Method of determining device operating state
By breaking down the petrochemical unit into subsystems, constructing a pre-defined database, and utilizing interpolation algorithms, feed and operating parameters can be obtained in real time, enabling rapid assessment of the unit's status. This solves the problems of high assessment costs and long assessment times in existing technologies, and improves both safety and economy.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA PETROLEUM & CHEMICAL CORP
- Filing Date
- 2024-12-10
- Publication Date
- 2026-06-12
Smart Images
Figure CN122194867A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of petrochemical production technology, and more specifically, to a method for determining the operating status of an apparatus. Background Technology
[0002] In the field of petrochemical production technology, in order to ensure production safety and maximize economic benefits, it is necessary to assess the operating status of petrochemical plants during the production process.
[0003] In related technologies, large-scale process simulation software is generally deployed online to simulate and evaluate the operating status of petrochemical plants, which has problems such as high cost and long evaluation time. Summary of the Invention
[0004] The purpose of this disclosure is to provide a method for determining the operating state of a device to solve the aforementioned technical problems.
[0005] To achieve the above objectives, the first aspect of this disclosure provides a method for determining the operating state of a device, the method comprising: Real-time determination of the feed information of the target device during the production process; The theoretical operating state value of the target device is determined based at least on the feeding information and the target information in the preset database. The preset database stores information indicating the theoretical operating state value of the target device under different feeding information. The theoretical operating state value is used to characterize the operating parameter value of the target device under the corresponding feeding information. The theoretical operating state of the target device is determined based on the theoretical operating state value.
[0006] Optionally, the real-time determination of the target device's feed information during the production process includes: The distributed control system deployed at the target device site acquires material flow and material composition information of the target device in real time during the production process. The material composition information is used to indicate the chemical composition and / or physical state distribution of the material. Based on the material flow rate information and the material composition information, the feeding information of the target device is determined.
[0007] Optionally, determining the theoretical operating state value of the target device based at least on the feed information and target information in a preset database includes: When no information for indicating the theoretical operating state value corresponding to the feed information exists in the preset database, at least two target feed information similar to the feed information are determined in the preset database, and a first interpolation variable is determined in the feed information according to the process flow of the target device. Based on the target feed information, the theoretical operating state value corresponding to the target feed information, and the preset interpolation algorithm, a first interpolation model is constructed; The theoretical operating state value of the target device is determined based on the first interpolation variable and the first interpolation model.
[0008] Optionally, the target device includes a subsystem, which is obtained by decomposing the target device according to the process flow of the target device; the preset interpolation algorithm is determined according to the characteristics of the subsystem. When the relationship between the interpolation variable and the feed in the feed information in the subsystem is linear, the preset interpolation algorithm is a linear interpolation algorithm; when the relationship between the interpolation variable and the feed in the feed information in the subsystem is polynomial, the preset interpolation algorithm is a polynomial interpolation algorithm; when the interpolation variable and the feed component distribution in the feed information in the subsystem are correlated, the preset interpolation algorithm is inverse distance weighted interpolation.
[0009] Optionally, the method further includes: The distributed control system deployed at the target device site acquires the actual operating parameter values of the target device during the production process in real time. The step of determining the theoretical operating state value of the target device based at least on the feed information and target information in a preset database includes: If no information for indicating the theoretical operating state value corresponding to the feed information is found in the preset database, at least two target feed information similar to the feed information are determined in the preset database, and a second interpolation variable is determined in the feed information and the actual operating parameter value according to the process flow of the target device. A second interpolation model is constructed based on the target feed information, the theoretical operating state value corresponding to the target feed information, and a preset interpolation algorithm. The theoretical operating state value of the target device is determined based on the second interpolation variable and the second interpolation model.
[0010] Optionally, the preset database includes multiple databases, which are obtained in the following manner: According to the technological process of the target device, the target device is decomposed into several subsystems; For each subsystem, a rigorous mechanistic model of the subsystem is established based on the subsystem's process flow and chemical reaction principle; the design parameters and pre-constructed theoretical feed information of the subsystem are obtained, and the design parameters and theoretical feed information are used as inputs to the rigorous mechanistic model to perform steady-state process simulation of the subsystem under the theoretical feed information to obtain theoretical operating state values; a preset database of the subsystem is constructed based on the theoretical feed information and theoretical operating state values.
[0011] Optionally, the method further includes: The operating parameter values of the target device during the production process are acquired in real time through a distributed control system deployed at the target device site; Based on the operating parameter values, calculate the actual operating status values of the target device during the production process; The deviation between the theoretical operating state value and the actual operating state value is calculated, and the operating parameter values of the target device are adjusted according to the deviation so that the actual operating state value is closer to the theoretical operating state value.
[0012] A second aspect of this disclosure provides a system for determining the operating state of an apparatus, comprising: The first determining module is used to determine the feeding information of the target device in real time during the production process; The second determining module is used to determine the theoretical operating state value of the target device based at least on the feeding information and the target information in the preset database, wherein the preset database stores information indicating the theoretical operating state value of the target device under different feeding information, and the theoretical operating state value is used to characterize the operating parameter value of the target device under the corresponding feeding information; The third determining module is used to determine the theoretical operating state of the target device based on the theoretical operating state value.
[0013] A third aspect of this disclosure provides a non-transitory computer-readable storage medium having a computer program stored thereon that, when executed by a processing device, implements the steps of the method described in any of the first aspects.
[0014] A fourth aspect of this disclosure provides an electronic device, comprising: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method of any one of the first aspects.
