Assessing the production of first and second generation bioethanol from sugarcane through the integration of global optimization and process detailed modeling

Furlan, Felipe F.; Costa, Caliane Bastos Borba; Fonseca, Gabriel de Castro; Soares, Rafael de Pelegrini; Secchi, Argimiro Resende; Cruz, Antonio José Gonçalves; Giordano, Roberto de Campos

doi:10.1016/j.compchemeng.2012.04.002

Cited by 93 publications

(42 citation statements)

References 24 publications

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“…Vários trabalhos publicados em anos recentes implementam a simulação de destilarias de etanol de primeira ou segunda geração, como Dias et al (2012), Furlan et al (2012), Palacios-Bereche et al (2013). Todos esses trabalhos, no entanto, modelam o processo de fermentação alcoólica com base em modelos de conversão estequiométrica.…”

Section: Introductionunclassified

Modelagem E Simulação De Destilaria Autônoma No Simulador De Processos Emso

Fonseca¹,

Costa²,

Cruz³

2015

Anais Do XX Congresso Brasileiro De Engenharia Química

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RESUMO -Implementou-se no simulador de processos EMSO uma destilaria autônoma de etanol hidratado. Foram representadas as etapas de lavagem da cana, extração e tratamento do caldo, preparo do mosto, fermentação e destilação. Duas configurações foram avaliadas para a etapa de fermentação: operação contínua em estado estacionário (quatro reatores em série) e operação batelada alimentada em regime dinâmico (seis reatores em paralelo). Em ambos os casos, os fermentadores foram modelados usando-se a cinética de Ghose e Tyagi e considerando-se uma alimentação de 500 t/h de cana de açúcar contendo 13% em massa de sacarose. Após a etapa de tratamento obteve-se uma corrente de 330 t/h de mosto contendo 18,7% em massa de sacarose, que resultou em ambos os casos em produções próximas a 30 t/h de etanol 93,5% em massa.

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Section: Introductionunclassified

Modelagem E Simulação De Destilaria Autônoma No Simulador De Processos Emso

Fonseca¹,

Costa²,

Cruz³

2015

Anais Do XX Congresso Brasileiro De Engenharia Química

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“…Table 9 shows the main parameters used in the simulations. A rigorous description of the main models used in this study can be found in Furlan et al [16]. The cogeneration system was also considered in the simulations.…”

Section: C5 Fermentationmentioning

confidence: 99%

Combined Biological and Chemical Pretreatment Method for Lignocellulosic Ethanol Production from Energy Cane

Gikonyo¹

2015

Sugarcane as Biofuel Feedstock

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Background: Sugarcane is the most efficient crop for production of (1G) ethanol. Additionally, sugarcane bagasse can be used to produce (2G) ethanol. However, the manufacture of 2G ethanol in large scale is not a consolidated process yet. Thus, a detailed economic analysis, based on consistent simulations of the process, is worthwhile. Moreover, both ethanol and electric energy markets have been extremely volatile in Brazil, which suggests that a flexible biorefinery, able to switch between 2G ethanol and electric energy production, could be an option to absorb fluctuations in relative prices. Simulations of three cases were run using the software EMSO: production of 1G ethanol + electric energy, of 1G + 2G ethanol and a flexible biorefinery. Bagasse for 2G ethanol was pretreated with a weak acid solution, followed by enzymatic hydrolysis, while 50% of sugarcane trash (mostly leaves) was used as surplus fuel. Results: With maximum diversion of bagasse to 2G ethanol (74% of the total), an increase of 25.8% in ethanol production (reaching 115.2 L/tonne of sugarcane) was achieved. An increase of 21.1% in the current ethanol price would be enough to make all three biorefineries economically viable (11.5% for the 1G + 2G dedicated biorefinery). For 2012 prices, the flexible biorefinery presented a lower Internal Rate of Return (IRR) than the 1G + 2G dedicated biorefinery. The impact of electric energy prices (auction and spot market) and of enzyme costs on the IRR was not as significant as it would be expected. Conclusions: For current market prices in Brazil, not even production of 1G bioethanol is economically feasible. However, the 1G + 2G dedicated biorefinery is closer to feasibility than the conventional 1G + electric energy industrial plant. Besides, the IRR of the 1G + 2G biorefinery is more sensitive with respect to the price of ethanol, and an increase of 11.5% in this value would be enough to achieve feasibility. The ability of the flexible biorefinery to take advantage of seasonal fluctuations does not make up for its higher investment cost, in the present scenario.

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“…Dias and others optimized the second-generation ethanol production [18], while other authors focused on obtaining the economical optima [19]. Here, the optimization of the η g was carried out with an algorithm based on the Pattern Search method [20,21].…”

Section: Numerical Optimizationmentioning

confidence: 99%

Challenges in Bioenergy Production from Sugarcane Mills in Developing Countries: A Case Study

2014

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Worldwide energy policies are moving towards a reduction of fossil fuels' share in the energy mix and to invest in renewable and green energy sources. Biomass is one of these, and it represents, in the form of sugarcane, a strategic source in Colombia, especially in the Valle del Cauca. In this region, the sugarcane industry is able to convert the energy content of the cane into different energy products, such as ethanol, electricity, and high-pressure steam, which are cogenerated via bagasse combustion. In this work, the case of a sucrose and ethanol production plant, which mills ten thousand tons of sugarcane per day, is considered. A tailor-made computational model was developed to assess the energy and material process balances in order to estimate the effect of different operating conditions on cogeneration boilers and turbines, and to optimize the overall process efficiency. The current situation was modeled with good precision from the developed model. Likewise, the concept of "Renewable Efficiency" was introduced to explain the degree of green power, which a process plant is able to produce. Consequently, new innovative solutions and process layouts were proposed in order to increase their renewable efficiency. With the new configurations, a convenient energy surplus of up to 33 MW can be reached, which could be sold in the national electricity grid, representing long-term interesting economic benefits for the company. OPEN ACCESSEnergies 2014, 7 5875

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Assessing the production of first and second generation bioethanol from sugarcane through the integration of global optimization and process detailed modeling

Cited by 93 publications

References 24 publications

Modelagem E Simulação De Destilaria Autônoma No Simulador De Processos Emso

Modelagem E Simulação De Destilaria Autônoma No Simulador De Processos Emso

Combined Biological and Chemical Pretreatment Method for Lignocellulosic Ethanol Production from Energy Cane

Challenges in Bioenergy Production from Sugarcane Mills in Developing Countries: A Case Study

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