Optimization of Microalgae-to-Biodiesel Production Process Using a Metaheuristic Technique
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Copyright 2019 American Chemical Society. This paper presents an effective computational scheme using metaheuristic techniques for the optimization of an integrated biodiesel production process from microalgae Chlorella vulgaris. Ten decision variables were optimized including temperatures and pressures of the five process reactors and the number of stages and feed stage of the three considered distillation columns. The model is a multiobjective formulation involving economic and environmental objectives. The economic objective function is aimed at maximizing the total annual income. The objective function associated with the environmental impact is to minimize the produced greenhouse gases. Process data were obtained from the simulation software Aspen Plus. Models for determining the properties for new substances missing in the database, such as fatty acids present in the microalgae, were considered to improve the predictions of the raw material properties. The free software Symyx Draw was used for the creation of all the components that were not in the Aspen Plus database. The optimization tool that was used in this paper consists of a stochastic algorithm called I-MODE (improved multiobjective differential evolution). Likewise, a linking subroutine based on COM (component object module) technology and developed in Excel-Visual Basic for Applications scripts was implemented to control the Aspen Plus software for various sets of decision variables. The results offer attractive options for both economic and environmental benefits.