Molecular-level catalytic reforming device simulation and optimization method

Abstract

The invention discloses a molecular-level catalytic reforming device simulation and optimization method, and belongs to the technical field of molecular-level catalytic reforming device optimization. The method comprises the following steps: performing accuracy evaluation on feed data measured by a gas chromatograph based on feed data acquisition and analysis parameters to provide an accurate input basis for subsequent catalytic reforming process simulation, and performing feed data marking based on an obtained accuracy evaluation result to avoid simulation deviation caused by sampling errors; state evaluation is performed on the catalytic reforming process on the basis of catalytic state parameters, the effect of the catalytic reforming process is monitored in real time, and whether state abnormity adjustment is performed or not is judged on the basis of a state simulation result obtained by a constructed molecular-level process model, so that inactivation compensation of a catalyst and process optimization of catalytic reforming device simulation are realized. The problem of simulation distortion caused by deactivation of the catalyst is solved, and the accuracy of simulating the conversion rate of the feed component under the action of the catalyst by the catalytic reforming device is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of molecular-level catalytic reforming device optimization technology, and in particular to a method for simulating and optimizing a molecular-level catalytic reforming device. Background Technology

[0002] Catalytic reforming is one of the main processes in the petrochemical industry. Its main feedstock is naphtha. Deep processing of naphtha can increase its added value. In the hydrogenation stage, unsaturated hydrocarbons in the feedstock are converted to saturated hydrocarbons through hydrogenation reactions, removing sulfur and nitrogen impurities and preventing catalyst poisoning. In the dehydrogenation stage, cycloalkanes are converted to aromatics through dehydrogenation reactions, increasing the composition ratio of reforming products. In the isomerization stage, n-alkanes are converted to isoalkanes with higher octane numbers, increasing the proportion of branched hydrocarbons. In the aromatization stage, the composition ratio of reforming products is further increased through aromatization reactions, causing a rearrangement of hydrocarbon structures, ultimately producing high-octane gasoline components (aromatics and isoalkanes) and hydrogen. However, in actual catalytic reforming processes, hydrocarbon molecules in naphtha may gradually form polycyclic aromatic hydrocarbons through polymerization, cyclization, and aromatization reactions, eventually transforming into graphite-like coke deposits that cover the catalyst surface and reduce catalyst activity.

[0003] The initial modeling of the molecular-level catalytic reforming model is first based on the bifunctional properties of the catalyst (including metal dehydrogenation and acid isomerization functions) and the composition of the feed molecules, constructing a kinetic network containing the main reaction pathways, and calibrating the kinetic parameters and coking model using experimental data. Subsequently, a multi-scale reactor model is established by integrating thermodynamic and mass transfer constraints. In actual operation, the system collects feed and product data in real time using gas chromatography and compares them with the model predictions. When the deviation exceeds a threshold, an optimization algorithm is used to automatically correct key parameters such as the catalyst deactivation factor, so that the model output matches the measured data, thereby achieving accurate simulation and optimized control of the reaction process.

[0004] For example, the invention patent with announcement number CN108287474B discloses a robust operation optimization method for catalytic reforming reactors based on raw material uncertainty, which includes: S1, constructing a reactor model for catalytic reforming; S2, collecting and processing raw data to generate a raw material uncertainty database; S3, performing sampling analysis based on the data in the raw material uncertainty database to obtain the sampling analysis results of the raw material uncertainty data; S4, based on steps S1 and S3, selecting the operating conditions to be optimized and the production target statistics as the optimization variables and optimization objectives, respectively, and constructing a robust operation optimization model; S5, optimizing and solving the robust operation optimization model to obtain a Pareto optimal solution set, which corresponds to a set of candidate optimal operating conditions; S6, selecting target operating conditions from the set of candidate optimal operating conditions according to application requirements.

[0005] For example, the invention patent with announcement number CN112782979B discloses a real-time optimization control system and method for a continuous catalytic reforming unit, including: a data acquisition module, a data conversion module, a data processing module, a human-machine interaction module, a central processing module, and a simulation control module. The central processing module establishes a relatively complete mechanistic model based on the fundamental principles of reforming kinetics, thermodynamics, material balance, and energy balance, and achieves real-time optimization control through optimal control algorithms. This invention constructs a real-time optimization control system for continuous catalytic reforming units in a modular form, achieving the goal of real-time optimization control through the cooperation of various modules and the combination of mechanistic modeling and optimal control algorithms.

[0006] The above-mentioned technology has at least the following technical problems:

[0007] In existing technologies, during catalytic reforming, the catalyst surface gradually deactivates due to carbon buildup, leading to a decrease in the actual reaction rate. However, current catalytic reforming units are modeled based on the assumption of "constant catalyst activity," which causes discrepancies between simulation results and actual operating conditions. When simulating the conversion rate of feed data under the action of the catalyst using a catalytic reforming unit, differences in catalyst state can lead to changes in the catalytic reforming reaction rate, resulting in low accuracy of simulation results for the catalytic reforming unit. Summary of the Invention

[0008] To address the issue that in existing catalytic reforming technologies, catalyst surfaces gradually deactivate due to carbon buildup, leading to a decrease in the actual reaction rate, current catalytic reforming units are modeled based on the assumption of "constant catalyst activity." This results in discrepancies between simulation results and actual operating conditions. When simulating the conversion rate of feed data under the action of the catalyst using a catalytic reforming unit, differences in catalyst state can cause variations in the catalytic reforming reaction rate, resulting in low accuracy in the simulation results. This invention provides a molecular-level catalytic reforming unit simulation and optimization method. The technical solution is as follows:

[0009] On the one hand, a method for simulating and optimizing a molecular-level catalytic reforming device is provided, the method comprising:

[0010] The accuracy of feed data measured by gas chromatography (GC) is evaluated based on feed data acquisition and analysis parameters, which describe the control of sampling interval time during the GC sampling process. Feed data is labeled based on the accuracy evaluation results, dynamically marking the feed data measured by GC. The molecular composition of the feedstock is obtained based on the labeled GC analysis data to improve the reliability of the simulation results of the catalytic reforming unit. The state of the catalytic reforming process is evaluated based on catalytic state parameters, and the state simulation results determine whether state anomaly adjustment is necessary. Catalytic state parameters describe the effect of the catalytic reforming process, and state anomaly adjustment dynamically regulates the catalyst deactivation factor, isomerization activity factor, dehydrogenation activity factor, and cracking activity factor during the catalytic reforming process to improve the catalytic reforming effect.

