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

Project Overview

Timeline– Start Date: October 2006

– End Date: September 2010

– Portion Complete: 70%

BudgetThe 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

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

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

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

Feedstock Supply Module

Mar 2008

Feedstock Logistics Module

Jun 2008

Conversion Module

Nov 2008

Distribution Logistics Module

Mar 2009

Dispensing Station Module

Feb 2009

Vehicle Module

Jul 2008

Petroleum Industry Module

Jun 2009

Integrator Module

Aug 2009

Information Flow

Material Flow

Contents & Concerns of BSM 2.0 Modules

SUPPLY CHAIN

Feedstock Production

Feedstock Logistics

Biofuels Production

Biofuels Distribution

Biofuels End Use

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

Feedstock Supply Moduleo 6 Feedstock typeso 10 geographic regionso 10+ land useso Farmer decision logico Land allocation dynamicso New agriculture practiceso Markets and prices

Feedstock Logistics Moduleo 5 Logistics stageso Cost breakdownso Transportation distanceo Land eligibility

Conversion Moduleo 5 conversion platformso 4 development stageso 6 learning attributeso Cascading learning curveso Project economicso Industry growth and

investment dynamics

Distribution Logistics Moduleo 3 distribution modeso Regional depot/storageo Transport costso Inter-regional transport

Dispensing Station Moduleo Fueling-station economicso Fuel-choice dynamicso Distribution-coverage effects

Vehicle Moduleo 7 vehicle technologieso 4 efficiency classeso Fleet ageingo E10/E20/E85 potential

POLICIES INCENTIVES EXTERNALITIES

Development Pathway

Design & Implementation

Vettingo Dimensional analysiso Design verificationo Dynamics testingo Historical comparisono Sensitivity analysis

Datao Modelso Expertso Provenance

Analysiso Dynamicso Policies/incentiveso Scenarios

Integration

Publicationo Informal pre-reviewo Peer review

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

Milestones

Number Title Due Date Status

n/a Finalize BSM v.2 model requirements

April 2008 Complete

n/a Finalize plan for bringing other players into BSM development

n.d. Ongoing

6.1.3.1.C.1.ML.1 Draft BSM Feedstock Journal Article

30 Nov 2009 In final external review

6.1.3.1.C.1.ML.2 Draft BSM Conversion Journal Article

28 Feb 2009 Expected April 2009

6.1.3.1.C.1.ML.3 Draft BSM Fuel Distribution/End-Use Journal Article

30 Jun 2009 On schedule

6.1.3.1.C.1.ML.4 Preliminary Integrated BSM Runs Complete

30 Dec 2009 Ahead of schedule

Accomplishments towards Biomass Program Goals

Supply Chain Element

Biomass Program Goal BSM 2.0

Feedstock Production

Produce large, sustainable supplies of regionally available biomass.

•Completed module now includes comprehensive land base, farmer-decision logic, regionalization, multiple feedstock sources, crop competition, markets/prices, potential subsidies•Module vetted and populated with best data•Publication prepared with analysis of feedstock aspects of AEO2008 forecast, EISA targets, and BCAP

Feedstock Logistics

Implement biomass feedstock infrastructure, equipment and systems.

•Completed module now includes detailed logistics cost breakdowns of grower payments, potential subsidies, accounting for spatial aspects of feedstock transportation•Module vetted and populated with best data•Analysis integrated into feedstock production publication

Biofuels Production

Deploy cost-effective, integrated biomass-to-biofuels conversion facilities

•Completed module now includes cascading learning curves, regionalization, financials-based plant-construction-decision logic, project failures, physical construction-capacity constraints, potential subsidies•Module vetted and populated with best data•Analysis for publication underway

Biofuels Distribution

Implement biofuels distribution infrastructure.

•Interim modules now include intra- and inter-regional costs of ethanol transport, deployment of ethanol fuels at dispensing-stations, consumer fuel choice, potential subsidies

BiofuelsEnd Use

Expand public availability of biofuels-compatible vehicles with same performance as petroleum fuels.

