Search Results (3)

Feedstock quality has been proven to be the single variable that most affects fluid catalytic cracking (FCC) unit performance, but catalyst characteristics have also been reported in the literature to have a considerable effect on cracking process performance. How these two main variables of the FCC process complement each other in the search for ways to optimize the performance of the FCC unit is the subject of current research. Twenty-one feedstocks with K_W-characterizing factors ranging from 11.08 to 12.06, Conradson carbon contents ranging from 0.05 to 12.8 wt.%, and nitrogen contents ranging from 800 to 3590 ppm (wt/wt) (basic nitrogen from 172 to 1125 ppm (wt/wt)) were cracked on 21 catalysts with micro-activity between 67% and 76% (wt/wt) in a laboratory-based advanced catalytic evaluation (ACE) unit at a reaction temperature of 527 °C, catalyst–to-oil ratios between 3.5 and 12.0 wt/wt, and a catalyst time on stream of 30 s. Some of the feeds and catalysts tested in the laboratory FCC ACE unit were also examined in a commercial short-contact-time FCC unit resembling a UOP side-by-side design. It was found that conversion can be very well predicted in both the laboratory ACE and the commercial FCC units using multiple linear correlations developed in this work from information about the following feed properties: K_W-characterizing factor, nitrogen content, and micro-activity of the catalyst. The coke on the catalyst that controls the catalyst-to-oil ratio and the regenerator temperature in the commercial FCC unit could be calculated using the correlations developed in this work for the laboratory ACE and commercial FCC units, based on feed characteristics and catalyst micro-activity. Due to the greater slope of the Δ coke/Δ micro-activity dependence observed in the ACE FCC unit, the more active catalysts show weaker results compared to the less active catalysts at a constant coke yield. In contrast, catalysts with higher activity are preferable for operation in the commercial FCC plant because they provide higher conversion at the same coke yield due to the lower slope of the Δ coke/Δ micro-activity relationship. Full article

It has been proven that the performance of fluid catalytic cracking (FCC), as the most important oil refining process for converting low-value heavy oils into high-value transportation fuels, light olefins, and feedstocks for petrochemicals, depends strongly on the quality of the feedstock. For this reason, characterization of feedstocks and their relationships to FCC performance are issues deserving special attention. This study systematically reviews various publications dealing with the influence of feedstock characteristics on FCC performance, with the aim of identifying the best characteristic descriptors allowing prediction of FCC feedstock cracking capability. These characteristics were obtained by mass spectrometry, SARA analysis, elemental analysis, and various empirical methods. This study also reviews published research dedicated to the catalytic cracking of biomass and waste oils, as well as blends of petroleum-derived feedstocks with sustainable oils, with the aim of searching for quantitative relationships allowing prediction of FCC performance during co-processing. Correlation analysis of the various FCC feed characteristics was carried out, and regression techniques were used to develop correlations predicting the conversion at maximum gasoline yield and that obtained under constant operating conditions. Artificial neural network (ANN) analysis and nonlinear regression techniques were applied to predict FCC conversion from feed characteristics at maximum gasoline yield, with the aim of distinguishing which technique provided the more accurate model. It was found that the correlation developed in this work based on the empirically determined aromatic carbon content according to the n-d-M method and the hydrogen content calculated via the Dhulesia correlation demonstrated highly accurate calculation of conversion at maximum gasoline yield (standard error of 1.3%) compared with that based on the gasoline precursor content determined by mass spectrometry (standard error of 1.5%). Using other data from 88 FCC feedstocks characterized by hydrogen content, saturates, aromatics, and polars contents to develop the ANN model and the nonlinear regression model, it was found that the ANN model demonstrated more accurate prediction of conversion at maximum gasoline yield, with a standard error of 1.4% versus 2.3% for the nonlinear regression model. During the co-processing of petroleum-derived feedstocks with sustainable oils, it was observed that FCC conversion and yields may obey the linear mixing rule or synergism, leading to higher yields of desirable products than those calculated according to the linear mixing rule. The exact reason for this observation has not yet been thoroughly investigated. Full article

Ebullated bed vacuum residue hydrocracking and fluid catalytic cracking (FCC) are among the most profitable processes in modern refining. Their optimal performance is vital for petroleum refining profitability. That is why a better understanding of their combined action and the interrelations between these two heavy oil conversion processes in a real-world refinery could provide valuable information for further performance optimization. Nine distinct petroleum crudes belonging to the extra light, light, and medium petroleum crude types were processed in the LUKOIL Neftohim Burgas refinery to study the combined performance of two processes: FCC of vacuum gas oil and ebullated bed vacuum residue H-Oil hydrocracking. The operating conditions along with the characterization data of the feeds and products of both processes were evaluated through the employment of intercriteria analysis to define the variables with statistically significant relationships. Maple 2023 Academic Edition mathematics software was used to develop models to predict the vacuum residue conversion level under different operating conditions. The plug flow reactor model with an activation energy of 215 kJ/mol and a reaction order of 1.59 was found to provide the highest accuracy of vacuum residue conversion, with an average absolute deviation of 2.2%. H-Oil yields were found to correlate with the vacuum residue conversion level and the content of FCC slurry oil (SLO), the recycling of partially blended fuel oil, a material boiling point below 360 °C, and the vacuum gas oil (VGO) in the H-Oil feed. FCC conversion was found to depend on the H-Oil VGO content in the FCC feed and the content of FCC SLO in the H-Oil feed. Full article