Brian W Bush

B. Bush, “Biomass-to-Bioenergy Supply-Chain Scenario Analysis,” presented at the 2013 Bioenergy Technologies Office Analysis and Sustainability Peer Review, Alexandria, Virginia. <https://www2.eere.energy.gov/biomass/peer_review2013/Portal/presenters/public/InsecureDownload.aspx?filename=Peer_Review_Analysis_Bush_4.pdf>
The Biomass Scenario Model (BSM) is a unique, carefully validated, state-of-the-art third-generation model of the domestic biofuels supply chain which explicitly focuses on policy issues and their potential side effects. It integrates resource availability, behavior, policy, and physical, technological, and economic constraints. The model uses a system-dynamics simulation (not optimization) to model dynamic interactions across the supply chain; the BSM tracks the deployment of biofuels given technological development and the reaction of the investment community to those technologies in the context of land availability, the competing oil market, consumer demand for biofuels, and government policies over time. It places a strong emphasis on the behavior and decision-making of various economic agents among ten geographic regions domestically. The BSM has been used to develop insights into biofuels industry growth and market penetration, particularly with respect to policies and incentives applicable to each supply-chain element (volumetric, capital, operating subsidies; carbon caps/taxes; R&D investment; loan guarantees; tax credits); the model treats the major infrastructure-compatible fuels such as biomass-based gasoline, diesel, jet fuel, ethanol, and butanol. In general, scenario analysis based on the BSM shows that the biofuels industry tends not to rapidly thrive without significant external actions in the early years of its evolution. An initial focus for jumpstarting the industry typically has strongest results in the BSM in areas where effects of intervention have been identified to be multiplicative: due to industrial learning dynamics, support for the construction of biofuel conversion facilities in the near future encourages the industry to flourish. In general, we find that policies which are coordinated across the whole supply chain have significant impact in fostering the growth of the biofuels industry and that the production of tens of billions of gallons of biofuels may occur under sufficiently favorable conditions.

B. Bush, “Biomass Scenario Model,” presented at the 2009 Office of the Biomass Program Analysis Platform Review, National Harbor, Maryland. <http://www.obpreview2009.govtools.us/analysis/documents/FutureFuels1_Bush.ppt>

B. Bush, “Applications of the Biomass Scenario Model,” presented at the Workshop on Biofuels Projections in the AEO, Washington, D.C. <http://www.eia.gov/biofuels/workshop/presentations/2013/pdf/presentation-14-032013.pdf>
U.S. policy targets 36 billion gallons per year of biofuels utilization by 2022, under the renewable fuels standard provisions of the Energy Independence and Security Act of 2007. Achieving such large scale biofuels adoption requires substantial development of new infrastructure, markets, and related systems. The U.S. Department of Energy is employing a system dynamics model, the Biomass Scenario Model (BSM), to represent the primary system effects and dependencies in the biomass-to-biofuels supply chain and to provide a framework for developing scenarios and conducting biofuels policy analysis. This approach is designed to help focus government action by determining which supply chain changes would have the greatest potential to accelerate the deployment of biofuels. Modeling the integration of all aspects of the supply chain from growing the feedstock through harvest, collection, transport, conversion, distribution of fuel and finally consumption of the fuel in applicable vehicles (including the availability of these vehicles) is critical to understanding where government funds might be utilized most effectively. This presentation provides an overview of the status of the BSM and a summary of recent results from system analysis based on it. We find that policies which are coordinated across the whole supply chain have significant impact in fostering the growth of the biofuels industry.

