Analysis and Simulation of Switchgrass Harvest Systems for Large-scale Biofuel Production

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dc.contributor.authorMcCullough, Devitaen
dc.contributor.committeechairGrisso, Robert D.en
dc.contributor.committeememberCundiff, John S.en
dc.contributor.committeememberSarin, Subhash C.en
dc.contributor.committeememberSenger, Ryan S.en
dc.contributor.departmentBiological Systems Engineeringen
dc.date.accessioned2014-03-14T20:50:47Zen
dc.date.adate2013-01-25en
dc.date.available2014-03-14T20:50:47Zen
dc.date.issued2012-08-15en
dc.date.rdate2013-01-25en
dc.date.sdate2012-12-24en
dc.description.abstractIn the United States, the Energy Independence and Security Act of 2007 mandates the annual production of 136 billion liters of renewable fuel in the US by 2022 (US Congress, 2007). As the nation moves towards energy independence, it is critical to address the current challenges associated with large-scale biofuel production. The biomass logistics network considered consists of three core operations: farmgate operations, highway-hauling operations, and receiving facility operations. To date, decision-making has been limited in post-production management (harvesting, in-field hauling, and storage) in farmgate operations. In this thesis, we study the impacts in the logistics network resulting from the selection of one of four harvest scenarios. A simulation model was developed, which simulated the harvest and filling of a Satellite Storage Location (SSL), using conventional hay harvest equipment, specifically, a round baler. The model evaluated the impacts of four harvest scenarios (ranging from short, October-December, to extended, July-March), on baler equipment requirements, baler utilization, and the storage capacity requirements of round bales, across a harvest production region. The production region selected for this study encompassed a 32-km radius surrounding a hypothetical bio-crude plant in Gretna, VA, and considered 141 optimally selected SSLs. The production region was divided into 6 sub-regions (i.e. tours). The total production region consisted of 15,438 ha and 682 fields. The fields ranged in size from 6 to 156 ha. Of the four scenarios examined in the analysis, each displayed similar trends across the six tours. Variations in the baler requirements that were observed among the tours resulted from variability in field size distribution, field to baler allocations, and total production area. The available work hours were found to have a significant impact on the resource requirements to fulfill harvest operations and resource requirements were greatly reduced when harvest operations were extended throughout the 9-month harvest season. Beginning harvest in July and extending harvest through March resulted in reductions in round balers ranging from 50-63%, as compared to the short harvest scenario, on a sub-regional basis. On a regional basis, beginning harvest in July and extending harvest through March resulted in baler reductions up to 58.2%, as compared to the short harvest scenario. For a 9-month harvest, harvesting approximately 50% of total switchgrass harvest in July-September, as compared to harvesting approximately 50% in October-December, resulted in reductions in round balers ranging from 33.3- 43.5%. An extended (9-month) harvest resulted in the lowest annual baler requirements, and on average lower baler utilization rates. The reduced harvest scenarios, when compared to the extended harvest scenarios, resulted in a significant increase in the number of annual balers required for harvest operations. However, among the reduced harvest scenarios (i.e. Scenario 3 and 4), the number of annual balers required for harvest operations showed significantly less variation than between the extended harvest scenarios (i.e. Scenarios 1 and 2). As a result, an increased utilization of the balers in the system, short harvest scenarios resulted in the highest average baler utilization rates. Storage capacity requirements were however found to be greater for short harvest scenarios. For the reduced harvest scenario, employing an October-December harvest window, approximately 50% of harvest was completed by the end of October, and 100% of total harvest was completed by the third month of harvest (i.e. December).en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-12242012-144807en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-12242012-144807/en
dc.identifier.urihttp://hdl.handle.net/10919/36444en
dc.publisherVirginia Techen
dc.relation.haspartMcCullough_DD_T_2012.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectSwitchgrasss (Panicum virgatum L.)en
dc.subjectbiomassen
dc.subjectharvesten
dc.subjectround baleen
dc.subjectround baleren
dc.subjectlogisticsen
dc.subjectstorageen
dc.subjecttransportationen
dc.subjectbiofuelen
dc.subjectMATLABen
dc.subjectSimulinken
dc.subjectSimEventsen
dc.subjectSimulationen
dc.subjectavailable harvest timeen
dc.subjectprobability work dayen
dc.subjectharvest scheduleen
dc.subjectharvest windowen
dc.subjectbaler utilizationen
dc.titleAnalysis and Simulation of Switchgrass Harvest Systems for Large-scale Biofuel Productionen
dc.typeThesisen
thesis.degree.disciplineBiological Systems Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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