Fluid Catalytic Cracking Unit Research Articles

CO2 capture and hydrogen generation from a solar-assisted and integrated fluid catalytic cracking process: Energy, exergy, and economic analysis

The fluid catalytic cracking (FCC) process transforms heavy wastes into lighter, more valuable (naphtha, light olefins and gases) products. However, the unit's byproducts contain a large quantity of CO2, which contributes to global warming. As a result, the purpose of this research was to increase the production of valuable products such as light olefins, naphtha, and hydrogen while reducing environmental impacts using the water gas shift reaction, with sensitivity analysis for three parameters (riser height, FCC feed temperature, and inlet naphtha mass flow). As a result of increasing the riser height, the output of light olefins (45%) and gases (32%) increased. Furthermore, the amount of hydrogen produced increases with a decrease in riser height (about 6%) and an increase in inlet naphtha mass flow (about 8%). Energy and exergy assessments were also carried out. It was determined that FCC had the lowest exergy destruction with a contribution of 23 MW when compared to its energy usage of 172 MW. The cooler, on the other hand, was one of the process's most energy-consuming (25%) and damaging (26%). As a result, this technique can lessen environmental effects by absorbing 125 tons of CO2 every hour and producing 3484 kg/h of hydrogen. Economic evaluations were also undertaken, and the results revealed that the cooler has the lowest exergoeconomic factor (1%) while the FCC unit contributes the most (95%). The fractionator column is also the most expensive device in the whole process.

Soyabean oil processed in fluid catalytic cracking unit

Soyabean oil processed in fluid catalytic cracking unit

Integration of Encoding and Temporal Forecasting: Toward End-to-End NOx Prediction for Industrial Chemical Process.

Forecasting NOx concentration in fluid catalytic cracking (FCC) regeneration flue gas can guide the real-time adjustment of treatment devices, and then furtherly prevent the excessive emission of pollutants. The process monitoring variables, which are usually high-dimensional time series, can provide valuable information for prediction. Although process features and cross-series correlations can be captured through feature extraction techniques, they are commonly linear transformation, and conducted or trained separately from forecasting model. This process is inefficient and might not be an optimal solution for the following forecasting modeling. Therefore, we propose a time series encoding temporal convolutional network (TSE-TCN). By parameterizing the hidden representation of the encoding-decoding structure with the temporal convolutional network (TCN), and combining the reconstruction error and the prediction error in the objective function, the encoding-decoding procedure and the temporal predicting procedure can be trained by a single optimizer. The effectiveness of the proposed method is verified through an industrial reaction and regeneration process of an FCC unit. Results demonstrate that TSE-TCN outperforms some state-of-art methods with lower root mean square error (RMSE) by 2.74% and higher R2 score by 3.77%.

Co-processing of organic fraction from groundnut shell biocrude with VGO in FCC unit to produce petrochemical products

This research work explores the transformative potential of biomass leading to sustainable production of biocrude and its utilization in refinery and petrochemical sector for reducing reliance on fossil fuels. In this study, groundnut shell biomass was thermally converted in a customized continuous semi pilot auger reactor in temperature range of 400–700 °C. The optimum temperature for maximizing biocrude was studied, and detailed chemical analysis revealed that biocrude contains hydrocarbons and alcohols with a calorific value of 29 MJ/kg. Furthermore, this study demonstrates the performance of the FCC (Fluid Catalytic Cracking) catalyst and feedstock (H-T- VGO (Hydrothermal vacuum gasoline oil) & Biocrude) in a laboratory-scale utilizing ACE R + MM (Advanced Cracking Evaluation - Residue and Metals Management) unit under predetermined temperatures (515 °C, 525 °C) and a fixed cat-to-oil weight ratio (CTO = 6 w/w). The organic phase and FCC feedstock in different weight ratios from 5 to 20 wt % were blended. There are marginal changes in the yields of dry gas, LCO (light cycle oil) and HCO (heavy cycle oil), with significant increase in the yields of LPG (liquified petroleum gas) and gasoline. Bottoms have been reduced, and coke formation has been adjusted. However, this process requires prudent blending and temperature choices, with future recommendations including improvement in the quality of biocrude to enhance the yields of both LPG and gasoline along with reduced coke formation.

