Application of Economics Optimizing Control to a Two-step Transesterification Reaction in a Pilot-Scale Reactive Distillation Column

Abstract

The challenges in the chemical process industry of tighter environmental and safety constraints, a higher economic efficiency and an operation in a more dynamic environment motivate the utilization of optimizing control where economic policies are integrated into a (often nonlinear) model predictive control scheme. This so-called one-layer approach or dynamic real-time optimization (D-RTO) has the advantage that the processes are dynamically steered towards the most profitable region. High-fidelity dynamic process models are a basic prerequisite for a good controller performance, and building such models is a challenge. Using highly complex models also may lead to long computation times and thus feedback delays. These issues are in practice avoided by applying only steady-state optimization based on nonlinear models (RTO) and/or using simplified models in MPC. However, the development of computational methods that are able to solve large-scale dynamic optimization problems efficiently have paved the way for applications of economics optimizing control to complex chemical processes. In this contribution, we will demonstrate that a real complex pilot-scale chemical processes, a two-step transesterification realized by reactive distillation that is described by a large DAE model can be operated at the economic optimum by using direct optimizing control. We discuss the problem formulation and the numerical methods used and show experimental data that were obtained at the real process.