Spatial Pricing Patterns of Cellulosic Biomass under Oligopsony – A Multi-agent Simulation Model

Agribusiness, Industrial Organization, Research Methods/ Statistical Methods, Resource /Energy Economics and Policy,

Choice of optimum feedstock portfolio for a cellulosic ethanol plant – A dynamic linear programming solution

When the lignocellulosic biofuels industry reaches maturity and many types of biomass sources become economically viable, management of multiple feedstock supplies – that vary in their yields, density (tons per unit area), harvest window, storage and seasonal costs, storage losses, transport distance to the production plant – will become increasingly important for the success of individual enterprises. The manager’s feedstock procurement problem is modeled as a multi-period sequence problem to account for dynamic management over time. The case is illustrated with a hypothetical 53 million annual US gallon cellulosic ethanol plant located in south west Kansas that requires approximately 700,000 metric dry tons of biomass. The problem is framed over 40 quarters (10 years), where the production manager minimizes cumulative costs by choosing the land acreage that has to be contracted with for corn stover collection, or dedicated energy production and the amount of biomass stored for off-season. The sensitivity of feedstock costs to changes in yield patterns, harvesting and transport costs, seasonal costs and the extent of area available for feedstock procurement are studied. The outputs of the model include expected feedstock cost and optimal mix of feedstocks used by the cellulosic ethanol plant every year. The problem is coded and solved using GAMS software. The analysis demonstrates how the feedstock choice affects the resulting raw material cost for cellulosic ethanol production, and how the optimal combination varies with two types of feedstocks (annual and perennial).Cellulosic ethanol, feedstock, switchgrass, miscanthus, corn stover, optimization, biofuels, biomass, energy, renewable, Agribusiness,

Testing for Speculative Behavior in US Corn Ethanol Investments

Crude oil price speculation during 2000s could have increased installed capacity in corn ethanol plants beyond what was warranted by the market factors. We use Muth’s commodity pricing model and Flood and Garber’s tests to test for speculative investment in US corn ethanol industry. The ethanol price expectations are derived using a system of supply-demand-inventory describing US ethanol markets under rational expectations (perfect foresight). These price expectations can help differentiate the installed capacity into two: capacity supported by the market fundamentals and the probable capacity that is installed based on speculation. Econometric estimation procedures and functional form approximations are discussed.ethanol, speculation, commodity prices, investment, Agricultural Finance, Financial Economics, Q14, Q41, D8, L71,

Biomass Supply for Biofuel Production: Estimates for the United States and Canada

Published in BioResources, Volume 4, Number 3, 2009, Pages 1070-1087.Biomass Supply, Resource Assessment, Lignocellulosic Biomass, Crop Production/Industries, Demand and Price Analysis, Production Economics, Resource /Energy Economics and Policy, Q42, Q11, Q2, Q20, Q29,

Intentional and Evolutionary Visions of U.S. Antitrust Law

This teaching module shows how U.S. antitrust laws are affected by 'intentional' and 'evolutionary' visions of socio-economic market processes. The extent of government's role is studied to review whether the U.S. antitrust laws should be strengthened, reformed or repealed. The focus of Chicago (and Austrian) school is discussed: 'antitrust laws should promote and enhance the trio of -- consumer welfare, competition process, and dynamic (productive and allocative) efficiency.’The role of U.S. antitrust laws in a globalized world and the need for universal law are mentioned. The economic reasons used to rule in U.S. antitrust enforcement since the 1890s are provided in a tabular format for easy use in the classrooms. Teaching tips are provided on how to use the material in classroom discussion and assessments.

Spatially and Temporally Optimal Biomass Procurement Contracting for Biorefineries

This paper evaluates the optimal composition of annual and perennial biomass feedstocks for a biorefinery. A generic optimization model is built to minimize costs – harvest, transport, storage, seasonal, and environmental costs – subject to various constraints on land availability, feedstock availability, processing capacity, contract terms, and storage losses. The model results are demonstrated through a case study for a midwestern U.S. location, focusing on bioethanol as the likely product. The results suggest that high-yielding energy crops feature prominently (70 to 80%) in the feedstock mix in spite of the higher establishment costs. The cost of biomass ranges from 0.16 to 0.20 $l-1 (US$ 0.60 to $0.75 per gallon) of biofuel. The harvest shed shows that high-yielding energy crops are preferably grown in fields closer to the biorefinery. Low-yielding agricultural residues primarily serve as a buffer crop to meet the shortfall in biomass requirement. For the case study parameters, the model results estimated a price premium for energy crops (2 to 4$ t-1 within a 16 km (10-mile) radius) and agricultural residues (5 to 17 $ t-1 in a 16 to 20 km (10 to 20 mile) radius

Choice of optimum feedstock portfolio for a cellulosic ethanol plant – A dynamic linear programming solution

When the lignocellulosic biofuels industry reaches maturity and many types of biomass sources become economically viable, management of multiple feedstock supplies – that vary in their yields, density (tons per unit area), harvest window, storage and seasonal costs, storage losses, transport distance to the production plant – will become increasingly important for the success of individual enterprises. The manager’s feedstock procurement problem is modeled as a multi-period sequence problem to account for dynamic management over time. The case is illustrated with a hypothetical 53 million annual US gallon cellulosic ethanol plant located in south west Kansas that requires approximately 700,000 metric dry tons of biomass. The problem is framed over 40 quarters (10 years), where the production manager minimizes cumulative costs by choosing the land acreage that has to be contracted with for corn stover collection, or dedicated energy production and the amount of biomass stored for off-season. The sensitivity of feedstock costs to changes in yield patterns, harvesting and transport costs, seasonal costs and the extent of area available for feedstock procurement are studied. The outputs of the model include expected feedstock cost and optimal mix of feedstocks used by the cellulosic ethanol plant every year. The problem is coded and solved using GAMS software. The analysis demonstrates how the feedstock choice affects the resulting raw material cost for cellulosic ethanol production, and how the optimal combination varies with two types of feedstocks (annual and perennial)