472533 Optimizing Overall Energy Consumptions and Dynamic Flexibilities of Air Separation Unit (ASU)
In this paper, multi-objective optimization and dynamic simulation are used to achieve two objectives: 1) reducing production costs; 2) increasing production flexibilities. Multi-objective optimization uses Pareto efficiency to state the relations of the two objectives. Pareto efficiency is not a single value, but a curve showing the frontier of the two objectives.
Dynamic simulation is used to illustrate operating strategies to achieve flexibilities. It tests and validates flexibility scenarios to confirm that they are not only therotically but also practically achievable. Moreover, dynamic simulation gives transition methods between flexibility scenarios.
An industrial scale Air Separation Unit (ASU) is used for case study. Dynamic simulation and multi-objective optimization results show a set of Pareto efficiency pairs for operating costs and flexibilities ranging from 0 to 30%.
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