[0015] The fifth aspect of this disclosure provides a computer program product including a computer program that, when executed by a processor, implements the steps of the method described in any of the first aspects.
[0016] Through the above technical solution, information indicating the theoretical operating status value of the target device under different feeding information can be stored in a preset database in advance. Thus, after obtaining the actual feeding information of the target device, the target theoretical operating status value corresponding to the actual feeding information can be obtained according to the target information and the actual feeding information stored in the preset database. Then, based on the theoretical operating status value, the theoretical operating status that can truly reflect the real-time status of the target device can be quickly determined, thereby improving the safety of the production process.
[0017] Other features and advantages of this disclosure will be described in detail in the following detailed description section. Attached Figure Description
[0018] The accompanying drawings are provided to further illustrate the present disclosure and form part of the specification. They are used together with the following detailed description to explain the present disclosure, but do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart illustrating a method for determining the operating state of a device according to an exemplary embodiment of the present disclosure; Figure 2 This is a flowchart illustrating another method for determining the operating state of a device according to an exemplary embodiment of the present disclosure; Figure 3 This is a schematic diagram illustrating an ethylene plant divided into multiple subsystems according to an exemplary embodiment of the present disclosure; Figure 4 This is a block diagram illustrating a system for determining the operating state of a device according to an exemplary embodiment of the present disclosure; Figure 5 This is a block diagram illustrating an electronic device according to an exemplary embodiment of the present disclosure; Figure 6 This is a block diagram illustrating another electronic device according to an exemplary embodiment of the present disclosure.
[0019] Explanation of reference numerals in the attached figures 1. Quenching system; 2. Cracking gas compression system; 3. High and low pressure propane removal tower system; 4. Cryogenic separation system; 5. Ethylene refrigeration system; 6. Propylene tower system; 7. Butane removal tower system. Detailed Implementation
[0020] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.
[0021] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.
[0022] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.
[0023] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.
[0024] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".
[0025] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.
[0026] As mentioned in the background section, related technologies typically employ online deployment of large-scale process simulation software to simulate and evaluate the operational status of petrochemical plants. However, the high purchase and maintenance costs of such software increase the overall evaluation cost. Furthermore, complex simulations require significant time to complete, reducing the efficiency of operational status assessment.
[0027] For example, when assessing the operational status of an ethylene plant using large-scale process simulation software, it is necessary to establish a rigorous steady-state process simulation of the ethylene plant and combine it with a mechanistic model of the ethylene plant's cracking furnace to conduct a real-time online simulation of the entire plant. Due to the complexity of the ethylene plant's process flow, involving complex cracking reactions in the cracking furnace and multi-cycle cryogenic separation, the calculation convergence time is typically greater than 20 minutes, which cannot meet the needs of rapid on-site analysis of the plant's operational status.
[0028] In view of this, the present disclosure provides a method for determining the operating state of a device to solve the above-mentioned technical problems.
[0029] The embodiments of this disclosure will be further explained below with reference to the accompanying drawings.
[0030] Figure 1 This is a flowchart illustrating a method for determining the operating state of a device according to an exemplary embodiment of the present disclosure, with reference to... Figure 1 The method for determining the operating status of the device may include the following steps: S101: Real-time determination of the feed information of the target device during the production process.
[0031] For example, the material flow rate and composition information of the target unit during the production process can be acquired in real time through a distributed control system (DCS) deployed at the target unit site. The material flow rate information can indicate the flow rate of materials at different production stages, such as the flow rate of product streams at the end of a separation process, the flow rate of intermediate products, and the flow rate of recycled products. The material composition information can indicate the chemical composition of the material (i.e., the types and proportions of elements and compounds contained in the material. For example, in petrochemical products, this may include elements such as carbon, hydrogen, sulfur, and nitrogen, as well as various hydrocarbon compounds formed from them) and / or the distribution of their physical states (e.g., solid, liquid, or gaseous). Then, based on the acquired material flow rate and composition information, the feed information of the target unit is determined according to the principles of material balance, energy balance, flow conservation, and / or component conservation. That is to say, in possible implementations, real-time determination of the feed information of the target unit during the production process may include: The distributed control system deployed at the target device site acquires material flow and composition information in real time during the production process of the target device. The material composition information is used to indicate the chemical composition and / or physical state distribution of the material. Based on the material flow and composition information, the feed information of the target device is determined.
[0032] The feed information may include the feed ratio and / or feed composition (e.g., crude oil, natural gas, heavy oil, light hydrocarbons, etc.). The target unit may be a petrochemical unit with typical chemical reactions or typical separation unit processes, such as an ethylene unit, a catalytic cracking unit, a steam cracking unit, or an ethylene glycol unit. It may also be a subsystem or sub-equipment within a petrochemical unit that processes a specific process; this disclosure does not impose any limitations on this. When the target unit is a subsystem that processes a specific process, the petrochemical unit can be pre-divided into several subsystems according to the petrochemical unit's process flow. Then, a distributed control system deployed at the petrochemical unit site can acquire the material flow and composition information of the petrochemical unit in real time during the production process. Finally, the feed information for each subsystem can be determined based on the material flow and composition information.
[0033] S102: Determine the theoretical operating state value of the target device based at least on the feed information and the target information in the preset database. The preset database stores information indicating the theoretical operating state value of the target device under different feed information. The theoretical operating state value is used to characterize the operating parameter value of the target device under the corresponding feed information.
