Optimal processing pathway selection for microalgae-based biorefinery under uncertainty

•Identification of optimal microalgae processing pathways under uncertainty.•Techno-economic uncertainties in the dataset are considered.•The optimization problem is formulated as a stochastic MINLP model.•Optimal processing pathways are determined under different objective functions.•Optimal struct...

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Vydáno v:	Computers & chemical engineering Ročník 82; s. 362 - 373
Hlavní autoři:	Rizwan, Muhammad, Zaman, Muhammad, Lee, Jay H., Gani, Rafiqul
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 02.11.2015
Témata:	Biofuels Chemical engineering Decision-making under uncertainty Mathematical models Microalgal biorefinery Nonlinear programming Optimization Pathways Refining Stochastic mixed integer nonlinear programming (sMINLP) Superstructures Uncertainty Uncertainty analysis Stochastic mixed integer nonlinear programming (sMINLP) Microalgal biorefinery Biofuels Uncertainty analysis Decision-making under uncertainty
ISSN:	0098-1354, 1873-4375
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Abstract	•Identification of optimal microalgae processing pathways under uncertainty.•Techno-economic uncertainties in the dataset are considered.•The optimization problem is formulated as a stochastic MINLP model.•Optimal processing pathways are determined under different objective functions.•Optimal structures are compared with respect to different objective functions used. We propose a systematic framework for the selection of optimal processing pathways for a microalgae-based biorefinery under techno-economic uncertainty. The proposed framework promotes robust decision making by taking into account the uncertainties that arise due to inconsistencies among and shortage in the available technical information. A stochastic mixed integer nonlinear programming (sMINLP) problem is formulated for determining the optimal biorefinery configurations based on a superstructure model where parameter uncertainties are modeled and included as sampled scenarios. The solution to the sMINLP problem determines the processing technologies, material flows, and product portfolio that are optimal with respect to all the sampled scenarios. The developed framework is implemented and tested on a specific case study. The optimal processing pathways selected with and without the accounting of uncertainty are compared with respect to different objectives.
AbstractList	We propose a systematic framework for the selection of optimal processing pathways for a microalgae-based biorefinery under techno-economic uncertainty. The proposed framework promotes robust decision making by taking into account the uncertainties that arise due to inconsistencies among and shortage in the available technical information. A stochastic mixed integer nonlinear programming (sMINLP) problem is formulated for determining the optimal biorefinery configurations based on a superstructure model where parameter uncertainties are modeled and included as sampled scenarios. The solution to the sMINLP problem determines the processing technologies, material flows, and product portfolio that are optimal with respect to all the sampled scenarios. The developed framework is implemented and tested on a specific case study. The optimal processing pathways selected with and without the accounting of uncertainty are compared with respect to different objectives. •Identification of optimal microalgae processing pathways under uncertainty.•Techno-economic uncertainties in the dataset are considered.•The optimization problem is formulated as a stochastic MINLP model.•Optimal processing pathways are determined under different objective functions.•Optimal structures are compared with respect to different objective functions used. We propose a systematic framework for the selection of optimal processing pathways for a microalgae-based biorefinery under techno-economic uncertainty. The proposed framework promotes robust decision making by taking into account the uncertainties that arise due to inconsistencies among and shortage in the available technical information. A stochastic mixed integer nonlinear programming (sMINLP) problem is formulated for determining the optimal biorefinery configurations based on a superstructure model where parameter uncertainties are modeled and included as sampled scenarios. The solution to the sMINLP problem determines the processing technologies, material flows, and product portfolio that are optimal with respect to all the sampled scenarios. The developed framework is implemented and tested on a specific case study. The optimal processing pathways selected with and without the accounting of uncertainty are compared with respect to different objectives.
Author	Rizwan, Muhammad Lee, Jay H. Gani, Rafiqul Zaman, Muhammad
Author_xml	– sequence: 1 givenname: Muhammad surname: Rizwan fullname: Rizwan, Muhammad organization: Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea – sequence: 2 givenname: Muhammad surname: Zaman fullname: Zaman, Muhammad organization: Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea – sequence: 3 givenname: Jay H. surname: Lee fullname: Lee, Jay H. email: jayhlee@kaist.ac.kr organization: Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea – sequence: 4 givenname: Rafiqul surname: Gani fullname: Gani, Rafiqul organization: CAPEC, Department of Chemical & Biochemical Engineering, Technical University of Denmark, 2800 Kgs Lyngby, Denmark
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Keywords	Stochastic mixed integer nonlinear programming (sMINLP) Microalgal biorefinery Biofuels Uncertainty analysis Decision-making under uncertainty
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publication-title: Environ Sci Technol doi: 10.1021/es2006995
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Snippet	•Identification of optimal microalgae processing pathways under uncertainty.•Techno-economic uncertainties in the dataset are considered.•The optimization... We propose a systematic framework for the selection of optimal processing pathways for a microalgae-based biorefinery under techno-economic uncertainty. The...
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SubjectTerms	Biofuels Chemical engineering Decision-making under uncertainty Mathematical models Microalgal biorefinery Nonlinear programming Optimization Pathways Refining Stochastic mixed integer nonlinear programming (sMINLP) Superstructures Uncertainty Uncertainty analysis
Title	Optimal processing pathway selection for microalgae-based biorefinery under uncertainty
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