Biomass Scenario Model (BSM) Development & Analysis

4 April 2011

Office of the Biomass Program Analysis Platform Peer Review

Brian W Bush

National Renewable Energy Laboratory This presentation does not contain any proprietary, confidential, or otherwise restricted information

Goals and Objectives

• Impact Analysis & Scenario Analysis [highlighted in MYPP] : e

xploring how rapidly biofuel technologies might be deployed to make a significant contribution to the country’s transportation energy

Government Policies – Generate plausible scenarios around Marketplace Structure Analysis Producer/Consumer exchanges transition dynamics.

Implications Investment

Evolution of

Inclusion decisions /scope – Investigate potential market penetration Financial decisions

Supply Chain for Biofuels

scenarios.

– Analyze prospective policies and incentives.

– Identify high-impact drivers and bottlenecks.

– Strategically assess R&D and deployment strategies.

Input Scenarios Feedstock demand • Completion of enhancements addressing Oil prices Learning curves recommendations of previous reviews and OBP and other customer needs – Finalization of full cellulosic ethanol supply chain capability – Addition of new infrastructure-compatible biofuels pathways • Customer-oriented application of the BSM – Ongoing analysis cycle (internal reports, papers, book chapters) – Ad-hoc analyses in response to DOE-OBP requests – Policy- and modeling-oriented stakeholder workshops that elicit high-impact analysis topics

Project Overview

Timeline

– Start Date: October 2006 – End Date: September 2012 – Portion Complete: 80%

Budget

The BSM task was not always 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: $2546k  100% DOE-funded – FY2009: $734k – FY2010: $580k – ARRA: n/a

Barriers

– “Lack of comparable, transparent and reproducible analysis” [At-A] – “Limitations of analytical tools and capabilities for system-level analysis” [At-B] – “Inaccessibility and unavailability of data” [At-C] – – – –

Partners

Project Lead:

NREL Systems Integration Office

Primary Model Developer:

Peterson Group

Modeling & Analysis Support:

Lexidyne LLC

Subject-Matter Expertise:

 National Bioenergy Center  DOE Laboratories  Issue-focused subcontracts

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 o o o o o Vetting Dimensional analysis Design verification Dynamics testing Historical comparison Sensitivity analysis • Modern software-engineering methodology Design & Implementation o o o Data Models Experts Provenance – Defensible and traceable inputs, with metadata – Data extracted from detailed analyses and models  o o o Analysis Dynamics Policies/incentives Scenarios POLYSYS agricultural sector economics, ASPEN Plus process models, BLM logistics model, etc.

– Logic developed and validated through stakeholder meetings  interviews, reviews, workshops, and colloquies Integration o o Publication Informal pre-review Peer review – configuration management – issue tracking – integral documentation – version control – data warehousing – collaborative web site • Agile, adaptive project management (parallel threads, careful triage)

Summary of Accomplishments

• Completed models for all major biofuels pathways – Cellulosic ethanol [Nov 2009] – Infrastructure-compatible biofuels [Feb 2011] • Policy- and modeling-oriented stakeholder workshops – May 2009 – Jan 2010 – Nov 2010 – Mar 2011 • Draft publications describing the BSM and presenting analysis results – feedstock supply & logistics – book chapter documenting the BSM – ethanol “downstream” supply chain – end-to-end ethanol supply chain • Analysis reports internal to DOE-OBP – routine, focused bimonthly reports – ad-hoc quick-response analyses • Parallel efforts (subcontracts) spawned, and mostly completed, to inform and refine upcoming BSM analyses: – biorefinery learning curves – econometric analysis of cost and demand couplings – dispensing-station incentives – forest-residue dynamics • Frequent outreach efforts

Completion of BSM 2.0 (End-to-End Cellulosic Ethanol)

SUPPLY CHAIN

Feedstock Production Feedstock Logistics Biofuels Production Biofuels Distribution Biofuels End Use

Feedstock Logistics Module o Multiple logistics stages o o o Cost breakdowns Transportation distance Land eligibility Distribution Logistics Module o o Distribution terminal focus Differential cost structure, based on infrastructure (storage and intra/inter region transport costs) Vehicle Module o 7 vehicle technologies o 4 efficiency classes o Fleet ageing o E10/E20/E85 potential o o o Feedstock Supply Module o 6 Feedstock types o 10 geographic regions o o 10+ land uses Farmer decision logic Land allocation dynamics New agriculture practices Markets and prices Conversion Module o 5 conversion platforms o 4 development stages o o 6 learning attributes Cascading learning curves o o Project economics Industry growth and investment dynamics Dispensing Station Module o Fueling-station economics o o Tankage and equipment investment decision Distribution-coverage effects

DYNAMIC MODELS OF SUPPLY INFRASTRUCTURE, PHYSICAL CONSTRAINTS, MARKETS, AND DECISION MAKING

Fuel Use Module o Non-, occasional, and frequent users o Relative price/fuel choice dynamics

POLICIES INCENTIVES

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EXTERNALITIES

Cellulosic Ethanol Analyses Recently Completed

1.

