Energy-Efficient Production Scheduling of a Cryogenic Air Separation Plant

Power-intensive processes, such as cryogenic air separation in which the major portion of the production cost is spent on energy/electricity, need to adopt a smart operational approach to ensure maximum usage of resources while minimizing the power cost. In this paper a state task network-based model of an air separation plant is designed to represent real world production constraints. A discrete time model-based production scheduling has been proposed and validated on several scenarios that reflects representative real time constraints. The optimal schedule found for every scenario chosen has shown efficient exploitation of all energy contracts and judicious utilization of the liquid products. Due to its granular and rigorous modeling approach along with computational efficiency, the proposed model manifests huge potential toward its implementation in a real-world air separation plant.