Energy efficiency evaluation method for optimizing operation of ferric material flow in steel manufacturing process, production operation optimization method and system

Abstract

The application discloses an energy efficiency evaluation method for optimizing the operation of ferrum material flow in a steel manufacturing process, a production operation optimization method and a system, and comprises the following steps: determining the steel manufacturing process and the process object, calculating the process energy efficiency of the steel manufacturing and the process energy efficiency under different process paths based on the operation mode of the ferrum material flow in different sections and the characteristics of the metallurgical process, and expanding the process energy efficiency calculation method to the whole process through the logistics connection relationship including the iron-steel interface and the casting-rolling interface; and establishing a multi-objective production operation optimization model taking the process energy efficiency, operation efficiency and cost as the object to optimize the multi-process path of the process. The technical scheme focuses on the different aspects of the metallurgical process of the process equipment and the production process operation control, realizes the dynamic tracking of the energy efficiency from the process to the process, optimizes the process path selection of the production operation of the steel enterprise, and is beneficial to the dynamic operation control optimization and energy saving and carbon reduction of production.

Description

Technical Field

[0001] This invention belongs to the field of energy efficiency evaluation technology, and relates to an energy efficiency evaluation method, production operation optimization method and system for optimizing the flow of ferrite materials in the steel manufacturing process. Background Technology

[0002] The steel industry urgently needs to explore efficient and energy-saving approaches to achieve low-carbon, green, and intelligent transformation and upgrading.

[0003] Energy efficiency evaluation is an important basis for energy conservation and consumption reduction in industrial production. It can comprehensively understand the energy consumption and utilization status of energy conversion systems, identify and improve inefficient links, guide cost reduction and efficiency improvement, and promote the development of production towards energy conservation, environmental protection and sustainability.

[0004] China's existing energy efficiency evaluation system for the steel industry is based on comprehensive energy consumption per ton of steel, comparable energy consumption per ton of steel, and process energy consumption. It measures energy consumption levels and utilization efficiency by comparing the energy consumed to complete steel production capacity within a statistical period with the actual amount of steel produced. However, the indicator system based on energy consumption per ton of steel and process energy consumption is a measurement method built on production statistics. Since steel is an intermediate product, it cannot distinguish the complexity of material transformation and energy conversion between different products and different process paths; it also fails to reflect the volatility of actual production and cannot adapt to the development trend of dynamic and flexible manufacturing. The steel industry is unique in that metallurgical reactors such as blast furnaces and converters are also energy conversion equipment, requiring solutions to the calculation of energy consumption and energy efficiency.

[0005] While existing research has made significant progress, there is still a lack of energy efficiency description and evaluation methods related to process operation characteristics and manufacturing process paths in the process of ferrous material flow carrying energy flow during the accompanying material transformation process or flow of steel product manufacturing. These methods cannot effectively measure the energy flow conversion and utilization effects of different types of metallurgical processes and different process paths in the production operation of product manufacturing, and cannot be used to guide the optimization of production operation management. Summary of the Invention

[0006] The purpose of this invention is to provide an energy efficiency evaluation method, production operation optimization method and system for optimizing the flow of ferrite materials in the steel manufacturing process. This system enables dynamic tracking of energy efficiency from process steps to the entire process, optimizes the operation of the steel manufacturing process and displays the results, and can guide the selection of the optimal process path.

[0007] To achieve the above objectives, the basic solution of this invention is: an energy efficiency evaluation method for optimizing the flow of ferrite materials in a steel manufacturing process, comprising the following steps:

[0008] Determine the production flow, process equipment, and technological path of the steel manufacturing process, and complete the collection and processing of operational optimization data in real time or in stages;

[0009] Based on production operation data of ferrite material flow and energy flow, and considering the material flow forms, metallurgical process characteristics, and process paths of ferrite material flow in different sections, the process energy efficiency and flow efficiency of steel manufacturing are calculated. This achieves the organic synergy between the manufacturing process carrying energy flow from ferrite material flow and the material and energy conversion and utilization in the process. The process energy efficiency includes chemical metallurgical process energy efficiency, physical metallurgical process energy efficiency, and process interface energy efficiency. The flow efficiency is the energy efficiency from the start to the end of the ferrite material flow manufacturing process of the process object. To ensure comparability between different processes, flows, interfaces, and paths, the energy efficiency calculation of material flow in all production processes is based on the material flow form of unit product. Material flow tracking, correspondence, and conversion can be performed between molten iron, molten steel, continuously cast billets, and steel products.

[0010] Dynamic energy efficiency evaluation is performed based on the process energy efficiency and workflow energy efficiency, which is used to optimize the operation of the steel manufacturing process. A production operation optimization system is constructed to complete the data collection and processing, model loading and solving, and optimization results display.

[0011] The working principle and beneficial effects of this basic scheme are as follows: This technical solution constructs an energy efficiency evaluation production operation optimization system. Through real-time data collection and analysis, it dynamically tracks energy efficiency changes from process steps to the entire process, providing real-time feedback for production operation optimization. Subsequently, a comprehensive objective function centered on process energy efficiency is constructed, considering factors such as process energy efficiency, operational efficiency, and production costs. Constraints such as quality constraints, equipment production capacity constraints, path feasibility, and production time are considered to solve for and determine the optimal process path. Based on the energy efficiency evaluation results, process control and path selection are optimized, implementing dynamic production operation optimization to achieve energy conservation and carbon reduction.

[0012] This paper focuses on the dynamic coupling relationship between the flow of ferrous materials and the energy flow they carry in the steel manufacturing process. It examines different levels of metallurgical process and production process operation and control of equipment, and proposes energy efficiency evaluation methods and calculation models related to metallurgical processes and process paths. This enables dynamic tracking of energy efficiency from process to process, optimizes process control and path selection in steel enterprises, and is conducive to dynamic production operation optimization and energy conservation and carbon reduction.