[0011] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0012] 1. This invention assesses the accuracy of gas chromatograph measurements by combining feed data acquisition and analysis parameters, enabling real-time monitoring of the rationality of gas chromatograph monitoring and ensuring the reliability of feed component data, thereby reducing measurement errors caused by instrument deviation. Based on the accuracy assessment results, the sampled data is dynamically labeled, effectively distinguishing between high-quality and abnormal data, improving the accuracy of catalytic reforming unit evaluation, and avoiding interference from low-quality data in catalyst activity analysis and product yield simulation. Utilizing catalytic state parameters to assess the reforming process comprehensively reflects the reaction efficiency, accurately identifying problems such as catalyst deactivation, decreased reaction efficiency, or uneven hydrogen distribution. Dynamic adjustments triggered by state simulation results can simulate and optimize reaction conditions, ensuring product distribution meets expectations while reducing energy consumption and catalyst loss, ultimately improving the operating efficiency and long-term stability of the actual catalytic reforming process.

[0013] 2. This invention comprehensively analyzes the parameters of feed data acquisition to obtain a feed acquisition accuracy index, which can quantify the measurement reliability of the gas chromatograph and provide an objective basis for subsequent data classification and dynamic compensation. By using the feed acquisition accuracy index for threshold comparison, it can accurately identify feed data with different reliability levels, avoid low-quality data from directly entering the catalytic reforming simulation evaluation process, and significantly improve the credibility of the catalytic reforming unit analysis. It not only optimizes the data quality of feed data, but also improves the operating efficiency of the unit while ensuring the accuracy of the catalytic reforming unit evaluation.

[0014] 3. This invention comprehensively analyzes catalytic state parameters to obtain a catalytic state evaluation index. By comprehensively monitoring key data such as process conditions and product distribution, it can quantify the real-time performance and deactivation trend of the catalyst in the catalytic reforming process in a real-time and comprehensive manner. This provides data support for subsequent dynamic optimization of catalyst compensation operations in the catalytic reforming process. By comparing the catalytic state evaluation index of each reaction stage with thresholds, it can accurately identify abnormal operating conditions in each reaction stage. Based on the hydrogen-to-hydrocarbon ratio and the composition ratio of reforming products, it can simulate and optimize operating conditions such as catalyst deactivation factors. This not only corrects the reaction deviations of each active factor in the actual catalytic reforming process in real time, but also considers the impact of carbon deposition on catalyst deactivation. It also significantly improves the operational stability of the catalytic reforming unit and the accuracy of product yield control. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart of a method for simulating and optimizing a molecular-level catalytic reforming device provided in an embodiment of the present invention;

[0017] Figure 2 This is a flowchart of the feed data acquisition and analysis provided in an embodiment of the present invention;

[0018] Figure 3 This is a flowchart of the catalytic reforming state assessment provided in an embodiment of the present invention. Detailed Implementation

[0019] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0020] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0021] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0022] This invention provides a method for simulating and optimizing a molecular-level catalytic reforming device. For example... Figure 1The flowchart shown is a simulation and optimization method for a molecular-level catalytic reforming device. The process flow of this method may include the following steps:

[0023] The accuracy of feed data measured by gas chromatography (GC) is evaluated based on feed data acquisition and analysis parameters. The feed data refers to naphtha, the reactant feedstock for the catalytic reforming unit. The feed data acquisition and analysis parameters describe the sampling interval control during the GC sampling process. Feed data is labeled based on the accuracy evaluation results. This labeling dynamically marks the feed data measured by the GC, and the molecular composition of the feedstock is obtained based on the labeled GC analysis data to improve the reliability of the catalytic reforming unit simulation results. The state of the catalytic reforming process is evaluated based on catalytic state parameters. The state simulation results determine whether state anomaly adjustments are necessary. These catalytic state parameters describe the effectiveness of the catalytic reforming process, and state anomaly adjustments dynamically regulate the catalyst deactivation factor, isomerization activity factor, dehydrogenation activity factor, and cracking activity factor during the catalytic reforming process to improve the catalytic reforming effect.

[0024] In this embodiment, the present invention, based on the accuracy assessment and dynamic labeling of feed data acquisition and analysis, can more accurately correct the data measured by the gas chromatograph, thereby improving the reliability of the simulation results of the catalytic reforming unit. By combining catalytic state parameters to evaluate the catalytic reforming process in real time and adjusting for state anomalies based on the evaluation results, it helps to optimize the catalytic reforming effect even when the catalyst surface gradually deactivates due to carbon deposition. Traditional catalytic reforming units typically assume that the catalyst activity remains constant, but this assumption leads to an underestimation of the conversion rate of the actual feed components under the action of the catalyst, thus affecting the accuracy of the simulation results. The present invention considers the impact of catalyst deactivation and adapts to changes in actual catalyst activity in real time based on the simulation results, achieving precise intervention while preventing over-operation. When the difference between the simulation results and real-time data exceeds a preset threshold, the device automatically triggers anomaly diagnosis, thereby improving the device's operating efficiency and simulation accuracy.

[0025] In addition, the catalytic reforming database is used to store data related to simulation and optimization methods of molecular-level catalytic reforming units, including: reference data for feed data acquisition and analysis parameters, first threshold for feed acquisition, and second threshold for feed acquisition. The data in the catalytic reforming database can be obtained directly from public databases such as petrochemical catalyst performance databases and refining industry statistical databases, or through cooperation with catalyst production companies, refining companies, and other related industries.

[0026] It is important to understand that molecular-level catalytic reforming unit simulation refers to constructing a mathematical model and reaction mechanism of the catalytic reforming process at the molecular level. Utilizing precise information on the molecular composition of the feed and the unit's operating parameters, it dynamically simulates and predicts the material changes within the entire reactor. This process relies on high-precision molecular data obtained experimentally and leverages advanced modeling and simulation technologies to achieve quantitative description and optimized control of complex reaction networks. It is widely applied in petroleum refining for goals such as aromatization upgrading, hydrogen yield enhancement, and product distribution regulation. In this simulation process, the core meaning of "molecular-level" is that the composition of the feed is no longer simply represented by overall properties like "light naphtha" or "reformed oil," but rather broken down into precise molecular types, such as hydrogen (H2), various hydrocarbon molecules with 1 to 12 carbon atoms (e.g., n-hexane, toluene, cyclohexane), and further refined into straight-chain alkanes, isoalkanes, alkenes, cycloalkanes, aromatics, and trace impurities (e.g., nitrogen-, sulfur-, and oxygen-containing organic compounds). This information on molecular detail can be obtained through modern experimental techniques and managed and integrated through digital systems.

