Iron and steel product carbon footprint management method and system based on life cycle assessment

Abstract

The present invention relates to the technical field of energy saving and carbon reduction of iron and steel enterprises. Disclosed are an iron and steel product carbon footprint management method and management system based on life cycle assessment. Aiming at an iron and steel enterprise with the characteristic of a blast furnace-converter long process, the present invention establishes an iron and steel product carbon footprint calculation model, an iron and steel product carbon footprint prediction model and an iron and steel product carbon footprint optimization model at a production device level by relying on the conversion relationship and the flow relationship of a substance flow and an energy flow in an iron and steel product production process during carbon footprint management. A plurality of carbon footprint management methods such as carbon footprint calculation, analysis, prediction and optimization are realized in view of the characteristic of path diversity in the iron and steel product production process, and a carbon footprint management system is formed on this basis. The carbon footprint management method overcomes the defect whereby existing carbon footprint management methods only analyze carbon footprints from the perspective of result comparison, and realizes targeted, interlocked and systematic carbon footprint management during the life cycle of an iron and steel product.

Description

A carbon footprint management method and system for steel products based on life cycle assessment Technical Field

[0001] The present invention relates to the technical field of energy conservation and carbon reduction in steel enterprises, and in particular to a carbon footprint management method and system for steel products based on life cycle assessment, in particular to a carbon footprint management method and system for long-process steel products. Background Art

[0002] Green, low-carbon development has become a top priority for the steel industry's transformation and upgrading. Steel companies should improve their carbon footprint management systems to thoroughly analyze and understand their steel product mix and emissions indicators, continuously optimize production processes and product mix, and enhance their competitiveness in carbon emission reduction.

[0003] Existing carbon footprint management systems within the steel industry are often not well-targeted and do not align with the actual production conditions of steel companies. This makes it difficult for companies to effectively integrate carbon emissions data into their carbon footprint management efforts, coordinate controls, and minimize their carbon footprint. Specifically, existing lifecycle carbon footprint calculation models simply linearly link upstream and downstream processes through material flows, focusing solely on crude steel products or simply allocating inputs and outputs of processes after ironmaking based on the quality of different types of steel products. In actual production, however, multiple production facilities with the same function often operate in parallel, and the specific production routes of different types of steel products vary between facilities, leading to variations in the carbon footprint of each product. Furthermore, the different sources of certain materials or energy inputs to the same facility also contribute to different direct and indirect carbon emissions. Carbon emissions from self-generated energy are determined by the energy conversion relationships between various devices in the energy system. Process-based models fail to fully reflect the specific energy conversion relationships within a steel company's energy system, nor the impact of the specific production paths between various facilities on the carbon footprint of products.

[0004] Furthermore, existing carbon footprint management systems lack a strong systemic framework and fail to incorporate comprehensive, effective carbon footprint management methods. Current carbon footprint management systems focus solely on comparative analysis of enterprise and product carbon footprints, providing a multi-dimensional basis for decision-making regarding adjustments to enterprise layout, product mix, energy and raw material structure, and other factors. For example, they compare various carbon emission data between different enterprise types, within the same enterprise, and within different time periods within the same enterprise to identify gaps and analyze potential for emission reductions. For specific steel enterprises, these comparisons often focus on comparing various product types, carbon emission boundaries, carbon emission contribution rates, and carbon emissions before and after the implementation of carbon reduction strategies. However, steel production processes involve a wide variety of energy resources, and production equipment and production paths are complex and variable. Consequently, the carbon footprint of steel products produced along different production paths will vary. Consequently, while comparative analysis focuses solely on the carbon footprint of steel product production, it lacks effective carbon footprint management methods for the production path itself. This makes it difficult to effectively manage and coordinate the carbon footprint of steel products throughout their lifecycle, integrating the production path with all lifecycle stages.

[0005] Summary of the Invention

[0006] In view of this, the purpose of the present invention is to provide a carbon footprint management method and system for steel products based on life cycle assessment, so as to overcome the defects of the existing process-based carbon footprint calculation model establishment and carbon footprint management scheme in that the carbon footprint results of different product types are calculated in a post-allocation manner, and there is a lack of carbon footprint calculation models that are refined into different production paths composed of the specific conversion relationships between various types of energy in the enterprise energy system and the input-output correspondence between various production equipment. The management method is single and there is a lack of management methods such as carbon footprint evaluation, analysis, prediction, and optimization related to the production path.

[0007] To this end, the present invention provides the following technical solutions:

[0008] The present invention provides a carbon footprint management method for steel products based on life cycle assessment, comprising:

[0009] Collect information on the company's steel products and the material flow, energy flow, and flow paths of the unit processes in the steel product production process; import the life cycle background database of the material flow and energy flow that have an exchange relationship with the outside of the factory during the production process; import the carbon emission factor library of the material flow and energy flow in the life cycle process;

[0010] Verify the collected material flow and energy flow data of each unit process in the production process by metal balance and carbon balance methods; update the background database and the carbon emission factor library; classify and store the corresponding data of different production paths, different steel grades, and different material flows and energy flows;

[0011] Determine the carbon footprint calculation functional units, production paths, and calculation system boundaries for different types of steel products; select data allocation principles; and establish a life cycle carbon footprint model;

[0012] Carbon footprint management is performed on the steel product based on the life cycle carbon footprint model.

