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Multi-objective optimization of a biodiesel production process using process simulation

Economic and environmental aspects have been contributing to the gradual reduction of fossil fuels and to the growth of research on renewable energy, such as biodiesel, that has been gaining representation in the national and world market. In this scenario, the optimal operation of continuous biodie...

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Bibliographic Details
Published in:Journal of cleaner production 2020-10, Vol.270, p.122322, Article 122322
Main Authors: Gonçalves, Paula Ciribeli, Monteiro, Luciane Pimentel Costa, Santos, Lizandro de Sousa
Format: Article
Language:English
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Summary:Economic and environmental aspects have been contributing to the gradual reduction of fossil fuels and to the growth of research on renewable energy, such as biodiesel, that has been gaining representation in the national and world market. In this scenario, the optimal operation of continuous biodiesel processes may be an attractive tool to optimize some economic/environmental indicators, e.g., biodiesel production and purity, residues, and energy consumption. To develop a multicriteria optimization, a multi-objective methodology must be performed in which two or more functions are used as performance measurements. In this sense, the present work aims to propose the multi-objective optimization (MOO) of a continuous biodiesel plant. The purpose of the optimization was to maximize the biodiesel flow rate and minimize the energy rate consumption subject to a minimum biodiesel purity. An additional study was performed to quantify a set of potential environmental impacts (PEIs) of the optimized scenarios. The results of MOO showed that there is a set of optimal solutions depending on the weights assigned to each individual objective function. It was verified that the reactor temperature has a significant influence on biodiesel production, but less influence on the energy rate consumption. The suggested methodology could serve as a basis for future work addressing multi-criteria optimization, where the optimal operating point solution depends on the decision-maker. These results suggest that the PEIs can serve as environmental constraints for the optimization problem, allowing the decision maker to evaluate these criteria for choosing the optimum operating point. •The simulation of a continuous plant for biodiesel production from soybean oil was carried out.•The weighted sum method was used for multi-objective optimization to maximize production and minimize energy use.•The multi-objective optimization allowed the construction of the Pareto curve encompassing the set of optimal points.•The environmental analysis was carried out to assess the environmental impacts for different optimal points.
ISSN:0959-6526
1879-1786
DOI:10.1016/j.jclepro.2020.122322