[0034] The theoretical operating state values can be determined based on actual conditions, and this disclosure does not impose any limitations on them. For example, the theoretical operating state values may include primary measurement parameters of the DCS (such as temperature, pressure, flow rate, and liquid level) and parameters calculated based on the primary measurement parameters to reflect the operating state, such as heat exchanger heat load, distillation column reflux ratio, pump and compressor effective power, etc.
[0035] The preset database can be obtained by constructing a rigorous mechanistic model of the target device and performing steady-state process simulation based on the pre-constructed feed information.
[0036] In one possible approach, to simplify the complexity of the rigorous mechanistic model and accelerate process simulation, the target device can be pre-decomposed into several subsystems based on its technological flow. Then, a rigorous mechanistic model can be constructed for each subsystem using process simulation software (such as PROII or ASPEN). Based on the rigorous mechanistic model of each subsystem, its design parameters, and pre-built feed information, the theoretical operating state values of each subsystem under different feed conditions can be obtained. In other words, in one possible approach, the pre-set database can include multiple databases, which can be obtained as follows: Based on the process flow of the target device, the target device is decomposed into several subsystems. For each subsystem, a rigorous mechanistic model is established based on the process flow and chemical reaction principle of the subsystem. The design parameters and pre-constructed theoretical feed information of the subsystem are obtained, and the design parameters and theoretical feed information are used as inputs to the rigorous mechanistic model to simulate the steady-state process of the subsystem under the theoretical feed information to obtain the theoretical operating state value. Based on the theoretical feed information and theoretical operating state value, a pre-set database of the subsystem is constructed.
[0037] The design parameters can be set according to actual conditions, and this disclosure does not impose any restrictions on them. For example, in the cracked gas compression subsystem of a petrochemical plant, the design parameters can be temperature, pressure, and compressor power. In the cryogenic separation system 4 of the petrochemical plant, the design parameters can be temperature, pressure, and heat exchanger heat load, etc.
[0038] The above approach decomposes the target device into several subsystems, and constructs a rigorous mechanistic model for each subsystem. Compared to the overall circulating material flow of the target device, the circulating material flow within a subsystem is smaller. This allows for the convenient acquisition of theoretical feed information for the subsystem based on the flow rate and composition distribution of the circulating material flow, thereby simplifying the construction complexity of the pre-built database and improving its efficiency. Furthermore, since the process flow within the subsystems is relatively simple, the constructed rigorous mechanistic model is lightweight. This facilitates on-site software deployment and improves convergence time, further enhancing the efficiency of the pre-built database.
[0039] Once the preset database is constructed, the theoretical operating state value of the target device can be determined based at least on the feed information and the preset database.
[0040] Among possible methods, determining the theoretical operating state value of the target device based at least on the feed information and target information in a preset database may include: When no information for indicating the theoretical operating state value corresponding to the feed information is found in the preset database, at least two target feed information similar to the feed information are determined in the preset database, and a first interpolation variable is determined in the feed information according to the process flow of the target device; a first interpolation model is constructed according to the target feed information, the theoretical operating state value corresponding to the target feed information and the preset interpolation algorithm; and the theoretical operating state value of the target device is determined according to the first interpolation variable and the first interpolation model.
[0041] The preset interpolation algorithm can be set according to actual conditions, and this embodiment does not impose any restrictions on it. In possible implementations, the preset interpolation algorithm can be obtained based on the relationship between the interpolation variable and the feed of the subsystem. For example, when the relationship between the interpolation variable and the feed in the feed information in the subsystem is linear, the preset interpolation algorithm can be set to a linear interpolation algorithm. When the relationship between the interpolation variable and the feed in the feed information in the subsystem is polynomial, the preset interpolation algorithm can be set to a polynomial interpolation algorithm. When the interpolation variable and the feed component distribution in the feed information in the subsystem are correlated, the preset interpolation algorithm can be set to inverse distance weighted interpolation.
[0042] For example, suppose a pre-defined database contains information on theoretical operating state values for different feed ratios (such as the ratio of ethane to propane). The feed information determined by the DCS includes ethane and propane, with ethane accounting for 60% and propane accounting for 40%. Furthermore, the database does not contain theoretical operating state values corresponding to 60% ethane and 40% propane. Therefore, at least two target feed information values similar to the given feed information can be determined from the pre-defined database based on the feed information. For example, the target preset database includes feed information 1, feed information 2, feed information 3, feed information 4, and feed information 5. Feed information 1 includes 20% ethane and 80% propane; feed information 2 includes 45% ethane and 55% propane; feed information 3 includes 50% ethane and 50% propane; feed information 4 includes 70% ethane and 30% propane; and feed information 5 includes 75% ethane and 25% propane. Since the ethane and propane percentages in feed information 3 and 4 are closest to those in the feed information, feed information 3 and 4 can be identified as target feed information similar to the target feed information. Then, independent variables (i.e., interpolation variables) can be determined in the feed information according to the process flow. For example, 60% ethane and 40% propane can be used as independent variables. A preset interpolation algorithm can then be determined based on the independent variables; for example, a linear interpolation algorithm can be used as the preset interpolation algorithm. Finally, linear interpolation can be performed between the two data points, feed information 3 and feed information 4, to obtain the dependent variable, which is the theoretical operating state value of the feed information.
[0043] It should be understood that this is merely illustrative and does not constitute a limitation on the proposed solution. In possible implementations, only a portion of the feed parameters in the feed information can be used as independent variables. For example, only the components that have a significant impact on the operating state of the subsystem can be used as independent variables, or the components with a high carbon content can be used as independent variables.