[0013] Furthermore, the life cycle carbon footprint model includes: a life cycle carbon footprint calculation model, a life cycle carbon footprint prediction model and / or a life cycle carbon footprint optimization model;

[0014] Build a life cycle carbon footprint model, including:

[0015] In line with the requirements for calculating the carbon footprint of steel products, the calculation scope and allocation principles are determined. According to the nature, quantity and use of steel products, appropriate functional units are selected. Based on the connection between intermediate products between each unit process in the steel product production process and the conversion relationship between material flow and energy flow within the unit process, a carbon footprint calculation model for the life cycle of steel products is established.

[0016] Based on the carbon footprint calculation model, obtain the historical production path of the steel grade to be predicted and the conversion relationship and efficiency of the material flow and energy flow of the unit process, analyze and select appropriate path information and unit process information as the life cycle carbon footprint prediction model for information and data training; and / or,

[0017] Based on the carbon footprint calculation model of the steel product life cycle, the conversion relationship and efficiency of the material flow and energy flow of the unit process, and the number and corresponding relationship of the intermediate flows between each unit process are obtained. According to the corresponding relationship, conversion relationship and efficiency, the objective function and constraint conditions are constructed to minimize the carbon footprint of the product without changing the production process.

[0018] Furthermore, a carbon footprint calculation model for the life cycle of steel products was established, including:

[0019] Establish a steel product production process model based on the transformation relationship between each unit process, material flow and energy flow within the unit process, and the flow relationship between intermediate products in different unit processes;

[0020] Based on the steel product production process model and the material flow and energy flow related to the production process in the background database, a steel product life cycle process model is constructed;

[0021] Based on the steel product production process model and the steel product life cycle process model, the material flow and energy flow in the process are converted into carbon flow according to the carbon emission factors of the material flow and energy flow related to the production process, and a carbon footprint calculation model for the steel product life cycle is constructed;

[0022] Establish a life cycle carbon footprint prediction model, including:

[0023] Based on the carbon footprint calculation model of steel products’ life cycle, all historical production paths of the carbon footprint calculation results of the steel products to be predicted are obtained, and appropriate path information is analyzed and selected;

[0024] Based on the conversion relationship and efficiency of material flow and energy flow in the unit process and path information, as well as the corresponding relationship between the intermediate flow of each unit process and its upstream and downstream, when the type, input quantity, input unit process and production path between unit processes of input energy and raw materials are known, the output of material flow and energy flow of the unit process and the quantity and corresponding relationship of the intermediate flow between each unit process of the entire production process are obtained;

[0025] Based on the output of material flow and energy flow of unit process and the number and corresponding relationship of intermediate flows between each unit process in the entire production process, the conversion relationship and conversion efficiency of material flow and energy flow of unit process are obtained;

[0026] Based on the conversion relationship and efficiency of the material flow and energy flow of each unit process, as well as the corresponding relationship between the intermediate flow of each unit process and its upstream and downstream, according to the historical production path of the steel grade to be predicted, combined with the basic information of each unit process, the appropriate path and path information are analyzed and selected as the life cycle carbon footprint prediction model for information and data training;

[0027] Establish a life cycle carbon footprint optimization model, including:

[0028] Based on the life cycle carbon footprint calculation model, according to the conversion relationship and conversion efficiency of the material flow and energy flow of the unit process, and the number and corresponding relationship of the intermediate flows between each unit process, the objective function and constraints are set to minimize the product carbon footprint by optimizing the production path without changing the production process.

[0029] Based on the life cycle carbon footprint calculation model, the historical production path information, production data and carbon footprint result data of a certain steel product that needs to be optimized are obtained. Combined with the objective function and constraint conditions, a carbon footprint optimization model for steel products is formed.

