APPLICATION OF ZEOLITE Y-BASED NI–W SUPPORTED AND IN SITU PREPARED CATALYSTS IN THE PROCESS OF VACUUM GAS OIL HYDROCRACKING
The activity of supported and in situ synthesized sulfide Ni–W catalysts based on a low-siliconzeolite Y (SiO2/Al2O3 = 5.2) in the hydrocracking of vacuum gas oil is studied. It is shown that the temperature and time of reaction affect the fractional composition and the sulfur content in conversion products. Itis found that the phase of tungsten sulfide as well as the mixed Ni−W−S phase active in hydrogenation areformed on the catalyst surface. It is proposed that an increase in activity for the in situ formed catalyst maybe explained by a high content of sulfide phases on the catalyst surface and accessibility of the zeolite pore system
The behavior of Pt-containing catalysts based on mesoporous amorphous aluminosilicate in the process of hydroconversion of C19–C38 n-paraffins with the goal to produce diesel and kerosene fractions with improved cold flow properties was investigated. These systems were characterized by high efficiency and selectivity in the process of producing diesel and kerosene fractions. A 91% degree of conversion was achieved with a yield of liquid hydrocarbons of 76% (320°C, volume feed rate 0.5 h–1, molar ratio hydrogen: feed = 600: 1, pressure 50 atm). The initial freezing point of the isolated kerosene fraction was below minus 50°C, and the cold filter plugging point of the diesel fraction was minus 34°C.
The hydroconversion of a mixture of rosin acids over a Pt-containing mesoporous aluminosilicate catalyst has been studied. It has been shown that in a temperature range of 300–350°C at pressures of 30–50 atm and a feedstock/catalyst weight ratio of 20/1, rosin acids undergo complete decarboxylation to form naphthenic and naphthene-aromatic hydrocarbons. Under optimum process conditions, the yield of diesel fuel hydrocarbons is more than 85%. The resulting fraction can be used as a fuel component.
The paper proposes a mathematical model to optimize the operation of the tar hydrocracking unit.
The purpose of modeling is to improve the economic effect of product output by selecting optimal parameters,
such as hydrogen flow rate and reactor temperature. Hot Filtered Precipitation (HFT) is used as a target.
The model involves the search for the minimum value of the functional with restrictions present-
ed in the form of a fine imposed when the parameters go beyond the permissible values, as well as
when the target parameter deviates from the specified value. The execution of the algorithm includes
two stages. The first stage is the simulation of the HFT value for a given state of the installation at the
selected parameters of temperature and hydrogen flow rate using a virtual analyzer, the second stage is
to solve the optimization problem by selecting the control parameters of the installation. For the first
stage, a model for assessing the HFT indicator by technological indicators was built, including the main
factors determining it; machine learning methods were used to find the parameters of the models.
The free standard library of optimum search tools scipy.optimize was used to solve the optimiza-
tion problem. Powell's algorithm was chosen as the optimization method. The paper presents the results of
testing the model on real data provided by an oil refinery in the city of Burgas in Bulgaria. The study period
includes several operating modes of the installation, in particular, the intensive load mode during 2018-
2019 and low load during the 2020 period. The results of testing the model on real data presented in the
work have been verified by experts in the field of oil refining for compliance with real conditions.
The application of mathematical modeling methods (with subsequent computer sales) to determine the parameters of accuracy geometry bands obtained with the new equipment and process the step deformation bands of hard alloys based on copper