[0027] First, the laboratory obtains the original molecular composition using conventional chemical and spectroscopic analysis methods. Commonly used analytical equipment includes gas chromatography (GC) and mass spectrometry (MS). These devices can identify and quantify hydrocarbon molecules with different carbon numbers and structures. To achieve high-throughput, high-efficiency, and structured data management, this experimental data is centrally integrated into a Laboratory Information Management System (LIMS). The LIMS system not only archives data from multiple batches of samples but also supports data format standardization and interface access with modeling software, enabling real-time interaction between experimental data and simulation systems. Further molecular structure identification can be achieved through real-time spectroscopic analysis, including near-infrared spectroscopy (NIR) and nuclear magnetic resonance (NMR). Near-infrared spectroscopy is primarily used to identify the presence of different types of functional groups and carbon-hydrogen bonds in the feed, enabling rapid prediction of saturation, aromaticity, and carbon number distribution. Nuclear magnetic resonance (NMR) technology, on the other hand, provides more refined molecular structure information, such as aromatic ring structures, the number of branched chains, and the distribution of hydrogen atoms in the environment, and is particularly suitable for detecting heteroatom structures containing oxygen (O), nitrogen (N), and sulfur (S). These methods collectively provide detailed molecular-level composition information of the reforming feed. After obtaining this precise data, the model assigns various molecules to corresponding reaction pathways, constructing a multi-pathway reaction network including dehydrogenation, isomerization, aromatization, and cracking. Each type of reaction involves specific molecular species, and its reaction rate and conversion direction are controlled by rate equations and thermodynamic parameters. Upon receiving this data, the simulation software solves the reaction kinetic equations and mass conservation equations through numerical calculations, ultimately outputting key indicators such as the concentration changes of each molecule within each reactor segment, product distribution, and hydrogen yield. In summary, molecular-level catalytic reforming unit simulation is a complete process encompassing feed molecular structure identification, data standardization and integration, reaction mechanism modeling, and process solution and optimization analysis. Its core lies in combining NIR, NMR, digital systems (such as LIMS), and simulation platforms to shift the simulation process from traditional macroscopic energy balance and property prediction to refined, mechanism-driven molecular-level simulation. This not only improves prediction accuracy but also provides a scientific basis for production optimization, reactor design, and catalyst selection.

[0028] Furthermore, the steps for evaluating the accuracy of feed data measured by the gas chromatograph based on feed data acquisition and analysis parameters include: obtaining stored reference data for feed data acquisition and analysis parameters from a pre-set catalytic reforming database, specifically including: critical sampling interval coverage, critical maximum sampling interval, and critical sampling delay; performing a proportion approximation calculation on the sampling interval coverage, critical maximum sampling interval, and critical sampling delay with the critical sampling interval coverage, maximum sampling interval, and sampling delay, respectively; then weighting the proportion approximation calculation results using the contribution data of the feed data acquisition and analysis parameters; and coupling the weighted results to obtain the feed acquisition accuracy index. The feed acquisition accuracy index represents the quantitative data of the accuracy of the feed data measured by the gas chromatograph, which is jointly measured by the feed data acquisition and analysis parameters; the feed data acquisition and analysis parameters include sampling interval coverage, maximum sampling interval, and sampling delay; and the contribution data of the feed data acquisition and analysis parameters include the contribution of sampling interval coverage, the contribution of maximum sampling interval, and the contribution of sampling delay.

[0029] The accuracy index of the feed acquisition is obtained as follows:

[0030] ;

[0031] In the formula, a1 represents the accuracy index of feed acquisition, β1 represents the contribution of sampling interval coverage, β2 represents the contribution of maximum sampling interval, and β3 represents the contribution of sampling delay.

[0032] s1 represents the critical sampling interval coverage, and s represents the sampling interval coverage, which is the ratio between the number of data points that the gas chromatograph can effectively collect and the theoretically maximum number of data points that can be collected.

[0033] m1 represents the critical maximum sampling interval, and m represents the maximum sampling interval, which is the longest interval between two consecutive valid data points within the monitoring period. It can be obtained by calculating the maximum interval time by monitoring the gas chromatograph sampling time in real time.

[0034] t1 represents the critical sampling delay, and t represents the sampling delay, which is the time difference between the injection of feed data and the start of detection by the gas chromatograph. It can be obtained by calculating the difference between the gas chromatograph sampling time and the feed data injection time.

[0035] In the catalytic reforming database, β1, β2, and β3 represent the contributions of sampling interval coverage, maximum sampling interval, and sampling delay, respectively. These contributions quantitatively characterize the degree to which the aforementioned feed data acquisition and analysis parameters contribute to the feed acquisition accuracy index. Specifically, sampling interval coverage, maximum sampling interval, and sampling delay are configured with independent mapping tables, containing one-to-one or many-to-one correspondences. These tables record the value of each possible feed data acquisition and analysis parameter and its corresponding contribution. In practical applications, the real-time measured sampling interval coverage, maximum sampling interval, and sampling delay are input into their respective mapping tables to automatically match their corresponding contributions, with the contribution value ranging from 0 to 1.

[0036] It is important to understand that the various mapping tables involved in this application were established by the pre-designed personnel before designing the simulation and optimization methods for the molecular-level catalytic reforming device. The logic behind their establishment is the degree of influence of these parameters on their corresponding dependent variables over historical periods. Taking the mapping table corresponding to the sampling interval coverage rate as an example, the sampling interval coverage rate and the error rate of feed collection during historical periods can be input into the mapping table. Then, based on the corresponding proportion, the corresponding contribution can be obtained. For example, if the error rate is 5%, the corresponding contribution is 95%.

