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Risk-conscious optimization model to support bioenergy investments in the Brazilian sugarcane industry

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  • Mutran, Victoria M.
  • Ribeiro, Celma O.
  • Nascimento, Claudio A.O.
  • Chachuat, Benoît
Abstract
The past decades have seen a diversification of the sugarcane industry with the emergence of new technology to produce bioenergy from by-product and waste process streams. Given Brazil’s ambitious goal of reducing green-house gas emissions by over 40% below 2005 levels by 2030, it is of paramount importance to develop reliable decision-making systems in order to stimulate investment in these low-carbon technologies. This paper seeks to develop a more accurate optimization model to inform risk-conscious investment decisions for bioenergy generation capacity in sugarcane mills. The main objective is for the model to enable a better understanding of how Brazilian government policies, such as the electricity price in the regulated market, may impact these investments, by taking into account the uncertainty in sugar, ethanol and spot electricity markets and the interdependency between production and investment decisions in terms of saleable product mix. The proposed methodology combines portfolio optimization theory with superstructure process modeling and it relies on simple surrogates derived from a detailed sugarcane plant simulator to retain computational tractability and enable scenario analysis. The case study of an existing sugarcane plant is used to demonstrate the methodology and illustrate how the model can assist decision-makers. In all of the scenarios assessed, the model recommends investment in extra bioelectricity capacity via the anaerobic digestion of vinasse but advises against investment in second-generation ethanol production via the hydrolysis of surplus bagasse. Furthermore, the decision to upgrade the cogeneration system with a condensation turbine is highly sensitive to the electricity price practiced in the regulated market, capacity constraints on the sugar-ethanol mix, and the accepted level of risk. Another key insight drawn from the case study is that recent market conditions have favored a production focused on the sugar business, making it challenging for policy-makers to create attractive scenarios for biofuels. Long-term electricity contracting appears to be the main hedging strategy for de-risking other products and investments in the sugarcane business, provided it is priced adequately.

