Operational strategy and planning for raw natural gas refining complexes: Process modeling and global optimization |
| |
| Authors: | Bing J. Zhang Qing L. Chen Jie Li Christodoulos A. Floudas |
| |
| Affiliation: | 1. School of Chemical Engineering and Technology, Guangdong Engineering Technology Research Center for Petrochemical Energy Conservation, Key Lab of Low‐carbon Chemistry & Energy Conservation of Guangdong Province, Sun Yat‐Sen University, Guangzhou, China;2. Artie McFerrin Dept. of Chemical Engineering, Texas A&M University, College Station, TX;3. Texas A&M Energy Institute, Texas A&M University, College Station, TX |
| |
| Abstract: | Optimal operational strategy and planning of a raw natural gas refining complex (RNGRC) is very challenging since it involves highly nonlinear processes, complex thermodynamics, blending, and utility systems. In this article, we first propose a superstructure integrating a utility system for the RNGRC, involving multiple gas feedstocks, and different product specifications. Then, we develop a large‐scale nonconvex mixed‐integer nonlinear programming (MINLP) optimization model. The model incorporates rigorous process models for input and output relations based on fundamentals of thermodynamics and unit operations and accurate models for utility systems. To reduce the noncovex items in the proposed MINLP model, equivalent reformulation techniques are introduced. Finally, the reformulated nonconvex MINLP model is solved to global optimality using state of the art deterministic global optimization approaches. The computational results demonstrate that a significant profit increase is achieved using the proposed approach compared to that from the real operation. © 2016 American Institute of Chemical Engineers AIChE J, 63: 652–668, 2017 |
| |
| Keywords: | natural gas operational planning mixed‐integer nonlinear programming enterprise‐wide optimization global optimization |
|
|