[0037] In this embodiment, the sampling interval coverage, maximum sampling interval, and sampling delay are interrelated. For example, a low sampling frequency means that the instrument may miss some changes, thus increasing the undetected time window and reducing the sampling interval coverage, because discontinuous data sampling cannot cover all changes. A low sampling interval coverage usually leads to a long sampling delay because the instrument response is slow and the update cycle is long. Therefore, the lower the data update frequency, the higher the delay usually is, affecting the real-time performance and accuracy of the data. A large sampling delay may lead to an increased undetected time window. In a rapidly changing process environment, a low sampling frequency may cause the system to miss some critical process changes, which increases the length of the undetected time window, thereby affecting the integrity and reliability of the data.

[0038] like Figure 2 The diagram shows a flowchart of the feed data acquisition and analysis provided in an embodiment of this application. In the diagram, the index is the feed acquisition accuracy index, the first threshold is the first threshold for feed acquisition, and the second threshold is the second threshold for feed acquisition. Figure 2The specific logic is as follows: the steps for marking feed data based on the obtained accuracy assessment results include: obtaining a first feed acquisition threshold and a second feed acquisition threshold from a preset catalytic reforming database; comparing the feed acquisition accuracy index with the first and second feed acquisition thresholds respectively; if the feed acquisition accuracy index is less than the first feed acquisition threshold, the current feed data is recorded as abnormal data, and the corresponding catalytic reforming unit simulation result is recorded as an abnormal result; if the feed acquisition accuracy index is greater than or equal to the first feed acquisition threshold and less than the second feed acquisition threshold, the current feed data is recorded as partially abnormal data, and the partially abnormal data is adjusted accordingly, and the corresponding catalytic reforming unit simulation result is recorded as partially abnormal result; if the feed acquisition accuracy index is greater than or equal to the second feed acquisition threshold, the current feed data is recorded as normal data, and the corresponding catalytic reforming unit simulation result is recorded as a normal result.

[0039] After the catalytic reforming unit simulation is completed, the simulation data showing normal results are compared with the laboratory data. If the deviation between the simulation results and the laboratory data exceeds a preset deviation threshold, the system self-tuning is triggered. Using a sequential quadratic programming algorithm, with the laboratory data as the optimization target and combined with operating constraints, the conversion rate of the feed components under the action of the catalyst is iteratively corrected until the objective function converges, obtaining a high-fidelity molecular-level conversion rate, thus completing the model self-tuning and verification. Simulation data showing some abnormal results are compared with the laboratory data. If the deviation between the simulation results and the laboratory data exceeds a preset deviation threshold, a simulation anomaly warning is issued. If the deviation does not exceed the preset deviation threshold, it indicates that the correction of some abnormal data is satisfactory, and monitoring is then performed according to the gas chromatograph monitoring frequency during the next catalytic reforming unit simulation. If the simulation results show abnormal results, a simulation anomaly warning is issued.

[0040] The steps for adjusting abnormal data include: recording the difference between the second threshold for feed acquisition and the feed acquisition accuracy index as the feed acquisition deviation index; matching the feed acquisition deviation index with the monitoring frequency adjustment values ​​corresponding to each preset feed acquisition deviation index range in the catalytic reforming database to obtain the monitoring frequency adjustment value; forming a mapping relationship table in the catalytic reforming database where each feed acquisition deviation index range and monitoring frequency adjustment value correspond one-to-one, recording each feed acquisition deviation index range and its corresponding monitoring frequency adjustment value. These relationships can be one-to-one or many-to-one. When obtaining the monitoring frequency adjustment value, simply input the feed acquisition deviation index into the mapping relationship table, and the catalytic reforming database can quickly locate and return the monitoring frequency adjustment value corresponding to that feed acquisition deviation index. The same applies to the catalyst deactivation factor adjustment value, dehydrogenation activity factor adjustment value, isomerization activity factor adjustment value, and cracking activity factor adjustment value. The monitoring frequency adjustment value is superimposed with the current monitoring frequency of the gas chromatograph to obtain the monitoring frequency of the gas chromatograph during the next simulation of the catalytic reforming unit.

[0041] Furthermore, the abnormal adjustment of some abnormal data also includes: obtaining corresponding backup feed data based on the backup sensor of the feed data; aligning the backup feed data with the partial abnormal data in time based on the abnormal part of the partial abnormal data measured by the gas chromatograph; using the historical accuracy rate of the gas chromatograph as the confidence level of the partial abnormal data; using the complement of the historical accuracy rate of the gas chromatograph as the confidence level of the backup feed data; and correcting the partial abnormal data based on the aligned backup feed data, the confidence level of the backup feed data, and the confidence level of the partial abnormal data. For example, when using a mass spectrometer as a backup sensor for feed data, a dynamic time warping algorithm is used to time-align the data acquired by the gas chromatograph and the mass spectrometer. The historical accuracy rate of the gas chromatograph is obtained from the device simulation log. This historical accuracy rate is used as the confidence level of the gas chromatograph data, and the complement of the historical accuracy rate is used as the confidence level of the mass spectrometer data. The confidence level of the gas chromatograph data is multiplied by the gas chromatograph data to obtain weighted chromatographic data. The confidence level of the mass spectrometer data is multiplied by the mass spectrometer data to obtain weighted mass spectrometry data. Finally, the two sets of weighted data are summed to obtain the corrected partial abnormal data.

[0042] In this embodiment, the present invention classifies and determines data based on the accuracy index of feed acquisition, accurately identifying abnormal, partially abnormal, and normal data, providing reliable classification labels for simulation results. It also dynamically adjusts the gas chromatograph monitoring frequency based on the deviation index, enhancing the timeliness of data acquisition for the next catalytic reforming unit simulation. Simultaneously, it utilizes backup sensor data and time alignment technology, combined with confidence weights, to intelligently correct some abnormal data, effectively compensating for reaction rate simulation deviations caused by catalyst deactivation and significantly improving the accuracy of the catalytic reforming unit simulation results. This not only compensates for the activity decay deviation caused by catalyst carbon deposition and deactivation but also significantly improves the reliability of the overall simulation evaluation of the catalytic reforming unit through data-driven dynamic optimization.

