Modeling, simulation, and optimization of multiproduct cryogenic air separation unit startup

Abstract The startup of multiproduct cryogenic air separation plants takes several hours, during which time limited revenue is generated with high costs incurred due to the highly energy‐intensive nature of these operations. This motivates the development of high‐fidelity dynamic models to capture the complexity of the startup process to aid decision‐making. This article focuses on the development of a startup model for a multiproduct air separation unit (ASU), and its use in dynamic simulation and optimization. To accomplish this, a first‐principles based dynamic ASU model is extended by including various discontinuities using smooth approximations, adding dynamics to the primary heat exchanger, and extending the handling phase change within process streams. Dynamic simulations demonstrate plant response behavior during startup, including a failed startup resulting from an injudicious choice of input trajectory. In addition, improvement of startup operation is demonstrated through the incorporation of the model within a dynamic optimization framework.