Modelling and optimisation of oxidative desulphurization process for model sulphur compounds and heavy gas oil. Determination of Rate of Reaction and Partition Coefficient via Pilot Plant Experiment; Modelling of Oxidation and Solvent Extraction Processes; Heat Integration of Oxidation Process; Economic Evaluation of the Total Process.
AuthorKhalfalla, Hamza Abdulmagid
SupervisorMujtaba, Iqbal M.
Model sulphur compounds
Heavy gas oil
The University of Bradford theses are licenced under a Creative Commons Licence.
InstitutionUniversity of Bradford
DepartmentSchool of Engineering, Design and Technology
MetadataShow full item record
AbstractHeightened concerns for cleaner air and increasingly more stringent regulations on sulphur content in transportation fuels will make desulphurization more and more important. The sulphur problem is becoming more serious in general, particularly for diesel fuels as the regulated sulphur content is getting an order of magnitude lower, while the sulphur contents of crude oils are becoming higher. This thesis aimed to develop a desulphurisation process (based on oxidation followed by extraction) with high efficiency, selectivity and minimum energy consumption leading to minimum environmental impact via laboratory batch experiments, mathematical modelling and optimisation. Deep desulphurization of model sulphur compounds (di-n-butyl sulphide, dimethyl sulfoxide and dibenzothiophene) and heavy gas oils (HGO) derived from Libyan crude oil were conducted. A series of batch experiments were carried out using a small reactor operating at various temperatures (40 ¿ 100 0C) with hydrogen peroxide (H2O2) as oxidant and formic acid (HCOOH) as catalyst. Kinetic models for the oxidation process are then developed based on `total sulphur approach¿. Extraction of unoxidised and oxidised gas oils was also investigated using methanol, dimethylformamide (DMF) and N-methyl pyrolidone (NMP) as solvents. For each solvent, the `measures¿ such as: the partition coefficient (KP), effectiveness factor (Kf) and extractor factor (Ef) are used to select the best/effective solvent and to find the effective heavy gas oil/solvent ratios. A CSTR model is then developed for the process for evaluating viability of the large scale operation. It is noted that while the energy consumption and recovery issues could be ignored for batch experiments these could not be ignored for large scale operation. Large amount of heating is necessary even to carry out the reaction at 30-40 0C, the recovery of which is very important for maximising the profitability of operation and also to minimise environmental impact by reducing net CO2 release. Here the heat integration of the oxidation process is considered to recover most of the external energy input. However, this leads to putting a number of heat exchangers in the oxidation process requiring capital investment. Optimisation problem is formulated using gPROMS modelling tool to optimise some of the design and operating parameters (such as reaction temperature, residence time and splitter ratio) of integrated process while minimising an objective function which is a coupled function of capital and operating costs involving design and operating parameters. Two cases are studied: where (i) HGO and catalyst are fed as one feed stream and (ii) HGO and catalyst are treated as two feed streams. A liquid-liquid extraction model is then developed for the extraction of sulphur compounds from the oxidised heavy gas oil. With the experimentally determined KP multi stage liquid-liquid extraction process is modelled using gPROMS software and the process is simulated for three different solvents at different oil/solvent ratios to select the best solvent, and to obtain the best heavy gas oil to solvent ratio and number of extraction stages to reduce the sulphur content to less than 10 ppm. Finally, an integrated oxidation and extraction steps of ODS process is developed based on the batch experiments and modelling. The recovery of oxidant, catalyst and solvent are considered and preliminary economic analysis for the integrated ODS process is presented.
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