[0043] Furthermore, the steps for state assessment of the catalytic reforming process based on catalytic state parameters include: obtaining stored catalytic state reference parameters and permissible deviations of catalytic state parameters from a pre-set catalytic reforming database. The catalytic state reference parameters include a reference hydrogen-to-hydrogen ratio, a reference reforming product composition ratio, and a reference catalytic temperature. The permissible deviations of the catalytic state parameters include permissible deviations of the hydrogen-to-hydrogen ratio, reforming product composition ratio, and catalytic temperature. The catalytic state parameters for each reaction stage are then subjected to deviation processing compared to the corresponding catalytic state reference parameters to obtain the actual deviations of the catalytic state parameters for each reaction stage. The actual deviations of the catalytic state parameters include actual deviations of the hydrogen-to-hydrogen ratio, reforming product composition ratio, and catalytic temperature. The reaction stages include six-membered cycloalkane dehydrogenation, five-membered cycloalkane dehydrogenation isomerization, alkane dehydrogenation cyclization, isomerization reactions, and addition reactions. Hydrogen cracking reaction; the actual deviations of catalytic state parameters at each reaction stage are compared with the allowable deviations of the corresponding catalytic state parameters at each reaction stage to obtain the catalytic state parameter influence parameters for each reaction stage. The catalytic state parameter influence parameters include the influence parameters of hydrogen-to-hydrogen ratio, reforming product composition ratio, and catalytic temperature. The catalytic state parameter influence parameters are weighted and coupled using the contribution data of catalytic state parameters, and then the reciprocal of the weighted coupling results is calculated to obtain the catalytic state evaluation index for each reaction stage. The catalytic state evaluation index represents the quantitative data of the stability of the catalytic reforming process state jointly contributed by the catalytic state parameters, including hydrogen-to-hydrogen ratio, reforming product composition ratio, and catalytic temperature; the catalytic state parameter contribution data include the contribution of hydrogen-to-hydrogen ratio, the contribution of reforming product composition ratio, and the contribution of catalytic temperature.

[0044] The catalytic state assessment indices for each reaction stage are obtained as follows:

[0045] ;

[0046] In the formula, a 2iβ4 represents the catalytic state assessment index for the i-th reaction stage, β5 represents the contribution of the hydrogen-to-hydrogen ratio, β6 represents the contribution of the reforming product composition ratio, and β7 represents the contribution of the catalytic temperature.

[0047] r i The hydrogen-to-hydrogen ratio in the i-th reaction stage can be obtained by measuring the ratio of hydrogen to reforming product using equipment such as gas chromatograph and comparing the results. r1 represents the reference hydrogen-to-hydrogen ratio, and r2 represents the allowable deviation of the hydrogen-to-hydrogen ratio.

[0048] h i The ratio of the reforming product composition in the i-th reaction stage is the ratio of aromatic hydrocarbons to isoalkanes, which can be directly measured using equipment such as gas chromatographs. h1 represents the reference reforming product composition ratio, and h2 represents the allowable deviation of the reforming product composition ratio.

[0049] c i The catalytic temperature of the i-th reaction stage can be directly measured by an infrared thermometer or other equipment. The catalytic state parameters can be obtained directly from the model operation log in the catalytic reforming model. c1 represents the reference catalytic temperature and c2 represents the allowable deviation of the catalytic temperature.

[0050] In the catalytic reforming database, β4, β5, and β6 represent the contributions of the hydrogen-to-hydrogen ratio, reformate composition ratio, and catalytic temperature, respectively. These contributions quantitatively characterize the degree to which these catalytic state parameters contribute to the catalytic state assessment index. Specifically, independent mapping tables are configured for the hydrogen-to-hydrogen ratio, reformate composition ratio, and catalytic temperature, containing one-to-one or many-to-one correspondences. These tables record each possible catalytic state parameter value and its corresponding contribution. In practical applications, the real-time measured hydrogen-to-hydrogen ratio, reformate composition ratio, and catalytic temperature are input into their respective mapping tables, and their corresponding contributions are automatically matched. The contribution value ranges from 0 to 1.

[0051] In this embodiment, the hydrogen-to-hydrocarbon ratio, reformate composition ratio, and catalytic temperature are interrelated. For example, when the dehydrogenation activity factor remains constant, a higher hydrogen-to-hydrocarbon ratio indicates less feed data, resulting in a relative surplus of hydrogen during the catalytic reforming reaction. This excess hydrogen will preferentially participate in the hydrocracking reaction rather than inhibit coking, instead inhibiting the aromatization reaction, leading to a decrease in the reformate composition ratio. Conversely, a lower hydrogen-to-hydrocarbon ratio indicates more feed data and a relative shortage of hydrogen, promoting the dehydrogenation reaction while increasing the risk of coking, leading to enhanced aromatization and an increase in the reformate composition ratio. A higher catalytic temperature promotes endothermic reactions such as the dehydrogenation of six-membered cycloalkanes, resulting in increased aromatics production and an increased reformate composition ratio. Conversely, a lower catalytic temperature promotes exothermic reactions such as hydrocracking, resulting in increased isoalkanes and a decreased reformate composition ratio.

[0052] like Figure 3 The diagram shows a flowchart of the catalytic reforming state assessment provided in an embodiment of this application. The assessment index is the catalytic state assessment index for each reaction stage, and the threshold is the catalytic state assessment threshold. The catalytic state assessment index for each reaction stage is compared with the catalytic state assessment threshold. If the catalytic state assessment index is greater than or equal to the catalytic state assessment threshold, no additional operation is performed. If the catalytic state assessment index for a certain reaction stage is less than the catalytic state assessment threshold, the catalyst deactivation factor is dynamically adjusted according to the catalytic state assessment index; the cracking activity factor and isomerization activity factor are dynamically adjusted according to the reforming product composition ratio; and the dehydrogenation activity factor is dynamically adjusted according to the hydrogen-to-hydrocarbon ratio.

[0053] Specifically, the steps for determining whether to perform state anomaly adjustment based on the obtained state simulation results include: obtaining the catalytic state assessment threshold and hydrogen-to-hydrogen ratio standard range from the preset catalytic reforming database; comparing the catalytic state assessment index of each reaction stage with the catalytic state assessment threshold; if the catalytic state assessment index is greater than or equal to the catalytic state assessment threshold, no additional operation is performed; if the catalytic state assessment index of a certain reaction stage is less than the catalytic state assessment threshold, the catalyst deactivation factor is dynamically adjusted according to the catalytic state assessment index, the cracking activity factor and isomerization activity factor are dynamically adjusted according to the reforming product composition ratio, and the dehydrogenation activity factor is dynamically adjusted according to the hydrogen-to-hydrogen ratio.

