Impact of government policies on Sustainable Petroleum Supply Chain (SPSC): A case study – Part II (The State of Nebraska)

• Autorzy: Ghahremanlou Davoud , Kubiak Wieslaw

Identyfikatory

DOI

10.7494/dmms.2020.14.1.3649

• 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.

Słowa kluczowe

EN

sustainable petroleum supply chain; two-stage stochastic programming; government policies

PL

zrównoważony łańcuch dostaw ropy naftowej; programowanie stochastyczne dwuetapowe; polityka rządu

• Wydawca: AGH University of Science and Technology Press
• Czasopismo: Decision Making in Manufacturing and Services
• Rocznik: 2020
• Tom: Vol. 14, no. 1
• Strony: 57--80
• Opis fizyczny: Bibliogr. 46 poz., tab., wykr.

Twórcy

autor

Ghahremanlou Davoud

• Faculty of Business Administration, Memorial University of Newfoundland, St. John’s, NL, Canada

• https://orcid.org/0000-0001-5186-8035

autor

Kubiak Wieslaw

• Faculty of Business Administration, Memorial University of Newfoundland, St. John’s, NL, Canada

• https://orcid.org/0000-0002-3181-3042

Bibliografia

• [1] AAA Gas Prices, 2017. National average gas prices. https://gasprices.aaa.com/?state=NE%20on%204/21/2017 [accessed on 04/21/2017].
• [2] CAMEO Chemicals, 2010. Ethanol. https://cameochemicals.noaa.gov/chemical/667 [accessedon 05/12/2017].
• [3] 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.
• [4] Chen, C.-W. and Fan, Y., 2012. Bioethanol supply chain system planning under supply anddemand uncertainties.Transportation Research Part E: Logistics and TransportationReview, 48(1), pp. 150–164.
• [5] DiNapoli, J. and Renshaw, J., 2018. Exclusive: Philadelphia Energy Solutions to filefor bankruptcy. https://www.reuters.com/article/us-philadelphiaenergysolutions-bankruptc/exclusive-philadelphia-energy-solutions-to-file-for-bankruptcy-memo-idUSKBN1FA18P [accessed on 01/21/2018].
• [6] Duffield, J. A., Xiarchos, I. M. and Halbrock, S. A., 2008. Ethanol policy: past, present, andfuture. South Dakota Law Review, 53, 425. E85 Prices, 2016.
• [7] E85 prices. https://e85prices.com/nebraska.html [accessed on 04/24/2017].
• [8] Gebreslassie, B. H., Yao, Y. and You, F., 2012. Design under uncertainty of hydrocarbonbiorefinery supply chains: multiobjective stochastic programming models, decompositionalgorithm, and a comparison between cvar and downside risk. AIChE Journal, 58(7),pp. 2155–2179.
• [9] Ghahremanlou, D. and W. Kubiak (2020). Impact of government policies on sustainablepetroleum supply chain (SPSC): A case study – Part I (models). Decision Making in Manufacturing and Services, 14(1).
• [10] Graham, R. L., Nelson, R., Sheehan, J., Perlack, R. and Wright, L. L., 2007. Current andpotential US corn stover supplies.Agronomy Journal, 99(1), pp. 1–11.
• [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.
• [12] Gurobi Optimizer LLC., 2008. Gurobi Optimizer Version 7.0. Houston, Texas: Gurobi Opti-mization, Inc. [accessed on 03/18/2018].
• [13] Huang, K., 2005.Multi-stage stochastic programming models in production planning. Ph. D.thesis, Georgia Institute of Technology.
• [14] 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 biochemicalconversion of lignocellulosic biomass to ethanol: dilute-acid pretreatment and enzymatichydrolysis of corn stover. Technical report, National Renewable Energy Laboratory (NREL), Golden, CO.
• [15] Kazemzadeh, N. and Hu, G., 2015. Evaluation of the impacts of governmental policies onthe biofuels supply chain design under uncertainty.International Journal of SustainableEconomy, 7(3), pp. 203–219.
• [16] Kim, S. and Dale, B. E., 2015. Potential job creation in the cellulosic biofuel industry: theeffect of feedstock price. Biofuels, Bioproducts and Biorefining, 9(6), pp. 639–647.
• [17] 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.
• [18] Li, Q. and Hu, G., 2014. Supply chain design under uncertainty for advanced biofuel productionbased on bio-oil gasification.Energy, 74, pp. 576–584.
• [19] Li, Y., Brown, T. and Hu, G., 2014. Optimization model for a thermochemical biofuels supplynetwork design. Journal of Energy Engineering, 140(4), 04014004.
• [20] Li, Y., Tseng, C.-L. and Hu, G., 2015. Is now a good time for Iowa to invest in cellulosicbiofuels? a real options approach considering construction lead times.InternationalJournal of Production Economics, 167, pp. 97–107.
• [21] Lux Research Inc., 2016. Cellulosic ethanol plants. http://www.luxresearchinc.com/sites/default/files/AF_KTA_1_16.pdf [accessed on 06/09/2016].
• [21] Nebraska Department of Revenue, 2017. Nebraska’s gasoline consumption. http://www.neo.ne.gov/statshtml/37a.html [accessed on 06/17/2017].