B. Bush and D. Stright, “Simulation Process and Data Flow for Large Scale System Dynamics Models.”

C. M. Clark, Y. Lin, B. G. Bierwagen, L. M. Eaton, M. H. Langholtz, P. E. Morefield, C. E. Ridley, L. Vimmerstedt, S. Peterson, and B. W. Bush, “Growing a sustainable biofuels industry: economics, environmental considerations, and the role of the Conservation Reserve Program,” Environ. Res. Lett., vol. 8, no. 2, p. 025016. <http://iopscience.iop.org/1748-9326/8/2/025016>
Biofuels are expected to be a major contributor to renewable energy in the coming decades under the Renewable Fuel Standard (RFS). These fuels have many attractive properties including the promotion of energy independence, rural development, and the reduction of national carbon emissions. However, several unresolved environmental and economic concerns remain. Environmentally, much of the biomass is expected to come from agricultural expansion and/or intensification, which may greatly affect the net environmental impact, and economically, the lack of a developed infrastructure and bottlenecks along the supply chain may affect the industry’s economic vitality. The approximately 30 million acres (12 million hectares) under the Conservation Reserve Program (CRP) represent one land base for possible expansion. Here, we examine the potential role of the CRP in biofuels industry development, by (1) assessing the range of environmental effects on six end points of concern, and (2) simulating differences in potential industry growth nationally using a systems dynamics model. The model examines seven land-use scenarios (various percentages of CRP cultivation for biofuel) and five economic scenarios (subsidy schemes) to explore the benefits of using the CRP. The environmental assessment revealed wide variation in potential impacts. Lignocellulosic feedstocks had the greatest potential to improve the environmental condition relative to row crops, but the most plausible impacts were considered to be neutral or slightly negative. Model simulations revealed that industry growth was much more sensitive to economic scenarios than land-use scenarios—similar volumes of biofuels could be produced with no CRP as with 100% utilization. The range of responses to economic policy was substantial, including long-term market stagnation at current levels of first-generation biofuels under minimal policy intervention, or RFS-scale quantities of biofuels if policy or market conditions were more favorable. In total, the combination of the environmental assessment and the supply chain model suggests that large-scale conversion of the CRP to row crops would likely incur a significant environmental cost, without a concomitant benefit in terms of biofuel production.

D. Inman, L. Vimmerstedt, E. Newes, B. Bush, and S. Peterson, “Biomass scenario model scenario library: definitions, construction, and description,” National Renewable Energy Laboratory, Golden, Colorado, Technical Report. <http://dx.doi.org/10.2172/1129277>
Understanding the development of the biofuels industry in the United States is important to policymakers and industry. The Biomass Scenario Model (BSM) is a system dynamics model of the biomass-to-biofuels system that can be used to explore many aspects of the industry. Because of the complexity of the model, as well as the wide range of possible future conditions that affect biofuels industry development, we have not developed a single reference case but instead have designed a set of six incentive-focused scenarios. The purpose of this report is to describe the scenarios that comprise the BSM scenario library. At present, we have the following six incentive-focused scenarios in our library: minimal incentives scenario; ethanol-focused incentives scenario; equal access to incentives scenario; output-focused incentives scenario; pathway-diversity-focused incentives scenario; and the point-of-production-focused incentives scenario. This report describes the model settings and rationale for each scenario.

Y. Lin, E. Newes, B. Bush, S. Peterson, and D. Stright, “Biomass Scenario Model Documentation: Data and References,” National Renewable Energy Laboratory, Golden, Colorado, Technical Report NREL/TP-6A20-57831. <http://www.osti.gov/bridge/servlets/purl/1082565/>
The Biomass Scenario Model (BSM) is a system dynamics model that represents the entire biomass-to-biofuels supply chain, from feedstock to fuel use. The BSM is a complex model that has been used for extensive analyses; the model and its results can be better understood if input data used for initialization and calibration are well-characterized. It has been carefully validated and calibrated against the available data, with data gaps filled in using expert opinion and internally consistent assumed values. Most of the main data sources that feed into the model are recognized as baseline values by the industry. This report documents data sources and references in Version 2 of the BSM (BSM2), which only contains the ethanol pathway, although subsequent versions of the BSM contain multiple conversion pathways. The BSM2 contains over 12,000 total input values, with 506 distinct variables. Many of the variables are opportunities for the user to define scenarios, while others are simply used to initialize a stock, such as the initial number of biorefineries. However, around 35% of the distinct variables are defined by external sources, such as models or reports. The focus of this report is to provide insight into which sources are most influential in each area of the supply chain. We find that data based on POLYSYS datasets and U.S. Department of Agriculture baseline projections are the most utilized sources in the feedstock sector, whereas the conversion module relies heavily on data found in National Renewable Energy Laboratory technical reports dealing with the techno-economic characteristics of different technologies. The distribution, dispensing, and fuel use modules utilize data on gasoline stations from the National Association of Convenience Stores.

E. K. Newes, B. W. Bush, C. Peck, and S. Peterson, “Insights into the effect of policy on the potential development of the cellulosic ethanol industry,” Environmental Science & Technology.
The U.S. government supports the biofuels industry through incentives, such as fixed capital investment grants, loan guarantees, and volumetric credits for production. The systemic effects of incentive policies are not fully understood, although they may interact with other influential factors and may have profound long-term impacts. We have used system dynamics modeling, employed in the BSM, to understand the biomass-to-biofuels system and to analyze effects of different policies on it. While this paper focuses on the cellulosic ethanol industry, the BSM also models other biofuels such as biomass-based gasoline, diesel, and aviation fuel. This paper highlights insights into specific policies, alone and in combination, which could increase industry success while tempering overall spending. We find that ethanol distribution and dispensing is a bottleneck to industry expansion, which can be overcome with targeted incentives for installation of infrastructure and tankage for ethanol. Aggressive initial investment in pilot, demonstration, and pioneer-scale conversion facilities, or an initial point-of-production subsidy for conversion facilities in conjunction with industry learning, helps to establish and sustain the cellulosic ethanol industry. Coordination of incentives for conversion and distribution of ethanol can increase the impact of policy on the industry.

