{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/42439"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/42439","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Economies of scale analysis and location studies for fuel ethanol refineries","abstract":"The development of commercial-scale cellulosic ethanol refineries is a challenging task, but it is a promising way to increase national energy independence and security. The main barrier to this development is high production costs. Biomass feedstock costs account for more than 30% of the total operational cost. The Area Utilization Factor (AUF) is a significant index representing the amount of agricultural residues or energy crops that can be collected and delivered to ethanol facilities. Most biomass studies have used fixed AUF values for feedstock procurement. However, plant location can greatly impact feedstock procurement cost. In addition, it is difficult to estimate biomass feedstock costs, since no large-scale commercial markets exist. It is, therefore, not easy to make plant siting decisions, as several factors need to be considered and evaluated. The objectives of this study are: (1) to build a base process and cost model and to conduct an economies of scale analysis for a cellulosic ethanol refinery, and. (2) to find an effective way to determine optimal plant size and location. To model biomass feedstock more practically, the AUF was assumed to be normally distribution, with the mean increasing with distance from the refinery. SuperPro Designer was used to build the process model using the dilute-acid prehydrolysis and enzymatic hydrolysis method. The process model was then used to conduct the economies of scale analysis and determine the optimal plant size. For plant site selection, suitability analyses to identify the candidate plant locations were conducted by examining the relative significance of siting criteria. In addition, a GIS tool was integrated with a grid analysis method and a mixed-integer programming model to determine the optimal plant locations. An engineering process model was built for the economies of scale analysis for cellulosic ethanol production. For feedstock procurement, normally-distributed AUFs resulted in more practical solutions than AUFs conforming to uniform or sine wave distributions. The result of economic analysis suggests that refineries are better off to employ the contract pricing method. Optimally, plants should be located in areas with easy access to transportation facilities, low water cost, low corn basis and high feedstock yield. In future work, the process and cost model need to be updated to use newer versions of SuperPro Designer. More effort need to be put on the selection of AUF distribution functions, since normal distributions may not best represent AUF variations. The study region, herein limited to local watersheds, need to be expanded to the entire Midwest or the whole country.","abstract_html":"The development of commercial-scale cellulosic ethanol refineries is a challenging task, but it is a promising way to increase national energy independence and security. The main barrier to this development is high production costs. Biomass feedstock costs account for more than 30% of the total operational cost. The Area Utilization Factor (AUF) is a significant index representing the amount of agricultural residues or energy crops that can be collected and delivered to ethanol facilities. Most biomass studies have used fixed AUF values for feedstock procurement. However, plant location can greatly impact feedstock procurement cost. In addition, it is difficult to estimate biomass feedstock costs, since no large-scale commercial markets exist. It is, therefore, not easy to make plant siting decisions, as several factors need to be considered and evaluated. The objectives of this study are: (1) to build a base process and cost model and to conduct an economies of scale analysis for a cellulosic ethanol refinery, and. (2) to find an effective way to determine optimal plant size and location. To model biomass feedstock more practically, the AUF was assumed to be normally distribution, with the mean increasing with distance from the refinery. SuperPro Designer was used to build the process model using the dilute-acid prehydrolysis and enzymatic hydrolysis method. The process model was then used to conduct the economies of scale analysis and determine the optimal plant size. For plant site selection, suitability analyses to identify the candidate plant locations were conducted by examining the relative significance of siting criteria. In addition, a GIS tool was integrated with a grid analysis method and a mixed-integer programming model to determine the optimal plant locations. An engineering process model was built for the economies of scale analysis for cellulosic ethanol production. For feedstock procurement, normally-distributed AUFs resulted in more practical solutions than AUFs conforming to uniform or sine wave distributions. The result of economic analysis suggests that refineries are better off to employ the contract pricing method. Optimally, plants should be located in areas with easy access to transportation facilities, low water cost, low corn basis and high feedstock yield. In future work, the process and cost model need to be updated to use newer versions of SuperPro Designer. More effort need to be put on the selection of AUF distribution functions, since normal distributions may not best represent AUF variations. The study region, herein limited to local watersheds, need to be expanded to the entire Midwest or the whole country.","abstract_has_math":false,"creators":["Ma, Shaochun"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Agricultural & Biological Engineering","degree_department":null,"school":null,"contributors":["Eckhoff, Steven R.","Spaulding, Aslihan D.","McIsaac, Gregory F.","Rodriguez, Luis F.","Ouyang, Yanfeng"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-02-03T19:45:41Z","date_published":"2013-02-03T19:45:41Z","updated_at":"2026-07-22T22:25:33Z","subjects":["Ethanol Refineries","Cost Model","Area Utilization Factor (AUF)","Mixed-integer Programming","Economies of Scale","Site Selection"],"languages":["en"],"rights":["Copyright 2012 Shaochun Ma"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/42439","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Eckhoff, Steven R.","Spaulding, Aslihan D.","McIsaac, Gregory