• [22] Perlack, R. D., Eaton, L. M., Jr., A. F. T. and Langholtz, M. H., 2011. U.S. billion-tonupdate: Biomass supply for a bioenergy and bioproducts industry. Technical report, U.S. Department of Energy.
• [23] Python Software Foundation, 2001. Welcome to Python.org. https://www.python.org/. (Accessed on 06/18/2018).
• [24] Renewable Fuels Association, 2018. Ethanol production capacity by state. http://www.neo.ne.gov/programs/stats/inf/121.htm [accessed on 03/21/2017].
• [25] Searcy, E., Flynn, P., Ghafoori, E. and Kumar, A., 2007. The relative cost of biomass energytransport. Applied Biochemistry and Biotechnology, 137, pp 639–652.
• [26] Shah, A., 2013. Techno-economic analysis and life cycle assessment of the corn stover biomassfeedstock supply chain system for a Midwest-based first-generation cellulosic biorefinery.Ph. D. thesis, Iowa State University.
• [27] Simeone, C., 2018. Philadelphia Energy Solutions bankruptcy basics. https://kleinmanenergy.upenn.edu/blog/2018/02/02/part-1-philadelphia-energy-solutions-bankruptcy-basics [accessed on 02/05/2018].
• [28] Stein,K.,2018. An entirely predictable bankruptcy. https://www.instituteforenergyresearch.org/renewable/entirely-predictable-bankruptcy/[accessed on 01/23/2018].
• [29] The Economist, 2016. Automation and anxiety – the impact on jobs. https://www.economist.com/special-report/2016/06/23/automation-and-anxiety [accessed on05/12/2017].
• [30] Tong, K., Gong, J., Yue, D. and You, F., 2013. Stochastic programming approach to optimaldesign and operations of integrated hydrocarbon biofuel and petroleum supply chains.ACS Sustainable Chemistry & Engineering, 2(1), pp. 49–61.
• [31] Tsanova, T., 2016. Raizen makes cheapest cellulosic ethanol, feedstock is key–study. https://renewablesnow.com/news/raizen-makes-cheapest-cellulosic-ethanol-feedstock-is%5C%20-key-study-514409/ [accessed on 06/05/2016].
• [32] U.S. Department of Agriculture, 2012. USDA/NASS quickstats ad-hoc query tool. https://quickstats.nass.usda.gov/ [accessed on 12/27/2016].
• [33] 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].
• [34] U.S. Environmental Protection Agency, 1980. Bulk gasoline terminals – background informa-tion for proposed standards [accessed on 08/15/2017].
• [35] U.S. Environmental Protection Agency, 2016. Notice of cellulosic waiver credit price calcula-tion for 2016. https://www.epa.gov/renewable-fuel-standard-program/notice-cellulosic-waiver-credit-price-calculation-2016 [accessed on 06/25/2017].
• [36] U.S. Environmental Protection Agency, 2017a. Final Renewable Fuel Standardsfor 2014, 2015 and 2016, and the biomass-based diesel volume for 2017.https://www.epa.gov/renewable-fuel-standard-program/final-renewable-fuel-standards-2014-2015-and-2016-and-biomass-based [accessed on 07/07/2017].
• [37] U.S. Environmental Protection Agency, 2017b. Overview for Renewable Fuel Standard– Renewable Fuel Standard program, https://www.epa.gov/renewable-fuel-standard-program/overview-renewable-fuel-standard [accessed on June 17, 2017].
• [38] University of Nebraska, 2016. Nebraska crop reports - 2016. https://cropwatch.unl.edu/2016/nebraska-crop-reports-2016 [accessed on 04/27/2017].
• [39] Vimmerstedt, L.J., Bush, B. and Peterson, S., 2012. Ethanol distribution, dispensing, anduse: Analysis of a portion of the biomass-to-biofuels supply chain using system dynamics.PloS one, 7(5), p.e35082.
• [40] Wight Hat Ltd., 2003a. Metric conversion charts and calculators. https://www.metric-conversions.org/weight/metric-tons-to-pounds.htm/#conversionTable?val=1 [accessedon 05/12/2017].
• [41] Wight Hat Ltd., 2003b. US gallons (liquid) to liters conversion. https://www.metric-conversions.org/volume/us-liquid-gallons-to-liters.htm [accessed on 04/02/2017].
• [42] Wikimedia Foundation Inc., 2017. Gasoline. https://en.wikipedia.org/wiki/Gasoline [accessedon 05/12/2017].
• [43] Wilhelm, W. W., Johnson, J. M., Karlen, D. L. and Lightle, D. T., 2007. Corn stover tosustain soil organic carbon further constrains biomass supply. Agronomy Journal, 99(6),pp. 1665–1667.
• [44] Wisner, R., 2009. Corn, ethanol and crude oil prices relationships. https://www.agmrc.org/renewable-energy/ethanol/corn-ethanol-and-crude-oil-prices-relationships-implications-for-the-biofuels-industry [accessed on 05/12/2017].
• [45] Wright, M. and Brown, R. C., 2007. Establishing the optimal sizes of different kinds ofbiorefineries.Biofuels, Bioproducts and Biorefining, 1(3), pp. 191–200.
• [46] Zhang, L. and Hu, G., 2013. Supply chain design and operational planning models for biomassto drop-in fuel production.Biomass and Bioenergy, 58, pp. 238–250.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021)