论文信息 - Optimal Design and Synthesis of Shale Gas Processing and NGL Recovery Processes

Optimal Design and Synthesis of Shale Gas Processing and NGL Recovery Processes

Abstract The booming of the shale gas industry is predicted to impact North American’s energy landscape. This paper addresses the robust design and synthesis of shale gas processing and natural gas liquids (NGLs) recovery processes under uncertain feedstock compositions. The problem is addressed via three steps. First, we construct an uncertainty set for raw shale gas compositions. Second, we develop a superstructure for shale gas processing and NGLs recovery processes that includes monoethanolamine and diethanol amine absorption processes in an acid gas removal section, triethylene glycol absorption and condensation processes in a dehydration section, standalone and integrated designs of a NGLs recovery process, and a nitrogen rejection process. The proposed superstructure explicitly shows process configurations for the feedstocks in the uncertainty set. In the last step, we propose a two-stage adaptive robust mixed-integer linear programming problem based on the superstructure and a tailored solution method for the proposed model. The obtained robust optimal design is immunized against uncertainty in feedstock compositions.

Fengqi You | Jian Gong

[1] Fengqi You,et al. A computational framework and solution algorithms for two‐stage adaptive robust scheduling of batch manufacturing processes under uncertainty , 2016 .

[2] Fengqi You,et al. Sustainable design and synthesis of energy systems , 2015 .

[3] Fengqi You,et al. Toward more cost‐effective and greener chemicals production from shale gas by integrating with bioethanol dehydration: Novel process design and simulation‐based optimization , 2015 .

[4] James G. Speight,et al. Shale Gas Properties and Processing , 2013 .

[5] Andrea P. Ortiz-Espinoza,et al. Techno-Economic Assessment and Environmental Impact of Shale Gas Alternatives to Methanol , 2014 .

[6] Keith A. Bullin,et al. Compositional nal variety complicates processing plans for US shale gas , 2009 .

[7] Fengqi You,et al. Deciphering and handling uncertainty in shale gas supply chain design and optimization: Novel modeling framework and computationally efficient solution algorithm , 2015 .

[8] Fengqi You,et al. Optimal design and operations of supply chain networks for water management in shale gas production: MILFP model and algorithms for the water‐energy nexus , 2015 .

[9] F. You,et al. Shale Gas Supply Chain Design and Operations toward Better Economic and Life Cycle Environmental Performance: MINLP Model and Global Optimization Algorithm , 2015 .