Dynamic Optimization of Multiproduct Cryogenic Air Separation Unit Startup

The startup of multiproduct air separation units (ASUs) is of relatively long duration with limited revenue generation, during which high costs are incurred due to the energy-intensive nature of ASU operations. With current energy market trends, there is a strong incentive to improve the startup operation of multiproduct ASUs. In this paper, we focus on the development of a dynamic optimization framework for improving the startup of multiproduct ASUs. The underlying model of the ASU utilized in the framework captures discontinuities present at startup, and both time and profit metrics are used for the objective function in the formulation. In the case studies presented here, improvements and trade-offs of the respective objective functions are assessed. The time-based formulation is also used for a liquid-assisted startup study using process liquid collected from a preceding shutdown. An increase in profits of 7% over a simulated base case startup is shown, and the time taken to reach steady state is reduced by 16%.