SO3 removal characteristics from flue gas of FCC regeneration process by activated carbon modified red mud adsorbent

Sulfur trioxide (SO3) is one of the major air pollutants in the flue gas of Fluid catalytic cracking (FCC) units during the regeneration process in refineries. However, it is difficult to remove SO3 with the existing desulfurization systems. Nowadays, alkaline adsorbent spraying technology has been a promising method to remove SO3. However, there is no relevant application research in the field of FCC regeneration flue gas. Therefore, in this paper, The SO3 removal characteristics from FCC flue gas by activated carbon modified red mud adsorbent were studied, including modification method, reaction temperature and flue gas components. Combined with characterization analysis of adsorbents, the mechanism of SO3 removal was studied. It was found that when the AC mass ratio is 10% and modification temperature is 400 ℃, the best LBRMAC adsorbent was achieved. When particle size is 0.096–0.125 mm and reaction temperature is 400 ℃, the highest SO3 adsorption efficiency is up to 83.4%. The addition of NO has little influence on the adsorption efficiency of SO3. The addition of SO2 leads to competitive adsorption between SO3 and SO2, resulting in a rapid decline in the removal efficiency of SO3. Meanwhile, the characterization analysis proves that the SO3 adsorption process mainly include chemical kinetics control stage and product layer diffusion stage.

Attention-based early warning framework for abnormal operating conditions in fluid catalytic cracking units

Fluid Catalytic Cracking Unit (FCCU) is a critical processing technology in the oil refining industry, playing a vital role in energy efficiency and environmental protection. However, FCCU often encounters various abnormal operating conditions, leading to safety hazards, downtime, and reduced production efficiency. Early warning of these abnormal conditions is crucial but challenging due to high noise, strong hysteresis, and class imbalance problems. To tackle these challenges, a novel and universal attention-based framework called AEW-AOC (Attention-based Early Warning for Abnormal Operating Conditions) is specifically designed for FCCU applications. The proposed AEW-AOC framework incorporates three key components: (1) a Self-Correlation Denoiser (SCD) module is proposed to exploit spatiotemporal data correlation to effectively reduce noise; (2) a Convolutional Long Short-Term Memory (Conv-LSTM) module is employed to address the issue of strong hysteresis by capturing temporal variation features of process parameters; (3) an Anomaly Pattern Attention (APA) module is proposed to enhance the distinguishability of abnormal operating conditions based on clustering results from historical abnormal instances. Extensive experiments demonstrate the effectiveness and superiority of the proposed AEW-AOC framework, particularly in practical applications. Specifically, the AEW-AOC framework obtains an impressive fβ score of 91.00% on LIC201, 90.45% on LIC202, and 90.64% on LIC801. The proposed AEW-AOC framework shows great potential in enhancing safety, reducing downtime, optimizing efficiency, promoting sustainability, and expanding its applicability beyond FCCU. Its proactive and versatile nature makes it a valuable tool for improving industrial processes and driving advancements in the field of abnormal operating condition detection and prevention.

A hybrid soft sensor for key product yield of FCC unit based on deep learning framework driven by data and process mechanism

The model for online prediction of product yield embedded in the optimization and control framework has the potential to improve the profits of fluid catalytic cracking (FCC) units. In this work, a hybrid soft sensor model is developed to predict key product yield in commercial FCC units. The deep learning framework based on semi-supervised learning is driven by data and process mechanism to construct the hybrid model with a double-layer structure. Moreover, process simulation strategy is utilized for key input variable selection of the hybrid model to ensure model reliability. The hybrid model is compared to a pure data-driven model in terms of accuracy and trend consistency of model predictions. The results demonstrate that the hybrid model exhibits a superior prediction performance. This work suggests that the hybrid model can drive innovation and industrial practice in the optimization and control of FCC units.