[0044] In possible implementations, the method for determining the operating state of the device may further include: The distributed control system deployed at the target device site acquires the actual operating parameter values of the target device during the production process in real time. Accordingly, based at least on the feed information and the target information in the preset database, the theoretical operating state value of the target device is determined, which may include: When no information corresponding to the theoretical operating state value of the feed information is found in the preset database, at least two target feed information similar to the feed information are determined in the preset database, and a second interpolation variable is determined in the feed information and actual operating parameter values according to the process flow of the target device; a second interpolation model is constructed according to the target feed information, the theoretical operating state value corresponding to the target feed information and the preset interpolation algorithm; and the theoretical operating state value of the target device is determined according to the second interpolation variable and the second interpolation model.
[0045] The operating parameter values can be determined according to actual conditions, and this disclosure does not impose any restrictions on them. For example, the operating parameter values can be temperature, pressure, flow rate, and liquid level, etc.
[0046] The inventors observed that, in actual production, the operating state of the target device is affected not only by the feed information but also by various other factors, including the actual operating parameters of the device. Therefore, to improve the accuracy of the theoretical operating state values, this embodiment constructs a more robust interpolation model by combining the feed information and actual operating parameters. This model is applicable to a wider range of operating conditions, thereby improving the accuracy of the theoretical operating state value prediction.
[0047] In this embodiment, since the target device is divided into multiple subsystems according to the process flow, the nonlinearity of the target device can be reduced. Therefore, for each subsystem, a reasonable interpolation method can be used to interpolate based on the relationship between the interpolation variable and the feed of the subsystem, thereby improving the accuracy and efficiency of interpolation.
[0048] S103: Determine the theoretical operating state of the target device based on the theoretical operating state value.
[0049] Through the above technical solution, information indicating the theoretical operating status value of the target device under different feeding information can be stored in a preset database in advance. Thus, after obtaining the actual feeding information of the target device, the target theoretical operating status value corresponding to the actual feeding information can be obtained according to the target information and the actual feeding information stored in the preset database. Then, based on the theoretical operating status value, the theoretical operating status that can truly reflect the real-time status of the target device can be quickly determined, thereby improving the safety of the production process.
[0050] Among the possible methods for determining the operating state of the device, the following may also be included: The distributed control system deployed at the target device site acquires the operating parameter values of the target device in real time during the production process; based on the operating parameter values, the actual operating state value of the target device during the production process is calculated; the deviation between the theoretical operating state value and the actual operating state value is calculated, and the operating parameter values of the target device are adjusted according to the deviation so that the actual operating state value is closer to the theoretical operating state value.
[0051] In this embodiment, adjusting the operating parameter value of the target device based on the deviation can be done automatically based on the deviation, or the equipment operator can determine a target operating parameter value based on the deviation and their own experience, and then adjust the current operating parameter value of the target device to the target operating parameter value.
[0052] The above technical solution can calculate the actual operating status value of the target device based on its actual operating parameter values. This allows for adjustments to the operating parameter values of the target device based on the deviation between the actual operating status value and the theoretical operating status value. In other words, it enables dynamic updates of operating parameter values based on changes in the distribution of raw materials and products on-site, thereby improving safety and economy in the production process.
[0053] To facilitate understanding of the method for determining the operating state of an apparatus provided in this disclosure, a possible implementation of the method for determining the operating state of an apparatus provided in this disclosure is described below using a petrochemical apparatus as an example: For example, such as Figure 2 As shown, the target unit can be pre-decomposed into three subsystems based on the petrochemical plant's process flow. For each subsystem, a rigorous mechanistic model can be constructed using process simulation software (such as PROII or ASPEN). Then, based on the rigorous mechanistic model, the subsystem's design parameters, and pre-constructed feed information, the theoretical operating state values of that subsystem under different feed information are obtained. After obtaining the theoretical operating state values of each subsystem, a theoretical operating state value database can be obtained based on the correspondence between the theoretical operating state values of each subsystem and the pre-constructed feed information.
[0054] After obtaining the theoretical operating status value database, for each subsystem, the material flow rate and material composition information of the subsystem during the production process can be read in real time from the DCS. Secondly, based on the material balance principle, energy balance principle, flow conservation principle, and / or component conservation principle, reverse calculations can be performed using the material flow rate and material composition information to obtain the actual feed information of the subsystem. Then, the theoretical operating status value is retrieved from the operating status value database based on the actual feed information. If a theoretical operating status value is matched, the operating parameter values of the subsystem during the production process can be read in real time from the DCS, and the actual operating status value of the subsystem during the production process can be calculated based on the operating parameter values. Finally, the deviation between the theoretical operating status value and the actual operating status value can be calculated, and the operating parameter values of the target device can be adjusted according to the deviation. If no theoretical operating status value is matched, the independent variable can be determined from the feed information, and then a preset interpolation algorithm can be obtained based on the relationship between the independent variable and the feed of the subsystem. Based on the preset interpolation algorithm and the independent variable, the dependent variable, i.e., the theoretical operating status value, can be obtained. Then, the operating parameter values of the subsystem during the production process can be read in real time from the DCS, and the actual operating status values of the subsystem during the production process can be calculated based on the operating parameter values. Finally, the deviation between the theoretical operating status values and the actual operating status values can be calculated, and the operating parameter values of the target device can be adjusted according to the deviation.