[0054] The step of dynamically adjusting the catalyst deactivation factor based on the catalytic state assessment index includes: recording the difference between the catalytic state assessment threshold and the catalytic state assessment index as the catalytic state deviation value; matching the catalytic state deviation value with the catalyst deactivation factor adjustment value corresponding to each preset catalytic state deviation range in the catalytic reforming database; and dynamically adjusting the catalyst deactivation factor of the next reaction stage based on the matched catalyst deactivation factor adjustment value.

[0055] The adjustment steps for the dynamic dehydrogenation activity factor based on the hydrogen-to-hydrogen ratio include: when the hydrogen-to-hydrogen ratio is lower than the minimum value of the preset standard range, the difference between the minimum value of the standard range and the hydrogen-to-hydrogen ratio is recorded as a negative deviation value. This negative deviation value is matched with the upward adjustment values ​​of the dehydrogenation activity factor corresponding to each preset negative deviation range of the hydrogen-to-hydrogen ratio in the catalytic reforming database. The dehydrogenation activity factor for the next reaction stage is dynamically adjusted based on the matched upward adjustment value. If the hydrogen-to-hydrogen ratio is still lower than the minimum value of the standard range after adjusting the dehydrogenation activity factor to the preset upper limit, a catalytic reaction is initiated. Catalyst metal function deactivation warning: When the hydrogen-to-hydrogen ratio is higher than the maximum value of the preset standard range for hydrogen-to-hydrogen ratio, the difference between the hydrogen-to-hydrogen ratio and the maximum value of the standard range for hydrogen-to-hydrogen ratio is recorded as the positive deviation value of the hydrogen-to-hydrogen ratio. The positive deviation value of the hydrogen-to-hydrogen ratio is matched with the down-adjustment value of the dehydrogenation activity factor corresponding to each preset positive deviation range of hydrogen-to-hydrogen ratio in the catalytic reforming database. The dehydrogenation activity factor of the next reaction stage is dynamically adjusted according to the matched down-adjustment value of the dehydrogenation activity factor. If the hydrogen-to-hydrogen ratio is still higher than the maximum value of the standard range for hydrogen-to-hydrogen ratio after the dehydrogenation activity factor is adjusted to the preset lower limit, an over-activation warning for the catalyst metal function is issued.

[0056] The steps for dynamically adjusting the cracking activity factor and isomerization activity factor based on the reforming product composition ratio include: when the reforming product composition ratio is lower than the minimum value of the preset standard range for reforming product composition, the difference between the minimum value of the standard range for reforming product composition ratio and the reforming product composition ratio is recorded as the negative deviation value of the product ratio. This negative deviation value is matched with the preset upward adjustment value of the cracking activity factor and the downward adjustment value of the isomerization activity factor corresponding to each negative deviation range of the product ratio in the catalytic reforming database. The cracking activity factor and isomerization activity factor for the next reaction stage are dynamically adjusted according to the matched upward adjustment value of the cracking activity factor and the downward adjustment value of the isomerization activity factor. If the reforming product composition ratio is still lower than the minimum value of the standard range for reforming product composition after adjusting the cracking activity factor to the preset upper limit, a catalyst acidic function deactivation warning is issued. If the reforming product composition ratio is still lower than the minimum value of the standard range for reforming product composition after adjusting the isomerization activity factor to the preset lower limit, then... The system issues a warning about overactivation of the catalyst's isomerization function. When the reforming product composition ratio is higher than the maximum value of the preset standard range for reforming product composition, the difference between the reforming product composition ratio and the maximum value of the standard range for reforming product composition ratio is recorded as a positive deviation value for the product ratio. This positive deviation value is matched with the downward adjustment value of the cracking activity factor and the upward adjustment value of the isomerization activity factor corresponding to each preset positive deviation range for product ratio in the catalytic reforming database. Based on the matched downward adjustment value of the cracking activity factor and the upward adjustment value of the isomerization activity factor, the cracking activity factor and the isomerization activity factor for the next reaction stage are dynamically adjusted. If the reforming product composition ratio is still higher than the maximum value of the standard range for reforming product composition after adjusting the cracking activity factor to the preset lower limit, a warning about overactivation of the catalyst's acidic function is issued. If the reforming product composition ratio is still higher than the maximum value of the standard range for reforming product composition after adjusting the isomerization activity factor to the preset upper limit, a warning about deactivation of the catalyst's isomerization function is issued.

[0057] In this embodiment, the isomerization activity factor is a parameter characterizing the catalyst's ability to promote isomerization reactions. During catalytic reforming, metal function and acid function are two key active components of the catalyst. Metal function primarily promotes dehydrogenation and aromatization reactions, with typical reactions including the dehydrogenation of cycloalkanes to aromatics and the dehydrogenation of alkanes to alkenes. Deactivation is manifested by a decrease in the hydrogen-to-hydrogen ratio, a reduction in aromatic yield, and a decrease in hydrogen production. Acid function primarily promotes isomerization and cracking reactions, with typical reactions including the isomerization of n-alkanes to branched alkanes and the hydrocracking of long-chain alkanes to short-chain alkanes. Deactivation is manifested by a decrease in the proportion of isoalkanes, a decrease in the octane number of the products, and a reduction in cracking products. During catalytic reforming, metal function is mainly responsible for generating aromatics, while acid function is mainly responsible for generating isoalkanes; their synergy is essential for achieving optimal product distribution. This invention first calculates the catalytic state assessment index using catalytic state parameters, enabling rapid location and adjustment of catalyst activity. Combined with dynamic comparative analysis of the hydrogen-to-hydrogen ratio and reformate composition ratio, it accurately identifies specific causes of anomalies, including overactivation and deactivation of catalyst metal and acid functions. During catalytic reforming simulation in a catalytic reforming unit, by comparing the catalytic state assessment index at each reaction stage with thresholds and flexibly adjusting the catalyst deactivation factor, isomerization activity factor, and dehydrogenation activity factor based on deviations in the hydrogen-to-hydrogen ratio and reformate composition ratio, reaction conditions can be optimized in real time, slowing down catalyst deactivation due to carbon deposition, and achieving adaptive adjustment based on catalyst activity. Compared to traditional simulation models with constant catalyst activity, this invention significantly reduces simulation bias caused by neglecting catalyst deactivation by introducing a dynamic catalyst state assessment and feedback adjustment mechanism, making performance evaluation closer to actual operating conditions. Especially under conditions of high reformate composition ratio or fluctuating hydrogen-to-hydrogen ratio, it can dynamically compensate for activity loss, extend catalyst life, and improve the accuracy of catalytic reforming unit simulation.