F.","Rodriguez, Luis F.","Ouyang, Yanfeng"]},{"key":"dc:creator","label":"Author","values":["Ma, Shaochun"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2013-02-03T19:45:41Z","2015-02-03T11:00:32Z","2012-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Agricultural & Biological Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Ethanol Refineries","Cost Model","Area Utilization Factor (AUF)","Mixed-integer Programming","Economies of Scale","Site Selection"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2012 Shaochun Ma"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/42439"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The development of commercial-scale cellulosic ethanol refineries is a challenging task, but it is a promising way to increase national energy independence and security. The main barrier to this development is high production costs. Biomass feedstock costs account for more than 30% of the total operational cost. The Area Utilization Factor (AUF) is a significant index representing the amount of agricultural residues or energy crops that can be collected and delivered to ethanol facilities. Most biomass studies have used fixed AUF values for feedstock procurement. However, plant location can greatly impact feedstock procurement cost. In addition, it is difficult to estimate biomass feedstock costs, since no large-scale commercial markets exist. It is, therefore, not easy to make plant siting decisions, as several factors need to be considered and evaluated. The objectives of this study are: (1) to build a base process and cost model and to conduct an economies of scale analysis for a cellulosic ethanol refinery, and. (2) to find an effective way to determine optimal plant size and location. To model biomass feedstock more practically, the AUF was assumed to be normally distribution, with the mean increasing with distance from the refinery. SuperPro Designer was used to build the process model using the dilute-acid prehydrolysis and enzymatic hydrolysis method. The process model was then used to conduct the economies of scale analysis and determine the optimal plant size. For plant site selection, suitability analyses to identify the candidate plant locations were conducted by examining the relative significance of siting criteria. In addition, a GIS tool was integrated with a grid analysis method and a mixed-integer programming model to determine the optimal plant locations. An engineering process model was built for the economies of scale analysis for cellulosic ethanol production. For feedstock procurement, normally-distributed AUFs resulted in more practical solutions than AUFs conforming to uniform or sine wave distributions. The result of economic analysis suggests that refineries are better off to employ the contract pricing method. Optimally, plants should be located in areas with easy access to transportation facilities, low water cost, low corn basis and high feedstock yield. In future work, the process and cost model need to be updated to use newer versions of SuperPro Designer. More effort need to be put on the selection of AUF distribution functions, since normal distributions may not best represent AUF variations. The study region, herein limited to local watersheds, need to be expanded to the entire Midwest or the whole country.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2012-11-26T15:10:45Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Ma_Shaochun.pdf: 3487610 bytes, checksum: 7a3ca45c2f9b13a6e2d8d44aab33f01f (MD5)","Made available in DSpace on 2013-02-03T19:45:41Z (GMT). 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The main barrier to this development is high production costs. Biomass feedstock costs account for more than 30% of the total operational cost. The Area Utilization Factor (AUF) is a significant index representing the amount of agricultural residues or energy crops that can be collected and delivered to ethanol facilities. Most biomass studies have used fixed AUF values for feedstock procurement. However, plant location can greatly impact feedstock procurement cost. In addition, it is difficult to estimate biomass feedstock costs, since no large-scale commercial markets exist. It is, therefore, not easy to make plant siting decisions, as several factors need to be considered and evaluated. The objectives of this study are: (1) to build a base process and cost model and to conduct an economies of scale analysis for a cellulosic ethanol refinery, and. (2) to find an effective way to determine optimal plant size and location. To model biomass feedstock more practically, the AUF was assumed to be normally distribution, with the mean increasing with distance from the refinery. SuperPro Designer was used to build the process model using the dilute-acid prehydrolysis and enzymatic hydrolysis method. The process model was then used to conduct the economies of scale analysis and determine the optimal plant size. For plant site selection, suitability analyses to identify the candidate plant locations were conducted by examining the relative significance of siting criteria. In addition, a GIS tool was integrated with a grid analysis method and a mixed-integer programming model to determine the optimal plant locations. An engineering process model was built for the economies of scale analysis for cellulosic ethanol production. For feedstock procurement, normally-distributed AUFs resulted in more practical solutions than AUFs conforming to uniform or sine wave distributions. The result of economic analysis suggests that refineries are better off to employ the contract pricing method. Optimally, plants should be located in areas with easy access to transportation facilities, low water cost, low corn basis and high feedstock yield. In future work, the process and cost model need to be updated to use newer versions of SuperPro Designer. More effort need to be put on the selection of AUF distribution functions, since normal distributions may not best represent AUF variations. The study region, herein limited to local watersheds, need to be expanded to the entire Midwest or the whole country.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2012-11-26T15:10:45Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Ma_Shaochun.pdf: 3487610 bytes, checksum: 7a3ca45c2f9b13a6e2d8d44aab33f01f (MD5)","Made available in DSpace on 2013-02-03T19:45:41Z (GMT). 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