extends the Modelica language with constructs for optimization problems, and JModelica.org, a novel framework to translate such optimization problems into NLP problems, grade transition optimization problems can be solved. The solution procedure and a transition example with optimal inputs and outputs are given in the paper showing promising results.