Fuzzy-modeling with particle swarm optimization for enhancing the production of biodiesel from microalga

Biodiesel is one of the promising energy sources that could replace petroleum oil in the near future. Microalgae is occupying a distinguished position among the promising sources for biodiesel production. Enhancement of the lipids production during the pretreatment is a key factor for the biodiesel production. High-pressure homogenizer is a better pretreatment procedure to enhance the lipid extraction from microalgae. In this research, a robust model of biodiesel system using fuzzy logic is built based on the experimental data for biodiesel system. Then, Particle Swarm Optimization (PSO)
optimizer is applied for determining the best operating parameters of biodiesel system. The decision variables used in the optimization process are; pressure, number of passes, and reaction time that maximizes the percentage of recovery lipids of biodiesel. A comparison study was carried out between the optimized results thought PSO algorithm and those obtained by the experimental results and the optimized results through the Response Surface Methodology (RMS). Results demonstrated that using
the proposed optimization methodology is significantly better than RSM, a nearly 78.7% increase in lipids extraction could be achieved according to the current model.