E. K. Newes, B. W. Bush, C. Peck, and S. Peterson, “Exploration of policy, shocks , and dynamic interactions within the cellulosic ethanol supply chain,” Biofpr.
The U.S. government supports the biofuels industry through incentives, such as fixed capital investment grants, loan guarantees, and volumetric credits for production. The systemic effects of incentive policies are not fully understood, although they may interact with other influential factors and may have profound long-term impacts. We have used system dynamics modeling, employed in the BSM, to understand the biomass-to-biofuels system and to analyze effects of different policies on it. While this paper focuses on the cellulosic ethanol industry, the BSM also models other biofuels such as biomass-based gasoline, diesel, and aviation fuel. This paper highlights insights into specific policies, alone and in combination, which could increase industry success while tempering overall spending. We find that ethanol distribution and dispensing is a bottleneck to industry expansion, which can be overcome with targeted incentives for installation of infrastructure and tankage for ethanol. Aggressive initial investment in pilot, demonstration, and pioneer-scale conversion facilities, or an initial point-of-production subsidy for conversion facilities in conjunction with industry learning, helps to establish and sustain the cellulosic ethanol industry. Coordination of incentives for conversion and distribution of ethanol can increase the impact of policy on the industry.

E. Newes, B. Bush, D. Inman, Y. Lin, T. Mai, A. Martinez, D. Mulcahy, W. Short, T. Simpkins, C. Uriarte, and C. Peck, “Biomass Resource Allocation among Competing End Uses,” National Renewable Energy Laboratory, Golden, Colorado, Technical Report NREL/TP-6A20-54217. <http://www.osti.gov/bridge/servlets/purl/1041351/>
The Biomass Scenario Model (BSM) is a system dynamics model developed by the U.S. Department of Energy as a tool to better understand the interaction of complex policies and their potential effects on the biofuels industry in the United States. However, it does not currently have the capability to account for allocation of biomass resources among the various end uses, which limits its utilization in analysis of policies that target biomass uses outside the biofuels industry. This report provides a more holistic understanding of the dynamics surrounding the allocation of biomass among uses that include traditional use, wood pellet exports, bio-based products and bioproducts, biopower, and biofuels by (1) highlighting the methods used in existing models’ treatments of competition for biomass resources; (2) identifying coverage and gaps in industry data regarding the competing end uses; and (3) exploring options for developing models of biomass allocation that could be integrated with the BSM to actively exchange and incorporate relevant information

E. Newes, D. Inman, and B. Bush, “Understanding the Developing Cellulosic Biofuels Industry through Dynamic Modeling,” in Economic Effects of Biofuel Production, M. A. dos Santos Bernardes, Ed. Rijeka, Croatia: InTech, pp. 373–404. <http://www.intechopen.com/books/economic-effects-of-biofuel-production/understanding-the-developing-cellulosic-biofuels-industry-through-dynamic-modeling>
Biofuels are promoted in the United States through aggressive legislation, as one part of an overall strategy to lessen dependence on imported energy as well as to reduce the emissions of greenhouse gases (Office of the Biomass Program and Energy Efficiency and Renewable Energy, 2008). For example, the Energy Independence and Security Act of 2007 (EISA) mandates 36 billion gallons of renewable liquid transportation fuel in the U.S. marketplace by the year 2022 (U.S. Government, 2007). Meeting such large volumetric targets has prompted an unprecedented increase in funding for biofuels research. Language in the EISA legislation limits the amount of renewable fuel derived from starch-based feedstocks (which are already established and feed the commercially viable ethanol industry in the United States); therefore, much of the current research is focused on producing ethanol—but from cellulosic feedstocks. These feedstocks, such as agricultural and forestry residues, perennial grasses, woody crops, and municipal solid wastes, are advantageous because they do not necessarily compete directly with food, feed, and fiber production and are envisaged to require fewer inputs (e.g., water, nutrients, and land) as compared to corn and other commodity crops. In order to help propel the biofuels industry in general and the cellulosic ethanol industry in particular, the U.S. government has enacted subsidies, fixed capital investment grants, loan guarantees, vehicle choice credits, and aggressive corporate average fuel economy standards as incentives. However, the effect of these policies on the cellulosic ethanol industry over time is not well understood. Policies such as those enacted in the United States, that are intended to incentivize the industry and promote industrial expansion, can have profound long-term effects on growth and industry takeoff as well as interact with other policies in unforeseen ways (both negative and positive). Qualifying the relative efficacies of incentive strategies could potentially lead to faster industry growth as well as optimize the government’s investment in policies to promote renewable fuels. The purpose of this chapter is to discuss a system dynamics model called the Biomass Scenario Model (BSM), which is being developed by the U.S. Department of Energy as a tool to better understand the interaction of complex policies and their potential effects on the burgeoning cellulosic biofuels industry in the United States. The model has also recently been expanded to include advanced conversion technologies and biofuels (i.e., conversion pathways that yield biomass-based gasoline, diesel, jet fuel, and butanol), but we focus on cellulosic ethanol conversion pathways here. The BSM uses a system dynamics modeling approach (Bush et al., 2008) built on the STELLA software platform (isee systems, 2010) to model the entire biomass-to-biofuels supply chain. Key components of the BSM are shown in Figure 1. In addition to describing the underpinnings of this model, we will share insights that have been gleaned from a myriad of scenario- and policy-driven model runs. These insights will focus on how roadblocks, bottlenecks, and incentives all work in concert to have profound effects on the future of the industry.

