A Framework for Optimization and Quantification of Uncertainty and Sensitivity for Developing Carbon Capture Systems

Eslick, John C.; Ng, Brenda; Gao, Qianwen; Tong, Charles H.; Sahinidis, Nikolaos V.; Miller, David C.

doi:10.1016/j.egypro.2014.11.113

Title: A Framework for Optimization and Quantification of Uncertainty and Sensitivity for Developing Carbon Capture Systems

Abstract

Under the auspices of the U.S. Department of Energy’s Carbon Capture Simulation Initiative (CCSI), a Framework for Optimization and Quantification of Uncertainty and Sensitivity (FOQUS) has been developed. This tool enables carbon capture systems to be rapidly synthesized and rigorously optimized, in an environment that accounts for and propagates uncertainties in parameters and models. FOQUS currently enables (1) the development of surrogate algebraic models utilizing the ALAMO algorithm, which can be used for superstructure optimization to identify optimal process configurations, (2) simulation-based optimization utilizing derivative free optimization (DFO) algorithms with detailed black-box process models, and (3) rigorous uncertainty quantification through PSUADE. FOQUS utilizes another CCSI technology, the Turbine Science Gateway, to manage the thousands of simulated runs necessary for optimization and UQ. Thus, this computational framework has been demonstrated for the design and analysis of a solid sorbent based carbon capture system.

Authors:: Eslick, John C.; Ng, Brenda; Gao, Qianwen; Tong, Charles H.; Sahinidis, Nikolaos V.; Miller, David C.

Publication Date:: Wed Jan 01 00:00:00 EST 2014

Research Org.:: National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV (United States); Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Org.:: USDOE Office of Fossil Energy and Carbon Management (FECM); USDOE Office of Fossil Energy (FE)

OSTI Identifier:: 1829101

Alternate Identifier(s):: OSTI ID: 1163761; OSTI ID: 1201556

Report Number(s):: NETL-PUB-953
Journal ID: ISSN 1876-6102; S1876610214019286; PII: S1876610214019286

Resource Type:: Published Article

Journal Name:: Energy Procedia (Online)

Additional Journal Information:: Journal Name: Energy Procedia (Online) Journal Volume: 63 Journal Issue: C; Journal ID: ISSN 1876-6102

Publisher:: Elsevier

Country of Publication:: Netherlands

Language:: English

Subject:: 54 ENVIRONMENTAL SCIENCES; 97 MATHEMATICS AND COMPUTING; optimization; uncertainty quantification; simulation; surrogate model; carbon capture

Citation Formats


                    Eslick, John C., Ng, Brenda, Gao, Qianwen, Tong, Charles H., Sahinidis, Nikolaos V., and Miller, David C. A Framework for Optimization and Quantification of Uncertainty and Sensitivity for Developing Carbon Capture Systems.  Netherlands: N. p., 2014. 
Web.  doi:10.1016/j.egypro.2014.11.113.

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                    Eslick, John C., Ng, Brenda, Gao, Qianwen, Tong, Charles H., Sahinidis, Nikolaos V., & Miller, David C. A Framework for Optimization and Quantification of Uncertainty and Sensitivity for Developing Carbon Capture Systems.  Netherlands.  https://doi.org/10.1016/j.egypro.2014.11.113

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                    Eslick, John C., Ng, Brenda, Gao, Qianwen, Tong, Charles H., Sahinidis, Nikolaos V., and Miller, David C. Wed .  
"A Framework for Optimization and Quantification of Uncertainty and Sensitivity for Developing Carbon Capture Systems".  Netherlands.  https://doi.org/10.1016/j.egypro.2014.11.113.

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@article{osti_1829101,

  title        = {A Framework for Optimization and Quantification of Uncertainty and Sensitivity for Developing Carbon Capture Systems},

  author       = {Eslick, John C. and Ng, Brenda and Gao, Qianwen and Tong, Charles H. and Sahinidis, Nikolaos V. and Miller, David C.},

  abstractNote = {Under the auspices of the U.S. Department of Energy’s Carbon Capture Simulation Initiative (CCSI), a Framework for Optimization and Quantification of Uncertainty and Sensitivity (FOQUS) has been developed. This tool enables carbon capture systems to be rapidly synthesized and rigorously optimized, in an environment that accounts for and propagates uncertainties in parameters and models. FOQUS currently enables (1) the development of surrogate algebraic models utilizing the ALAMO algorithm, which can be used for superstructure optimization to identify optimal process configurations, (2) simulation-based optimization utilizing derivative free optimization (DFO) algorithms with detailed black-box process models, and (3) rigorous uncertainty quantification through PSUADE. FOQUS utilizes another CCSI technology, the Turbine Science Gateway, to manage the thousands of simulated runs necessary for optimization and UQ. Thus, this computational framework has been demonstrated for the design and analysis of a solid sorbent based carbon capture system.},

  doi          = {10.1016/j.egypro.2014.11.113},

  journal      = {Energy Procedia (Online)},

  number       = C,

  volume       = 63,

  place        = {Netherlands},

  year         = {Wed Jan 01 00:00:00 EST 2014},

  month        = {Wed Jan 01 00:00:00 EST 2014}

}

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Works referenced in this record:

Introduction to Derivative-Free Optimization
book, January 2009

Conn, Andrew R.; Scheinberg, Katya; Vicente, Luis N.
DOI: 10.1137/1.9780898718768

GAMS, a user's guide
journal, December 1988

Brook, Anthony; Kendrick, David; Meeraus, Alexander
ACM SIGNUM Newsletter, Vol. 23, Issue 3-4
DOI: 10.1145/58859.58863

Advanced Computational Tools for Optimization and Uncertainty Quantification of Carbon Capture Processes
book, January 2014

Miller, David C.; Ng, Brenda; Eslick, John
Proceedings of the 8th International Conference on Foundations of Computer-Aided Process Design
DOI: 10.1016/B978-0-444-63433-7.50021-3

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Title: A Framework for Optimization and Quantification of Uncertainty and Sensitivity for Developing Carbon Capture Systems

Abstract

Citation Formats

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Introduction to Derivative-Free Optimization
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journal, December 1988

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