A bottom-up biofuel market equilibrium model for policy analysis

详细信息    查看全文

• 作者：Leilei Zhang ; Guping Hu ; Lizhi Wang ; Yihsu Chen
• 关键词：Biofuel ; Supply chain ; Game theory ; Linear complementarity problem
• 刊名：Annals of Operations Research
• 出版年：2016
• 出版时间：January 2016
• 年：2016
• 卷：236
• 期：1
• 页码：75-101
• 全文大小：1,905 KB
• 参考文献：Bai, Y., Ouyang, Y., & Pang, J. S. (2012). Biofuel supply chain design under competitive agricultural land use and feedstock market equilibrium. Energy Economics, 34(5), 1623–1633. CrossRef
  Beach, R. H., & McCarl, B. A. (2010). U.S. agricultural and forestry impacts of the energy independence and security act: FASOM results and model description (Technical report). U.S. Environmental Protection Agency.
  Census, U.S. (2011). U.S. Census Bureau, state and county quickfacts. http://​quickfacts.​census.​gov/​qfd/​states/​19000.​html . Accessed 1 December 2012.
  Chen, X. (2010). A dynamic analysis of US biofuel policy impact on land use, greenhouse gas emission and social welfare. Ph.D. thesis, University of Illinois at Urbana-Champaign.
  Chen, Y., & Wang, L. (2013). Renewable Portfolio Standards in the presence of green consumers and emissions trading. Networks and Spatial Economics, 13, 149–181. CrossRef
  Chen, Y., Sijm, J., Hobbs, B. F., & Lise, W. (2008). Implications of CO2 emissions trading for short-run electricity market outcomes in Northwest Europe. Journal of Regulatory Economics, 34(3), 251–281. CrossRef
  Chen, Y., Liu, A. L., & Hobbs, B. F. (2011). Economic and emissions implications of load-based, source-based, and first-seller emissions trading programs under California AB32. Operations Research, 59(3), 696–712. CrossRef
  Cottle, R. W., Pang, J. S., & Stone, R. E. (1992). The linear complementarity problem. San Diego: Academic Press.
  EIA, U.S. Energy Information Administration (2011). Annual energy review (Technical Report).
  EIA, U.S. Energy Information Administration (2012). U.S. regular gasoline prices, full history. http://​www.​eia.​gov/​petroleum/​gasdiesel/​ . Accessed 1 December 2012.
  Eksioglu, S. D., & Acharya, A. M. (2009). Models for supply chain design and logistics management of biorefineries. In Transportation Research Board 88th annual meeting. http://​trid.​trb.​org/​view.​aspx?​id=​880559 . Accessed 1 December 2012.
  Facchinei, F., & Kanzow, C. (2010). Generalized Nash equilibrium problems. Annals of Operations Research, 175, 177–211. CrossRef
  FCEA (2008). Food, conservation, and energy act of 2008, section 15321. http://​www.​finance.​senate.​gov/​legislation/​details/​?​id=​2b05ac5a-9dd1-e25d-16dc-23cf01e31cc2 . Accessed 1 December 2012.
  Ferris, M. C., & Pang, J. S. (1997). Engineering and economic applications of complementarity problems. SIAM Review, 39, 669–713. CrossRef
  Fischer, C. (2010). Renewable portfolio standards: when do they lower energy prices? The Energy Journal, 0(1), 101–120.
  Gabriel, S. A., Conejo, A. J., Fuller, J. D., Hobbs, B. F., & Ruiz, C. (2012). International series in operations research & management science. Complementarity modeling in energy markets. Berlin: Springer. ISBN-13:978-1441961228.
  Gebreslassie, B. H., Yao, Y., & You, F. (2012). Design under uncertainty of hydrocarbon biorefinery supply chains: multiobjective stochastic programming models, decomposition algorithm, and a comparison between CVaR and downside risk. AIChE Journal, 58(7), 2155–2179. CrossRef
  Huang, H. J., Ramaswamy, S., Al-Dajani, W., Tschimer, U., & Cairncross, R. A. (2009). Effect of biomass species and plant size on cellulosic ethanol: a comparative process and economic analysis. Biomass & Bioenergy, 33(2), 234–246. CrossRef
  Jones, S. B., Holladay, J. E., Valkenburg, C., Stevens, D. J., Walton, C. W., Kinchin, C., Elliott, D. C., & Czernik, S. (2009). Production of gasoline and diesel from biomass via fast pyrolysis, hydrotreating and hydrocracking: a design case (Technical report PNNL-18284). U.S. Department of Energy.
  Li, Z., & Ierapetritou, M. G. (2010). A method for solving the general parametric linear complementarity problem. Annals of Operations Research, 181, 485–501. CrossRef
  Lin, C. Y., Zhang, W., Rouhani, O., & Prince, L. (2009). The implications of an E10 ethanol-blend policy for California. California State Controller John Chiang Statement of General Fund Cash Receipts and Disbursements, 5(5), 6–7.
  Miranowski, J., & Rosburg, A. (2010). Using cellulocis ethanol to ’Go Green’: what price for carbon? In Agricultural & Applied Economics Associations 2010 AAEA, CAES & WAEA joint annual meeting, Denver, CO, 25–27 July.
  Muller, T. (2000). Integrating bottom-up and top-down models for energy policy analysis: a dynamic framework. Centre Universitaire d’Étude des Problèmes de l’Énergie Policy, 28 pages.
  RFA, U.S. Renewable Fuels Association (2012). Historic U.S. fuel ethanol production. http://​www.​ethanolrfa.​org/​pages/​statistics . Accessed 1 December 2012.
  RFS2, The Revised Renewable Fuels Standards (2012). Renewable fuels: regulations & standards. http://​www.​epa.​gov/​otaq/​fuels/​renewablefuels/​regulations.​htm . Accessed 1 December 2012.
  RITA, Research and Innovative Technology Administration (2012). National transportation—Bureau of Transportation statistics: average freight revenue per ton-mile. Research and Innovative Technology Administration. http://​www.​rita.​dot.​gov/​bts/​sites/​rita.​dot.​gov.​bts/​files/​publications/​national_​transportation_​statistics/​html/​table_​03_​21.​html . Accessed 1 December 2012.
  Sabatier, P. A. (1986). Top-down and bottom-up approaches to implementation research: a critical analysis and suggested synthesis. Journal of Public Policy, 6(1), 21–48. CrossRef
  Satrio, J. A., Wright, M. M., & Brown, R. C. (2010). Techno-economic analysis of biomass fast pyrolysis to transportation fuels (National Renewable Energy Laboratory NREL/TP-6A20-46586).
  Searcy, E., Flynn, P., Ghafoori, E., & Kumar, A. (2007). The relative cost of biomass energy transport. Applied Biochemistry and Biotechnology, 137–140(1–12), 639–652.
  SECO, State Energy Conservation Office (2012). Energy policy act of 2005 (H.R. 6). http://​www.​seco.​cpa.​state.​tx.​us/​energy-sources/​biomass/​epact2005.​php . Accessed 1 December 2012.
  Tirole, J. (1988). The theory of industrial organization. Cambridge: The MIT Press.
  UI, University of Illinois (2007). Corn-based ethanol in Illinois and the U.S.: a report from the Department of Agricultural and Consumer Economics (Technical report). University of Illinois.
  U.S. Government (2012). General Books LLC, reference series. Process design and economics for biochemical conversion of lignocellulosic biomass to ethanol: dilute-acid pretreatment and enzymatic hydrolysis of corn stover. ISBN-13:978-1234454555.
  Venema, H. D., & Calamai, P. H. (2003). Bioenergy systems planning using location-allocation and landscapes ecology design principles. Annals of Operations Research, 123, 241–264. CrossRef
  Walls, W. D., Rusco, F., & Kendix, M. (2011). Biofuels policy and the US market for motor fuels: empirical analysis of ethanol splashing. Energy Policy, 39(7), 3999–4006. CrossRef
  Westhoff, P., Baur, R., Stephens, D. L., & Meyers, W. H. (1990). FAPRI U.S. crops model documentation (Technical Report 90-TR 17). Center for Agricultural and Rural Development, Iowa State University.
  Wight, S. J. (1996). A path-following interior-point algorithm for linear and quadratic problems. Annals of Operations Research, 62, 103–130. CrossRef
  You, F., Tao, L., Graziano, D. J., & Snyder, S. W. (2012). Optimal design of sustainable cellulosic biofuel supply chains: multiobjective optimization coupled with life cycle assessment and input–output analysis. AIChE Journal, 58(4), 1157–1180. CrossRef
  Zhang, L., & Hu, G. (2013, in press). Supply chain design and operational planning models for biomass to drop-in fuel production. Biomass and Bioenergy.
  
