(667e) Dynamic Scheduling to Maximize the Profitability of Air Separation Units | AIChE

(667e) Dynamic Scheduling to Maximize the Profitability of Air Separation Units


Xu, Q., Lamar University
Zhang, J., Lamar University
Wang, Z., East China University of Science and Technology
Dynamic Scheduling to Maximize the Profitability of Air Separation Units

Song Wang, Jian Zhang, and Qiang Xu

Dan F. Smith Department of Chemical Engineering
Lamar University, Beaumont, TX 77710, USA


The Air Separation Units (ASUs) generate oxygen, nitrogen, and argon productions from air, which were widely used in many industries. Unlike other chemical processes, the cost of feedstocks of an ASU can be negligible because of the raw material of air is free; meanwhile, Besides, the energy supply of the entire process is totally in the charge of electricity power. ASUs are also characterized by fluctuating operating conditions to respond to changing product demands [1]. Although it is not much necessary to improve current ASU designs since there are quite proven techniques of cryogenic air separation design existing in industries; however, there are still significant potentials for improving their profitability in terms of optimal scheduling and operation ASU manufacturing.
Currently, many air separation plants are operated in a dynamic economic environment [2]. The electricity price could frequently fluctuate according to real time marketing (RTM) demands in different regions. In this paper, a general methodology based on dynamic simulation and scheduling of an ASU has been developed, which can optimize the ASU operation with respect to the electricity cost to achieve the best profit as well as highly efficiency. First, the methodology develops reliable dynamic simulation models under various production modes (capacities) and studies the dynamic transition performance among those production modes. Second, the optimal scheduling and transition will be conducted to maximize the plant profitability under the electricity cost pattern. Finally, the optimized ASU scheduling and operations will be fine turned and validated by rigorous dynamic simulations. The developed methodology can be further extended to help ASUs for the predictive and proactive smart manufacturing.

Keywords: Air Separation Unit, Production Scheduling, Maximum Profitability, Smart Manufacturing

[1] Rui, H; Victor M. Zavala; Lorenz T. Biegler *. Advanced Step Nonlinear Model Predictive Control for Air Separation Units. Journal of Process Control. www.elsevier.com/locate/jprocont.
[2] Li, T*; Thierry, R; and Marc, B. Production Scheduling of Air Separation Processes. Air Liquide, Newark, DE 19702; Air Liquide, Champigny-sur-Marne, France; Air Liquide, Madrid, Spain.