Impact of Government Policies on Sustainable Petroleum Supply Chain (SPSC): A Case Study - Part II (The State of Nebraska)

• Autorzy: Davoud Ghahremanlou , Wiesław Kubiak
• Języki publikacji: EN

Abstrakty

EN

The accompanying part I (Ghahremanlou and Kubiak 2020) developed the Lean Model (LM), a two-stage stochastic programming model which incorporates Renewable Fuel Standard 2 (RFS2), Tax Credits, Tariffs, and Blend Wall (BW), to study the policy impact on the Sustainable Petroleum Supply Chain (SPSC) using cellulosic ethanol. The model enables us to study the impact by running computational experiments more efficiently and consequently by arriving at robust managerial insights much faster. In this paper, we present a case study of the policy impact on the SPSC in the State of Nebraska using the model. The case study uses available real-life data. The study shows that increasing RFS2 does not impact the amount of ethanol blended with gasoline but it might lead to bankruptcy of the refineries. We recommend that the government consider increasing the BW because of its positive economic, environmental and social impacts. For the same reason, we recommend that the tax credit for blending the US produced ethanol with gasoline be at least 0:189 $/gal and the tariff for imported ethanol be at least 1:501 $/gal. These also make the State independent from foreign ethanol thereby enhancing its energy security. Finally, the change in policy impacts the SPSC itself, most importantly it influences the strategic decisions, however setting up a bio-refinery at York county and a blending site at Douglas county emerge as the most robust location decisions against the policy change in the study. (original abstract)

Słowa kluczowe

EN

Petroleum industry; Oil; Sustainable supply chain; Government policy; Stochastic programming

PL

Przemysł naftowy; Ropa naftowa; Zrównoważony łańcuch dostaw; Polityka rządu; Programowanie stochastyczne

• Czasopismo: Decision Making in Manufacturing and Services
• Rocznik: 2020
• Tom: 14
• Numer: nr 1
• Strony: 57--80

