Biomass Scenario Model (BSM)

1. Biomass Scenario Model (BSM) 20 March 2009 Office of the Biomass ProgramAnalysis Platform Peer Review Brian W Bush National Renewable Energy Laboratory This presentation does not contain any proprietary, confidential, or otherwise restricted information

2. Timeline Start Date: October 2006 End Date: September 2010 Portion Complete: 70% Budget The BSM task is not separately budgeted (in the four-level WBS) from other biomass systems integration work. The biomass systems integration subcontracts that are closely related to the BSM are included in the totals below. Total: $1966k 100% DOE-funded FY2008: $550k FY2009: $734k Barriers “High Risk of Large Capital Investments” “Agricultural Sector-Wide Paradigm Shift” “Inadequate Supply Chain Infrastructure” Partners Project Lead: NREL Systems Integration Office Primary Model Developer: Peterson Group Subject-Matter Expertise: National Bioenergy Center DOE Laboratories Issue-focused subcontracts Project Overview

3. Goals and Objectives • Deployment Analysis: “exploring how rapidly cellulosic ethanol technologies might be deployed to make a significant contribution to the country’s transportation energy” [from MYPP] • Generate plausible scenarios • Understand the transition dynamics • Investigate potential market penetration scenarios • Identify high-impact drivers and bottlenecks • Completion of the BSM 2.0 enhancements addressing recommendations of previous reviews and OBP and other customer needs • Modest expansion of BSM capabilities to other advanced biofuels • Customer-oriented application of the BSM • Develop peer-reviewed publications suitable for citation in the OBP’s 2010 IPCC contributions. • Strategically assess OBP’s R&D and deployment strategies • Enable and facilitate focused discussion among the broad community of policy makers, analysts, modelers, and other stakeholders • academics, national laboratories, DOE offices including EIA, private-sector analysts, industry

4. Approach • System-dynamics modeling framework • Established methodology for analyzing the behavior of complex real-world feedback systems over time • Broad, high level approach that captures entire supply chain • Flexible, modular model architecture • Defensible and traceable inputs, with metadata • Data extracted from detailed analyses and models • POLYSYS agricultural sector economics, ASPEN Plus process models, etc. • Logic developed and validated through stakeholder meetings • interviews, reviews, workshops, and colloquies • Modern software-engineering methodology • configuration management – version control • issue tracking – data warehousing • integral documentation – collaborative web site • Agile, adaptive project management • multiple parallel threads of effort • careful triage of new requirements and other information as it arises

5. Architectural Overview of BSM 2.0 • Modular • vetting and data management simplified • modules runnable in isolation or in combination • High level regional disaggregation • facilitates analysis of regional differences • e.g., corn belt, areas of concentration of autos • STELLA software platform

6. Contents & Concerns of BSM 2.0 Modules

7. Development Pathway

8. Accomplishments, Progress, & Results • Completion of investment colloquies: • meetings to improve BSM characterization of investment decision-making across the supply chain through discussions with experts from farming, chemical process, financial sectors • Completion of interim and/or final versions of key BSM 2.0 modules: • Feedstock Production – Feedstock Logistics – Conversion • Distribution Logistics – Dispensing Station – Vehicle • Preparation of publications describing the BSM and presenting analysis results: • structural description – end-to-end supply chain analysis • feedstock supply & logistics analysis – feedstock conversion to ethanol • Spawning of parallel efforts to inform and refine upcoming BSM analyses: • biorefinery learning curves • econometric analysis of cost and demand couplings • biomass-based diesel • dispensing-station incentives • distribution infrastructure

9. Milestones

10. Accomplishments towards Biomass Program Goals

11. Results: Synergistic Effect of Combining Policies • Grower Payment • Feedstock grower payment of $20/ton for 2007-2017. • Production Subsidy • Cellulosic ethanol production subsidy of $2/gallon up to 500MM gallon cellulosic ethanol produced for 2009 until production volume met. • Capital Cost Reduction • Capital subsidy for commercial-scale cellulosic ethanol production plants, 40% per project up to a total government expenditure of $1.5B for 2009 until funds depleted.

12. Results: Production, Price, & Land-Use Implications of EISA

13. Results: Exploration of Competition between Pathways

14. Sample Insights from BSM Analyses The insights highlighted here must be seen in the context of a larger analysis that looks at properties of the biomass/biofuels supply-chain system and the key support factors for its dynamics. Every conclusion is paired with an analysis of what conditions would have to hold in order for the state of affairs to be otherwise.