[0013] Furthermore, based on the characteristics of the metallurgical process, the process is divided into chemical metallurgy (such as blast furnace and converter smelting) and physical metallurgy (such as continuous casting solidification and hot rolling heating furnace). The energy efficiency calculation method for chemical metallurgical processes is as follows:

[0014]

[0015] in, Energy efficiency of chemical metallurgical processes for metallurgical process j; and These represent the physical heat and chemical heat outputs of the ferrite material flow during the metallurgical process, respectively. The energy medium for recovering reusable energy in metallurgical processes includes the physical and chemical heat carried by the energy medium itself. and These are the physical heat and chemical heat inputs of the ferrite material flow in the metallurgical process, respectively. The energy carried by the materials that participate in the chemical reaction during the metallurgical process; The energy supplied for metallurgical process j.

[0016] Chemical metallurgy processes, mainly in the iron and steel metallurgy stage, involve a large number of complex chemical reactions, resulting in significant changes in the input and output physical and chemical heat, and there is an interconversion between the two.

[0017] Furthermore, the energy efficiency of the physical metallurgical process is as follows:

[0018]

[0019] in, The physical metallurgical process energy efficiency of metallurgical process j. Energy media recovery and reuse of energy in metallurgical processes; The energy carried by the energy medium in the metallurgical process j; The physical heat output of the ferrite material flow in the metallurgical process; This refers to the physical heat input of the ferrite material flow in the metallurgical process.

[0020] The physical metallurgical process begins with the solidification and heat transfer process of continuous casting. The chemical composition of the ferrite material stream remains unchanged, and it changes from liquid steel to a continuously cast billet. Subsequent production focuses on the billet, only changing the morphology, structure, properties, and specifications of the ferrite material stream.

[0021] Furthermore, considering the iron-steel interface (the material flow transport process from the blast furnace to the converter) and the casting-rolling interface (the material flow transport process from hot rolling to continuous casting), the process interface energy efficiency is as follows: This involves the physical and thermal changes of ferrite material flow at the interface due to temperature drop caused by transport.

[0022]

[0023] in, The interface energy efficiency between any two processes p1 and p2; and These are the physical heat of the ferrite material flowing into process p1 and out of process p2, respectively, which mainly reflect the energy dissipation during the material flow transportation process.

[0024] Furthermore, considering the entire production process as a large system, the system state changes are considered as follows: the input of physical and chemical heat from the ferrite material flow is based on the initial process m, and the output of physical and chemical heat is based on the final process n. The intermediate processes only consider the heat recovered from the input and output energy media. The process energy efficiency is:

[0025]

[0026] in, The process energy efficiency from metallurgical process m to metallurgical process n; and These are the chemical heat and physical heat outputs of ferrite material flow in metallurgical process n, respectively. To recover reusable energy from all types of energy media in all processes from m to n in the metallurgical process; and These are the chemical and physical heat inputs of the ferrite material flow in the metallurgical process m, respectively. This represents the energy carried by externally supplied materials in all metallurgical processes from m to n. It represents the total energy directly supplied from the outside for all processes from m to n in the metallurgical process.

[0027] By acquiring process energy efficiency data, dynamic tracking of energy efficiency can be achieved from individual processes to the entire process.

[0028] The present invention also provides a production operation optimization method, comprising the following steps:

[0029] The energy efficiency evaluation method for optimizing the ferrite material flow in the steel manufacturing process described in this invention is used to dynamically evaluate process energy efficiency and process energy efficiency.

[0030] Establish a production operation optimization system;

[0031] The operation of the steel manufacturing process is optimized based on the dynamic evaluation results.

[0032] This method can be used to optimize production operations.

[0033] Furthermore, the method for optimizing the operation of the steel manufacturing process based on the dynamic evaluation results is as follows:

[0034] Taking a product-oriented approach, this study traces the logistics path of steel production from the product end in reverse, constructing a logistics mapping relationship for ferrous material flow within the steel manufacturing process. This mapping process covers the entire process from finished steel products, continuously cast billets, steelmaking furnace cycles, back to the blast furnace ladle, identifying key nodes and resource conversion paths in the logistics transfer process, and establishing dynamic correspondences between ferrous material flows. Particularly in the converter steelmaking stage, the addition of scrap steel has a significant impact on energy efficiency improvement and cost reduction, and must be included in the path modeling and optimization considerations.

[0035] Using unit products as the evaluation object, the resource consumption and energy efficiency characteristics under the logistics path are calculated, serving as one of the basic data sources for production operation optimization. Under the premise of ensuring product quality, by calculating the comprehensive consideration of energy efficiency, operational efficiency, and cost of various process paths in the production process corresponding to m to n in the metallurgical process, a more optimized product production process route is selected to achieve the goal of improving quality and efficiency. A production operation optimization objective function Maxmize Z, with process energy efficiency as its core, is constructed:

[0036]

[0037] in, The process energy efficiency is the energy efficiency from metallurgical process m to n in the technological process. The production efficiency from metallurgical process m to n; Let α, γ, and ω represent the production and operating costs from metallurgical process m to n, respectively, and let α, γ, and ω be the process energy efficiency, operating efficiency, and cost weighting coefficients.

