BioSTEAM: The Biorefinery Simulation and Techno-Economic Analysis Modules

BioSTEAM is a fast and flexible package for the design, simulation, and techno-economic analysis of biorefineries under uncertainty. BioSTEAM is built to streamline and automate early-stage technology evaluations and to enable rigorous sensitivity and uncertainty analyses. Complete biorefinery configurations are available at the Bioindustrial-Park GitHub repository, BioSTEAM’s premier repository for biorefinery models and results. The long-term growth and maintenance of BioSTEAM is supported through both community-led development and the research institutions invested in BioSTEAM, including the Center for Advanced Bioenergy and Bioproducts Innovation (CABBI). Through its open-source and community-lead platform, BioSTEAM aims to foster communication and transparency within the biorefinery research community for an integrated effort to expedite the evaluation of candidate biofuels and bioproducts.

Key Features & Capabilities

• Fast and flexible techno-economic analysis. BioSTEAM presents basic building blocks to design and simulate a biorefinery. These include objects that handle material properties, material flows, unit operations, and recycle loops.
• Clear representation of streams, unit operations, and recycle systems. Dynamic generation of flowsheets and a clear representation of data allows users to visualize biorefineries in detail. BioSTEAM does not yet have a GUI but we are on our way to building one.
• Automated process and technology evaluations. The evaluation of thousands of biorefinery designs is streamlined through smart and efficient management of biorefinery parameters to evaluate sets of design decisions and scenarios.
• Complete biorefinery examples. Two complete biorefineries models are included in BioSTEAM: the co-production of ethanol and biodiesel from lipid-cane, and 2nd generation ethanol production from corn stover. Please refer to the tutorial to get started.

Benchmarks

The BioSTEAM software has been steadily improved since the original BioSTEAM publication [1]. In particular, more rigorous thermodynamic and unit operation models have been implemented, improving the accuracy of the software. In the figures below, the applicability of BioSTEAM is demonstrated 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. All results were generated under uncertainty through Monte Carlo simulations, whereby thousands of biorefinery designs were evaluated across a joint distribution of uncertain parameters. Economic metrics evaluated in BioSTEAM closely match benchmark designs modeled in proprietary software (SuperPro Designer, Aspen Plus). Estimates for the net steam demand and electricity production of the co-heat and power facilities have improved since the original BioSTEAM publication. It is thanks to both community involvement and the institutions supporting BioSTEAM that continuous improvements like these are made possible.

Sensitivity of (A) internal rate of return, (B) total capital investment, (C) steam demand, (D) ethanol and biodiesel production, (E) production cost, and (F) consumption and excess production of electricity as a function of lipid-cane feedstock lipid content by dry weight. BioSTEAM results are presented with median values (dark, solid lines), 25th to 75th percentiles (shaded region), and 5th and 95th percentiles (dash-dotted lines). BioSTEAM results are presented alongside results from the benchmark study by Huang et al. (circles) simulated in SuperPro Designer [2].

Relative magnitude of (A) net electricity and (B) installation cost across areas of the corn stover biorefinery in the benchmark study (Humbird et al., simulated in Aspen plus) and estimates of (C) net electricity, (D) installation cost, and (E) steam demand, ethanol production, and MESP under uncertainty from BioSTEAM relative to the benchmark study [3]. Boxes in (C)–(E) identify 25th to 75th percentiles, lines are median values, whiskers extend to 5th and 95th percentiles, and diamonds represent individual simulations below the 5th percentile or above the 95th percentiles.

