PROCESS OPTIMIZATION, KINETIC MODELLING AND CHARACTERIZATION OF BIODIESEL PRODUCED FROM MORINGA OLEIFERA OIL: A REVIEW

Abstract

The rise in world population has resulted in subsequent increase in demand for energy which led to insufficient energy supply. Fossil fuel reserves such as coal, crude oil, and natural oil has been utilized as fuel energy and has been continuously used in large-scale and would get exhausted. Hence development, adoption and diffusion of several alternative technologies such as biomass, wind, solar, ocean thermal, hydrogen, and geothermal energy. Biodiesel has garnered increasing attention because it is renewable and eco-friendly because of its non-emission of CO2 compared to the conventional diesel. Optimization and kinetic modelling are receiving more importance in characterization of biodiesel production. This paper is an attempt to review recent development and application of different optimization and kinetic modelling processes for the optimum production of biodiesel. Optimization of different reaction parameters such as reaction temperature, time, solvent/solid ratio, 1 catalyst concentration, catalyst amount, particle size, stirring speed, etc., optimization software’s such as response surface methodology, different statistical tools (factorial design, ANOVA etc.) were reviewed. Also, thermodynamic and kinetic studies and modeling has been studied. Among these optimization parameters studied, it has been observed that temperature and time has more effect on the biodiesel production yield. Advanced optimization and modelling software’s such as Artificial Neural Network (ANN), Laplacian Harris Hawk Optimization (LHHO), and adaptive neuro-fuzzy inference system (ANFIS) were observed to be efficient in the production of high yield (91.45 %, 96.8199 %, 99.8 %) biodiesel.