15. Success Factors • Existing and prospective policies and incentives for any element of the supply chain can be flexibly incorporated into BSM scenario generation and analysis. • The BSM possess the capability to identify optimal synergies between policies/incentives across the supply chain that make coordinated policies/incentives superior to uncoordinated ones or ones focused on single supply-chain elements. • BSM-based analysis forces consistency in assumptions and scenario inputs across the full supply chain in a manner lacking in analyses focused on single supply-chain elements. • The model represents the key feedback mechanisms and dynamics identified by subject-matter experts and systems analysts so that BSM-based analyses identify critical leverage points, bottlenecks, and information-gaps in the supply chain. • The BSM’s representation of interdependencies within and between supply-chain elements allows for consistent ranking and assessment of the importance of the influence of particular forces on the biomass/biofuels system.

16. Challenges • Data and expert opinion for underdeveloped segments of the cellulosic ethanol supply chain are sometimes inadequate for modeling, highly uncertain, or lacking. • Strategies: • Close consultation with subject-matter experts • Parameter-sensitivity studies • Focused subcontracting • Analysis aimed at delimiting alternative qualitative futures • Boundary effects can strongly influence the evolution of the cellulosic ethanol industry. • Strategies: • Direct representation of first-order couplings • Semi-dynamic boundary conditions • Flexible control of module inputs

17. Future Work • Specific to FY2009: • Complete implementation, vetting, data population, and review for all BSM 2.0 modules • Submit analysis papers for each major BSM 2.0 module for peer-reviewed publication • Implement initial biomass-based diesel module • Specific to FY2010: • Implement key additional pathways (chosen in consultation with OBP) such as algae, pyrolysis oil, Fischer-Tropsch liquids, etc. • Submit whole-supply-chain analysis paper(s) for peer-reviewed publication • Provide interpretability with environmental analysis tools (sustainability etc.) for broader, combined analyses • Enhance processes around analysis QA/QC, data interconnectivity, etc. • Ongoing outreach and community-building: • Biomass/biofuels supply-chain modeling workshop (May 2009) • Coordination with and input to EIA’s NEMS modeling for 2010 and beyond • Coordination of input data sets, scenarios, and analytic metrics with other models such as SEDS and ReEDS and possibly GPRA analyses

18. Summary • High-impact BSM analyses tie RD&D to market realities and policies/incentives: e.g., • Grower payments have synergies with capital subsidies at conversion plants. • Forest residue and then herbaceous energy crops dominate production. • Feedstock prices rise from $50-80/ton in near term to over $100/ton. • Overemphasis on development of commercial-scale conversion projects may result in high expense over a substantial time frame and high number of plant failures. • The BSM is a carefully validated, second-generation model of the full cellulosic biomass/biofuel supply chain. • Ready for expansion toadditional advanced biofuels • Easily tailored for specialized studies • Making contributions to OBP analysisgoals • The model explicit focuses onpolicy issues, their feasibility,and potential side effects.

19. Supplement

20. Responses to Previous Reviewers’ Comments • Although the BSM was presented at the 2007 review, no formal comments on the project were included in the 2007 review report.

21. Publications and Presentations • D. Sandor, R. Wallace, and S. Peterson. “Understanding the Growth of the Cellulosic Ethanol Industry”. NREL Technical Report NREL/TP-150-42120, April 2008. http://www.nrel.gov/docs/fy08osti/42120.pdf • B. Bush, M. Duffy, D. Sandor, and S. Peterson. “Using System Dynamics to Model the Transition to Biofuels in the United States”. Third International Conference on Systems of Systems Engineering, Monterey, California, June 2–4, 2008. http://www.nrel.gov/docs/fy08osti/43153.pdf • C. Riley and D. Sandor. “Transitioning to Biofuels: A System-of-Systems Perspective”. 2008 INCOSE International Symposium, The Netherlands, June 15–19, 2008. http://www.nrel.gov/docs/fy08osti/42990.pdf • S. Peterson, B. Bush, and J. Geiger. “Design & Implementation ofBiomass Scenario Model Conversion Module”. BSM Conversion Module Informal Review Presentation. November 2007. • B. Bush, D. Sandor, and S. Peterson. “Dynamics of Deploying Cellulosic Feedstocks to Meet U.S. EISA Mandates”. To be submitted to the Journal of Sustainable and Renewable Energy.