Modeling and optimization of biodiesel production from microalgae in a batch reactor. (15th November 2020)

• Record Type: Journal Article
• Authors: Reza Talaghat, Mohammad; Mokhtari, Shahin; Saadat, Mohammad
• Is Part Of: Fuel. Volume 280(2020)
• Publication Date: 2020-11-15
• Subjects: Biodiesel -- Microalgae -- Modeling -- Optimization -- Enteromorphacompressa -- Scenedesmus; Fuel -- Periodicals; Coal -- Periodicals; Coal; Fuel; Periodicals; 662.6
• DOI: 10.1016/j.fuel.2020.118578
• Languages: English
• ISSNs: 0016-2361

Abstract

Highlights: The results of the model and the laboratory data are consistent. Prediction of biodiesel yield is affected by reaction rate constant function type. The efficiency of biodiesel production is more than 99% at optimal condition. Biodiesel yield is low when the reaction rate constant is only temperature dependent. The reaction rate constant is affected by the concentration of the catalyst. Abstract: In this research, biodiesel production from two types microalgae including Enteromorphacompressa, and Scenedesmus in the presence of acid catalyst and methanol in batch reactors was modeled. In this study, the reaction rate constants have been considered as different functions of both temperatures and catalyst concentrations to evaluate and compare the effect of these reaction rate constants on biodiesel production yield. Then the models were used to find the optimal conditions in order to maximize the biodiesel yield. In this regard, the kinetic parameters of models were calculated by using experimental data. Then, the effect of temperature, catalyst concentration, and methanol to oil ratio on the biodiesel yield were calculated. According to results, the models can accurately predict the effect of temperature, catalyst concentration, and methanol to oil ratio on the biodiesel yield. According to the results, there are direct relationship between biodiesel yield and the effective parameters. Results showed that the efficiency of biodiesel production more than 99% can be achieved at optimal condition.