A New Approach to Development of Molecular Based Kinetic Lumping Model for Design and Simulation of Hydrodesulfurization Process
Modeling of chemical kinetics is critically important for the design and simulation, control and operation of refinery reactors. The conventional modeling method, which groups all the components in the feedstock into lumps based on boiling ranges, has been proven capability of effectively predicting product yield. However, its usefulness is limited due to the inability of predicting product’s composition and detailed molecular information.
Petroleomics has emerged as a new field of petroleum technology, in which all components of petroleum are characterized and their properties and reactivity are correlated with the composition data. The application of petroleomics opens variety of opportunities to noble and efficient use of both conventional and unconventional crude oils, elimination of control and operation problems, reduction of production cost, etc. To capture the wealth of available information of molecular based characterization, chemical properties and reactivity provided by petroleomics, a new kinetic model at molecular level needs to be developed. Overcoming the limitations of conventional model, the molecular based kinetic model can provide basic insight into the composition and molecular based characterization of product, which are essential information for the design of ultrahigh efficient refinery reactor and optimization and control of product slate.
In this study, we present a new method for developing molecular based kinetic lumping model for design and simulation of hydrodesulfurization (HDS) process. The developed method includes three main steps: 1) Reducing elementary reaction network by eliminating the unimportant elementary reactions and species; 2) Defining lumps of species and reaction network between the lumps based on the molecular structure and reactivity of remained species; and 3) Estimating kinetic parameters of lump-based reactions. Kinetic modeler toolbox is utilized to generate necessary data of chemical species included in feedstock and types of elementary reactions and associated kinetic parameters involved in HDS process. The applicability of the method is validated through the demonstration of case study on HDS of light gas oil.
This work was supported by Ministry of Economy, Trade and Industry (METI) and Japan Petroleum Energy Center (JPEC).