Scientific Papers

Several studies have leveraged the BioSTEAM platform to compare conversion technologies and chart development pathways for various bioproducts:

• McClelland et al. Renewable linear alpha-olefins by base-catalyzed dehydration of biologically-derived fatty alcohols. Green Chemistry 2021
• Li et al. Sustainable Lactic Acid Production from Lignocellulosic Biomass. ACS Sustainable Chem. Eng. 2021
• Sanchis-Sebastiá et al. Techno-Economic Evaluation of Biorefineries Based on Low-Value Feedstocks Using the BioSTEAM Software: A Case Study for Animal Bedding. Processes 2020
• Shi et al. An Integrated Modeling Framework for Agile Life Cycle Assessment of Biorefineries under Uncertainty. ACS Sustainable Chem. Eng. 2020

Tutorial

• 1. Overview
• 2. Installation
  • 2.1. Common Issues
• 3. Getting started
  • 3.1. Initialize streams
  • 3.2. Process settings
  • 3.3. Find design requirements and cost with Unit objects
  • 3.4. Solve recycle loops and process specifications with System objects
• 4. Creating a Unit
  • 4.1. Key parameters
  • 4.2. Parameter defaults
  • 4.3. Area naming convention
• 5. Managing flowsheets
  • 5.1. Retrieve any Unit, Stream or System object by ID
  • 5.2. Switch between flowsheets
• 6. -pipe- notation
• 7. Unit operation results
  • 7.1. A note on design and modeling
  • 7.2. A good example
  • 7.3. References
• 8. Process specifications
  • 8.1. Analytical specifications
  • 8.2. Numerical specifications
• 9. Inheriting from Unit
  • 9.1. Abstract attributes and methods
  • 9.2. Subclass example
  • 9.3. Simulation test
  • 9.4. Graphviz attributes
• 10. Unit decorators
  • 10.1. cost decorator
  • 10.2. References
• 11. Techno-economic analysis
  • 11.1. Inhereting from TEA objects
  • 11.2. Perform cash flow analysis
  • 11.3. Find production cost, price, and IRR
  • 11.4. System report

Advanced Tutorial

• 1. Creating a System
  • 1.1. Conventional methods
  • 1.2. Drop-in systems
• 2. Building a biorefinery
  • 2.1. Sugarcane biorefinery
• 3. Agile systems
  • 3.1. Overview
  • 3.2. Agile sugarcane and sweet sorghum biorefinery
• 4. Uncertainty and sensitivity
  • 4.1. Monte Carlo uncertainty analysis
  • 4.2. Sensitivity with Spearman’s rank order correlation
  • 4.3. Single point sensitivity
• 5. TRY-Analysis
  • 5.1. Setup up the biorefinery model
  • 5.2. Load reactor specifications
  • 5.3. Evaluate the performance landscape
  • 5.4. Perform Monte Carlo analysis

BioSTEAM API

• Unit
• PowerUtility
• UtilityAgent
• HeatUtility
• System
• TEA
• Flowsheet
• exceptions
• units
  • decorators
  • design_tools
  • facilities
  • distillation
  • heat_exchange
  • liquid_liquid_extraction
  • mixing
  • solids_separation
  • splitting
  • wastewater
  • Pump
  • BatchBioreactor
  • Duplicator
  • Fermentation
  • Flash
  • Junction
  • MassBalance
  • MolecularSieve
  • MultiEffectEvaporator
  • ProcessSpecification
  • Transesterification
• process_tools
  • UnitGroup
  • SystemFactory
  • BoundedNumericalSpecification
  • utils
• evaluation
  • Variable
  • Parameter
  • Metric
  • Model
  • State

What's new?

• 2.24
• 2.23
• 2.22
• 2.21
• 2.20

Developer's guide

• Authors & Acknowledgements
• License
• Contributing to BioSTEAM
• Code of conduct

References

[1]	Cortes-Peña, et al. BioSTEAM: A Fast and Flexible Platform for the Design, Simulation, and Techno-Economic Analysis of Biorefineries under Uncertainty. ACS Sustainable Chem. Eng. 2020

[2]	Huang et al. Techno-Economic Analysis of Biodiesel and Ethanol Co-Production from Lipid-Producing Sugarcane. Biofuels, Bioproducts and Biorefining 2016

[3]	Humbird et al. Process Design and Economics for Biochemical Conversion of Lignocellulosic Biomass to Ethanol: Dilute-Acid Pretreatment and Enzymatic Hydrolysis of Corn Stover; Technical Report NREL/TP-5100-47764; DOE: NREL, 2011.

Indices and tables

• Index
• Module Index
• Search Page