A multiscale adaptive framework based on convolutional neural network: Application to fluid catalytic cracking product yield prediction

Since chemical processes are highly non-linear and multiscale, it is vital to deeply mine the multiscale coupling relationships embedded in the massive process data for the prediction and anomaly tracing of crucial process parameters and production indicators. While the integrated method of adaptive signal decomposition combined with time series models could effectively predict process variables, it does have limitations in capturing the high-frequency detail of the operation state when applied to complex chemical processes. In light of this, a novel Multiscale Multi-radius Multi-step Convolutional Neural Network (MsrtNet) is proposed for mining spatiotemporal multiscale information. First, the industrial data from the Fluid Catalytic Cracking (FCC) process decomposition using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) extract the multi-energy scale information of the feature subset. Then, convolution kernels with varying stride and padding structures are established to decouple the long-period operation process information encapsulated within the multi-energy scale data. Finally, a reconciliation network is trained to reconstruct the multiscale prediction results and obtain the final output. MsrtNet is initially assessed for its capability to untangle the spatiotemporal multiscale relationships among variables in the Tennessee Eastman process (TEP). Subsequently, the performance of MsrtNet is evaluated in predicting product yield for a 2.80 × 106 t/a FCC unit, taking diesel and gasoline yield as examples. In conclusion, MsrtNet can decouple and effectively extract spatiotemporal multiscale information from chemical process data and achieve a approximately reduction of 30% in prediction error compared to other time-series models. Furthermore, its robustness and transferability underscore its promising potential for broader applications.

Alternative Options for Ebullated Bed Vacuum Residue Hydrocracker Naphtha Utilization

The vacuum residue hydrocracker naphtha (VRHN) is a chemically unstable product that during storage changes its colour and forms sediments after two weeks. It cannot be directly exported from the refinery without improving its chemical stability. In this research, the hydrotreatment of H-Oil naphtha with straight run naphtha in a commercial hydrotreater, its co-processing with fluid catalytic cracking (FCC) gasoline in a commercial Prime-G+ post-treater, and its co-processing with vacuum gas oil (VGO) in a commercial FCC unit were discussed. The hydrotreatment improves the chemical stability of H-Oil naphtha and reduces its sulphur content to 3 ppm. The Prime-G+ co-hydrotreating increases the H-Oil naphtha blending research octane number (RON) by 6 points and motor octane number (MON) by 9 points. The FCC co-cracking with VGO enhances the blending RON by 11.5 points and blending MON by 17.6 points. H-Oil naphtha conversion to gaseous products (C1–C4 hydrocarbons) in the commercial FCC unit was found to be 50%. The use of ZSM 5 containing catalyst additive during processing H-Oil naphtha showed to lead to FCC gasoline blending octane enhancement by 2 points. This enabled an increment of low octane number naphtha in the commodity premium near zero sulphur automotive gasoline by 2.4 vol.% and substantial improvement of refinery margin. The processing of H-Oil naphtha in the FCC unit leads also to energy saving as a result of an equivalent lift steam substitution in the FCC riser.

Enhancing dynamic operation optimization feasibility for constrained economic model predictive control systems

AbstractBased on the hierarchical control structure, optimization and control problems of large‐scale and multivariate plants are solved sequentially. The economic performance of the plant plays an essential role in the plant‐wide modern industry. The optimal operating conditions will change as the economic criteria changes throughout the operation of the plant as the result of variations in raw material prices, product prices, production demand, market fluctuations, disturbances, and so forth. In reality, soft constraints are frequently used to denote the production requirements of various operating conditions. In order to improve economic performance and guarantee feasibility for the entire plant operation, a novel economic model predictive control (EMPC) strategy is proposed to control the constrained multi‐variable process system with varying economic performance criteria under soft constraints. By incorporating the transient steady‐state and two categories of slack variables for soft constraints, a modified economic performance index is optimized to cope with the changing criteria. In addition, a contractive constraint is added to the closed‐loop system to guarantee stability for non‐dissipative stage costs. This approach ensures recursive feasibility and asymptotic stability. The effectiveness of the proposed method is demonstrated by numerical examples and the fluid catalytic cracking unit (FCCU) process.