2.

3.

4.

5.

Effect of biomass crop assistance program Sensitivity of feedstock and ethanol production to plant-gate feedstock prices Price-stabilizing influence of forest and crop residues Effects of industrial learning rates Differential investment in competing conversion technologies 6.

7.

8.

9.

Conditions under which conversion technologies compete Tradeoffs between grants and loan guarantees Likelihood of boom/bust cycles Extent to which policy exacerbates instabilities 10. Nature of price fluctuations in various elements of the supply chain 11. Effects of reverse-auctions for volumetric credits 7 12. Methods for reducing bottlenecks from lack of distribution or dispensing infrastructure 13. Policy mixes with high benefits for low cost 14. Coupling of petroleum and biofuels prices 15. Effects of E85 pricing strategies at fueling stations 16. Impacts of petroleum price scenarios and price shocks 17. Influence of ethanol tariffs 18. Conditions for achieving RFS or other targets 19. Most effective points for volumetric subsidies 20. Effects of phasing out supportive policies 21. Synergies between volumetric and capital-oriented policies

Completion of BSM 3.0 (Infrastructure-Compatible Biofuels)

Biomass Feedstocks Lignocellulosic Biomass Gasification Biorefinery Processing Syn Gas

Catalytic synthesis Methanol Synthesis, MTG

Petrochemical Refining

FT synthesis

Energy crops (herbaceous and woody) Pyrolysis & Liquefaction Bio-Oils Residues (herbaceous, woody, urban) Pretreatment & Hydrolysis

HydroCracking/Treating Aqueous Phase Reforming Fermentation

Sugars

Fermentation

Hydrolysis Corn

Fermentation

Natural Oils ( Oilseeds and Algae) Extraction Oils

Hydrodeoxygenation

Blending at Refinery Finished Fuels Ethanol and Mixed Alcohols Gasoline Gasoline Diesel Jet Butanol Ethanol Diesel and Jet Green text

Processes currently in the BSM Processes skipped, lines are for reference Optional processes November, 2010 8

Key Insights from Full Supply-Chain Analyses for Cellulosic Ethanol

Four keys to industry development: 1. High level of infrastructure investment in dispensing mechanisms that sustain low enough point-of-use prices 2. Profitability at point of production 3. High rates of industry learning 4. An aggressive start in building pilot, demonstration, and pioneer-scale plants The “take off” is likely to be wild and wooly: 1. Unstable, higher than anticipated, feedstock prices 2. Boom/bust development of ethanol production capacity 3. Potential for price instability 4. Less than full penetration of potential E85 market Supportive policies will be expensive.

1. Cumulative subsidies have substantial costs over 2010-30 Potential maximum consumption in AEO vehicle fleet

Selected Insights along the Cellulosic Ethanol Supply Chain

The availability of forest residue helps stabilize feedstock prices in early years, as herbaceous energy crops are brought into production; crop residues, urban residues, and woody perennials play smaller roles.

Without sufficient external support (e.g., counter-cyclical policies), “boom and bust” development of ethanol production capacity is likely.

Competition between the different technologies is very noticeable in favorable cellulosic biofuels scenarios.

In the absence of subsidies, the lack of distribution infrastructure seriously hinders downstream availability and adoption of high blend ethanol.

Due to the small operating margins of refueling stations, comprehensive subsidies are essential in fostering the installation of high blend ethanol refueling capacity.

Feedstock Supply Feedstock Logistics Conversion Distribution Logistics Dispensing Station Fuel Use

In most geographic regions, moderate feedstock prices are sufficient to meet near-term targets by 2015, but higher prices are necessary to meet aggressive targets by 2030. Prices are subject to periodic fluctuations in early years.

The prices of annual commercial crops such as wheat and corn are not unduly affected by EISA targets.

Sixty miles is the typical economical radius for crop residue and energy crop feedstock collection.

There is a “tipping point” related to level of initial investment in pilot and demonstration plants: investment must cross a threshold of approximately ten demo plants for a pathway to flourish.

Pathway progress is critically dependent on the cascade of learning throughout developmental scales: low capabilities for learning would inhibit industry growth.

Favorable ethanol selling prices substantially accelerate industry development.

There is a strong tension between maintaining high feedstock prices for farmers, and high ethanol mark-ups for producers, distributors, and dispensors while keeping ethanol prices low for end users.