[0055] To facilitate a further understanding of the method for determining the operating state of an apparatus provided in the embodiments of this disclosure, the following description uses a process flow involving pre-propane removal during the separation of ethylene and other major products from other components in an ethylene plant as an example to illustrate this scheme: The pre-propane removal process can be described as follows: The cracked gas from the cracking furnace is gradually separated through a quenching, multi-stage compression, and cryogenic system, separating hydrogen, methane, ethylene, propylene, mixed C4, crude cracked gasoline, cracked diesel, and cracked fuel oil as products from different units. The first separation tower after multi-stage compression is the propane removal tower. Therefore, based on this process flow, to interrupt the circulating flow of the separation process and reduce the material supply pipelines between subsystems, the ethylene unit can be divided into seven subsystems: quenching system 1, cracked gas compression system 2, high and low pressure propane removal tower system 3, cryogenic separation system 4, ethylene refrigeration system 5, propylene tower system 6, and butane removal tower system 7. Figure 3As shown. For each of the above subsystems, a rigorous mechanistic model is established using process simulation software PROⅡ or ASPEN, and multiple sets of reasonable feed information are selected for steady-state process simulation. Specifically, the design parameters and feed information of each subsystem are used as input conditions for modeling to realize a process simulation mechanism model that conforms to the original design for a single system, thereby forming a theoretical operating state value database (i.e., a preset database). After forming the theoretical operating state value database, the feed components that have a significant impact on the operating state of each subsystem can be analyzed, while feed components with a smaller impact on the operating state are ignored, thus reducing the number of independent variables without affecting the accuracy of the operating state calculation. Subsequently, after obtaining the material flow information and material composition information fed back in real time by the DCS, the feed information of each subsystem can be calculated in reverse according to principles such as material balance. After obtaining the feed information, the feed components that have a significant impact on the operating state of each subsystem can be used as independent variables (i.e., interpolation variables) in the feed information, and interpolated in the corresponding theoretical operating state value database to obtain the theoretical operating state values of each subsystem based on the actual product distribution of the DCS.
[0056] For example, the following explanation uses the butanizer system 7 as an example: The sole feed to the butane debutanizer system 7 originates entirely from the upstream system. After separation in the butane debutanizer, mixed C4 hydrocarbons are obtained at the top and crude cracked gasoline at the bottom. In other words, the feed to the butane debutanizer system 7 is a mixture of mixed C4 hydrocarbons and crude cracked gasoline. The mixed C4 hydrocarbons typically include C4 alkanes, alkenes, and alkynes, while the crude cracked gasoline includes C5 to C9 components. Ignoring the influence of the subdivided components on the system's state parameters, the feed composition to the butane debutanizer is assumed to have only two variables: mixed C4 hydrocarbons and crude cracked gasoline.
[0057] Then, a steady-state process simulation of the butane removal tower system 7 can be established using process simulation software.
[0058] Simulations were performed to calculate the proportion of mixed C4 in the total feed at different ratios. The operating pressure of the butanizer was considered a crucial parameter affecting the system's operating state. A series of process simulations were conducted for different feed ratios and tower pressures to obtain the theoretical energy consumption values of the tower system under various operating conditions. Using a mass fraction of mixed C4 in the total feed ranging from 0.1 to 0.9, and considering three sets of tower pressures (P = 0.45 / 0.4 / 0.35 MPaG) as independent variables, process simulations were performed, outputting a database of theoretical operating state values such as the butanizer reboiler load and reflux ratio.
[0059] After the theoretical operating state value database is constructed, if the flow rates of mixed C4 and cracked gasoline products are obtained from the flow meters in the on-site DCS, with the mixed C4 product flow rate being 32.15 t / h and the crude cracked gasoline product flow rate being 18.17 t / h, then the total feed flow rate into the butanizer and the mass fraction of mixed C4 in the total feed can be calculated according to the principle of material conservation, which is 0.639. The DCS butanizer pressure is also taken as 0.41 MPaG. Then, the theoretical operating state value database of the butanizer system 7 can be interpolated using the above DCS calculation data as independent variables. Specifically, the reboiler load is interpolated linearly, with an interpolation output of 5.15 MW; the reflux ratio is interpolated using a quadratic polynomial, with an interpolation output of 1.049.
[0060] After obtaining the interpolation results, the operating parameter values can be obtained through the on-site DCS, and the actual operating status values of the butanizer tower system 7 during the production process can be calculated based on the operating parameter values, as well as the deviation between the theoretical operating status values and the actual operating status values.
[0061] If the low-pressure steam flow rate of the butanizer reboiler is obtained as 8.50 t / h from the on-site DCS, the actual load of the butanizer reboiler can be calculated to be 6.18 MW based on the low-pressure steam heat capacity and phase change enthalpy. Therefore, the deviation between the actual and theoretical load parameters of the butanizer reboiler is +20%. If the reflux flow rate of the butanizer is obtained as 33.74 t / h and the mixed C4 product flow rate is 32.16 t / h from the on-site DCS, the actual reflux ratio of the butanizer can be calculated to be 1.08. Therefore, the deviation between the actual and theoretical reflux ratio parameters of the butanizer is +3%.
[0062] Using the above method, the deviation between the actual state parameter values and the theoretical state parameter values can be calculated in real time. In this example, it is shown that the actual state parameter values of the reboiling load and reflux ratio of the butanizer system 7 are larger than the theoretical state parameter values. There may be a situation where the reboiling rate and reflux rate are too large and the energy consumption is too high on site. Therefore, it can guide the staff to adjust the parameter values of the butanizer system 7.
