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Bioenergy production from sugarcane bagasse with carbon capture and storage: Surrogate models for techno-economic decisions

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  • Wiesberg, Igor Lapenda
  • de Medeiros, José Luiz
  • Paes de Mello, Raphael V.
  • Santos Maia, Jeiveison G.S.
  • Bastos, João Bruno V.
  • Araújo, Ofélia de Queiroz F.

Abstract

The use of biomass in cogeneration is a sustainable alternative of energy production, allowing replacing fossil fuels and reduction of greenhouse gas emissions. This work discloses an integrated process analyzer framework comprising surrogate models for estimation of fixed capital investment, revenues, costs of manufacturing as well as several performance responses of cogeneration units of sugarcane-biorefineries burning bagasse, with/without post-combustion carbon capture and storage. A restricted number of inputs are required, namely bagasse availability and heat requirements of the sugarcane-biorefinery. To develop the investment models, a 3³ factorial computational-experimental design was performed, where AspenOne Portfolio was used in each run to simulate the process allowing estimating the fixed capital investment. Surrogate models were adjusted to fit capital estimates, resulting in 1.9% and 1.3% mean errors for the cogeneration and the post-combustion capture steps, respectively. Capture costs were estimated by analytical equations using the investment values and other estimates from the process analyzer framework, reaching 262 USD/t, but can be as low as 17.2 USD/t if limitations from the agricultural sector are disregarded; namely seasonality, operating time and capacity. The developed framework can assist in sugarcane-biorefinery investment decision making regarding bioenergy with carbon capture and storage or to develop carbon mitigation policies.

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  • Wiesberg, Igor Lapenda & de Medeiros, José Luiz & Paes de Mello, Raphael V. & Santos Maia, Jeiveison G.S. & Bastos, João Bruno V. & Araújo, Ofélia de Queiroz F., 2021. "Bioenergy production from sugarcane bagasse with carbon capture and storage: Surrogate models for techno-economic decisions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    • Handle: RePEc:eee:rensus:v:150:y:2021:i:c:s136403212100767x
    DOI: 10.1016/j.rser.2021.111486
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