Aggressive E85 penetration scenarios require FFV adoption substantially beyond AEO forecasts.

Vehicles

The market for E85 does not persist in cases where E85 price-advantage or parity is lost: consumption quickly reverts mostly to gasoline when the price gap with E85 closes.

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Cumulatively, several billions dollars of multiple subsidies, carefully coordinated across the supply chain, may be required to reach 30B gallons per year by 2030.

BSM Answers to Key Cellulosic-Ethanol Supply-Chain Questions

How likely is the biofuels supply chain naturally inclined to develop towards meeting targets What chain?

such as RFS?

points of leverage What supply-chain incentives and policies policies and incentives exist for accelerating the adoption of biofuels?

bottlenecks slow the growth of high-blend ethanol consumption?

How do tipping-point dynamics affect the dominance of particular biofuels pathways?

What opportunities exist for across the supply How does the effectiveness of particular rank ?

coordinating

The systemic orchestration of timing and location of intervention is necessary for effective industry takeoff.

Policies that create industrial learning or, better yet, improve the learning rate can dramatically accelerate industry growth.

The lack of available tankage and dispensing equipment and refueling stations hampers E85 adoption.

Initial investments and industrial learning around particular biochemical or thermochemical technologies/pathways may lock those in for long-term prevalence.

Specific combinations of realistic policies and incentives do exist that would effectively accelerate cellulosic ethanol consumption.

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Volumetric incentives tend to be more effective the further down they are in the supply chain.

Example Insight from a Specific Policy Analysis

FFV Potential Cons'n Actual Consumption Actual Production

Aggressive initial investment in conversion plants combined with sustained policy support in downstream portions of the ethanol supply chain efficiently underwrites a moderate take-off of the industry.

Supply-Chain Element Policy

Feedstock Production Production/harvesting subsidy Feedstock Logistics Conversion Logistics/transportation subsidy Feedstock subsidy Fixed capital investment grant for conversion plants Loan guarantee for conversion plants Production subsidy Distribution Dispensing Fuel Use Storage subsidy Fixed capital investment grant for new tankage at refueling stations Fixed capital investment grant for repurposed tankage at refueling stations Point-of-use subsidy (Carbon) tax on gasoline 12

Magnitude

none none none 60% 30% $0.25/gal cellulosic ethanol $0.25/gal ethanol 80% 2020 2050 2035 2030 80%

Expiration Year

n/a n/a n/a 2020 2030 $0.25/gal E85 $0.50/gal gasoline 2040 2050

Relevance to Biomass Program Goals

Supply Chain Element

Feedstock Supply Conversion R&D and Biofuels Integrated Refineries Distribution Infrastructure & End Use Strategic Analysis

Biomass Program Goal BSM Contribution

Provide a secure, reliable and affordable biomass feedstock supply • Analysis of (i) EISA targets and (ii) BCAP, the biomass crop assistance program, with respect to cellulosic ethanol • Publication prepared on insights from analysis of biomass feedstock supply and logistics for cellulosic ethanol Develop technologies for converting feedstocks into cost-competitive liquid transportation fuels Demonstrate and validate integrated technologies to achieve commercially acceptable performance Create the conditions whereby all biofuels can . . . reach their markets and be used by consumers as a replacement for petroleum fuels.

Provide context and justification for decisions at all levels • Analyses of (i) tradeoffs between capital cost reduction policies and volumetric credits and (ii) use of reverse auctions to incentivize the construction of integrated biorefineries • All significant biomass-to-biofuels pathways now represented in the BSM analytic framework • Rough draft of publication on insights from analysis of the potential development of the celluosic ethanol conversion industry • Detailed report on industrial learning in the biofuels and analogous industries • Analyses identifying and quantifying the severity of bottlenecks in the distribution and dispensing infrastructure for cellulosic ethanol • Publication prepared on insights from analysis of “downstream” supply chain elements of the cellulosic and starch ethanol • Ongoing focused analyses of element-specific and whole-supply chain issues affecting biofuels adoption • Quick-response analyses supporting the understanding of emerging policy options • Policy- and modeling-oriented stakeholder workshops for communicating BSM insights and collecting analysis requirements

Benefits

• 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.

Expected Outcomes

• Policy analyses supporting the tactical and strategic decision making within the DOE Biomass Program • A transparent and accessible tool for the analysis of the evolution of and influences on the biofuels industry • Publications documenting methodology and results of biofuels analysis • Development of a broad community understanding of the complex dynamics and feedbacks influencing the potential growth of the biofuels industry Representative Policies Addressed by the BSM Feedstock Supply & Logistics – Subsidies • Biomass Crop Assistance Program Ethanol Production – R&D Investment – Production Credits – Capital Cost Share – Loan Guarantee – Tax Reduction “Downstream” Portions of the Supply Chain – Carbon Cap or Tax – Renewable Fuels Standard – Distribution Infrastructure Investment Incentives – Dispensing Station Infrastructure Investment Incentives – Fuel Taxes and/or Subsidies – Vehicle Purchase Incentives • Future work will expand BSM capabilities to . . .