Fluid–structure interaction with a Finite Element–Immersed Boundary approach for compressible flows

This paper presents the mathematical modeling and numerical simulations of fluid–structure interaction (FSI) problems. The fluid domain is discretized using a Cartesian block-structured mesh and solved using the Finite Volume Method (FVM), using the LES methodology with Smagorinsky turbulent closure model. The fluid flow in the system is considered compressible, with properties that vary. The Immersed Boundary Method (IBM) is used to model the solid–fluid interface, and the structure deformation was solved using the Finite Element Method (FEM). The Multi-direct Forcing Scheme is used to calculate the fluid-dynamics forces through the IBM. After calculating the fluid forces exerted on the solid, the forces are interpolated and transferred to the FEM model, providing the deformation of the structure at each time step. The structural domain was discretized with Hexahedral eight-noded element with extra shape functions. The simulations were carried out using MFSIm (in-house code), a multiphysics simulation framework developed by the Fluid Mechanics Laboratory of the Federal University of Uberlândia with financial support from Petrobras. This paper demonstrates the practical application of FSI analysis in an industrial context, specifically focusing on a pipeline system within a Fluid Catalytic Cracking Unit (FCCU) used in the oil and gas industry. The analysis involves the use of butterfly valves positioned at different angles of opening. The results are treated statistically, and a surface response is generated. Machine learning is employed to predict the surface response, showing the valve configurations that yield the maximum and minimum displacement magnitudes of the evaluated structural probes.

Non-Linear PID Control of Fluid Catalytic Cracking Unit

Non-Linear PID Control of Fluid Catalytic Cracking Unit

Online Dynamic Optimization of Multi-Rate Processes with the Case of a Fluid Catalytic Cracking Unit

Due to operational limitations in the industrial field, the operating variables of fluid catalytic cracking units (FCCU) are of multiple operating frequencies, which are CO combustion promoter amount, recycle slurry flow rate, combustion air flow rate, heat escape, and reaction temperature, from low frequency to high frequency. There are usually two schemes for operation optimization of FCCU. The former is called single-rate, single-window optimization, whose operating variables are optimized only once in the whole operation cycle, which is easy to achieve, but the optimization effect is poor. The latter is called single-rate multi-window optimization, whose operating variables are optimized repeatedly and whose operation cycle is discretized into multiple optimization periods with the same frequency, which costs a heavy calculation burden and cannot adapt to the optimization variables with multiple operating frequencies. So, a multi-rate, variable-window online dynamic optimization method is proposed. In an operation cycle, the high-frequency operating variable is optimized in a short optimization period, and the low-frequency operating variable is optimized in a long optimization period; each optimization period has integer multiples to the minimum optimization period. Each optimized result for each optimization period is put into use online immediately. The optimization model involves the time domain differential equations, integral cost objective function, and measured disturbances. The experimental results show that compared with the single-rate, single-window optimization method and single-rate multi-window optimization method, the optimization effect of multi-rate, variable-window online dynamic optimization is better than single-rate, single-window optimization but worse than single-rate multi-window optimization. However, the optimization results are consistent with the operation frequency of each optimization variable, which can be implemented in complex chemical processes and increase certain economic benefits.

Migration and emission characteristics of metal pollutants in fluid catalytic cracking (FCC) process

Fluid catalytic cracking (FCC) is the core unit for heavy oil conversion in refineries. In the FCC process, the metal contaminants from the feedstock are deposited on the catalysts, causing catalyst deactivation and metal particulate matter (PM) emission. However, the migration and emission characteristics of metal pollutants in FCC units are still unclear. Here, the stack tests of three FCC units were carried out to monitor metal PM emissions, and the metal contents of the feedstock oil and spent catalyst were detected. For the metal migration from the feedstock to the catalysts, Ni, Fe, and V have high concentrations and migration rates while other metals perform much lower. The metal distribution on the spent catalysts profoundly determines the metal mobility to the flue gas and the regeneration process affects the catalyst attrition, leading to metal PM emissions discrepancy. The migration rate and emission concentration of V in the deeper layers of the catalysts are much lower than those of Ni at the particle’s exterior. Finally, the stack data was used to calculate the emission factors and ratio factors of the metal PM. This work is expected to advance metal migration cognition and metal pollutants emissions estimation in FCC units.