•Interim module now includes vehicle fleet mix (technologies, efficiency, age distribution), fleet ageing, ethanol potential (E10, E20, E85)•Calibrated against AEO2008 forecasts•Plans for inclusion of vehicle-choice logic in final module version

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.

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017Year

0

1000

2000

3000

4000

5000

6000

7000

Million G

allons

per

Yea

r

Grower Payment + Capital Cost Reduction

Effect of combined policies(relative to baseline)

Sum of effects of individualpolicies (relative to baseline)

Synergistic effect

Cellulosic Ethanol Production

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017Year

0

1000

2000

3000

4000

5000

6000

7000

Million G

allons

per

Yea

r

Base Case

Capital Cost Reduction

Grower Payment

Grower Payment + Capital Cost Reduction

Production Subsidy

Production Subsidy + Capital Cost Reduction

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

Results: Exploration of Competition between Pathways

2010 2020 2030

Year

0

5

10

15

20

Output [bb gal / yr]

Output exceeds 20 billion gallons per year by 2030.

2010 2020 2030

Year

0

100

200

300

400

Plants On-Line

Biochem and thermochem plants begin to "take off".

Significantly fewer starch plants than in base case.

2010 2020 2030

Year

0

10

20

Cumulative Failures

High cummulative number of failures as industry matures.

2010 2020 2030

Year

-0.10

-0.05

0.00

0.05

0.10

Pioneer NPV [bb$]

0.10-

0.05-

0.00

0.05

0.10

Commercial NPV [bb$]

Economic viability

TechnologyBiochemThermochemStarch

Sample Insights from BSM Analyses

Which sources of cellulosic feedstock might plausibly contribute substantially to production in different regions of the United States at different times under EISA scenarios?

Herbaceous energy crops (such as switchgrass) and forest residue are the major contributors to the cellulosic feedstock supply in both the AEO2008 and EISA2007 scenarios. . . .

What is the general magnitude of biorefinery plant gate prices required to support substantial cellulosic feedstock production on the scale implied by the EISA?

The AEO2008 and EISA2007 scenarios imply prices of$50-80/ton at the plant gate to about 2015, and then regionally varying prices that eventually increase up to $125/ton. . . .

Under what conditions could large-scale cellulosic ethanol production cause noticeable price increases in traditional agricultural crops such as corn and wheat?

High demand years at end of the EISA2007 scenario (2022-2030) stretch the system to its limits and cause substantial increases in crop prices. . . .

What are the land-use implications for cropland and pasture land associated with large-scale production of cellulosic energy crops?

Large scale production of cellulosic energy crops has a greater impact on pasture land than on active cropland. In both the AEO2008 and EISA2007 scenarios, substantial inroads into pasture land (~25%) occur in moderate- and high-demand years. . . .

Roughly how long and how large would feedstock-production and -logistics subsidies like those being established under the Biomass Crop Assistance Program (BCAP) need to persist to significantly accelerate the growth of cellulosic ethanol production?

Subsidies on the scale of BCAP produce only minor perturbations, mostly in the form of shifts in sequencing of feedstock production. There is more production of woody perennials, but this comes at the expense of forest residue production. . . .

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.

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.

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

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

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 to

additional advanced biofuels

– Easily tailored for specialized studies

– Making contributions to OBP analysisgoals

• The model explicit focuses onpolicy issues, their feasibility,and potential side effects.

Model

Subject Matter Expertise

Model Resultsmodel runs

Customer Stakeholders

verification

requirements

evalua

tion

of

scen

arios an

d

impa

cts

test of intuition

review, validation, improvem

ent

vetti

ng o

f res

ults

,

new p

uzzle

s or

pot

entia

l ins

ight

s

new insights, intuitions, research issues, potential requirements

Supplement

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.

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.