Twórcy

autor

Davoud Ghahremanlou

• Memorial University of Newfoundland, Canada

autor

Wiesław Kubiak

• Memorial University of Newfoundland, Canada

Bibliografia

• AAA Gas Prices, 2017. National average gas prices. https://gasprices.aaa.com/?state=NE on 4/21/2017 [accessed on 04/21/2017].
• CAMEO Chemicals, 2010. Ethanol. https://cameochemicals.noaa.gov/chemical/667 [accessed on 05/12/2017].
• Carneiro, M. C., Ribas, G. P. and Hamacher, S., 2010. Risk management in the oil supply chain: a CVaR approach. Industrial & Engineering Chemistry Research, 49(7), pp. 3286-3294.
• Chen, C.-W. and Fan, Y., 2012. Bioethanol supply chain system planning under supply and demand uncertainties. Transportation Research Part E: Logistics and Transportation Review, 48(1), pp. 150-164.
• DiNapoli, J. and Renshaw, J., 2018. Exclusive: Philadelphia Energy Solutions to file for bankruptcy. https://www.reuters.com/article/us-philadelphiaenergysolutionsbankruptc/exclusive-philadelphia-energy-solutions-to-file-for-bankruptcy-memoidUSKBN1FA18P [accessed on 01/21/2018].
• Duffield, J. A., Xiarchos, I. M. and Halbrock, S. A., 2008. Ethanol policy: past, present, and future. South Dakota Law Review, 53, 425.
• E85 Prices, 2016. E85 prices. https://e85prices.com/nebraska.html [accessed on 04/24/2017].
• Gebreslassie, B. H., Yao, Y. and 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), pp. 2155-2179.
• Ghahremanlou, D. and W. Kubiak (2020). Impact of government policies on sustainable petroleum supply chain (SPSC): A case study - Part I (models). Decision Making in Manufacturing and Services, 14(1).
• Graham, R. L., Nelson, R., Sheehan, J., Perlack, R. and Wright, L. L., 2007. Current and potential US corn stover supplies. Agronomy Journal, 99(1), pp. 1-11.
• Gupta, A. and Verma, J. P., 2015. Sustainable bio-ethanol production from agro-residues: a review. Renewable and Sustainable Energy Reviews, 41, pp. 550-567.
• Gurobi Optimizer LLC., 2008. Gurobi Optimizer Version 7.0. Houston, Texas: Gurobi Optimization, Inc. [accessed on 03/18/2018].
• Huang, K., 2005. Multi-stage stochastic programming models in production planning. Ph. D. thesis, Georgia Institute of Technology.
• Humbird, D., Davis, R., Tao, L., Kinchin, C., Hsu, D., Aden, A., Schoen, P., Lukas, J., Olthof, B., Worley, M. et al., 2011. Process design and economics for biochemical conversion of lignocellulosic biomass to ethanol: dilute-acid pretreatment and enzymatic hydrolysis of corn stover. Technical report, National Renewable Energy Laboratory (NREL), Golden, CO.
• Kazemzadeh, N. and Hu, G., 2015. Evaluation of the impacts of governmental policies on the biofuels supply chain design under uncertainty. International Journal of Sustainable Economy, 7(3), pp. 203-219.
• Kim, S. and Dale, B. E., 2015. Potential job creation in the cellulosic biofuel industry: the effect of feedstock price. Biofuels, Bioproducts and Biorefining, 9(6), pp. ]639-647.
• Klein-Marcuschamer, D., Oleskowicz-Popiel, P., Simmons, B. A. and Blanch, H. W., 2010. Technoeconomic analysis of biofuels: A wiki-based platform for lignocellulosic biorefineries. Biomass and Bioenergy, 34(12), pp. 1914-1921. Current and Potential Capabilities of Wood Production Systems in the Southeastern U.S.
• Li, Q. and Hu, G., 2014. Supply chain design under uncertainty for advanced biofuel production based on bio-oil gasification. Energy, 74, pp. 576-584.
• Li, Y., Brown, T. and Hu, G., 2014. Optimization model for a thermochemical biofuels supply network design. Journal of Energy Engineering, 140(4), 04014004.
• Li, Y., Tseng, C.-L. and Hu, G., 2015. Is now a good time for Iowa to invest in cellulosic biofuels? a real options approach considering construction lead times. International Journal of Production Economics, 167, pp. 97-107.
• Lux Research Inc., 2016. Cellulosic ethanol plants. http://www.luxresearchinc.com/sites/default/files/AF_KTA_1_16.pdf [accessed on 06/09/2016].
• Nebraska Department of Revenue, 2017. Nebraska's gasoline consumption. http://www.neo.ne.gov/statshtml/37a.html [accessed on 06/17/2017].
• Perlack, R. D., Eaton, L. M., Jr., A. F. T. and Langholtz, M. H., 2011. U.S. billion-ton update: Biomass supply for a bioenergy and bioproducts industry. Technical report, U.S. Department of Energy.
• Python Software Foundation, 2001. Welcome to Python.org. https://www.python.org/. (Accessed on 06/18/2018).
• Renewable Fuels Association, 2018. Ethanol production capacity by state. http://www.neo.ne.gov/programs/stats/inf/121.htm [accessed on 03/21/2017].
• Searcy, E., Flynn, P., Ghafoori, E. and Kumar, A., 2007. The relative cost of biomass Energy transport. Applied Biochemistry and Biotechnology, 137, pp 639-652.
• Shah, A., 2013. Techno-economic analysis and life cycle assessment of the corn stover biomass feedstock supply chain system for a Midwest-based first-generation cellulosic biorefinery. Ph. D. thesis, Iowa State University.
• Simeone, C., 2018. Philadelphia Energy Solutions bankruptcy basics. https: //kleinmanenergy.upenn.edu/blog/2018/02/02/part-1-philadelphia-energy-solutionsbankruptcy-basics [accessed on 02/05/2018].
• Stein, K., 2018. An entirely predictable bankruptcy. https://www.instituteforenergyresearch.org/renewable/entirely-predictable-bankruptcy/ [accessed on 01/23/2018].
• The Economist, 2016. Automation and anxiety - the impact on jobs. https://www.economist.com/special-report/2016/06/23/automation-and-anxiety [accessed on 05/12/2017].
• Tong, K., Gong, J., Yue, D. and You, F., 2013. Stochastic programming approach to optimal design and operations of integrated hydrocarbon biofuel and petroleum supply chains. ACS Sustainable Chemistry & Engineering, 2(1), pp. 49-61.
• Tsanova, T., 2016. Raizen makes cheapest cellulosic ethanol, feedstock is key - study. https://renewablesnow.com/news/raizen-makes-cheapest-cellulosic-ethanolfeedstock-is -key-study-514409/ [accessed on 06/05/2016].
• U.S. Department of Agriculture, 2012. USDA/NASS quickstats ad-hoc query tool. https: //quickstats.nass.usda.gov/ [accessed on 12/27/2016].
• U.S. Energy Information Administration, 2017. Petroleum & other liquids. https://www.eia.gov/dnav/pet/pet_pri_gnd_dcus_nus_a.htm [accessed on 05/08/2017].
• U.S. Environmental Protection Agency, 1980. Bulk gasoline terminals - background information for proposed standards [accessed on 08/15/2017].
• U.S. Environmental Protection Agency, 2016. Notice of cellulosic waiver credit price calculation for 2016. https://www.epa.gov/renewable-fuel-standard-program/notice-cellulosicwaiver-credit-price-calculation-2016 [accessed on 06/25/2017].
• U.S. Environmental Protection Agency, 2017a. Final Renewable Fuel Standards for 2014, 2015 and 2016, and the biomass-based diesel volume for 2017. https://www.epa.gov/renewable-fuel-standard-program/final-renewable-fuelstandards-2014-2015-and-2016-and-biomass-based [accessed on 07/07/2017].
• U.S. Environmental Protection Agency, 2017b. Overview for Renewable Fuel Standard - Renewable Fuel Standard program, https://www.epa.gov/renewable-fuel-standardprogram/overview-renewable-fuel-standard [accessed on June 17, 2017].
• University of Nebraska, 2016. Nebraska crop reports - 2016. https://cropwatch.unl.edu/2016/nebraska-crop-reports-2016 [accessed on 04/27/2017].
• Vimmerstedt, L.J., Bush, B. and Peterson, S., 2012. Ethanol distribution, dispensing, and use: Analysis of a portion of the biomass-to-biofuels supply chain using system dynamics. PloS one, 7(5), p.e35082.
• Wight Hat Ltd., 2003a. Metric conversion charts and calculators. https://www.metricconversions.org/weight/metric-tons-to-pounds.htm/

Identyfikatory

DOI

10.7494/dmms.2020.14.1.3649