Catalytic cracking of a model bio-petroleum compound (sugar di-ketals) using beta zeolite as catalyst

Conversion of biomass (BM) to fuel is a promising solution to reduce the carbon footprint. By modifying BM by ketalization, a stable, neutral liquid we call bio-petroleum (BP) is obtained. In this study, a representative compound of BP, DX (1,2:3,5-di-O-isopropylidene-α-D-xylofuranose) was co-processed with n-hexane(nC6) into biofuel. In the search for a process to deoxygenate the DX and avoid over-cracking, to optimize gas and coke yields using a beta catalyst in a fluidized bed catalytic cracking (FCC) unit at a process temperature of 540 °C, we explored mixing 10–70 wt% DX in nC6, with catalyst/feed ratios from 3 to 6 and feed injection time of 30 versus 60 s. DX was fully converting under all conditions tested, while nC6 conversion decreased, reaching zero conversion when DX > 50 wt%. Coke yield varied from 3 to 9 wt%. The mixture containing a low amount of DX provided hydrocarbons without oxygenates. The mixture of 50% DX in nC6 only gave 2.7 wt% of oxygenates such as furans and ketones. Hence, the results confirmed the strong potential of beta catalysts to produce biofuel, superior to ZSM-5 and Y zeolites. Furthermore, the results of the variations of processing parameters added insights about the bio-petroleum conversion steps, contributing to further catalyst and process development.

Molecular dynamics study influence of factors on the structure, phase transition, and crystallization of the Ag1-xAux, x = 0.25, 0.5, 0.75 alloy

In this research, Molecular Dynamics (MD) method simulations were used to study the influence factors such as concentration of Au doping in Ag1-xAux alloy, atomic number, temperature, annealing time on the structure, transition process phase, and crystallization of Ag1-xAux alloy by choosing Sutton-Chen (SC) interaction potential field and periodic boundary conditions. The results show that, when the concentration of Au doping in Ag1-xAux alloy increases, the number of crystallization processes decreases at temperature, while the number of atoms and the annealing time at the glass temperature Tg = 900 K increase, the process results for crystallization increase. The crystallization process is expressed through the number of structural units Hexagonal Close Packed (HCP), Body-Centered Cubic (BCC) and Amorphous (Amor), and the total energy of the system (Etot). The results show that there is a significant influence of doping concentration, atomic number, temperature, and annealing time. Then the length of the links Ag-Ag, and Au-Au varies greatly. The link Ag-Au remains constant because with the r = 2.82 Å value, the total energy of the system and the size of the material change very little. During the phase transition, the length of the links (r), the total energy of the system, size (Etot), and the number of FCC, HCP, BCC, and Amor structural units change significantly. The results obtained on Ag1-xAux alloy can serve as a basis for future experimental studies.

Servo and Regulatory Response of an Industrial Fluid Catalytic Cracking (FCC) Unit under Fuzzy Logic Supervisory Control

A self-tuning hierarchical controller in which a Fuzzy logic controller supervises the control actions of a conventional PID has been proposed, implemented and presented in this paper. The controller has been applied to a control study of Fluid Catalytic Cracking unit (FCCU) riser temperature, and regenerator temperature respectively. Comparison between the performance of the proposed Fuzzy-PID controller and the conventional PID was made in simulation studies of regulatory and servo performances of the two controller types. Six performance measures: Percent overshoot (OS), settling time (ST), integral absolute error (IAE), integral square error (ISE), integral time absolute error (ITAE) and integral time square error (ITSE) were employed as the tools for performance comparison between the conventional PID and the Fuzzy-PID controller. For the tracking of riser temperature with a set point at 524oC, the performance indicators under PID control gave the following results overshoot (14.5%); settling time (40 seconds) Integral absolute error (8.246), integral square error (3.3); integral time absolute error(1762);integral time square error (43.77) while for the same indicators under Fuzzy-PID control the following values: overshoot (3.3%); settling time (40 seconds) ;Integral absolute error (8.811); integral square error (14.5); integral time absolute error(280),;integral time square error (31.11) .The results allude to the superiority of the fuzzy-PID scheme over the PID scheme in tracking the optimal set point of riser temperature. More so, for tracking the regenerator set point temperature of 746oC, comparative study of step response under the two schemes gave the following results in six performance indicators: overshoot (PID (12.6%) / Fuzzy-PID (6%)); settling time (PID (80 seconds) / Fuzzy-PID (20seconds)); Integral absolute error (PID (14.29) / Fuzzy-PID (8.63)); integral square error (PID(6.713). Fuzzy-PID (4.506)); integral time absolute error(PID(2858)/Fuzzy-PID(305.9)), integral time square error (PID(77.55)/Fuzzy-PID(33.05)) . Moreover, the fuzzy-PID controller also showed superior performance over the conventional PID controller in terms disturbance rejection (regulatory response) of both riser and regenerator temperature. The results from this study suggest that the application of fuzzy-PID scheme to temperature control offers good promise of improved fluid catalytic cracking unit (FCCU) operations.