[0058] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0059] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0060] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for simulation and optimization of a molecular catalytic reformer, characterized in that, The method comprises: Based on the feed data acquisition analysis parameter, the accuracy of the feed data measured by the gas chromatograph is evaluated, and the feed data acquisition analysis parameter is used to describe the sampling interval time control during the sampling process of the gas chromatograph; Based on the obtained accuracy evaluation result, the feed data is marked, the feed data measured by the gas chromatograph is dynamically marked based on the marked gas chromatograph analysis data, and the molecular composition of the raw material is obtained; Based on the catalytic state parameter, the state of the catalytic reforming process is evaluated, and based on the obtained state simulation result, it is judged whether to perform state abnormal adjustment, the catalytic state parameter is used to describe the effect of the catalytic reforming process in the catalytic reforming device, and the state abnormal adjustment represents dynamic adjustment of the catalyst deactivation factor, isomerization activity factor, dehydrogenation activity factor and cracking activity factor in the catalytic reforming process of the catalytic reforming device.

2. The method of claim 1, wherein the catalyst is a molecular sieve catalyst. The step of evaluating the accuracy of the feed data measured by the gas chromatograph based on the feed data acquisition analysis parameter comprises: Obtain the feed data acquisition analysis parameter reference data from the preset catalytic reforming database, specifically including: critical sampling interval coverage, critical maximum sampling interval and critical sampling delay; The sampling interval coverage, the critical maximum sampling interval and the critical sampling delay are respectively operated with the critical sampling interval coverage, the maximum sampling interval and the sampling delay, and then the proportion approaching degree operation result is weighted and processed by using the feed data acquisition analysis parameter contribution degree data, the weighted processing result is coupled, and the feed collection accuracy index is obtained, which represents the accuracy degree quantization data of the feed data measured by the gas chromatograph jointly measured by the feed data acquisition analysis parameter; The feed data acquisition analysis parameter includes sampling interval coverage, maximum sampling interval and sampling delay; The feed data acquisition analysis parameter contribution degree data includes sampling interval coverage contribution degree, maximum sampling interval contribution degree and sampling delay contribution degree.

3. The method of claim 2, wherein the catalyst is a molecular sieve catalyst. The step of marking the feed data based on the obtained accuracy evaluation result comprises: Obtain the feed collection first threshold and the feed collection second threshold from the preset catalytic reforming database; Compare the feed collection accuracy index with the feed collection first threshold and the feed collection second threshold respectively, if the feed collection accuracy index is less than the feed collection first threshold, the current feed data is recorded as abnormal data, and the corresponding catalytic reforming device simulation result is recorded as abnormal result; If the feed collection accuracy index is greater than or equal to the feed collection first threshold and less than the feed collection second threshold, the current feed data is recorded as partial abnormal data, and the partial abnormal data is adjusted, and the corresponding catalytic reforming device simulation result is recorded as partial abnormal result; If the feed collection accuracy index is greater than or equal to the feed collection second threshold, the current feed data is recorded as normal data, and the corresponding catalytic reforming device simulation result is recorded as normal result.

4. The method of claim 3, wherein the catalyst is selected from the group consisting of platinum, palladium, rhodium, ruthenium, iridium, osmium, rhenium, gold, silver, copper, zinc, cadmium, mercury, and combinations thereof. The step of adjusting the partial abnormal data comprises: The difference between the second threshold value of the feed collection and the feed collection accuracy index is denoted as a feed collection deviation index; The feed collection deviation index is matched with a monitoring frequency adjustment value corresponding to each feed collection deviation index range in the preset catalytic reforming database to obtain the monitoring frequency adjustment value, and the monitoring frequency adjustment value is superimposed with the current monitoring frequency of the gas chromatograph to obtain the monitoring frequency of the gas chromatograph in the next catalytic reforming device simulation.

5. The method of claim 3, wherein the catalyst is selected from the group consisting of platinum, palladium, rhodium, ruthenium, iridium, osmium, rhenium, gold, silver, copper, zinc, cadmium, mercury, and combinations thereof. The step of performing abnormal adjustment on the partial abnormal data further includes: The corresponding backup feed data is obtained according to the backup sensor of the feed data, the backup feed data is time-aligned with the corresponding marked partial abnormal data, the historical accuracy of the gas chromatograph is taken as the confidence of the partial abnormal data, the complement of the historical accuracy of the gas chromatograph is taken as the confidence of the backup feed data, and the partial abnormal data is corrected according to the aligned backup feed data, the confidence of the backup feed data and the confidence of the partial abnormal data.

6. The method of claim 1, wherein the method is characterized by: The step of performing state evaluation on the catalytic reforming process based on the catalytic state parameter includes: The catalytic state reference parameter and the catalytic state parameter allowable deviation are obtained from the preset catalytic reforming database, the catalytic state reference parameter includes the reference hydrogen hydrocarbon ratio, the reference reformate composition ratio and the reference catalytic temperature, and the catalytic state parameter allowable deviation includes the hydrogen hydrocarbon ratio allowable deviation, the reformate composition ratio allowable deviation and the catalytic temperature allowable deviation; The catalytic state parameter actual deviation of each reaction stage is obtained by performing deviation processing on the catalytic state parameter of each reaction stage and the corresponding catalytic state reference parameter of each reaction stage, the catalytic state parameter actual deviation includes the hydrogen hydrocarbon ratio actual deviation, the reformate composition ratio actual deviation and the catalytic temperature actual deviation, and the reaction stage includes the hydrogenation stage, the dehydrogenation stage, the isomerization stage and the aromatization stage; The catalytic state parameter influence parameter of each reaction stage is obtained by performing comparison processing on the catalytic state parameter actual deviation of each reaction stage and the corresponding catalytic state parameter allowable deviation, the catalytic state parameter influence parameter includes the hydrogen hydrocarbon ratio influence parameter, the reformate composition ratio influence parameter and the catalytic temperature influence parameter; The catalytic state evaluation index of each reaction stage is obtained by performing weighting coupling processing on the catalytic state parameter influence parameter using the catalytic state parameter contribution degree data, and then performing reciprocal operation on the weighting coupling processing result. The catalytic state evaluation index represents the stability degree quantitative data of the catalytic state parameter on the state of the catalytic reforming process, and the catalytic state parameter includes the hydrogen hydrocarbon ratio, the reformate composition ratio and the catalytic temperature. The catalytic state parameter contribution degree data includes the hydrogen hydrocarbon ratio contribution degree, the reformate composition ratio contribution degree and the catalytic temperature contribution degree.