Suggested Citation

  • Mutran, Victoria M. & Ribeiro, Celma O. & Nascimento, Claudio A.O. & Chachuat, Benoît, 2020. "Risk-conscious optimization model to support bioenergy investments in the Brazilian sugarcane industry," Applied Energy, Elsevier, vol. 258(C).
    • Handle: RePEc:eee:appene:v:258:y:2020:i:c:s0306261919316654
    DOI: 10.1016/j.apenergy.2019.113978
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    as
    1. Resul Cesur & Pinar Mine Gunes & Erdal Tekin & Aydogan Ulker, 2023. "Socialized Healthcare and Women’s Fertility Decisions," Journal of Human Resources, University of Wisconsin Press, vol. 58(3), pages 1028-1055.
    2. Rego, Erik Eduardo, 2013. "Reserve price: Lessons learned from Brazilian electricity procurement auctions," Energy Policy, Elsevier, vol. 60(C), pages 217-223.
    3. de Carvalho, Ariovaldo Lopes & Antunes, Carlos Henggeler & Freire, Fausto, 2016. "Economic-energy-environment analysis of prospective sugarcane bioethanol production in Brazil," Applied Energy, Elsevier, vol. 181(C), pages 514-526.
    4. Costa, Caliane Bastos Borba & Potrich, Erich & Cruz, Antonio José Gonçalves, 2016. "Multiobjective optimization of a sugarcane biorefinery involving process and environmental aspects," Renewable Energy, Elsevier, vol. 96(PB), pages 1142-1152.
    5. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    6. Pazuch, Felix Augusto & Nogueira, Carlos Eduardo Camargo & Souza, Samuel Nelson Melegari & Micuanski, Viviane Cavaler & Friedrich, Leandro & Lenz, Anderson Miguel, 2017. "Economic evaluation of the replacement of sugar cane bagasse by vinasse, as a source of energy in a power plant in the state of Paraná, Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 34-42.
    7. Cheng, Lingfeng & Anderson, C. Lindsay, 2016. "Financial sustainability for a lignocellulosic biorefinery under carbon constraints and price downside risk," Applied Energy, Elsevier, vol. 177(C), pages 98-107.
    8. Grisi, Edson F. & Yusta, Jose M. & Dufo-López, Rodolfo, 2012. "Opportunity costs for bioelectricity sales in Brazilian sucro-energetic industries," Applied Energy, Elsevier, vol. 92(C), pages 860-867.
    9. Kermani, Maziar & Wallerand, Anna S. & Kantor, Ivan D. & Maréchal, François, 2018. "Generic superstructure synthesis of organic Rankine cycles for waste heat recovery in industrial processes," Applied Energy, Elsevier, vol. 212(C), pages 1203-1225.
    10. Katharine Ricke & Laurent Drouet & Ken Caldeira & Massimo Tavoni, 2018. "Country-level social cost of carbon," Nature Climate Change, Nature, vol. 8(10), pages 895-900, October.
    11. Bechara, Rami & Gomez, Adrien & Saint-Antonin, Valérie & Schweitzer, Jean-Marc & Maréchal, François, 2016. "Methodology for the design and comparison of optimal production configurations of first and first and second generation ethanol with power," Applied Energy, Elsevier, vol. 184(C), pages 247-265.
    12. Carpio, Lucio Guido Tapia & Simone de Souza, Fábio, 2017. "Optimal allocation of sugarcane bagasse for producing bioelectricity and second generation ethanol in Brazil: Scenarios of cost reductions," Renewable Energy, Elsevier, vol. 111(C), pages 771-780.
    13. de Souza, Fabio Cavaliere & Legey, Luiz Fernando Loureiro, 2010. "Dynamics of risk management tools and auctions in the second phase of the Brazilian Electricity Market reform," Energy Policy, Elsevier, vol. 38(4), pages 1715-1733, April.
    14. Arnold, Uwe & Yildiz, Özgür, 2015. "Economic risk analysis of decentralized renewable energy infrastructures – A Monte Carlo Simulation approach," Renewable Energy, Elsevier, vol. 77(C), pages 227-239.
    15. Dias, Marina O.S. & Junqueira, Tassia L. & Cavalett, Otávio & Pavanello, Lucas G. & Cunha, Marcelo P. & Jesus, Charles D.F. & Maciel Filho, Rubens & Bonomi, Antonio, 2013. "Biorefineries for the production of first and second generation ethanol and electricity from sugarcane," Applied Energy, Elsevier, vol. 109(C), pages 72-78.
    16. Dantas, Guilherme A. & Legey, Luiz F.L. & Mazzone, Antonella, 2013. "Energy from sugarcane bagasse in Brazil: An assessment of the productivity and cost of different technological routes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 356-364.
    17. Khatiwada, Dilip & Leduc, Sylvain & Silveira, Semida & McCallum, Ian, 2016. "Optimizing ethanol and bioelectricity production in sugarcane biorefineries in Brazil," Renewable Energy, Elsevier, vol. 85(C), pages 371-386.
    18. Schnitkey, Gary, 2018. "Fertilizer Prices Higher for 2019 Crop," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 8, September.
    19. Moraes, Bruna S. & Junqueira, Tassia L. & Pavanello, Lucas G. & Cavalett, Otávio & Mantelatto, Paulo E. & Bonomi, Antonio & Zaiat, Marcelo, 2014. "Anaerobic digestion of vinasse from sugarcane biorefineries in Brazil from energy, environmental, and economic perspectives: Profit or expense?," Applied Energy, Elsevier, vol. 113(C), pages 825-835.
    20. Oliveira, Sydnei Marssal de & Ribeiro, Celma de Oliveira & Cicogna, Maria Paula Vieira, 2018. "Uncertainty effects on production mix and on hedging decisions: The case of Brazilian ethanol and sugar," Energy Economics, Elsevier, vol. 70(C), pages 516-524.
    21. David E. Bell, 1982. "Regret in Decision Making under Uncertainty," Operations Research, INFORMS, vol. 30(5), pages 961-981, October.
    22. Yokoyama, Ryohei & Tokunaga, Akira & Wakui, Tetsuya, 2018. "Robust optimal design of energy supply systems under uncertain energy demands based on a mixed-integer linear model," Energy, Elsevier, vol. 153(C), pages 159-169.
    23. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    24. de Moraes Dutenkefer, Raphael & de Oliveira Ribeiro, Celma & Morgado Mutran, Victoria & Eduardo Rego, Erik, 2018. "The insertion of biogas in the sugarcane mill product portfolio: A study using the robust optimization approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 729-740.
    25. Yılmaz, Sebnem & Selim, Hasan, 2013. "A review on the methods for biomass to energy conversion systems design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 420-430.
    26. Karmellos, M. & Georgiou, P.N. & Mavrotas, G., 2019. "A comparison of methods for the optimal design of Distributed Energy Systems under uncertainty," Energy, Elsevier, vol. 178(C), pages 318-333.
    27. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
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    Cited by:

    1. Fuess, L.T. & Cruz, R.B.C.M. & Zaiat, M. & Nascimento, C.A.O., 2021. "Diversifying the portfolio of sugarcane biorefineries: Anaerobic digestion as the core process for enhanced resource recovery," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    2. Munir Younes Soares & Dorel Soares Ramos & Margareth de Oliveira Pavan & Fabio A. Diuana, 2023. "Barriers to the Expansion of Sugarcane Bioelectricity in Brazilian Energy Transition," Energies, MDPI, vol. 16(2), pages 1-18, January.
    3. Elias, Andrew Milli & Longati, Andreza Aparecida & de Campos Giordano, Roberto & Furlan, Felipe Fernando, 2021. "Retro-techno-economic-environmental analysis improves the operation efficiency of 1G-2G bioethanol and bioelectricity facilities," Applied Energy, Elsevier, vol. 282(PA).
    4. Izanloo, Milad & Aslani, Alireza & Zahedi, Rahim, 2022. "Development of a Machine learning assessment method for renewable energy investment decision making," Applied Energy, Elsevier, vol. 327(C).

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