Techno-economic feasibility of fluid catalytic cracking unit integrated chemical looping combustion – A novel approach for CO2 capture

Oil refineries are collectively responsible for about 4–6% of the global CO2 emissions, largely because of the regenerator part of the Fluid Catalytic Cracking (FCC) unit (25–35%). An advanced combustion technology, also called chemical looping combustion (CLC), has been recently presented as a novel CO2 capture process for FCC units; however, no study provides the economic feasibility of a CLC-FCC unit. In this study, a techno-economic feasibility of the novel CLC-FCC unit was presented for the first time based on a case study with 50,000 barrels feed per day. A rigorous mass and energy balance estimation shows that 96 vol% of coke regeneration (combustion) was achieved in the FCC regenerator by using a stoichiometrically required amount of metal oxide (CuO modified catalysts) at 750 °C for 45 min. The preliminary energy penalty calculations of the proposed CLC-FCC unit (0.21 GJ/ton CO2) is relatively lower compared to the post-combustion (3.1–4.2 GJ/t CO2) via amine solvent and oxy-fuel combustion (1.8–2.5 GJ/t CO2) units reported in the literature. The equipment purchase cost (EPC) is 1.1 times higher than a standalone FCC unit due to the increase in the number of processing equipment required. The cash flow analysis results reveal a yearly basis average CO2 capture cost of 0.0106 US$/kg of CO2 (∼10.6 US$/ton CO2) for the CLC-FCC unit, which is lower compared to the other conventional CCS technologies i.e. oxy-fuel combustion and post-combustion. Factors such as EPC, capital expenditure (CAPEX), and discount rate significantly influenced the capture cost. In contrast, the CO2 capture cost is not influenced by a change in oxygen carrier and electricity cost.

CO-Selective Catalytic Reduction of NOx in Fluid Catalytic Cracking Units and Applications of the Generated Exhaust Gas for Enhanced Shale Gas Recovery and Sequestration

CO-Selective Catalytic Reduction of NO_<i>x</i> in Fluid Catalytic Cracking Units and Applications of the Generated Exhaust Gas for Enhanced Shale Gas Recovery and Sequestration

Optimized Operation of Fluidized Catalytic Cracking Considering CO2 Fixation and Carbon Pricing

Recently, Japan and the European Union have been experiencing declining petroleum demand owing to global initiatives aimed at reducing environmental impact by curtailing CO2 emissions. Consequently, alternative products and operational conditions should be developed to utilize the fluid catalytic cracking (FCC) unit. Using simulation software (Aspen Hysys), this study modeled a typical FCC unit and compared the simulation results with operational data to ensure reproducibility. Two new process models were developed to investigate two scenarios: (i) the slurry discharged from the FCC unit is utilized as a feedstock for the FCC process and (ii) the slurry and fraction obtained from the downstream absorber of the FCC unit are introduced into a delayed coker unit to facilitate carbon fixation. Within an optimum riser outlet temperature (ROT) of 520–530 °C, the yields of gasoline and liquefied petroleum gas increased up to 4%. For profit performance, although ROT of 535–545 °C yielded peak efficiency, the CO2 emissions increased by 70%. Thus, a ROT of 530–540 °C, coupled with a delayed coker unit, can maximize profitability. Furthermore, a correlation graph illustrated the relationship between CO2 emissions and profit for selecting optimal FCC operational conditions.