BioSTEAM: A Fast and Flexible Platform for the Design, Simulation, and Techno-Economic Analysis of Biorefineries under Uncertainty
Abstract
BioSTEAM, the Biorefinery Simulation and Techno-Economic Analysis Modules, is an open-source steady-state process simulator in Python that enables biorefinery design, simulation, and techno-economic analysis (TEA) under uncertainty through its fast and flexible framework. By incorporating uncertainty as a key feature, BioSTEAM aims to evaluate the landscape of design decisions and scenarios for conceptual and emerging technologies. The applicability of BioSTEAM is demonstrated here in the context of (i) the co-production of biodiesel and ethanol from lipid-cane and (ii) the production of second-generation ethanol from corn stover. Economic metrics evaluated in BioSTEAM closely match benchmark designs modeled in proprietary software (SuperPro Designer, Aspen Plus). Through the automation of unit operation sizing and characterization of utility requirements, process waste streams, and make-up water usage, BioSTEAM also generates data needed for environmental sustainability analyses (e.g., via life cycle assessment). Ultimately, BioSTEAM enables rapid and robust process design, mass and energy balances, and TEA to compare established and early-stage technologies and prioritize research, development, and deployment.
- Authors:
-
- Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 3221 Newmark Civil Engineering Laboratory, 205 N. Mathews Avenue, Urbana, Illinois 61801, United States, DOE Center for Advanced Bioenergy and Bioproducts Innovation (CABBI), University of Illinois at Urbana-Champaign, 1206 W. Gregory Drive, Urbana, Illinois 61801, United States
- DOE Center for Advanced Bioenergy and Bioproducts Innovation (CABBI), University of Illinois at Urbana-Champaign, 1206 W. Gregory Drive, Urbana, Illinois 61801, United States, Department of Paper and Bioprocess Engineering, State University of New York College of Environmental Science and Forestry, 402 Walters Hall, 1 Forestry Drive, Syracuse, New York 13210, United States
- DOE Center for Advanced Bioenergy and Bioproducts Innovation (CABBI), University of Illinois at Urbana-Champaign, 1206 W. Gregory Drive, Urbana, Illinois 61801, United States, Department of Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign, 360 G Agricultural Sciences Building, 1304 W. Pennsylvania Avenue, Urbana, Illinois 61801, United States
- Publication Date:
- Research Org.:
- Univ. of Illinois at Urbana-Champaign, IL (United States). Center for Advanced Bioenergy and Bioproducts Innovation (CABBI); Center for Advanced Bioenergy and Bioproducts Innovation (CABBI), Urbana, IL (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF); National Science Foundation Graduate Research Fellowship Program
- OSTI Identifier:
- 1599970
- Alternate Identifier(s):
- OSTI ID: 1600934; OSTI ID: 1991871
- Grant/Contract Number:
- SC0018420; DGE-1746047
- Resource Type:
- Published Article
- Journal Name:
- ACS Sustainable Chemistry & Engineering
- Additional Journal Information:
- Journal Name: ACS Sustainable Chemistry & Engineering Journal Volume: 8 Journal Issue: 8; Journal ID: ISSN 2168-0485
- Publisher:
- American Chemical Society (ACS)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; 97 MATHEMATICS AND COMPUTING; biochemical process; unit operations; thermodynamics; uncertainty; Monte Carlo; beverages; biorefineries; ethanol; lipids; plant derived food
Citation Formats
Cortes-Peña, Yoel, Kumar, Deepak, Singh, Vijay, and Guest, Jeremy S. BioSTEAM: A Fast and Flexible Platform for the Design, Simulation, and Techno-Economic Analysis of Biorefineries under Uncertainty. United States: N. p., 2020.
Web. doi:10.1021/acssuschemeng.9b07040.
Cortes-Peña, Yoel, Kumar, Deepak, Singh, Vijay, & Guest, Jeremy S. BioSTEAM: A Fast and Flexible Platform for the Design, Simulation, and Techno-Economic Analysis of Biorefineries under Uncertainty. United States. https://doi.org/10.1021/acssuschemeng.9b07040
Cortes-Peña, Yoel, Kumar, Deepak, Singh, Vijay, and Guest, Jeremy S. Thu .
"BioSTEAM: A Fast and Flexible Platform for the Design, Simulation, and Techno-Economic Analysis of Biorefineries under Uncertainty". United States. https://doi.org/10.1021/acssuschemeng.9b07040.
@article{osti_1599970,
title = {BioSTEAM: A Fast and Flexible Platform for the Design, Simulation, and Techno-Economic Analysis of Biorefineries under Uncertainty},
author = {Cortes-Peña, Yoel and Kumar, Deepak and Singh, Vijay and Guest, Jeremy S.},
abstractNote = {BioSTEAM, the Biorefinery Simulation and Techno-Economic Analysis Modules, is an open-source steady-state process simulator in Python that enables biorefinery design, simulation, and techno-economic analysis (TEA) under uncertainty through its fast and flexible framework. By incorporating uncertainty as a key feature, BioSTEAM aims to evaluate the landscape of design decisions and scenarios for conceptual and emerging technologies. The applicability of BioSTEAM is demonstrated here in the context of (i) the co-production of biodiesel and ethanol from lipid-cane and (ii) the production of second-generation ethanol from corn stover. Economic metrics evaluated in BioSTEAM closely match benchmark designs modeled in proprietary software (SuperPro Designer, Aspen Plus). Through the automation of unit operation sizing and characterization of utility requirements, process waste streams, and make-up water usage, BioSTEAM also generates data needed for environmental sustainability analyses (e.g., via life cycle assessment). Ultimately, BioSTEAM enables rapid and robust process design, mass and energy balances, and TEA to compare established and early-stage technologies and prioritize research, development, and deployment.},
doi = {10.1021/acssuschemeng.9b07040},
journal = {ACS Sustainable Chemistry & Engineering},
number = 8,
volume = 8,
place = {United States},
year = {Thu Jan 30 00:00:00 EST 2020},
month = {Thu Jan 30 00:00:00 EST 2020}
}
https://doi.org/10.1021/acssuschemeng.9b07040
Web of Science
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