An Improved Approach for Online Optimization of Large-Scale Process Facilities

Online close-loop optimization of large-scale facilities using nonlinear programming techniques has been practiced for more than 30 years. Traditional approaches are limited by the need to wait for the entire facility to reach steady-state for the purpose of model parameterization, and the computational effort required to solve the engineering principles model-based full-state nonlinear problem.

This paper describes a novel approach to decompose large-scale engineering models into smaller modules that can be parameterized asynchronously, and to reduce the order of the plant-wide model used for determining economically optimal targets. The paper will also illustrate application of the approach to a feed-flexible ethylene plant.