• 作者单位：Leilei Zhang (1)
  Guping Hu (1)
  Lizhi Wang (2)
  Yihsu Chen (3) (4)
  
  1. Industrial and Manufacturing Systems Engineering (IMSE), Iowa State University, 3014 Black Engineering, Ames, IA, 50011, USA
  2. Industrial and Manufacturing Systems Engineering (IMSE), Iowa State University, 3016 Black Engineering, Ames, IA, 50011, USA
  3. School of Social Sciences, Humanities and Arts, School of Engineering, Sierra Nevada Research Institute, University of California, Merced, USA
  4. The National Graduate Institute for Policy Studies (GRIPS), 7-22-1 Roppongi, Minato-ku, Tokyo, 106-8677, Japan
  
• 刊物类别：Business and Economics
• 刊物主题：Economics
  Operation Research and Decision Theory
  Combinatorics
  Theory of Computation
  
• 出版者：Springer Netherlands
• ISSN：1572-9338

文摘

Although the biofuel market remains at its early stage, it is expected to play an important role in climate policy in the future in the transportation sector. In this paper, we develop a bottom-up equilibrium model to study the supply chain of the biofuel market, explicitly formulating the interactions among farmers, biofuel producers, blenders, and consumers. The model is built on optimization problems faced by each entity and considers decisions associated with farmers’ land allocation, biomass transportation, biofuel production, and biofuel blending. As such, the model is capable of and appropriate for policy analysis related to interactions among multiple stakeholders. For example, the model can be used to analyze the impacts of biofuel policies on market outcomes, pass-through of taxes or subsidies, and distribution of consumers’ or producers’ surplus. The equilibrium model can also serve as an analytical tool to study the price impact of biomass, biofuel, and Renewable Identification Numbers (RINs) for biofuels. We demonstrate the model by applying it to a case study of Iowa. We specifically focus on the effects of market structure, i.e., points-of-implementation on subsidies on market outcomes. The results indicate that some entities can benefit greatly at the expense of others when they possess market power. Government oversight is therefore needed to safeguard the development of the sector.