7. The method of claim 6, wherein the method further comprises: The step of judging whether to perform state abnormal adjustment based on the obtained state simulation result includes: The catalytic state evaluation threshold and the hydrogen hydrocarbon ratio standard range are obtained from the preset catalytic reforming database; The catalytic state evaluation index of each reaction stage is compared with the catalytic state evaluation threshold, and if the catalytic state evaluation index is greater than or equal to the catalytic state evaluation threshold, no additional operation is performed. If the catalytic state evaluation index of a reaction stage is less than the catalytic state evaluation threshold, the catalyst deactivation factor is dynamically adjusted according to the catalytic state evaluation index, the dehydrogenation activity factor is dynamically adjusted according to the hydrogen to hydrocarbon ratio, and the cracking activity factor and the isomerization activity factor are dynamically adjusted according to the reformate composition ratio.

8. The method of claim 7, wherein the method further comprises: The step of dynamically adjusting the catalyst deactivation factor according to the catalytic state evaluation index comprises: The difference between the catalytic state evaluation threshold and the catalytic state evaluation index is recorded as a catalytic state deviation value, the catalytic state deviation value is matched with the catalyst deactivation factor adjustment value corresponding to each catalytic state deviation range preset in the catalytic reforming database, and the catalyst deactivation factor of the next reaction stage is dynamically adjusted according to the matched catalyst deactivation factor adjustment value.

9. The method of claim 7, wherein the method further comprises: The step of dynamically adjusting the dehydrogenation activity factor according to the hydrogen to hydrocarbon ratio comprises: When the hydrogen to hydrocarbon ratio is lower than the minimum value of the preset hydrogen to hydrocarbon ratio standard range, the difference between the minimum value of the hydrogen to hydrocarbon ratio standard range and the hydrogen to hydrocarbon ratio is recorded as a hydrogen to hydrocarbon ratio negative deviation value, the hydrogen to hydrocarbon ratio negative deviation value is matched with the dehydrogenation activity factor up-regulation value corresponding to each hydrogen to hydrocarbon ratio negative deviation range preset in the catalytic reforming database, the dehydrogenation activity factor of the next reaction stage is dynamically adjusted according to the matched dehydrogenation activity factor up-regulation value, and if the dehydrogenation activity factor is adjusted to the preset upper limit and the hydrogen to hydrocarbon ratio is still lower than the minimum value of the hydrogen to hydrocarbon ratio standard range, a catalyst metal function deactivation prompt is issued. When the hydrogen to hydrocarbon ratio is higher than the maximum value of the preset hydrogen to hydrocarbon ratio standard range, the difference between the hydrogen to hydrocarbon ratio and the maximum value of the hydrogen to hydrocarbon ratio standard range is recorded as a hydrogen to hydrocarbon ratio positive deviation value, the hydrogen to hydrocarbon ratio positive deviation value is matched with the dehydrogenation activity factor down-regulation value corresponding to each hydrogen to hydrocarbon ratio positive deviation range preset in the catalytic reforming database, the dehydrogenation activity factor of the next reaction stage is dynamically adjusted according to the matched dehydrogenation activity factor down-regulation value, and if the dehydrogenation activity factor is adjusted to the preset lower limit and the hydrogen to hydrocarbon ratio is still higher than the maximum value of the hydrogen to hydrocarbon ratio standard range, a catalyst metal function over-activation prompt is issued.

10. The method of claim 7, wherein the method further comprises: The step of dynamically adjusting the cracking activity factor and the isomerization activity factor according to the reformate composition ratio comprises: When the reformate composition ratio is lower than the minimum value of the preset reformate composition standard range, the difference between the minimum value of the reformate composition standard range and the reformate composition ratio is recorded as a product ratio negative deviation value, the product ratio negative deviation value is matched with the cracking activity factor up-regulation value and the isomerization activity factor down-regulation value corresponding to each product ratio negative deviation range preset in the catalytic reforming database, the cracking activity factor and the isomerization activity factor of the next reaction stage are dynamically adjusted according to the matched cracking activity factor up-regulation value and the isomerization activity factor down-regulation value, respectively, if the cracking activity factor is adjusted to the preset upper limit and the reformate composition ratio is still lower than the minimum value of the reformate composition standard range, a catalyst acid function deactivation prompt is issued, and if the isomerization activity factor is adjusted to the preset lower limit and the reformate composition ratio is still lower than the minimum value of the reformate composition standard range, a catalyst isomerization function over-activation prompt is issued. When the reforming product composition ratio is higher than the preset maximum value of the reforming product composition standard range, the difference between the reforming product composition ratio and the maximum value of the reforming product composition standard range is recorded as a product ratio positive deviation value, the product ratio positive deviation value is matched with a cracking activity factor down-regulation value and an isomerization activity factor up-regulation value corresponding to each product ratio positive deviation range in the preset catalytic reforming database, and the cracking activity factor and the isomerization activity factor of the next reaction stage are dynamically adjusted according to the matched cracking activity factor down-regulation value and the isomerization activity factor up-regulation value, respectively. If the reforming product composition ratio is still higher than the maximum value of the reforming product composition standard range after the cracking activity factor is adjusted to the preset lower limit, a catalyst acid function over-activation prompt is issued. If the reforming product composition ratio is still higher than the maximum value of the reforming product composition standard range after the isomerization activity factor is adjusted to the preset upper limit, a catalyst isomerization function over-activation prompt is issued.

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