Multi-objective atom search optimization of biodiesel production from palm empty fruit bunch pyrolysis - Rawinun Junsittiwate; Thongchai Rohitatisha Srinophakun; Somboon Sukpancharoen (Heliyon, 2022)
In this study, palm empty fruit bunch (PEFB) pyrolysis, bio-oil improvement, and generating electricity were all simulated using Aspen plus. This research employed a kinetic reactor for pyrolysis at 500 °C based on 1,000 tons of PEFB per day. The simulation results indicated that 1 kg/hr. PEFB generated 0.11 kg/hr of char, 0.21 kg/hr of gas, and 0.67 kg/hr of bio-oil, which is in good agreement with literature. The relationship between biodiesel yield, CO2 emissions, and utility costs was then investigated the effect of the distillate-to-feed ratio of biodiesel distillation, heat exchanger temperature, and the flash drum pressure from the process simulation by using central composite design (CCD). The coefficient of determination (R2) values for biodiesel yield, CO2 emissions, and utility costs were 0.9940, 0.9941, and 0.9959, respectively, which was a reason for the excellent model fitting. The optimum response (the biodiesel yield, the CO2 emission, and the utility cost) was obtained at 5,562.73 kg/hr, 33,696.55 kg/hr, and 2,953.99 USD/hr., respectively, with optimum conditions for the distillate-to-feed ratio of 0.899999, temperature of 56.0356 °C and pressure of 18.1479 bar. After that, a quadratic polynomial equation from the RSM was employed as the fitness function to evaluate the fitness value of the multi-objective optimization (MOO) by atom search optimization (ASO) to maximize biodiesel yield and minimize the CO2 emissions and utility costs. The ASO performance was generated into the Pareto optimal solution of 200 generations. The optimal CCD was then compared with the ASO results. It was found that the ASO could reduce CO2 emissions by 1.33% and reduce utility costs by 5.03% while increasing biodiesel yields by 7.01%. It can be observed that the ASO was more efficient at finding parameters than the CCD.