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Multiscale Equation-Oriented Optimization Decreases the Carbon Intensity of Shale Gas to Liquid Fuel Processes.
Ghosh, Kanishka; Salas, Santiago D; Garciadiego, Alejandro; Dunn, Jennifer B; Dowling, Alexander W.
Afiliación
  • Ghosh K; Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States.
  • Salas SD; Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States.
  • Garciadiego A; Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States.
  • Dunn JB; Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States.
  • Dowling AW; Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States.
ACS Sustain Chem Eng ; 12(28): 10351-10362, 2024 Jul 15.
Article en En | MEDLINE | ID: mdl-39027727
ABSTRACT
Shale gas is revolutionizing the U.S. energy and chemical commodity landscape and can ease the transition to a sustainable decarbonized economy. This work develops an equation-oriented (EO) multiscale modeling framework using the open-source IDAES-PSE platform that tractably incorporates microkinetic detail in process design via reduced-order kinetic (ROK) models. Using multiobjective optimization with embedded heat integration and life-cycle analysis, we simultaneously minimize the minimum selling price of liquid hydrocarbons (e.g., liquid fuels/additives from shale gas) and process emissions (via a CO2 tax). Optimization reduces greenhouse gas emissions per MJ of fuel produced by over 35% compared to the literature and achieves a carbon efficiency of 87%. The optimizer changes the recycling rate, temperatures, and pressures to mitigate the effect of ROK model-form uncertainty on product portfolio predictions. Moreover, we show that the optimal process design is insensitive to changing CO2 tax rates. Finally, the EO framework enables a fast sensitivity analysis of shale gas composition variability across 12 regions of the Eagle Ford basin. These results highlight the benefits of the open-source EO framework fast, scalable, customized, and reproducible system analysis and optimization for sustainable energy technologies beyond shale utilization.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: ACS Sustain Chem Eng Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: ACS Sustain Chem Eng Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos