Optimal control method, device and electronic equipment for steel smelting system

Abstract

This application discloses an optimization control method, apparatus, equipment, and medium for an iron and steel smelting system, relating to the technical field of iron and steel smelting systems. The method includes: determining target control parameters for each subsystem based on material parameters and target optimization parameters; adjusting the target control parameters based on the global energy parameters of the iron and steel smelting system and the weight information of each subsystem in the smelting process to generate actual control parameters for each subsystem; and controlling the operation of each subsystem based on the actual control parameters. This optimization control method can control the operation of each subsystem of the iron and steel smelting system from the perspective of global energy parameters and the importance of each subsystem, avoiding the impact of optimizing a single link on the overall optimization effect of the smelting process, and improving the overall optimization effect of the iron and steel smelting system operation.

Description

Technical Field

[0001] This application relates to the field of steel smelting system technology, and in particular to an optimized control method, apparatus and electronic equipment for steel smelting systems. Background Technology

[0002] Iron and steel smelting systems typically include multiple interconnected subsystems such as coking, sintering, ironmaking, steelmaking, and rolling. Current energy-saving optimization technologies for iron and steel smelting processes focus on localized optimization of single processes or equipment, lacking a systematic consideration from the perspective of the coordinated flow of materials and energy throughout the entire process. The independent operation of each process prevents optimal overall energy efficiency. Furthermore, in the actual operation of an iron and steel smelting system, optimization of a single stage can only guarantee the optimization effect of that stage and may affect other stages, thus impacting the overall optimization effect of the smelting process. Summary of the Invention

[0003] The summary section introduces a series of simplified concepts, which will be further explained in detail in the detailed description section. This summary section is not intended to limit the key and essential technical features of the claimed technical solutions, nor is it intended to determine the scope of protection of the claimed technical solutions.

[0004] Firstly, this application provides an optimization control method for an iron and steel smelting system. The iron and steel smelting system includes multiple subsystems, each subsystem corresponding to a target process in the smelting process. The control method includes: Based on the material parameters and target optimization parameters of each subsystem, determine the target control parameters for each subsystem; Based on the global energy parameters of the steel smelting system and the weight information of each subsystem in the smelting process, the target control parameters are adjusted to generate the actual control parameters of each subsystem. Control the operation of each subsystem according to the actual control parameters; The target control parameters and actual control parameters include the material ratio parameters of the subsystem and the global energy scheduling parameters. The material ratio parameters are used to indicate the material ratio of the subsystem, the global energy scheduling parameters are used to indicate the energy consumption of the subsystem, and the weight information is used to characterize the importance of the target process of the corresponding subsystem in the smelting process.

[0005] In some implementations, target control parameters for each subsystem are determined based on the material parameters and target optimization parameters of each subsystem, including: Based on the subsystem production model, the target material ratio parameters of the subsystem are determined according to the material parameters and target optimization parameters. Determine the target energy consumption of the subsystem based on the target material ratio parameters; Based on the subsystem energy model, the target global energy scheduling parameters of the subsystem are determined according to the target energy consumption.

[0006] In some implementations, the target control parameters are adjusted based on the global energy parameters of the steel smelting system and the weight information of each subsystem in the smelting process to generate the actual control parameters for each subsystem, including: An energy coordination module is used to determine the actual energy consumption of each subsystem based on the global energy parameters and weight information of the iron and steel smelting system. Based on the actual energy consumption, the target material ratio parameters and target global energy scheduling parameters are adjusted to obtain the actual material ratio parameters and actual global energy scheduling parameters for each subsystem.

[0007] In some implementations, before determining the actual energy consumption of each subsystem based on the global energy parameters and weight information of the steel smelting system using an energy coordination module, the control method further includes: A weight allocation module is used to determine the weight information of each subsystem in the smelting process based on the status information of all subsystems.

[0008] In some implementations, after controlling the operation of each subsystem according to actual control parameters, the control method further includes: Obtain the actual optimization parameters for each subsystem; Based on the actual control parameters, target optimization parameters, and actual optimization parameters, at least one of the energy coordination module and weight allocation module is updated.

[0009] In some implementations, before determining the target control parameters for each subsystem based on its material parameters and target optimization parameters, the control method further includes: Obtain historical production data and historical energy consumption data of the subsystem within the current historical time period; Based on historical production data and historical energy consumption data, establish subsystem production models and subsystem energy models.

[0010] Secondly, this application proposes an optimized control device for an iron and steel smelting system. The iron and steel smelting system includes multiple subsystems, each subsystem corresponding to a target process in the smelting process. The control device includes: The determination unit is used to determine the target control parameters of each subsystem based on the material parameters and target optimization parameters of each subsystem. The adjustment unit is used to adjust the target control parameters and generate the actual control parameters for each subsystem based on the global energy parameters of the steel smelting system and the weight information of each subsystem in the smelting process. The control unit is used to control the operation of each subsystem according to the actual control parameters; The target control parameters and actual control parameters include the material ratio parameters of the subsystem and the global energy scheduling parameters. The material ratio parameters are used to indicate the material ratio of the subsystem, the global energy scheduling parameters are used to indicate the energy consumption of the subsystem, and the weight information is used to characterize the importance of the target process of the corresponding subsystem in the smelting process.

[0011] In some implementations, the determining unit is specifically used for: Based on the subsystem production model, the target material ratio parameters of the subsystem are determined according to the material parameters and target optimization parameters. Determine the target energy consumption of the subsystem based on the target material ratio parameters; Based on the subsystem energy model, the target global energy scheduling parameters of the subsystem are determined according to the target energy consumption.

[0012] The adjustment unit is specifically used for: An energy coordination module using a pre-defined neural network model determines the actual energy consumption of each subsystem based on the global energy parameters and weight information of the iron and steel smelting system. Based on the actual energy consumption, the target material ratio parameters and target global energy scheduling parameters are adjusted to obtain the actual material ratio parameters and actual global energy scheduling parameters for each subsystem.

[0013] Thirdly, an electronic device includes: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus, and the machine-readable instructions are executed by the processor to perform the steps of the optimized control method for the steel smelting system as described in any of the above technical solutions.

[0014] Fourthly, this application also proposes a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the optimized control method for the steel smelting system as described in any of the above technical solutions.

[0015] In summary, the optimization control method for the iron and steel smelting system proposed in this application allows for the adjustment of target control parameters for each subsystem based on the overall energy parameters of the iron and steel smelting system and the importance of each subsystem's target process in the smelting process. This adjustment, based on the total energy of the iron and steel smelting system and the importance of each subsystem, enables the adjustment of target control parameters for multiple subsystems, thereby achieving coordinated optimization of each stage from the perspective of the entire smelting process. Furthermore, since the target control parameters of each subsystem are derived from material parameters and target optimization parameters, the actual control parameters obtained after adjusting the target control parameters can both satisfy the target optimization parameters of each subsystem as much as possible and control the operation of each subsystem from the perspective of overall energy parameters and the importance of each subsystem. This avoids compromising the overall optimization effect of the smelting process by prioritizing the optimization effect of a single stage, thus improving the overall optimization effect of the iron and steel smelting system operation. Attached Figure Description

[0016] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit this specification. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 This application provides a schematic flowchart of an optimized control method for an iron and steel smelting system. Figure 2 A structural block diagram of an iron and steel smelting system provided in this application embodiment; Figure 3 A schematic flowchart illustrating the operation of an iron and steel smelting system provided in this application embodiment; Figure 4 A schematic diagram of a device for determining the occurrence time of an event, provided in an embodiment of this application; Figure 5 This is a schematic diagram of a screen-controlled electronic device provided in an embodiment of this application. Detailed Implementation

[0017] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus. The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them.

[0018] Please see Figure 1 This is a schematic flowchart of an optimization control method for an iron and steel smelting system provided in an embodiment of this application. The iron and steel smelting system includes multiple subsystems, each corresponding to a target process in the smelting process. The optimization control method for the iron and steel smelting system proposed in this application can be used to control the operation process of the iron and steel smelting system. Specifically, the iron and steel smelting system may include multiple subsystems. For example, for the iron and steel smelting process, the iron and steel smelting system may include multiple subsystems such as coking, sintering, ironmaking, steelmaking, and rolling. Controlling the operation process of the iron and steel smelting system can specifically involve controlling the material allocation parameters of each subsystem during actual operation and the global energy scheduling parameters of multiple subsystems. The material allocation parameters specifically indicate the ratio of various raw materials consumed by each subsystem during operation, that is, the consumption amount of each raw material during the operation of the subsystem. The global energy scheduling parameters specifically indicate the energy consumption of each subsystem, that is, the total amount of energy consumed by each subsystem during operation.

[0019] Optimization control methods for iron and steel smelting systems may specifically include: S110. Determine the target control parameters for each subsystem based on the material parameters and target optimization parameters of each subsystem.

[0020] In controlling the operation of an iron and steel smelting system, the material parameters and target optimization parameters for each subsystem can be obtained first. Specifically, the material parameters refer to the quantity of each raw material that can be provided to the subsystem during actual operation. For example, for each subsystem, to ensure its normal operation and production of corresponding products, multiple raw materials need to be provided. Each raw material has a lower limit, and correspondingly, based on factors such as the actual production environment, product output requirements, and quality requirements, each raw material also has an upper limit. The material parameters for each subsystem are the upper and lower limits of the quantity of each raw material required for the subsystem's operation. The target optimization parameters refer to the items that need to be optimized during the subsystem's operation. For example, target optimization parameters may include energy consumption, carbon emissions, product qualification rate, and production costs.

[0021] Based on the material parameters and target optimization parameters of each subsystem, the target control parameters for each subsystem can be determined. Specifically, the target control parameters may include the target material ratio parameters and the target global energy scheduling parameters for the subsystem. The target material ratio parameters specifically indicate the material ratio corresponding to the target optimization parameters during the subsystem's operation; that is, if the subsystem operates according to the target material ratio parameters, it can achieve its corresponding target optimization parameters. The target global energy scheduling parameters indicate the energy consumption required for the subsystem's operation; that is, the amount of energy consumed by the subsystem to operate according to the target material ratio parameters. It should be noted that the target control parameters of a subsystem refer to the material ratio and energy consumption under the condition that the subsystem can achieve its corresponding target optimization parameters.

[0022] S120. Based on the global energy parameters of the steel smelting system and the weight information of each subsystem in the smelting process, adjust the target control parameters and generate the actual control parameters for each subsystem.

[0023] After determining the target control parameters of the subsystems, the target control parameters can be adjusted based on the global energy parameters of the iron and steel smelting system and the weight information of each subsystem in the smelting process to generate the actual control parameters for each subsystem. The global energy parameters of the iron and steel smelting system indicate the total energy consumption during the system's operation, while the weight information characterizes the importance of the target process within the corresponding subsystem during the smelting process.

[0024] Understandably, the target control parameters of a subsystem refer to the material ratio and energy consumption under the condition that the subsystem can achieve its corresponding target optimization parameters. However, in the actual operation of an iron and steel smelting system, multiple subsystems operate in tandem. The global energy parameters of the iron and steel smelting system, that is, the total energy provided to the iron and steel smelting system, may not be able to meet the energy consumption requirements of each subsystem. In this case, it is necessary to reallocate the energy consumption of each subsystem according to the importance of the target process in the smelting process. That is, to adjust the target global energy scheduling parameters of each subsystem to generate the actual global energy scheduling parameters. Then, based on the actual global energy scheduling parameters, the target material ratio parameters of the subsystem are adjusted to generate the actual material ratio parameters of the subsystem.

[0025] S130. Control the operation of each subsystem according to the actual control parameters.

[0026] The target control parameters and actual control parameters include the material ratio parameters of the subsystem and the global energy scheduling parameters. The material ratio parameters are used to indicate the material ratio of the subsystem, the global energy scheduling parameters are used to indicate the energy consumption of the subsystem, and the weight information is used to characterize the importance of the target process of the corresponding subsystem in the smelting process.

[0027] Finally, after adjusting the target control parameters of each subsystem to obtain the actual control parameters, the operation of each subsystem can be controlled based on these actual control parameters. It is understandable that, since the target control parameters of each subsystem are based on material parameters and target optimization parameters, the actual control parameters obtained after adjusting the target control parameters can not only satisfy the target optimization parameters of each subsystem as much as possible, but also control the operation of each subsystem from the perspective of global energy parameters and the importance of each subsystem. This avoids affecting the overall optimization effect of the smelting process in order to ensure the optimization effect of a single link, thus improving the overall optimization effect of the steel smelting system operation.

[0028] In summary, the optimization control method for the iron and steel smelting system proposed in this application allows for the adjustment of target control parameters for each subsystem based on the overall energy parameters of the iron and steel smelting system and the importance of each subsystem's target process in the smelting process. This adjustment, based on the total energy of the iron and steel smelting system and the importance of each subsystem, enables the adjustment of target control parameters for multiple subsystems, thereby achieving coordinated optimization of each stage from the perspective of the entire smelting process. Furthermore, since the target control parameters of each subsystem are derived from material parameters and target optimization parameters, the actual control parameters obtained after adjusting the target control parameters can both satisfy the target optimization parameters of each subsystem as much as possible and control the operation of each subsystem from the perspective of overall energy parameters and the importance of each subsystem. This avoids compromising the overall optimization effect of the smelting process by prioritizing the optimization effect of a single stage, thus improving the overall optimization effect of the iron and steel smelting system operation.

[0029] In some instances, the target control parameters for each subsystem are determined based on the material parameters and target optimization parameters for each subsystem, including: Based on the subsystem production model, the target material ratio parameters of the subsystem are determined according to the material parameters and target optimization parameters. Determine the target energy consumption of the subsystem based on the target material ratio parameters; Based on the subsystem energy model, the target global energy scheduling parameters of the subsystem are determined according to the target energy consumption.

[0030] In this embodiment, for the target material ratio parameters of each subsystem, the material parameters and target optimization parameters of the subsystem can be processed based on the subsystem production model to obtain the target material ratio parameters of each subsystem.

[0031] Specifically, for each subsystem, to ensure its normal operation and production of corresponding products, it is necessary to provide various essential raw materials. Therefore, a mathematical model of subsystem operation, i.e., a subsystem production model, can be constructed based on the necessary raw materials required for subsystem operation. Furthermore, in actual operation, the quantity of each raw material has a lower limit, and correspondingly, based on factors such as the actual production environment, product output requirements, and quality requirements, the quantity of each raw material also has an upper limit. The material parameters of each subsystem are the upper and lower limits of the quantity of each raw material required for subsystem operation. Thus, the subsystem production model can adjust the proportion of each material based on the upper and lower limits of the quantity of each raw material and the subsystem's target optimization parameters, thereby obtaining the target material proportion parameters corresponding to the target optimization parameters.

[0032] Furthermore, after determining the target material ratio parameters for each subsystem, the target energy consumption required by the subsystem during actual operation can be determined based on these parameters. At this point, a subsystem energy consumption model can be used to determine the target global energy scheduling parameters for each subsystem based on its target energy consumption. This subsystem energy consumption model is a mathematical model established based on energy scheduling for each subsystem during the actual operation of the iron and steel smelting system. After determining the target energy consumption for each subsystem, the subsystem energy consumption model can be used to determine the corresponding target energy scheduling parameters for each subsystem, thereby allocating appropriate energy to each subsystem.

[0033] In summary, by using the subsystem production model and the subsystem energy model, the target material ratio parameters and target global energy scheduling parameters of each subsystem can be automatically generated based on the material parameters and target optimization parameters of each subsystem. In other words, the target control parameters of each subsystem are determined, which simplifies the process of determining the target control parameters.

[0034] In some instances, based on the global energy parameters of the steel smelting system and the weight information of each subsystem in the smelting process, the target control parameters are adjusted to generate the actual control parameters for each subsystem, including: An energy coordination module is used to determine the actual energy consumption of each subsystem based on the global energy parameters and weight information of the iron and steel smelting system. Based on the actual energy consumption, the target material ratio parameters and target global energy scheduling parameters are adjusted to obtain the actual material ratio parameters and actual global energy scheduling parameters for each subsystem.

[0035] In this embodiment, the process of adjusting the target control parameters of each subsystem can first employ an energy coordination module to calculate the actual energy consumption that each subsystem can be allocated during actual operation, based on the global energy parameters of the steel smelting system and the importance of the target process of each subsystem in the smelting process.

[0036] Understandably, in the actual operation of an iron and steel smelting system, multiple subsystems operate in tandem. The overall energy parameters of the iron and steel smelting system—that is, the total energy provided to the system—may not be sufficient to meet the energy consumption needs of each subsystem. In this case, it is necessary to reallocate energy consumption for each subsystem based on the importance of its target process within the smelting process, thereby determining the actual energy consumption of each subsystem. An energy coordination module can be used to calculate the actual energy consumption that can be allocated during operation. This module can be a pre-trained neural network model based on historical operating data of the subsystems. Using this module can effectively improve the efficiency of determining the actual energy consumption of each subsystem.

[0037] Furthermore, after determining the actual energy consumption of each subsystem, the target material ratio parameters and target global energy scheduling parameters of each subsystem can be adjusted according to the actual energy consumption, thereby obtaining the actual material ratio parameters and actual global energy scheduling parameters of each subsystem.

[0038] Specifically, the subsystem production model can also be used to determine the actual target material ratio parameters of the subsystem. It should be noted that when the subsystem production model determines the target material ratio parameters of the subsystem, it is not necessary to consider the actual energy consumption of the subsystem, only the target optimization parameters of the subsystem. At this time, after determining the actual energy consumption of the subsystem, the subsystem production model can combine the actual energy consumption and the target optimization parameters to obtain the actual material ratio parameters of each subsystem. In this way, the target material ratio parameters can not only meet the actual energy consumption of the subsystem, but also meet the target optimization parameters of the subsystem as much as possible.

[0039] The actual global energy scheduling parameters for each subsystem can also be determined using the subsystem energy model. That is, after determining the actual energy consumption of each subsystem, the actual global energy scheduling parameters for each subsystem can be determined using the subsystem energy consumption model based on the actual energy consumption of each subsystem.

[0040] In summary, the optimization control method for the iron and steel smelting system proposed in this application allows for the adjustment of target control parameters for each subsystem based on the overall energy parameters of the iron and steel smelting system and the importance of each subsystem's target process in the smelting process. This adjustment, based on the total energy of the iron and steel smelting system and the importance of each subsystem, enables the adjustment of target control parameters for multiple subsystems, thereby achieving coordinated optimization of each stage from the perspective of the entire smelting process. Furthermore, since the target control parameters of each subsystem are derived from material parameters and target optimization parameters, the actual control parameters obtained after adjusting the target control parameters can both satisfy the target optimization parameters of each subsystem as much as possible and control the operation of each subsystem from the perspective of overall energy parameters and the importance of each subsystem. This avoids compromising the overall optimization effect of the smelting process by prioritizing the optimization effect of a single stage, thus improving the overall optimization effect of the iron and steel smelting system operation.

[0041] In some instances, an energy coordination module is used to determine the actual energy consumption of each subsystem before determining the actual energy consumption of each subsystem based on the global energy parameters and weight information of the steel smelting system. Other control methods include: A weight allocation module is used to determine the weight information of each subsystem in the smelting process based on the status information of all subsystems.

[0042] In this embodiment, before determining the actual energy consumption of each subsystem, a weight allocation module can be used to determine the weight information of each subsystem in the smelting process based on the state information of all subsystems, that is, to determine the importance of the target process of each subsystem in the smelting process.

[0043] It should be noted that the weight allocation module can be a communication module based on the attention mechanism. This communication module can calculate the importance weight of the target process of each subsystem to the smelting process based on the state information of each subsystem, that is, determine the weight information of each subsystem.

[0044] In summary, by using the weight allocation module to determine the weight information of each subsystem in the smelting process based on the state information of all subsystems, the importance of the target process of each subsystem in the smelting process can be determined. Then, based on the importance of the target process of each subsystem in the smelting process, the actual energy consumption is allocated to each subsystem, thereby adjusting the control parameters of the subsystem.

[0045] In some instances, after controlling the operation of each subsystem according to actual control parameters, the control method also includes: Obtain the actual optimization parameters for each subsystem; Based on the actual control parameters, target optimization parameters, and actual optimization parameters, at least one of the energy coordination module and weight allocation module is updated.

[0046] In this embodiment, after each operating cycle of the steel smelting system, that is, after controlling the operation of each subsystem according to the actual operating parameters, the actual optimization parameters of each subsystem can be collected. By comparing the actual optimization parameters with the target optimization parameters, the optimization effect of each subsystem after actual operation can be determined. Then, based on the actual optimization parameters, the energy coordination module and the weight allocation module are updated so that the actual energy consumption obtained by the updated energy coordination module and the weight information of the subsystem calculated by the updated weight allocation module can better match the target optimization parameters of the subsystem, thereby improving the optimization effect of the steel smelting system operation process in the next operating cycle.

[0047] Specifically, the energy coordination model and weight allocation module can be updated based on the actual optimization parameters, target optimization parameters, and actual control parameters of each subsystem. This allows the energy coordination model and weight allocation module to learn and train models based on the actual optimization parameters, target optimization parameters, and actual control parameters. As a result, the output data of the updated energy coordination model and weight allocation module can better match the target optimization parameters of the subsystem, thereby improving the optimization effect of the steel smelting system's operation.

[0048] Before determining the target control parameters for each subsystem based on its material parameters and target optimization parameters, the control method also includes: Obtain historical production data and historical energy consumption data of the subsystem within the current historical time period; Based on historical production data and historical energy consumption data, establish subsystem production models and subsystem energy models.

[0049] In this embodiment, a subsystem production model and a subsystem energy model can be established for each subsystem by acquiring historical production data and historical energy consumption data of the subsystem within a historical time period.

[0050] Specifically, data acquisition sensors can be deployed in each subsystem and on the energy website to collect historical production data such as material ratios and energy consumption data of the subsystems. Then, based on the historical production data of each subsystem, a subsystem production model can be established, and based on the historical energy consumption data of each subsystem, a subsystem energy model can be established.

[0051] Please see Figure 4This application provides an optimized control device for an iron and steel smelting system. The iron and steel smelting system includes multiple subsystems, each corresponding to a target process in the smelting process. The control device includes: The determining unit 21 is used to determine the target control parameters of each subsystem based on the material parameters and target optimization parameters of each subsystem. The adjustment unit 22 is used to adjust the target control parameters and generate the actual control parameters of each subsystem based on the global energy parameters of the steel smelting system and the weight information of each subsystem in the smelting process. Control unit 23 is used to control the operation of each subsystem according to actual control parameters; The target control parameters and actual control parameters include the material ratio parameters of the subsystem and the global energy scheduling parameters. The material ratio parameters are used to indicate the material ratio of the subsystem, the global energy scheduling parameters are used to indicate the energy consumption of the subsystem, and the weight information is used to characterize the importance of the target process of the corresponding subsystem in the smelting process.

[0052] The optimized control device for the iron and steel smelting system proposed in this application can adjust the target control parameters of each subsystem based on the global energy parameters of the iron and steel smelting system and the importance of each subsystem's target process in the smelting process. This adjustment, based on the total energy of the iron and steel smelting system and the importance of each subsystem, achieves coordinated optimization of various stages from the perspective of the entire smelting process. Furthermore, since the target control parameters of each subsystem are derived from material parameters and target optimization parameters, the actual control parameters obtained after adjusting the target control parameters can not only satisfy the target optimization parameters of each subsystem as much as possible, but also control the operation of each subsystem from the perspective of global energy parameters and the importance of each subsystem. This avoids compromising the overall optimization effect of the smelting process by ensuring the optimization effect of a single stage, thus improving the overall optimization effect of the iron and steel smelting system operation.

[0053] In some embodiments, the determining unit 21 is specifically used for: Based on the subsystem production model, the target material ratio parameters of the subsystem are determined according to the material parameters and target optimization parameters. Determine the target energy consumption of the subsystem based on the target material ratio parameters; Based on the subsystem energy model, the target global energy scheduling parameters of the subsystem are determined according to the target energy consumption.

[0054] In some embodiments, the adjustment unit 22 is specifically used for: An energy coordination module using a pre-defined neural network model determines the actual energy consumption of each subsystem based on the global energy parameters and weight information of the iron and steel smelting system. Based on the actual energy consumption, the target material ratio parameters and target global energy scheduling parameters are adjusted to obtain the actual material ratio parameters and actual global energy scheduling parameters for each subsystem.

[0055] In some embodiments, the determining unit 21 is further configured to: A weight allocation module is used to determine the weight information of each subsystem in the smelting process based on the status information of all subsystems.

[0056] In some embodiments, the optimization control device for the steel smelting system further includes: The update unit is used to obtain the actual optimization parameters for each subsystem; Based on the actual control parameters, target optimization parameters, and actual optimization parameters, at least one of the energy coordination module and weight allocation module is updated.

[0057] In some embodiments, the optimization control device for the steel smelting system further includes: The model building unit is used to acquire historical production data and historical energy consumption data of the subsystem within the current historical time period. Based on historical production data and historical energy consumption data, establish subsystem production models and subsystem energy models.

[0058] Please see Figure 2 This is a structural block diagram of an iron and steel smelting system provided in an embodiment of this application. The iron and steel smelting system includes an intelligent decision-making layer, which includes multiple process intelligent agents and multiple energy intelligent agents. Specifically, each process intelligent agent is a subsystem production model corresponding to each subsystem described in any of the above embodiments. Specifically, the multiple subsystems of the iron and steel smelting system may include a sintering system, a pelletizing system, a blast furnace system, a steelmaking system, and a rolling system. Correspondingly, the multiple process intelligent agents are the sintering intelligent agent, the pelletizing intelligent agent, the blast furnace intelligent agent, the steelmaking intelligent agent, and the rolling intelligent agent.

[0059] The energy agent is specifically the subsystem energy model corresponding to each subsystem in any of the above embodiments. Specifically, the energy that the iron and steel smelting system can consume may include coal gas, steam, electricity, gas and carbon flow. Correspondingly, the energy agent can be coal gas balance, steam scheduling, electricity optimization, gas allocation and carbon and sulfur control.

[0060] Furthermore, the steel smelting system also includes a data sensing and execution layer. This layer specifically comprises sensor networks and actuators deployed in various subsystems of the steel smelting system. The sensor network is used to collect real-time production status data and energy data from each process and feed them back to the respective intelligent agents. The actuators are used to receive and execute optimized control commands issued by the intelligent agents. Specifically, the sensor network can be used to collect raw material and fuel parameters, energy medium parameters, monitor equipment status, and collect equipment monitoring data. The execution structure can include PLC actuators used to control the production processes of subsystems and control the operation of the energy system.

[0061] Furthermore, the steel smelting system also includes an application layer, which can be used to set target optimization parameters during the operation of the steel smelting system, such as improving energy efficiency, reducing energy consumption, reducing carbon emissions, stabilizing quality, and optimizing costs.

[0062] The data perception and execution layer and the application layer are all connected to the intelligent decision-making layer, which enables the intelligent agents of each process and energy in the intelligent decision-making layer to receive the production status data and energy data collected by the sensor network, as well as the optimization parameters provided by the application layer. The intelligent agents of each process and energy generate corresponding control parameters based on the production status data, energy data and optimization parameters, and send the control parameters to the actuator to realize the operation of the iron and steel smelting system.

[0063] Furthermore, the steel smelting system also includes a global coordinator, which is connected to the data perception and execution layer, the application layer, and the intelligent decision-making layer. Specifically, the global coordinator includes an energy coordination module and a weight allocation module as described in any of the above embodiments. Based on the production status data and energy data collected by the sensor network and the optimization parameters set by the application layer, the energy coordination module and the weight allocation module adjust the target control parameters determined by the intelligent decision-making layer. This allows for the adjustment of the target control parameters of multiple subsystems based on the total energy of the steel smelting system and the importance of each subsystem, thereby achieving coordinated optimization of each link from the perspective of the entire smelting process.

[0064] Specifically, the overall operation process of the iron and steel smelting system is as follows: Hardware system deployment: High-precision sensors are deployed at key process nodes of the steel smelting system (e.g., sintering system, pelletizing system, blast furnace system, steelmaking system, and rolling system) and various energy pipelines (e.g., coal gas, steam, electricity, gas, and carbon flow) to form a sensor network. A high-performance server cluster is deployed in the central computer room to run reinforcement learning algorithm models for each agent. Control commands are distributed via the industrial network to programmable logic controllers (PLCs) and actuators (such as valves, frequency converters, and regulating valves) at each process stage.

[0065] Software system and algorithm implementation: 1. Agent Modeling: Process agents are established for core processes such as sintering, coking, blast furnace, converter, and rolling; energy agents are established for major energy media such as coal gas, steam, electricity, gas, and carbon flow. The state space of each agent contains key process parameters and energy parameters within its jurisdiction, and its action space contains its adjustable key operational variables.

[0066] 2. Global Coordinator Design: The energy coordination module calculates the actual energy consumption allocated to each subsystem during operation based on the global energy parameters of the steel smelting system and the importance of the target process in each subsystem during the smelting process. The weight allocation module receives the state information of all agents. This module can be an attention-based communication module that calculates the importance weight of the target process of each subsystem to the smelting process based on the state information of each subsystem, thus determining the weight information of each subsystem.

[0067] 3. Training and Deployment: First, the system is initially trained using historical production data to enable the agents to learn basic operating rules. Then, a high-fidelity, end-to-end digital twin model is constructed and subjected to large-scale offline training in a simulation environment, using the MADDPG algorithm to optimize the strategies of each agent. Once the agents perform stably in the simulation environment and the energy-saving and carbon-reduction effects achieve the expected goals (e.g., a reduction of more than 5% in the simulated comprehensive energy consumption per ton of steel), the trained model is deployed to the online system.

[0068] Please see Figure 3 This application provides a flowchart illustrating the operation of an iron and steel smelting system. The software system can run online after being deployed to the iron and steel smelting system. Specifically, within one operating cycle, firstly, high-precision sensors deployed at key process nodes and energy pipelines monitor the state of the iron and steel smelting system. Then, the global coordinator makes collaborative decisions for each process agent and energy agent based on the system's state. The process agents and energy agents send control commands to the execution mechanism to execute the commands. After executing the commands, it is determined whether the actual optimization parameters of the iron and steel smelting system meet the optimization requirements. That is, after executing the commands, the target rewards corresponding to multiple items such as energy efficiency and carbon emissions during the operation of the iron and steel smelting system are calculated. If the target rewards meet the actual requirements, the actual operating parameters and actual optimization parameters of the iron and steel smelting system are stored. The model is trained and updated based on the stored actual operating parameters and actual optimization parameters so that the updated model can be used to control the operation of the iron and steel smelting system in the next operating cycle.

[0069] Please see Figure 5 This application also provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor. When the processor 320 executes the computer program 311, it implements the steps of an optimized control method for an iron and steel smelting system.

[0070] Since the electronic device described in this embodiment is a device used to implement an event occurrence time determination device in the embodiments of this application, those skilled in the art can understand the specific implementation method and various variations of the electronic device in this embodiment based on the method described in the embodiments of this application. Therefore, how the electronic device implements the method in the embodiments of this application will not be described in detail here. Any device used by those skilled in the art to implement the method in the embodiments of this application falls within the scope of protection of this application.

[0071] In practice, when the computer program 311 is executed by the processor, it can implement any of the embodiments corresponding to the first aspect.

[0072] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0073] Those skilled in the art will understand that embodiments of this application can provide methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-readable storage media containing computer-readable program code.

[0074] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0075] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0076] These computer program instructions can also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0077] This application also provides a computer program product, which includes computer software instructions that, when executed on a processing device, cause the processing device to perform... Figure 1 The flowchart of an optimized control method for an iron and steel smelting system in a corresponding embodiment.

[0078] A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, computer instructions may be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium may be any usable medium that a computer can store or a data storage device such as a server or data center that integrates one or more usable media. The usable medium may be a magnetic medium, an optical medium, or a semiconductor medium, etc.

[0079] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0080] In the several embodiments provided in this application, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Furthermore, the mutual couplings or direct couplings or communication connections shown or discussed may be indirect couplings or communication connections through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0081] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0082] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in the form of hardware and / or software functional units.

[0083] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device to execute all or part of the steps of the methods in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, magnetic disks, or optical disks.

[0084] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

[0085] Although preferred embodiments have been described in this specification, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications that fall outside the scope of this specification.

[0086] Obviously, those skilled in the art can make various modifications to this specification without departing from its spirit and scope. Therefore, this specification is intended to include any modifications that fall within the scope of the claims and their equivalents.

Claims

1. A method of optimal control of a steelmaking system, characterized in that, The steel smelting system includes multiple subsystems, each subsystem corresponding to a target process in the smelting process, and the control method includes: Based on the material parameters of each subsystem and the target optimization parameters, determine the target control parameters for each subsystem; Based on the global energy parameters of the steel smelting system and the weight information of each subsystem in the smelting process, the target control parameters are adjusted to generate the actual control parameters of each subsystem. Control the operation of each subsystem according to the actual control parameters; The target control parameters and the actual control parameters both include the material ratio parameters and global energy scheduling parameters of the subsystem. The material ratio parameters are used to indicate the material ratio of the subsystem, and the global energy scheduling parameters are used to indicate the energy consumption of the subsystem. The weight information is used to characterize the importance of the target process of the corresponding subsystem in the smelting process.

2. The optimal control method according to claim 1, characterized in that, The step of determining the target control parameters for each subsystem based on the material parameters and the target optimization parameters of each subsystem includes: Based on the subsystem production model, the target material ratio parameters of the subsystem are determined according to the material parameters and the target optimization parameters. Based on the target material ratio parameters, determine the target energy consumption of the subsystem; Based on the subsystem energy model, the target global energy scheduling parameters of the subsystem are determined according to the target energy consumption.

3. The optimal control method according to claim 2, characterized in that, The step of adjusting the target control parameters and generating the actual control parameters for each subsystem based on the global energy parameters of the steel smelting system and the weight information of each subsystem in the smelting process includes: An energy coordination module is used to determine the actual energy consumption of each subsystem based on the global energy parameters of the steel smelting system and the weight information. Based on the actual energy consumption, the target material ratio parameters and the target global energy scheduling parameters are adjusted to obtain the actual material ratio parameters and actual global energy scheduling parameters for each subsystem.

4. The optimized control method according to claim 3, characterized in that, Before determining the actual energy consumption of each subsystem based on the global energy parameters of the steel smelting system and the weight information using the energy coordination module, the control method further includes: A weight allocation module is used to determine the weight information of each subsystem in the smelting process based on the state information of all the subsystems.

5. The optimized control method according to claim 3, characterized in that, After controlling the operation of each subsystem according to the actual control parameters, the control method further includes: Obtain the actual optimization parameters for each of the subsystems; Based on the actual control parameters, the target optimization parameters, and the actual optimization parameters, at least one of the energy coordination module and the weight allocation module is updated.

6. The optimized control method according to claim 2, characterized in that, Before determining the target control parameters for each subsystem based on the material parameters and the target optimization parameters of each subsystem, the control method further includes: Obtain historical production data and historical energy consumption data of the subsystem within the current historical time period; Based on the historical production data and historical energy consumption data, establish the subsystem production model and the subsystem energy model.

7. An optimized control device for an iron and steel smelting system, characterized in that, The steel smelting system includes multiple subsystems, each subsystem corresponding to a target process in the smelting process, and the control device includes: The determining unit is configured to determine the target control parameters for each of the subsystems based on the material parameters of each subsystem and the target optimization parameters. The adjustment unit is used to adjust the target control parameters based on the global energy parameters of the steel smelting system and the weight information of each subsystem in the smelting process, and to generate the actual control parameters of each subsystem. A control unit is used to control the operation of each of the subsystems according to the actual control parameters; The target control parameters and the actual control parameters both include the material ratio parameters and global energy scheduling parameters of the subsystem. The material ratio parameters are used to indicate the material ratio of the subsystem, and the global energy scheduling parameters are used to indicate the energy consumption of the subsystem. The weight information is used to characterize the importance of the target process of the corresponding subsystem in the smelting process.

8. The optimized control device according to claim 7, characterized in that, The determining unit is specifically used for: Based on the subsystem production model, the target material ratio parameters of the subsystem are determined according to the material parameters and the target optimization parameters. Based on the target material ratio parameters, determine the target energy consumption of the subsystem; Based on the subsystem energy model, the target global energy scheduling parameters of the subsystem are determined according to the target energy consumption.

9. The optimized control device according to claim 8, characterized in that, The adjustment unit is specifically used for: An energy coordination module employing a pre-defined neural network model determines the actual energy consumption of each subsystem based on the global energy parameters of the steel smelting system and the weight information. Based on the actual energy consumption, the target material ratio parameters and the target global energy scheduling parameters are adjusted to obtain the actual material ratio parameters and actual global energy scheduling parameters for each subsystem.

10. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program stored in the memory, implements the steps of the optimized control method for the steel smelting system as described in any one of claims 1 to 6.

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