[0063] The following explanation uses cryogenic separation system 4 as an example: The sole feed to the cryogenic separation system 4 comes from the high- and low-pressure propane stripper system 3. The effluents of the cryogenic separation system 4 include product hydrogen, methane, a mixed C2 component, and a mixed C3 component. The mixed C2 component mainly consists of product ethylene and recycled ethane, while the mixed C3 component mainly consists of product propylene and product propane. Based on process experience, the state parameters of the cryogenic separation system 4 are determined by the distribution of the main products in the feed, with the distribution of substances with different carbon numbers being the decisive factor. The ratio of ethylene to ethane in the mixed C2 and the ratio of propylene to propane in the mixed C3 have negligible impact on the system's state parameters. Therefore, the product distribution of the feed to the cryogenic separation system 4 can be simplified in this method to hydrogen, methane, the mixed C2 component, and the mixed C3 component.
[0064] Afterwards, a steady-state process simulation of the cryogenic separation system 4 can be established using process simulation software.
[0065] Using the feed composition shown in Table 1, process simulation calculations were performed to obtain a database of theoretical operating state values for the cryogenic separation system 4 under different operating conditions. This database includes theoretical operating state values for the demethanizer condenser, pre-demethanizer condenser, demethanizer sensitive plate temperature, and pre-demethanizer sensitive plate temperature in the cryogenic separation system 4.
[0066] Table 1. Feed composition of cryogenic separation system 4
[0067] After the theoretical operating state value database is established, methane is obtained through the on-site DCS. ,hydrogen The flow rates of ethylene products, recycled ethane, propylene products, and recycled propane are considered. Taking into account the impurity content in different products, as well as the hydrogen loss and olefin and alkane generation during the alkyne hydrogenation reaction, material conservation calculations are performed in reverse from the product distribution. This yields the feed distribution of the cold separation system, which is summarized as hydrogen, methane, mixed C2, and mixed C3.
[0068] The material balance of the feed composition for the cryogenic separation system 4 in this example involves multiple material flows and multiple measurement parameters. Therefore, the feed composition can be determined by the following formula:
[0069]
[0070] in, Represents molar flow rate, Indicates mass flow rate. Indicates molecular weight. This indicates the mole fraction.
[0071] After determining the feed composition of the cryogenic separation system 4, if the flow measurement units and component measurement units of the on-site DCS calculate the feed composition of the cryogenic separation system 4 as 18.42 mol% hydrogen, 26.58 mol% methane, 41.39 mol% mixed C2, and 13.61 mol% mixed C3, then the above DCS calculation data can be used as independent variables to interpolate the theoretical operating state value database of the cryogenic separation system 4. For example, inverse distance weighted interpolation can be used to obtain: the demethanizer condenser load is 1.83 MW; the pre-demethanizer condenser load is 0.68 MW; the demethanizer sensitive plate temperature is -19.2℃; and the pre-demethanizer sensitive plate temperature is -0.8℃.
[0072] Subsequently, if the feed flow rate of the demethanizer condenser is obtained as 24.771 t / h via the DCS, the load of the demethanizer condenser can be calculated as 1.86 MW based on the phase change enthalpy of the refrigerant flow rate. If the load of the pre-demethanizer condenser is obtained as 9.944 t / h, the load of the demethanizer condenser can be calculated as 0.75 MW based on the phase change enthalpy of the refrigerant flow rate. If the sensitive plate temperature of the demethanizer is obtained as -22.0℃, the sensitive plate temperature of the pre-demethanizer can be calculated as -3.3℃.
[0073] Finally, calculations show that the deviation between the actual and theoretical load parameters of the demethanizer condenser is +1.6%, the deviation between the actual and theoretical load parameters of the pre-demethanizer condenser is +10.3%, the deviation between the actual and theoretical temperature parameters of the demethanizer sensitive plate is -2.8℃, and the deviation between the actual and theoretical temperature parameters of the pre-demethanizer sensitive plate is -2.5℃.
[0074] Based on the calculation results of this method, the deviation between the actual state parameter values and the theoretical state parameter values can be calculated in real time. In this example, it is shown that the actual state parameter values of the load of the condenser of the demethanizer and pre-demethanizer in the cryogenic separation system 4 are slightly larger than the theoretical state parameter values. The actual state parameter values of the sensitive plate temperature of the two towers are about 2°C lower than the theoretical state parameter values, indicating that the condensation load is too large and the energy consumption is too high. Therefore, it can guide the staff to adjust the parameter values of the cryogenic separation system 4.
[0075] Based on the same concept, embodiments of this disclosure also provide a system for determining the operating state of a device, such as... Figure 4 As shown, the system 400 for determining the operating state of the device may include: The first determining module 401 is used to determine the feeding information of the target device in the production process in real time; The second determining module 402 is used to determine the theoretical operating state value of the target device based at least on the feeding information and the target information in the preset database, wherein the preset database stores information indicating the theoretical operating state value of the target device under different feeding information, and the theoretical operating state value is used to characterize the operating parameter value of the target device under the corresponding feeding information; The third determining module 403 is used to determine the theoretical operating state of the target device based on the theoretical operating state value.
[0076] The system 400, which determines the operating status of the device as described above, can store information in a preset database to indicate the theoretical operating status values of the target device under different feeding information. Thus, after obtaining the actual feeding information of the target device, the theoretical operating status value corresponding to the actual feeding information can be obtained based on the target information and the actual feeding information stored in the preset database. Then, based on the theoretical operating status value, the theoretical operating status that can truly reflect the real-time status of the target device can be quickly determined, thereby improving the safety of the production process.
[0077] In one possible manner, the first determining module 401 may include: The acquisition unit is used to acquire, in real time, the material flow rate information and material composition information of the target device during the production process through a distributed control system deployed at the target device site. The material composition information is used to indicate the chemical composition and / or physical state distribution of the material. The first determining unit is used to determine the feeding information of the target device based on the material flow information and the material composition information.
[0078] In one possible manner, the second determining module 402 may include: The second determining unit is configured to, when there is no information in the preset database for indicating the theoretical operating state value corresponding to the feeding information, determine at least two target feeding information similar to the feeding information in the preset database, and determine a first interpolation variable in the feeding information according to the process flow of the target device; The first construction unit is used to construct a first interpolation model based on the target feed information, the theoretical operating state value corresponding to the target feed information, and a preset interpolation algorithm. The third determining unit is used to determine the theoretical operating state value of the target device based on the first interpolation variable and the first interpolation model.
[0079] In one possible manner, the target device includes a subsystem, which is obtained by decomposing the target device according to the process flow of the target device; the preset interpolation algorithm is determined based on the characteristics of the subsystem. When the relationship between the interpolation variable in the subsystem and the feed in the feed information is linear, the preset interpolation algorithm is a linear interpolation algorithm; when the relationship between the interpolation variable in the subsystem and the feed in the feed information is polynomial, the preset interpolation algorithm is a polynomial interpolation algorithm; when the interpolation variable in the subsystem is correlated with the feed component distribution in the feed information, the preset interpolation algorithm is inverse distance weighted interpolation.
[0080] In some possible ways, the system 400 for determining the operating state of the device may also include: The first acquisition module is used to acquire the actual operating parameter values of the target device in the production process in real time through the distributed control system deployed at the target device site; Accordingly, the second determining module 402 may include: The fourth determining unit is used to determine at least two target feed information similar to the feed information in the preset database when there is no information in the preset database indicating the theoretical operating state value corresponding to the feed information, and to determine a second interpolation variable in the feed information and the actual operating parameter value according to the process flow of the target device. The second construction unit is used to construct a second interpolation model based on the target feed information, the theoretical operating state value corresponding to the target feed information, and a preset interpolation algorithm. The fifth determining unit is used to determine the theoretical operating state value of the target device based on the second interpolation variable and the second interpolation model.
[0081] In some possible ways, the preset database includes multiple databases, which are obtained in the following manner: According to the technological process of the target device, the target device is decomposed into several subsystems; For each subsystem, a rigorous mechanistic model of the subsystem is established based on the subsystem's process flow and chemical reaction principle; the design parameters and pre-constructed theoretical feed information of the subsystem are obtained, and the design parameters and theoretical feed information are used as inputs to the rigorous mechanistic model to perform steady-state process simulation of the subsystem under the theoretical feed information to obtain theoretical operating state values; a preset database of the subsystem is constructed based on the theoretical feed information and theoretical operating state values.
[0082] In some possible ways, the system 400 for determining the operating state of the device may also include: The second acquisition module is used to acquire the operating parameter values of the target device in the production process in real time through the distributed control system deployed at the target device site; The calculation module is used to calculate the actual operating status value of the target device during the production process based on the operating parameter values; An adjustment module is used to calculate the deviation between the theoretical operating state value and the actual operating state value, and to adjust the operating parameter value of the target device according to the deviation, so that the actual operating state value is closer to the theoretical operating state value.
[0083] Regarding the system 400 for determining the operating state of the device in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated here.
[0084] Based on the same concept, embodiments of this disclosure also provide a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for determining the operating state of the device described above.
[0085] Based on the same concept, embodiments of this disclosure also provide an electronic device, including: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method for determining the operating state of the apparatus described above; Based on the same concept, this disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the method for determining the operating state of a device as described above.
[0086] Figure 5 This is a block diagram illustrating an electronic device according to an exemplary embodiment. Figure 5 As shown, the electronic device 500 may include a processor 501 and a memory 502. The electronic device 500 may also include one or more of a multimedia component 503, an input / output (I / O) interface 504, and a communication component 505.
[0087] The processor 501 controls the overall operation of the electronic device 500 to complete all or part of the steps in the method for determining the operating state of the device described above. The memory 502 stores various types of data to support the operation of the electronic device 500. This data may include, for example, instructions for any application or method operating on the electronic device 500, and application-related data such as contact data, sent and received messages, pictures, audio, video, etc. The memory 502 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The multimedia component 503 may include a screen and audio components. The screen may be, for example, a touchscreen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in memory 502 or transmitted via communication component 505. The audio component also includes at least one speaker for outputting audio signals. I / O interface 504 provides an interface between processor 501 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual or physical. Communication component 505 is used for wired or wireless communication between the electronic device 500 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IoT, eMTC, or other 5G technologies, or combinations thereof, is not limited here. Therefore, the corresponding communication component 505 may include: a Wi-Fi module, a Bluetooth module, an NFC module, etc.
[0088] In an exemplary embodiment, the electronic device 500 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the method for determining the operating state of the device described above.
[0089] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the method for determining the operating state of a device described above. For example, the computer-readable storage medium may be the memory 502 including program instructions described above, which may be executed by the processor 501 of the electronic device 500 to complete the method for determining the operating state of a device described above.
[0090] Figure 6 This is a block diagram illustrating an electronic device according to an exemplary embodiment. For example, electronic device 600 may be provided as a server. (Refer to...) Figure 6 The electronic device 600 includes a processor 622, which may be one or more, and a memory 632 for storing computer programs executable by the processor 622. The computer programs stored in the memory 632 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processor 622 may be configured to execute the computer program to perform the aforementioned method for determining the operating state of the device.