S. Peterson, E. Newes, D. Inman, L. Vimmerstedt, D. Hsu, C. Peck, D. Stright, and B. Bush, “An Overview of the Biomass Scenario Model,” presented at the The 31st International Conference of the System Dynamics Society, Cambridge, Massachusetts. <http://www.systemdynamics.org/conferences/2013/proceed/papers/P1352.pdf>
Biofuels are promoted in the United States through aggressive legislation as one part of an overall strategy to lessen dependence on imported energy as well as to reduce the emissions of greenhouse gases. Meeting mandated volumetric targets has prompted substantial funding for biofuels research, much of it focused on producing ethanol and other fuel types from biomass feedstocks. A variety of incentive programs (including subsidies, fixed capital investment grants, loan guarantees, vehicle choice credits, and aggressive corporate average fuel economy standards)have been developed, but their short-and long-term ramifications are not well known. This paper describes the Biomass Scenario Model, a system dynamics model developed under the support of the U.S. Department of Energy as the result of a multi-year project at the National Renewable Energy Laboratory. The model represents multiple pathways leading to the production of fuel ethanol as well as advanced biofuels such as biomass-based gasoline, diesel, jet fuel, and butanol). This paper details the BSM system dynamics architecture, the design of the supporting database infrastructure, the associated scenario libraries used in model runs, as well as key insights resulting from BSM simulations and analyses.

L. J. Vimmerstedt, B. W. Bush, and S. Peterson, “Effects of Deployment Investment on the Growth of the Biofuels Industry,” National Renewable Energy Laboratory, Golden, Colorado, Technical Report. <http://dx.doi.org/10.2172/1118095>
In support of the national goals for biofuel use in the United States, numerous technologies have been developed that convert biomass to biofuels. Some of these biomass-to-biofuel conversion technology pathways are fully commercial, while others are in earlier stages of development. The advancement of a new pathway towards commercialization involves various types of improvements, including yield improvements through chemical and biochemical refinements, process engineering, and financial performance. Actions of private investors and public programs can accelerate the demonstration and deployment of new conversion technology pathways. These investors (both private and public) will pursue a range of pilot-, demonstration-, and pioneer-commercial-scale biorefinery investments, because the most cost-effective set of investments for advancing the maturity of the pathway is unknown. In some cases whether or not the pathway itself will ultimately be technically and financially successful is unknown. This report presents results from the Biomass Scenario Model—a system dynamics model of the biomass-to-biofuels system—that estimate effects of investment in one particular demonstration and deployment plan. This plan is a multi-stage combination of pilot, demonstration, and pioneer-commercial-scale biorefineries. The report discusses challenges in estimating effects of such investments. The report concludes that investment in demonstration and deployment appears to have a substantive positive effect on the development of the biofuels industry, and that other conditions, such as supportive policies, are likely to have major impacts on the effectiveness of such investments.

