Opportunity costs for bioelectricity sales in Brazilian sucro-energetic industries

Grisi, Edson F.; Yusta, José M.; Dufo-López, Rodolfo

doi:10.1016/j.apenergy.2011.08.045

Cited by 23 publications

(15 citation statements)

References 32 publications

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“…Each investment cost is reported in terms of an EAC. Since the production cost of prospective technologies may be unknown or unreliable, we assume as a first approximation that the production costs of ethanol and electricity are the same for all the possible technological routes: cost for 1G or 2G ethanol and sugar productions from [65]; and cost of electricity produced by basic or improved cogeneration system or vinasse digester from [37]. We consider a confidence level of β = 90% to calculate the risk in the portfolio optimization model (24) throughout.…”

Section: Resultsmentioning

confidence: 99%

“…Several recent studies have focused on developing optimization models in response to this need. Grisi et al [37] developed an optimization model that decides the product mix in order to maximize profit in a sugarcane mill. They concluded that the electricity prices practiced in Brazil's free and regulated markets are not sufficiently attractive to justify surplus electricity generation.…”

Section: Need For Reliable Decision-making In the Brazilian Sugarcanementioning

confidence: 99%

“…These production decisions are furthermore concomitant with investment decisions, since introducing a new energy recovery process will often modify a plant's overall energy balance on an annual basis [9,36]. Finally, a number of optimization-based assessments allowed for a variable product mix [10,[37][38][39]], yet without accounting for the risk incurred by price variability on the decision to invest in new technologies to increase power production.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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 greenhouse 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.

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Section: Resultsmentioning

confidence: 99%

Section: Need For Reliable Decision-making In the Brazilian Sugarcanementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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“…Biomass facilitates the combination of the commercial production of electricity and other services or products (Grisi et al, 2012). Fig.…”

Section: Discussion About Different Projects Of Capacity Additionmentioning

confidence: 99%

Sustainability deterioration of electricity generation in Brazil

2015

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“…In this work, we assumed that the volume of bagasse produced is 250 kg per ton of processed sugarcane and the percentage of straw produced (dry basis) is 14% per ton of sugarcane harvested [7]. The bioelectricity produced using the LM is 0.19 MWh per tonne of sugarcane [20], assuming that only 32% of LM is used for bioelectricity production. Then, the bioelectricity productivity is 0.59 MWh per ton of ML.…”

Section: Methods and Datamentioning

confidence: 99%

Competition between Second-Generation Ethanol and Bioelectricity using the Residual Biomass of Sugarcane: Effects of Uncertainty on the Production Mix

Carpio

Souza

2019

Molecules

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Several economies around the world are using second-generation (2G) ethanol produced from agricultural residues, like sugarcane straw and bagasse, as a sustainable solution to replace petroleum products. Since first-generation (1G) ethanol uses the sugars of sugarcane, an integrated 1G–2G production would enable the production of more ethanol from the same amount of sugarcane without leading to increased use of arable land. The ethanol production process is complex, involving different high-energy consumption operations such as evaporation and distillation. The economic competitiveness of this process depends heavily on the amount of thermal and electrical energy produced using sugarcane straw and bagasse as input. Thus, the objective of this study was to use the mean-variance methodology to determine the optimal allocation of residual sugarcane biomass between 2G ethanol and bioelectricity productions, with simultaneous objectives of maximizing the return and minimizing the risk for investors of this sector. In this paper, four scenarios are analyzed. The first one is the base scenario that represents the current state of production costs and investments. scenarios 2, 3, and 4 considered four cuts of 10%, 20%, and 40% in the production cost of ethanol 2G, respectively. The results show the optimum biomass allocations and the growth rates of returns as a function of risk growth. It can be concluded that from scenario 4, the production of 2G ethanol becomes financially advantageous for the investor, presenting greater returns with smaller risks.

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Opportunity costs for bioelectricity sales in Brazilian sucro-energetic industries

Cited by 23 publications

References 32 publications

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

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

Sustainability deterioration of electricity generation in Brazil

Competition between Second-Generation Ethanol and Bioelectricity using the Residual Biomass of Sugarcane: Effects of Uncertainty on the Production Mix

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