[0091] Additionally, the electronic device 600 may also include a power supply component 626 and a communication component 650. The power supply component 626 can be configured to perform power management of the electronic device 600, and the communication component 650 can be configured to enable communication of the electronic device 600, such as wired or wireless communication. Furthermore, the electronic device 600 may also include an input / output (I / O) interface 658. The electronic device 600 can operate on an operating system stored in memory 632.
[0092] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the method for determining the operating state of a device described above. For example, the non-transitory computer-readable storage medium may be the memory 632 including the program instructions described above, which may be executed by the processor 622 of the electronic device 600 to complete the method for determining the operating state of a device described above.
[0093] In another exemplary embodiment, a computer program product is also provided, the computer program product comprising a computer program executable by a programmable device, the computer program having a code portion for performing the method described above for determining the operating state of the device when executed by the programmable device.
[0094] The preferred embodiments of this disclosure have been described in detail above with reference to the accompanying drawings. However, this disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of this disclosure, various simple modifications can be made to the technical solutions of this disclosure, and these simple modifications all fall within the protection scope of this disclosure.
[0095] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.
[0096] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.
Claims
1. A method for determining the operating state of a device, characterized in that, The method includes: Real-time determination of the feed information of the target device during the production process; The theoretical operating state value of the target device is determined based at least on the feeding information and the target information in the preset database. The preset database stores information indicating the theoretical operating state value of the target device under different feeding information. The theoretical operating state value is used to characterize the operating parameter value of the target device under the corresponding feeding information. The theoretical operating state of the target device is determined based on the theoretical operating state value.
2. The method according to claim 1, characterized in that, The real-time determination of the target device's feed information during the production process includes: The distributed control system deployed at the target device site acquires material flow and material composition information of the target device in real time during the production process. The material composition information is used to indicate the chemical composition and / or physical state distribution of the material. Based on the material flow rate information and the material composition information, the feeding information of the target device is determined.
3. The method according to claim 1 or 2, characterized in that, The step of determining the theoretical operating state value of the target device based at least on the feed information and target information in a preset database includes: When no information for indicating the theoretical operating state value corresponding to the feed information exists in the preset database, at least two target feed information similar to the feed information are determined in the preset database, and a first interpolation variable is determined in the feed information according to the process flow of the target device. Based on the target feed information, the theoretical operating state value corresponding to the target feed information, and the preset interpolation algorithm, a first interpolation model is constructed; The theoretical operating state value of the target device is determined based on the first interpolation variable and the first interpolation model.
4. The method according to claim 3, characterized in that, The target device includes a subsystem, which is decomposed according to the process flow of the target device. When the relationship between the interpolation variable and the feed in the feed information in the subsystem is linear, the preset interpolation algorithm is a linear interpolation algorithm. When the relationship between the interpolation variable and the feed in the feed information in the subsystem is polynomial, the preset interpolation algorithm is a polynomial interpolation algorithm. When the interpolation variable and the feed component distribution in the feed information in the subsystem are correlated, the preset interpolation algorithm is inverse distance weighted interpolation.
5. The method according to claim 1 or 2, characterized in that, The method further includes: The distributed control system deployed at the target device site acquires the actual operating parameter values of the target device during the production process in real time. The step of determining the theoretical operating state value of the target device based at least on the feed information and target information in a preset database includes: If no information for indicating the theoretical operating state value corresponding to the feed information is found in the preset database, at least two target feed information similar to the feed information are determined in the preset database, and a second interpolation variable is determined in the feed information and the actual operating parameter value according to the process flow of the target device. A second interpolation model is constructed based on the target feed information, the theoretical operating state value corresponding to the target feed information, and a preset interpolation algorithm. The theoretical operating state value of the target device is determined based on the second interpolation variable and the second interpolation model.
6. The method according to claim 1 or 2, characterized in that, The preset database includes multiple databases, which are obtained through the following methods: According to the technological process of the target device, the target device is decomposed into several subsystems; For each subsystem, a rigorous mechanistic model of the subsystem is established based on the process flow and chemical reaction principle of the subsystem; The design parameters of the subsystem and the pre-constructed theoretical feed information are obtained, and the design parameters and the theoretical feed information are used as inputs to the rigorous mechanism model to perform steady-state process simulation of the subsystem under the theoretical feed information to obtain theoretical operating state values; based on the theoretical feed information and the theoretical operating state values, a preset database of the subsystem is constructed.
7. The method according to claim 1 or 2, characterized in that, The method further includes: The operating parameter values of the target device during the production process are acquired in real time through a distributed control system deployed at the target device site; Based on the operating parameter values, calculate the actual operating status values of the target device during the production process; The deviation between the theoretical operating state value and the actual operating state value is calculated, and the operating parameter values of the target device are adjusted according to the deviation so that the actual operating state value is closer to the theoretical operating state value.
8. A system for determining the operating state of a device, characterized in that, include: The first determining module is used to determine the feeding information of the target device in real time during the production process; The second determining module is used to determine the theoretical operating state value of the target device based at least on the feeding information and the target information in the preset database, wherein the preset database stores information indicating the theoretical operating state value of the target device under different feeding information, and the theoretical operating state value is used to characterize the operating parameter value of the target device under the corresponding feeding information; The third determining module is used to determine the theoretical operating state of the target device based on the theoretical operating state value.
9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method described in any one of claims 1-7.
10. An electronic device, characterized in that, include: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method according to any one of claims 1-7.
11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-7.