[0038] For the operational efficiency target, the operational efficiency is represented by the process time of the ferrite material flow:

[0039]

[0040] in, τ represents the operating efficiency from metallurgical process m to n. j This refers to the material transport time from the first metallurgical process (j) to the next metallurgical process (j). The interface transportation time between the kth process contained in the path;

[0041] The cost objective function is expressed in terms of the conversion rate of ferrite material flow and equipment utilization efficiency:

[0042]

[0043] Among them, M m M n M scrapThese represent the material flow weights corresponding to metallurgical processes m and n in the process path from m to n, and the amount of scrap steel added during the process; τ′ j Let j be the production operation time of the material flow in the metallurgical process. ω1 represents the total operating time of all processes in the metallurgical process j corresponding to the material flow; ω1 and ω2 are the weights of the material conversion rate and the scrap steel addition rate, respectively, which can be adjusted according to process requirements.

[0044] Optimization of steel production operations also requires meeting the following constraints:

[0045] Product quality constraints:

[0046] Among them, Q j These are the quality indicators that a material flow needs to meet during a metallurgical process, including temperature and composition or grade indicators. and These are the minimum and maximum quality indicators corresponding to the material flow in the metallurgical process j;

[0047] Equipment capacity constraints:

[0048] in, The quantity of resources used in the metallurgical process j, primarily based on equipment production capacity. and This refers to the upper and lower limits of the production capacity of equipment in the metallurgical process.

[0049] Feasible process path constraints:

[0050]

[0051] Among them, P j For the set of all feasible process paths containing metallurgical process j

[0052] Production time constraints:

[0053] The production time of the material flow in the metallurgical process; and These represent the minimum and maximum allowable times for material flow in metallurgical process j, respectively.

[0054] Obtain the optimal process path and optimize the process flow.

[0055] The present invention also provides a production operation optimization system, including a processing unit. The processing unit executes the production operation optimization method of the present invention to optimize the operation of the steel manufacturing process and display the results. Specifically, it can optimize process control and / or path selection based on the dynamic evaluation, and / or implement dynamic production operation optimization, and / or save energy and reduce carbon emissions.

[0056] This system can effectively distinguish the energy efficiency differences of different types of steel products in different processes, equipment and process paths. The energy efficiency evaluation based on the ferrite material flow characteristics can provide a basis for steel enterprises to optimize process control and path selection, implement dynamic production operation optimization and energy saving and carbon reduction. Attached Figure Description

[0057] Figure 1 This is a schematic diagram of the energy efficiency evaluation method for optimizing the flow of ferrite materials in the steel manufacturing process according to the present invention. Detailed Implementation

[0058] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0059] In the description of this invention, it should be understood that the terms "longitudinal", "lateral", "up", "down", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0060] In the description of this invention, unless otherwise specified and limited, it should be noted that the terms "installation", "connection" and "linking" should be interpreted broadly. For example, they can refer to mechanical or electrical connections, or internal connections between two components. They can be direct connections or indirect connections through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms according to the specific circumstances.

[0061] This invention discloses an energy efficiency evaluation method for optimizing the operation of ferrite material flow in steel manufacturing processes. Addressing the current issues in the steel industry, such as the conflation of "energy consumption" and "energy efficiency," and the inability of evaluation indicators based on energy consumption per ton of steel and process energy consumption to differentiate between different products and processes, this invention proposes the concept of "process effective energy." This is defined as the sum of the energy acquired by the ferrite material flow during the metallurgical processes of each process step to achieve metallurgical goals per unit product output, and the energy recovered and reusable during the process. Process energy efficiency is calculated by dividing the effective energy by the energy brought into the process and the total energy supplied, thus describing the energy conversion and utilization effects of the ferrite material flow through each metallurgical process step.

[0062] By analyzing the input-output relationship of material flow and energy flow in multiple processes, and combining the characteristics of metallurgical processes, calculation models for the energy efficiency of chemical metallurgy (converter, refining, etc.) and physical metallurgy (continuous casting solidification, etc.) processes are constructed, and calculation methods for process interface energy efficiency and process energy efficiency are given.

[0063] By analyzing the input and output of material and energy flows across multiple processes and combining them with thermodynamic equilibrium relationships, dynamic tracking of energy efficiency from process to the entire process is achieved.

[0064] The energy efficiency differences of different process paths, metallurgical equipment and products were quantitatively analyzed. The energy efficiency evaluation method based on the ferrite material flow operation characteristics can provide a basis for steel enterprises to optimize process control and path selection, implement dynamic production operation optimization and energy saving and carbon reduction.

[0065] like Figure 1 As shown, the energy efficiency evaluation method for optimizing the ferrite material flow in the steel manufacturing process of this invention includes the following steps:

[0066] The production flow, process equipment, and technological paths of the steel manufacturing process are determined, and data collection and processing for operational optimization are completed in real time or in stages. Specifically, the technological sections of ferrite material flow in the steel manufacturing process are identified:

[0067] Because the manufacturing process involves single-supply and demand internal energy conversion and process synergy between various processes due to waste heat recovery and energy connection, energy efficiency evaluation is divided into process energy efficiency and process energy efficiency.

[0068] Process energy efficiency is divided into chemical metallurgical process energy efficiency, physical metallurgical process energy efficiency, and process interface energy efficiency.

[0069] Process energy efficiency includes energy efficiency of processes with multiple process paths.

[0070] Based on production operation data of ferrite material flow and energy flow, and considering the material flow forms of ferrite material flow in different sections, metallurgical process characteristics, and process paths, the process energy efficiency and flow efficiency of steel manufacturing are calculated. This achieves the organic synergy between the manufacturing process carrying energy flow from ferrite material flow and the material and energy conversion and utilization in the process. Process energy efficiency includes chemical metallurgical process energy efficiency, physical metallurgical process energy efficiency, and process interface energy efficiency. Flow efficiency is the energy efficiency from the start to the end of the ferrite material flow manufacturing process of the process object. To ensure comparability between different processes, flows, interfaces, and paths, the energy efficiency calculation of material flow in all production processes is based on the material flow form of unit product. Material flow tracking, correspondence, and conversion can be performed between molten iron, molten steel, continuously cast billets, and steel products.

[0071] Dynamic energy efficiency evaluation is performed based on the process energy efficiency and workflow energy efficiency to optimize the operation of the steel manufacturing process. A production operation optimization system is constructed to complete the data collection and processing, model loading and solving, and optimization results display.

[0072] A production operation optimization system for energy efficiency evaluation is constructed. Through real-time data collection and analysis, it dynamically tracks energy efficiency changes from individual processes to the entire production flow, providing real-time feedback for production operation optimization. A comprehensive objective function centered on process energy efficiency is constructed, considering factors such as process energy efficiency, operational efficiency, and production costs. Constraints such as product quality constraints, resource quantity constraints, feasible path constraints, and production time constraints are considered to solve for and determine the optimal process path. Based on the energy efficiency evaluation results, process control and path selection are optimized, implementing dynamic production operation optimization to achieve energy conservation and carbon reduction.

[0073] This invention focuses on the dynamic coupling relationship between ferrous material flow and energy flow in the steel manufacturing process, and proposes an energy efficiency evaluation method related to the metallurgical process and production process operation and control of equipment.

[0074] This paper focuses on the ferrite material flow carrying energy flow in the steelmaking-continuous casting section and its upstream and downstream interfaces of a converter steel plant, where there is frequent material-energy interaction. The material flow undergoes a discrete-continuous / quasi-continuous transformation process from molten iron to molten steel to cast billet, accompanied by energy conversion and utilization in the process and flow. Based on this, the concept of process effective energy is proposed.

[0075] In a preferred embodiment of the present invention, "process efficiency" can be defined as the energy obtained from the change in the properties and form of the ferrous material flow during the metallurgical process to achieve the metallurgical objectives of each process step, plus the recovered and reusable energy. Different energy sources are unified according to the calorific value of the energy medium. Dividing the metallurgical process efficiency within the corresponding spatiotemporal range by the total energy consumption yields the concept and calculation method of "process energy efficiency."

[0076]

[0077] Where, η j Energy efficiency of metallurgical process j; G total G represents the overall effective energy of metallurgical process j; input The input energy for metallurgical process j; and G″ pj The effective energy carried by the material flow output of metallurgical process j and the total energy supplied by the material flow process are respectively considered. and G″ pj These are the effective energy carried by the material flow output in metallurgical process j and the total energy supplied by the material flow process, respectively. Taking the converter process as an example, its smelting objective is to ensure that the quality of the molten steel output meets the standards. The material flow carries energy, including physical heat and chemical heat, which serve as the effective energy of the material flow.

[0078] Chemical metallurgical processes, primarily occurring in the iron and steel metallurgical stage, involve numerous complex chemical reactions, leading to significant changes in the input and output physical and chemical heat, with interconversion between the two. Based on their characteristics, metallurgical processes are categorized into chemical metallurgy (e.g., blast furnace and converter smelting) and physical metallurgy (e.g., continuous casting solidification and hot rolling furnace heating). The energy efficiency calculation method for chemical metallurgical processes is as follows:

[0079]

[0080] in, Energy efficiency of chemical metallurgical processes for metallurgical process j; and These represent the physical heat and chemical heat outputs of the ferrite material flow during the metallurgical process, respectively. The energy medium for recovering reusable energy in metallurgical processes includes the physical and chemical heat carried by the energy medium itself. and These are the physical heat and chemical heat inputs of the ferrite material flow in the metallurgical process, respectively. The energy carried by the materials that participate in the chemical reaction during the metallurgical process; The energy supplied for metallurgical process j.

[0081] In a preferred embodiment of the present invention, the physical metallurgical process begins with the solidification and heat transfer process of continuous casting. The chemical composition of the ferrite material stream remains unchanged, but it transforms from liquid steel into a continuously cast billet. Subsequent production focuses on the cast billet, only altering the morphology, microstructure, properties, and specifications of the ferrite material stream. The input and output physical heat of the material stream undergoes corresponding changes during the physical metallurgical process. The energy efficiency calculation formula for the physical metallurgical process is as follows:

[0082]

[0083] in, The physical metallurgical process energy efficiency of metallurgical process j. Energy media recovery and reuse of energy in metallurgical processes; The energy carried by the energy medium in the metallurgical process j; The physical heat output of the ferrite material flow in the metallurgical process; This refers to the physical heat input of the ferrite material flow in the metallurgical process.

[0084] In a preferred embodiment of the present invention, the core of the process interface energy efficiency calculation lies in the physical heat loss caused by temperature drop during the transfer of ferrous material between interfaces. For example, at the iron-steel interface, molten iron loses physical heat due to temperature drop during transportation from the blast furnace to the steel plant; at the casting-rolling interface, molten steel also loses some physical heat due to temperature drop while waiting in the silo. These physical heat losses not only relate to energy waste but may also affect the operational efficiency and product quality of subsequent processes. Therefore, process interface energy efficiency is also included in the energy efficiency assessment system.

[0085] The process interface considers the iron-steel interface (the material flow transport process from blast furnace to converter) and the casting-rolling interface (the material flow transport process from hot rolling to continuous casting), involving the physical and thermal changes of ferrite material flow at the interface due to temperature drop caused by transport. Therefore, its energy efficiency calculation model is similar to that of physical metallurgy energy efficiency calculation, but it lacks the energy carried by the energy medium and the recovered energy. The calculation model for process interface energy efficiency is as follows:

[0086]

[0087] in, The interface energy efficiency between any two processes p1 and p2; and These are the physical heat of the ferrite material flowing into process p1 and out of process p2, respectively, which mainly reflect the energy dissipation during the material flow transportation process.

[0088] In a preferred embodiment of the present invention, energy efficiency calculations in the steel manufacturing process need to consider the energy synergy of each process and the conversion of material flow benchmarks for product input and output at different stages. During energy efficiency calculations, the product benchmarks differ at different stages, necessitating material flow conversion. For example, when converting converter energy efficiency to ton-of-product, the input ferrite material flow is first calculated based on the quality and physicochemical state of molten iron and scrap steel, while the output ferrite material flow is calculated based on the quality and physicochemical state of the tapped steel. The energy efficiency calculation for the continuous casting process is based on the input molten steel quality and its physicochemical state, and the total output billet quality and its physicochemical state.

[0089] When calculating process energy efficiency, the entire production process is considered as a large system. The system state changes are considered as follows: the input of physical and chemical heat of ferrite material flow is based on the initial process m, and the output of physical and chemical heat is based on the final process n. The intermediate processes only consider the heat recovered from the input energy medium and output energy. The process energy efficiency is:

[0090]

[0091] in, The process energy efficiency from metallurgical process m to metallurgical process n; and These are the chemical heat and physical heat outputs of ferrite material flow in metallurgical process n, respectively. To recover reusable energy from all types of energy media in all processes from m to n in the metallurgical process; and These are the chemical and physical heat inputs of the ferrite material flow in the metallurgical process m, respectively. This represents the energy carried by externally supplied materials in all metallurgical processes from m to n. It represents the total energy directly supplied from the outside for all processes from m to n in the metallurgical process.

[0092] The present invention also provides a production operation optimization method, comprising the following steps:

[0093] The energy efficiency evaluation method for optimizing the ferrite material flow in the steel manufacturing process described in this invention is used to dynamically evaluate process energy efficiency and process energy efficiency.

[0094] Establish a production operation optimization system;

[0095] The operation of the steel manufacturing process is optimized based on the dynamic evaluation results.

[0096] This method can be used to optimize production operations.

[0097] In a preferred embodiment of the present invention, the method for optimizing the operation of the steel manufacturing process based on dynamic evaluation results is as follows:

[0098] Taking a product-oriented approach, this study traces the logistics path of steel production from the product end in reverse, constructing a logistics mapping relationship for ferrous material flow within the steel manufacturing process. This mapping process covers the entire process from finished steel products, continuously cast billets, steelmaking furnace cycles, back to the blast furnace ladle, identifying key nodes and resource conversion paths in the logistics transfer process, and establishing dynamic correspondences between ferrous material flows. Particularly in the converter steelmaking stage, the addition of scrap steel has a significant impact on energy efficiency improvement and cost reduction, and must be included in the path modeling and optimization considerations.

[0099] Using unit products as the evaluation object, the resource consumption and energy efficiency characteristics under the logistics path are calculated, serving as one of the basic data sources for production operation optimization. Under the premise of ensuring product quality, by calculating the comprehensive consideration of energy efficiency, operational efficiency, and cost of various process paths in the production process corresponding to m to n in the metallurgical process, a more optimized product production process route is selected to achieve the goal of improving quality and efficiency. A production operation optimization objective function Maxmize Z, with process energy efficiency as its core, is constructed:

[0100]

[0101] in, The process energy efficiency is the energy efficiency from metallurgical process m to n in the technological process. The production efficiency from metallurgical process m to n; Let α, γ, and ω represent the production and operating costs from metallurgical process m to n, respectively, and let α, γ, and ω be the process energy efficiency, operating efficiency, and cost weighting coefficients.

[0102] For the operational efficiency target, the operational efficiency is represented by the process time of the ferrite material flow:

[0103]

[0104] in, τ represents the operating efficiency from metallurgical process m to n. j This refers to the material transport time from the first metallurgical process (j) to the next metallurgical process (j). The interface transportation time between the kth process contained in the path;

[0105] The cost objective function is expressed in terms of the conversion rate of ferrite material flow and equipment utilization efficiency:

[0106]

[0107] Among them, M m M n M scrap These represent the material flow weights corresponding to metallurgical processes m and n in the process path from m to n, and the amount of scrap steel added during the process; τ′ j Let j be the production operation time of the material flow in the metallurgical process. ω1 represents the total operating time of all processes in the metallurgical process j corresponding to the material flow; ω1 and ω2 are the weights of the material conversion rate and the scrap steel addition rate, respectively, which can be adjusted according to process requirements.

[0108] Optimization of steel production operations also requires meeting the following constraints:

[0109] Product quality constraints:

[0110] Among them, Q j These are the quality indicators that a material flow needs to meet during a metallurgical process, including temperature and composition or grade indicators. and These are the minimum and maximum quality indicators corresponding to the material flow in the metallurgical process j;

[0111] Equipment capacity constraints:

[0112] in, The quantity of resources used in the metallurgical process j, primarily based on equipment production capacity. and This refers to the upper and lower limits of the production capacity of equipment in the metallurgical process.

[0113] Feasible process path constraints:

[0114]

[0115] Among them, P j For the set of all feasible process paths containing metallurgical process j

[0116] Production time constraints:

[0117] The production time of the material flow in the metallurgical process; and These represent the minimum and maximum allowable times for material flow in metallurgical process j, respectively.

[0118] This invention, from the perspective of optimizing the operation and control of the main steel production process, is based on the understanding of the energy flow carried by the ferrous material flow from molten iron to molten steel to continuously cast billets. It analyzes the input and output of physical heat and chemical heat in chemical metallurgy, physical metallurgy, process interfaces, and the main steel metallurgical process. Combined with the smelting objectives of each metallurgical process, it can establish calculation models for the energy efficiency of different types of metallurgical processes.

[0119] For example, taking a steelmaking plant of a steel company as the research object, the energy efficiency evaluation models of its chemical metallurgy, physical metallurgy, and process interfaces were calculated and verified. This steelmaking plant mainly produces hot-rolled coils, and its molten iron resources mainly come from two blast furnaces. All products adopt different process paths in the converter and refining processes according to the different product varieties, quality and specification requirements, as well as the production organization.

[0120] Production data from the converter steel plant was continuously collected for one month. The quantities of molten iron and steel (in tons) and the corresponding continuous casting slabs were calculated based on the weight of molten iron and steel carried by the ladles and ladles, thus achieving a continuous flow of ferrite material. All data required for the model calculations were collected from the steel plant's information systems at different levels, including production management, energy control, and process control. All data was collected within the same production cycle to differentiate energy consumption differences among various intermediate steel products. To facilitate the evaluation of energy efficiency variations per ton of product throughout the entire process, 2973 complete and valid ferrite material flow data samples were obtained after data screening. Each sample represents a complete data chain from KR to continuous casting for one heat, and is linked to the molten iron at the iron-steel interface and the slab at the casting-rolling interface.

[0121] Ferrite material flow and transportation at the iron-steel interface are carried out in units of molten iron ladles. Based on the molten iron mass in the molten iron ladle, the receiving temperature, and the KR inlet temperature, the average iron-steel interface energy efficiency of 2,973 heats is calculated, as shown in Table 1.

[0122] Table 1 Energy Efficiency Evaluation Table for Iron-Steel Interface

[0123]

[0124] Two conventional paths, KR-conventional BOF-RH-CC and KR-conventional BOF-LF-CC, were selected for analysis. The process energy efficiency and flow efficiency calculation based on the furnace batch are shown in Table 2. The molten iron, molten steel and billet of the furnace batch are converted to tons of steel.

[0125] Table 2KR-Conventional BOF-RH-CC Energy Efficiency Evaluation Table

[0126]

[0127]

[0128] Table 3 shows the calculations of process energy efficiency based on the furnace batch and the flow process energy efficiency after the KR-conventional BOF-LF-CC process path, converting the molten iron, molten steel and billet of the furnace batch to tons of steel.

[0129] Table 3KR-Conventional BOF-LF-CC Energy Efficiency Evaluation Table

[0130]

[0131]

[0132] The casting-rolling interface uses the cast billet as the object, and calculates energy efficiency based on the billet's temperature upon leaving the continuous casting furnace and its temperature upon entering the furnace. During production, two charging modes are used for the furnace: hot charging and cold charging, depending on the casting-rolling rhythm. Hot-charged billets have a temperature above 400℃ (in this case, the average furnace entry temperature is considered to be 552℃), while cold-charged billets have a temperature below 400℃ (in this case, the average furnace entry temperature is considered to be 193℃). The continuous casting billets are matched to the heats according to the casting schedule, and the average energy efficiency of the casting-rolling interface based on the heat is shown in Table 4.

[0133] Table 4 Energy Efficiency Evaluation Table for Casting-Rolling Interface

[0134]

[0135] Based on the energy efficiency calculation of the interface and multi-process of the ferrous material flow from blast furnace tapping to steelmaking-continuous casting and hot rolling, the average energy efficiency results of 2,973 heats in each process are shown in Table 5.

[0136] Table 5 Energy efficiency levels of each unit process in the converter steel plant manufacturing process.

[0137] BF-KR KR BOF CAS LF RH CC CC-HR 92.27 91.17 71.54 / 67.78 98.2 96.4 91.1 67.3 44.4 / 14.8

[0138] Table 5 clearly shows significant differences in energy efficiency levels across different processes. Core processes such as converters and continuous casting have relatively low energy efficiency levels and high energy consumption. The chemical reactions and physical changes in the ferrite material flow are significant, and the synergistic relationship between material and energy flows is complex. There is room for improvement in energy efficiency by enhancing the precision of process control and improving energy recovery and reuse. Auxiliary processes such as KR, CAS, LF, and RH have relatively high energy efficiency levels. These processes only require minor adjustments to the composition of the ferrite material flow, with relatively low energy input and small changes in physical and chemical heat. The energy efficiency of the iron-steel interface and the casting-rolling interface is closely related to the interface connection method. Energy dissipation mainly depends on controlling the temperature drop of the ferrite material flow; obviously, a more efficient interface connection method can significantly improve energy efficiency. This analysis shows that the new energy efficiency index can better reflect the energy utilization level of each process, distinguish the differences between different types of processes and process paths, and provide guidance for energy conservation and carbon reduction in metallurgical processes.

[0139] Table 6. Operational efficiency levels of each refining unit in the converter steel plant.

[0140]

[0141]

[0142] Table 6 clearly shows significant differences in the distribution of the number of furnaces across different smelting processes over different time intervals. CAS and RH processes have a higher number of furnaces in shorter smelting time intervals, indicating relatively high processing efficiency. However, the number of furnaces decreases rapidly as smelting time increases, possibly due to material flow requirements. LF and LF-RH processes have a relatively higher number of furnaces in longer smelting time intervals, suggesting that their processes may require more time and that energy utilization efficiency needs improvement. Overall, the synergistic relationship between material flow and energy flow in each process is complex, and there is significant room for energy efficiency improvement in optimizing process control precision, balancing energy medium consumption, and enhancing energy recovery and reuse.

[0143] Table 7 Equipment Utilization Efficiency Levels of Each Refining Unit in the Converter Steel Plant

[0144]

[0145] Table 7 clearly shows significant differences in equipment utilization efficiency across different refining units in the converter steel plant. Refining processes like CAS and RH have a higher number of heats with higher equipment utilization rates, indicating relatively high equipment utilization. Conversely, LF and LF-RH processes have a relatively higher number of heats with lower equipment utilization rates, suggesting room for improvement in equipment utilization efficiency. Overall, the equipment utilization efficiency varies considerably across refining processes, and the coordination between material and energy flows is complex. There is significant room for improvement in optimizing equipment operation, increasing equipment utilization, and optimizing energy efficiency.

[0146] Table 8 Material conversion rate levels of each refining unit process in the converter steel plant

[0147]

[0148] Table 8 clearly shows significant differences in material conversion rates across various refining units in the converter steel plant. Major refining processes such as CAS, RH, and LF have a higher number of heats in the medium-to-high material conversion rate range, indicating relatively good material conversion efficiency. However, some heats are concentrated in the lower conversion rate range, suggesting unstable conversion efficiency. In contrast, processes like LF-RH and various duplex processes have relatively fewer heats and are more dispersed, indicating room for improvement in material conversion stability. Overall, the material conversion rates across refining processes are uneven, and the synergistic relationship between material and energy flows is complex. There is significant room for improvement in optimizing process control, enhancing material conversion efficiency, and reducing conversion fluctuations.

[0149] Therefore, while deepening the research on the mechanism of metallurgical processes, it is also necessary to strengthen the research on the synergistic relationship between material flow and energy flow from the perspective of system control. By calculating energy consumption per ton of steel, it is possible to clearly distinguish the energy efficiency differences of smelting the same steel grade using different paths. The production of high-energy-efficiency, high-quality, and high-efficiency products in the process presents a contradiction in path selection, requiring appropriate trade-offs based on the importance of production objectives.

[0150] Industrial application cases demonstrate that the new method can effectively differentiate the energy efficiency differences of different types of steel products across various process equipment and pathways. For example, the energy efficiency of conventional converter smelting is higher than that of duplex smelting. In the refining process, the energy efficiency of CAS, LF, and RH processes decreases in that order. However, the RH and CAS processes have shorter running times and higher material flow efficiency; while LF has a high material conversion rate, its material flow time is longer, resulting in lower material flow efficiency. Clearly, there are contradictions between energy efficiency, process running time, and production costs.

[0151] Therefore, in order to achieve the goals of improving quality and efficiency and low-carbon green development for steel enterprises, we should start from the perspective of optimizing production operation and control, conduct a comprehensive assessment of production orders in the steel manufacturing process from multiple aspects such as product quality, manufacturing cost, energy consumption and efficiency, and then formulate reasonable process equipment selection standards, process path priorities and control methods and strategies for different types of product manufacturing.

[0152] The present invention also provides a production operation optimization system, including a processing unit. The processing unit executes the production operation optimization method described in the present invention to optimize the operation of the steel manufacturing process and displays the results. It can optimize process control and / or path selection based on the dynamic evaluation, and / or implement dynamic production operation optimization, and / or save energy and reduce carbon emissions.

[0153] From the perspective of optimizing the material flow operation in the steel manufacturing process, this invention proposes the concepts of "process energy efficiency" and "process energy efficiency" based on the material and energy change characteristics of the metallurgical process and process operation. These concepts are used to describe the energy conversion and utilization of ferrite material flow in the production process where the material properties are transformed or the morphological properties are changed in each metallurgical process step.

[0154] The "effective energy" of the ferrite material flow energy state change process used to achieve metallurgical objectives is defined. The effective energy of the metallurgical process is then added to the energy recovered and entered into the energy system. This effective energy is divided by the total energy provided by the system in the process to obtain the process energy efficiency.

[0155] Similarly, process energy efficiency considers the entire steel manufacturing process as a larger system. System changes are measured by the ratio of the sum of the energy state changes of the output product and the total energy recovery to the energy flow carried by the input material flow. That is, the input is the energy state carried by the material flow of the first process, and the output is the product and energy state of the final process. Intermediate processes only consider the energy brought in by the input energy media and auxiliary materials. Based on this, the concepts and calculation methods of "process energy efficiency" and "process flow efficiency" are clarified.

[0156] The new energy efficiency evaluation method can distinguish between energy consumption and energy efficiency in metallurgical processes and equipment, improving the accuracy of energy efficiency calculations. It can also calculate energy efficiency per ton of product, and show the proportion of energy efficiency in each process within the overall process energy efficiency. This enables energy efficiency tracking and evaluation of different stages of the converter steelmaking process, achieving production operation optimization oriented towards product quality and energy conversion and utilization, and promoting refined management and control in steel production. This method provides steel enterprises with a new evaluation approach for production cost and benefit assessment, process path optimization, and energy conservation and carbon reduction, and also provides a decision-making basis for optimizing material flow.