– analysis of the potential takeoff of infrastructure-compatible biofuels – competition between biofuels, biopower, advanced bioproducts, and traditional uses of the biomass resource – deeply examine international influences on domestic biofuels development – potential external deployment of the BSM

Community & Collaboration

• Review of models, data, and results by subject-experts • Modeling workshop participants: national laboratories, universities, private industry

Model

• Policy workshop participants: – DOE program offices – OSTP – EIA – USDA – EPA – DOT – FAA rev iew , v alid atio n, i m pro ve m en t re qu ire m en ts te st of in tu itio n • Use of Bioenergy KDF for posting results verification model runs

Model Results

ev al sc ua en tio ar io im n of s pa an ct s d

Customer Stakeholders

new insights, intuitions, research issues, potential requirements

Subject Matter Expertise

ne w ve pu tti zz ng le s o or f r p es ot ul ts en , tia l i ns ig ht s • Integrated roles within project:

Requirements Review Project Mgmt Domain Expertise Model Development Data Processing Analysis

DOE OBP NREL Peterson Group, Lexidyne LLC Nat’l labs, federal agencies, universities, subcontractors

√ √ √ √ √ √ √ √ √ √ √ √

Summary: The Strategic Perspective on the BSM Project

Challenge/Objective • Develop an analytic platform to explore and understand the entire biofuels supply-chain evolution over the long term.

High-impact BSM analyses tie RD&D to market realities and policies/incentives.

– The model explicitly focuses on policy issues, their feasibility, and potential side effects. – The BSM is a carefully validated, third-generation model of the full biomass/biofuel supply chain.

Marketplace Structure Producer/Consumer exchanges Government Policies Analysis Implications Products Investment Inclusion decisions /scope

Evolution of

• System-dynamics simulation of the Financial decisions

Supply Chain for Biofuels

biofuels supply chain • Analyses providing insights into system behavior and policy/incentive effectiveness • Stakeholder workshops • Reports and datasets summarizing supporting research Input Scenarios Feedstock demand Oil prices Learning curves

Supplement

Responses to Previous Reviewers’ Comments

“Running of model by people who don’t understand what all is there can be dangerous.” Agreed. The model’s use has so far been restricted to DOE and DOE laboratories. In the second half of FY2011 we are carefully exploring potential deployment options for the BSM and may cautiously pursue this in FY2012.

“While the project uses the best data, results should not be over interpreted. For example, the land use/environmental side is very aggregate. The world market effects also appear to be very generally modeled, if at all.” We have made a conscious decision to focus the capabilities on domestic biofuels and the core influences on the growth of the domestics biofuels industry,in order to avoid “scope creep”. At this point, we have left sustainability and world-market analysis to be conducted in joint studies involving the BSM instead of modeling those directly with the BSM.

“Only as good as assumptions since data is a large challenge.” Agreed. A large part of the project resources are devoted to vetting and updating input data for the BSM. Model results can identify priorities for data improvement through sensitivity/uncertainty analysis.

Publications and Presentations

• Sandor, D. “Biomass System Modeling.” Presented at NREL Analysis Program Technical Review, 13 Oct 2009.

• Bush, B. “Biofuels System Dynamics Modeling.” Presented at Colorado State University at Fort Collins, 19 Nov 2009.

• Bush, B. “Biomass Supply-Chain System Analysis.” Presented at National Bioenergy Center, NREL, 7 Dec 2009.

• Bush, B. “Biomass Scenario Model (BSM) Overview and Status.” Presented at NREL Biofuels Technical Review Panel (NBTRP), 29 April 2010.

• Newes, E.; Inman, D.; Bush, B. “Understanding the Developing Cellulosic Biofuels Industry through Dynamic Modeling.” Abstract accepted and book chapter submitted for publication in

Biofuel

(ISBN 978-953-307-178-7).

• Vimmerstedt, L.; Peterson, S.; Bush, B. “Ethanol Distribution, Dispensing, and Use: Analysis of a Portion of the Biomass-to Biofuels Supply Chain Using System Dynamics.” In review for submission to

PLoS ONE

.

• Bush, B.; Sandor, D.; Peterson, S. “Dynamics of Deploying Cellulosic Feedstocks to Meet U.S. EISA Mandates.” In review for submission to

PLoS ONE

.