Abstract
Abstract In this study a typical continuous lumping model with five parameters has been used for kinetic modeling of thermal and catalytic hydrocracking. Model parameters have been optimized according to experimental product distributions using a particle swarm optimization (PSO) algorithm. Experimental data from the hydrocracker setup have been employed to validate the proposed model. In this setup hydrogen and vacuum gasoil feed were introduced from the top of a vertical reactor and, after passing through a catalyst bed, the liquid and gas products were separated and analyzed. Temperature of the reactor was adjusted in the range of 440-470°C for thermal hydrocracking, and 410-430°C for catalytic hydrocracking. Liquid hourly space velocities (LHSV) were in the range of 0.5-1.5 feed flow rate per catalyst volume in both sets of experiments. Results of optimization showed that the parameters were only temperature dependent. The comparison between model results and experimental data indicates that the model is capable of predicting product yield with maximum errors of 0.986 and 0.041 for RMSE and AARE values, respectively.
Highlights
Hydrocracking is a catalytic conversion process for producing lighter petroleum fractions such as diesel, kerosene, naphtha and gases from highboiling constituent hydrocarbons in petroleum such as vacuum gasoil (VGO) feedstock, in the presence of hydrogen-rich gas
Optimization of model parameters were performed for all operating conditions individually, using a particle swarm optimization (PSO) algorithm
By using this optimum set as input in the prediction mode of the computer program, product concentrations were calculated in other severities including Liquid hourly space velocities (LHSV)=0.5 and LHSV=1.5
Summary
Hydrocracking is a catalytic conversion process for producing lighter petroleum fractions such as diesel, kerosene, naphtha and gases from highboiling constituent hydrocarbons in petroleum such as vacuum gasoil (VGO) feedstock, in the presence of hydrogen-rich gas. A kinetic model which can predict the performance of the process within the operating severity is very important. A commonly used approach is to consider the mixture in terms of selected lumps, which can be specified in terms of structural characteristics, such as boiling point This approach is attractive for the kinetic modeling of complex mixtures because of its simplicity (Ancheyta et al, 1999). Elizalde et al (2009) reported that the continuous kinetic lumping model versus discrete lumped model is able to predict the whole distillation curve of hydrocracked products. The main advantages of the lumping technique are its easy computational implementation and the small amount of data required for parameter estimation
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call