L. J. Vimmerstedt, B. W. Bush, and S. O. Peterson, “Dynamic Modeling of Learning in Emerging Energy Industries.”
The Energy Independence and Security Act of 2007 mandates 36 billion gallons of renewable liquid transportation fuel in the U.S. marketplace by the year 2022, reflecting U.S. government goals to reduce petroleum use and carbon emissions. New biomass-to-biofuels conversion technology pathways are being developed to support these policy goals. The U.S. Department of Energy and the National Renewable Energy Laboratory developed the Biomass Scenario Model (BSM) to explore the impact of biofuel policy on the evolution of the supply chain for biofuels. The BSM couples investment, production, and learning among competing biofuel conversion options that may be at different stages of industrial development. The BSM can simulate the impact of differing assumptions about mature industry techno-economics and about learning rates that facilitate industry maturation, while accounting for the different maturity levels of various conversion pathways. This paper explores the impact of different learning rates and different techno-economics on industry evolution in a learning model excerpted from the BSM. The sensitivity study shows that the parameters studied (fixed capital investment, process yield, progress ratios, and pre-commercial investment) exhibit highly interactive effects, yielding insights on market dominance, pathway failure, competition, and learning dynamics. The results could have implications for cost effectiveness and timing of policies that intend to accelerate biofuels industry development.

L. J. Vimmerstedt, B. W. Bush, D. D. Hsu, D. Inman, and S. Peterson, “Maturation of Biomass-to-Biofuels Conversion Technology Pathways for Rapid Expansion of Biofuels Production: A System Dynamics Perspective,” Biofpr.
The potential for rapid expansion of the biofuels industry is explored using a system-dynamics simulation model named the Biomass Scenario Model (BSM), emphasizing how policy incentives and technological learning-by-doing can accelerate industry growth. The BSM simulates major sectors of the biofuels industry, including feedstock production and logistics, conversion, distribution, and end use, as well as their interaction with one another. The model represents conversion of biomass to biofuels as a set of technology pathways, each having characteristics that include allowable feedstocks, capital and operating costs, and allowable products. Simulations indicate that coordination of investments—with respect to timing, pathway, and target sector within the biofuels industry—is needed to accelerate learning-by-doing and most effectively expand biofuels production to meet Renewable Fuel Standards (RFS). Metrics of effectiveness include timing and magnitude of increased production, incentive cost and cost-effectiveness, and avoidance of windfall profits. Due to risks and uncertainties, investment costs and optimal investment targets—such as relative value of investment in more-mature versus less-mature pathways—can be explored through scenarios but not predicted with precision. During rapid growth, dynamic competition intensifies, including competition for cellulosic feedstocks and ethanol market shares. Rapid growth in ethanol production occurs in simulations that allow higher blending proportions of ethanol in gasoline-fueled vehicles, even up to RFS-targeted volumes of biofuel.

L. J. Vimmerstedt, B. Bush, and S. Peterson, “Ethanol Distribution, Dispensing, and Use: Analysis of a Portion of the Biomass-to-Biofuels Supply Chain Using System Dynamics,” PLoS ONE, vol. 7, no. 5, p. e35082. <http://dx.doi.org/10.1371/journal.pone.0035082>
The Energy Independence and Security Act of 2007 targets use of 36 billion gallons of biofuels per year by 2022. Achieving this may require substantial changes to current transportation fuel systems for distribution, dispensing, and use in vehicles. The U.S. Department of Energy and the National Renewable Energy Laboratory designed a system dynamics approach to help focus government action by determining what supply chain changes would have the greatest potential to accelerate biofuels deployment. The National Renewable Energy Laboratory developed the Biomass Scenario Model, a system dynamics model which represents the primary system effects and dependencies in the biomass-to-biofuels supply chain. The model provides a framework for developing scenarios and conducting biofuels policy analysis. This paper focuses on the downstream portion of the supply chain–represented in the distribution logistics, dispensing station, and fuel utilization, and vehicle modules of the Biomass Scenario Model. This model initially focused on ethanol, but has since been expanded to include other biofuels. Some portions of this system are represented dynamically with major interactions and feedbacks, especially those related to a dispensing station owner’s decision whether to offer ethanol fuel and a consumer’s choice whether to purchase that fuel. Other portions of the system are modeled with little or no dynamics; the vehicle choices of consumers are represented as discrete scenarios. This paper explores conditions needed to sustain an ethanol fuel market and identifies implications of these findings for program and policy goals. A large, economically sustainable ethanol fuel market (or other biofuel market) requires low end-user fuel price relative to gasoline and sufficient producer payment, which are difficult to achieve simultaneously. Other requirements (different for ethanol vs. other biofuel markets) include the need for infrastructure for distribution and dispensing and widespread use of high ethanol blends in flexible-fuel vehicles.