Conventional feedstock supply systems exist and have been developed for traditional agriculture and forestry systems. These conventional feedstock supply systems can be effective in high biomass-yielding areas (such as for corn stover in Iowa and plantation-grown pine trees in the southern United States), but they have their limits, particularly with respect to addressing feedstock quality and reducing feedstock supply risk to biorefineries. They also are limited in their ability to efficiently deliver energy crops.
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The Biomass Energy Data Book is a statistical compendium prepared and published by Oak Ridge National Laboratory (ORNL) under contract with the Biomass Program in the Energy Efficiency and Renewable Energy (EERE) program of the Department of Energy (DOE). Designed for use as a convenient reference, the book represents an assembly and display of statistics and information that characterize the biomass industry, from the production of biomass feedstocks to their end use, including discussions on sustainability.
Abstract: To ensure effective biomass feedstock provision for large-scale ethanol production, a three-stage supply chain was proposed to include biomass supply sites, centralized storage and preprocessing (CSP) sites, and biorefi nery sites. A GIS-enabled biomass supply chain optimization model (BioScope) was developed to minimize annual biomass-ethanol production costs by selecting the optimal numbers, locations, and capacities of farms, CSPs, and biorefi neries as well as identifying the optimal biomass fl ow pattern from farms to biorefi neries.
An efficient and sustainable biomass feedstock production system is critical for the success of the biomass based energy sector. An integrated systems analysis framework to coordinate various feedstock production related activities is, therefore, highly desirable. This article presents research conducted towards the creation of such a framework.
Bioenergy has been recognized as an important source of energy that will reduce nation’s dependency on petroleum, and have a positive impact on the economy, environment, and society. Production of bioenergy is expected to increase. As a result, we foresee an increase in the number of biorefineries in the near future. This paper analyzes logistical challenges with supplying biomass to a biorefinery.
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 National Renewable Energy Laboratory (NREL) originally developed this application for biopower with funding from the Environmental Protection Agency's Blue Skyways Collaborative. The Department of Energy's Office of Biomass Program provided funding for biofuels functionality. More information on funding agencies is available: http://www.blueskyways.org and http://www.eere.energy.gov/biomass/.
This paper describes a methodology to explore the (future) spatial distribution of biofuel crops in Europe. Two main types of biofuel crops are distinguished: biofuel crops used for the production of biodiesel or bioethanol, and second-generation biofuel crops. A multiscale, multi-model approach is used in which biofuel crops are allocated over the period 2000?2030. The area of biofuel crops at the national level is determined by a macroeconomic model. A spatially explicit land use model is used to allocate the biofuel crops within the countries.