[0157] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0158] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. An energy efficiency evaluation method for optimizing the flow of ferrous materials in a steel manufacturing process, characterized in that, Includes the following steps: Determine the production flow, process equipment, and technological path of the steel manufacturing process, and complete the collection and processing of operational optimization data in real time or in stages; Based on production operation data of ferrite material flow and energy flow, and considering the material flow forms, metallurgical process characteristics, and process paths of ferrite material flow in different sections, the process energy efficiency and flow efficiency of steel manufacturing are calculated. This achieves the organic synergy between the manufacturing process carrying energy flow from ferrite material flow and the material and energy conversion and utilization in the process. The process energy efficiency includes chemical metallurgical process energy efficiency, physical metallurgical process energy efficiency, and process interface energy efficiency. The flow efficiency is the energy efficiency from the start to the end of the ferrite material flow manufacturing process of the process object. To ensure comparability between different processes, flows, interfaces, and paths, the energy efficiency calculation of material flow in all production processes is based on the material flow form of unit product. Material flow tracking, correspondence, and conversion can be performed between molten iron, molten steel, continuously cast billets, and steel products. Based on the process energy efficiency and workflow energy efficiency, dynamic energy efficiency evaluation is carried out for the operation optimization of the steel manufacturing process. A production operation optimization system is constructed to complete the data collection and processing, model loading and solving, and optimization results display. The method for optimizing the operation of the steel manufacturing process based on the dynamic evaluation results is as follows: With a product-oriented approach, this study traces the logistics path of steel manufacturing from the product end backwards through the process, constructing a logistics mapping relationship of ferrous material flow in the steel manufacturing process. This logistics mapping process covers the entire process from finished steel products and continuously cast slabs and billets backwards to steelmaking furnaces, tracing back to the blast furnace molten iron ladle, identifying key nodes and resource conversion paths in the logistics transfer process, and establishing dynamic correspondence between ferrous material flows in logistics units. Taking unit product as the evaluation object, this study calculates the resource consumption and energy efficiency characteristics under the logistics path, using this as one of the basic data sources for production operation optimization. Under the premise of ensuring product quality, it calculates the comprehensive consideration of energy efficiency, operational efficiency, and cost of various process paths in the production process corresponding to m to n in the metallurgical process, selecting a more optimized product production process route to achieve the goal of improving quality and efficiency. A target function for production operation optimization with process energy efficiency as the core is constructed. : ， in, For the process flow from the metallurgical process arrive Process energy efficiency; To the metallurgical process arrive Production and operational efficiency; To the metallurgical process arrive The production and operating costs, These are respectively process energy efficiency, operational efficiency, and cost weighting coefficients; For the operational efficiency target, the operational efficiency is represented by the process time of the ferrite material flow: ， in, To the metallurgical process arrive Operating efficiency For material flow in metallurgical processes Logistics and transportation time to the next metallurgical process The interface transportation time between the kth process contained in the path; The cost objective function is expressed in terms of the conversion rate of ferrite material flow and equipment utilization efficiency: ， in, The process routes are respectively from the metallurgical process arrive In the metallurgical process and The corresponding material flow weights and the amount of scrap steel added during the process; For material flow in metallurgical processes Production operation time, For material flow in metallurgical processes The total operation time for all processes in the corresponding procedure; and These are the weights for material conversion rate and scrap steel addition rate, which can be adjusted according to process requirements; Optimization of steel production operations also requires meeting the following constraints: Product quality constraints: , in, For material flow in metallurgical processes The required quality indicators include temperature parameters and composition or grade parameters. and For material flow in metallurgical processes The corresponding minimum and maximum quality indicators; Equipment capacity constraints: , in, For material flow in metallurgical processes The amount of resources used is primarily based on equipment production capacity. and In the metallurgical process Equipment production capacity upper and lower limits; Feasible process path constraints: , ， in, For including metallurgical processes Set of all feasible process routes Production time constraints: , The production time of the material flow in the metallurgical process; and These are material flows in the metallurgical process. The minimum and maximum allowed time.

2. The energy efficiency evaluation method for optimizing the ferrite material flow in the steel manufacturing process as described in claim 1, characterized in that, Based on the characteristics of metallurgical processes, processes are classified into chemical metallurgy and physical metallurgy. The energy efficiency calculation method for chemical metallurgical processes is as follows: ， in, For metallurgical process Energy efficiency of chemical metallurgical processes; and Metallurgical processes The output of physical and chemical heat of ferrite material flow; For metallurgical process The energy medium recovers reusable energy, including the physical and chemical heat carried by the energy medium itself; and Metallurgical processes The input of physical and chemical heat to the ferrite material flow; For metallurgical process The energy carried by the materials that participate in the chemical reaction; For metallurgical process The energy supplied by it.

3. The energy efficiency evaluation method for optimizing the ferrite material flow in the steel manufacturing process as described in claim 2, characterized in that, The energy efficiency of physical metallurgical processes is: ， in, For metallurgical process Energy efficiency of physical metallurgical processes Metallurgical process Energy media can be used to recover and reuse energy; For metallurgical process The energy carried by the energy medium; For metallurgical process The physical heat output of ferrite material flow; For metallurgical process The physical heat input of ferrite material flow.

4. The energy efficiency evaluation method for optimizing the ferrite material flow in the steel manufacturing process as described in claim 1, characterized in that, The process interface energy efficiency is: ， in, For any two processes With process Interface energy efficiency; and The processes into which ferrous materials flow are respectively and outflow process The physical heat is mainly manifested as the energy dissipation during the material flow and transportation process.

5. The energy efficiency evaluation method for optimizing the ferrite material flow in the steel manufacturing process as described in claim 1, characterized in that, The entire production process is viewed as a large system, and the changes in the system state are considered as the input of physical and chemical heat from the ferrite material flow to the initial process. For this purpose, the physical and chemical heat outputs are used to terminate the process. For accuracy, each intermediate process only considers the heat recovered from each input energy medium and output energy source, and the process energy efficiency is: ， in, For metallurgical process To the metallurgical process Process energy efficiency; and Metallurgical processes The chemical and physical heat output of ferrite material flow; To recover reusable energy from all types of energy media in all processes from m to n in the metallurgical process; and These are the chemical and physical heat inputs of the ferrite material flow in the metallurgical process m, respectively. This represents the energy carried by externally supplied materials in all metallurgical processes from m to n. It represents the total energy directly supplied from the outside for all processes from m to n in the metallurgical process.

6. A production operation optimization method, characterized in that, Includes the following steps: The energy efficiency evaluation method for optimizing the ferrite material flow in the steel manufacturing process according to any one of claims 1-5 is used to dynamically evaluate the process energy efficiency and flow efficiency. Establish a production operation optimization system; The operation of the steel manufacturing process is optimized based on the dynamic evaluation results.

7. A production operation optimization system, characterized in that, The system includes a processing unit that executes the production operation optimization method of claim 6 to optimize the operation of the steel manufacturing process and display the results.

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