[0030] Furthermore, carbon footprint management of steel products based on the life cycle carbon footprint model includes:

[0031] Based on the carbon footprint calculation model for the life cycle of steel products, the material flow and energy flow data, background data, and carbon emission factor data of the corresponding unit processes are imported; based on the relevant data of the steel products and the quality of the relevant data, the carbon footprint result data and the uncertainty interval of the results of the steel products are calculated; based on the carbon footprint result data of the steel products, the differences in the carbon footprints of different products and the differences in the contributions of various factors to the carbon footprint results are analyzed; based on the carbon footprint calculation model for the life cycle of steel products, the corresponding changes in the carbon footprint when a certain factor changes within the actual production value range are analyzed, thereby obtaining the sensitivity of the carbon footprint to the factor; the calculation and analysis results are classified and stored;

[0032] Based on the same carbon footprint calculation model and the carbon footprint results of steel products, we compared and analyzed the carbon footprint results of various steel products of the company, the sub-grades of the same category of steel products, and the same steel grade within different calculation time ranges;

[0033] Based on carbon footprint calculation models with different calculation boundaries, and based on the carbon footprint results of steel products, the carbon footprint results of the same steel grade within different calculation boundaries are compared and analyzed to help companies understand their actual carbon footprint situation;

[0034] Based on the carbon footprint data of steel products, the process contribution of the carbon footprint data of steel products is classified and calculated from three aspects: direct emissions from the production process, indirect emissions from external electricity and heat consumption, and emissions in the supply chain. The composition ratio and potential contribution impact of the carbon footprint data of each link of steel products are demonstrated;

[0035] Based on the carbon footprint results of steel products, during the production process within the factory, the process contribution of the carbon footprint data of steel products is classified and calculated from three dimensions: each production process, the equipment included in each process, and the input and output of each equipment. This shows the composition ratio and potential contribution impact of the carbon footprint data of each link of steel products.

[0036] Furthermore, carbon footprint management of steel products based on the life cycle carbon footprint model includes:

[0037] When the production path of steel products and the material and energy flows input in the unit process are known, the carbon footprint of steel products after production can be predicted based on the energy and raw material input locations and input quantities or during the product production process through the life cycle carbon footprint prediction model.

[0038] Furthermore, the carbon footprint of steel products after production is predicted, including:

[0039] Based on the carbon footprint prediction model of steel products’ life cycle, the carbon footprint calculation model of steel products can be used to predict the carbon footprint of steel products after production at the time of energy and raw material input or during the production process.

[0040] When the type, quantity, and unit processes of input energy and raw materials are known, and the final steel product has not yet been produced through the production process, the carbon footprint prediction model is used to obtain the input and output of the material and energy flows of each unit process of the steel product, as well as the intermediate flows and corresponding relationships between the various unit processes in the entire production process;

[0041] When the path of a certain link in the steel production process changes, the unit process of the link and the downstream unit processes connected to the unit process are adjusted in a timely manner based on the steel product carbon footprint prediction model, realizing real-time updated carbon footprint prediction when the path changes in the production process;

[0042] The corresponding relationships selected in the carbon footprint prediction model are combined with the input and output data of each unit process to obtain the carbon footprint prediction results; the accuracy of the prediction results is compared with the carbon footprint prediction results calculated based on the data collected from each unit process after the production of the steel product; based on the relevant data of the steel product and the quality of the relevant data, the carbon footprint prediction result data and the uncertainty interval of the results are calculated;

[0043] Based on the carbon footprint prediction result data and the uncertainty interval of the results, a comparative analysis is conducted with the carbon footprint calculation results and the uncertainty interval of the results calculated based on the post-production unit process data of the steel product produced through the same production path. By comparing the results within the uncertainty interval, the accuracy of the prediction results within the uncertainty interval is analyzed.

[0044] Furthermore, carbon footprint management of steel products based on the life cycle carbon footprint model includes:

[0045] When steel products have not yet been produced or are in the production process, the carbon footprint of the product is minimized by adjusting the path of this type of steel products based on the life cycle carbon footprint optimization model.

[0046] Furthermore, adjustments to the path for this type of steel products include:

[0047] Based on the optimized production path in the carbon footprint optimization model and combined with the input and output data of each unit process, the carbon footprint optimization results are obtained; based on the relevant data of the steel products and the quality of the relevant data, the carbon footprint optimization result data and the uncertainty interval of the results of the steel products are calculated;

[0048] When the path of a certain link in the steel production process can be optimized and adjusted during the production process, based on the carbon footprint optimization model, the path optimization is realized in the unit process in the link that can be optimized and adjusted, and in each downstream unit process connected to the unit process. When the path changes during the production process, real-time carbon footprint optimization is achieved. By comparing the changes in the steel product production path and the carbon footprint results after the original production path and the adjusted production path, the carbon footprint reduction is obtained, thereby analyzing the optimization potential of the carbon footprint of steel products;

[0049] After the product production process is completed, based on the carbon footprint optimization model, the carbon footprint results after the product path optimization are compared with the actual results to analyze whether the product production path is a low-carbon production path. If there is room for optimization, the optimization potential of the production path is analyzed;

[0050] Based on the carbon footprint optimization result data and the uncertainty interval of the results, a comparative analysis is conducted with the carbon footprint calculation results and the uncertainty interval of the results of the steel product produced through the original production path, and the effect of reducing the carbon footprint based on the comparison of the results and the optimization results within the uncertainty interval is analyzed.

[0051] The present invention also provides a carbon footprint management system for steel products based on life cycle assessment, comprising:

[0052] The data acquisition module is used to collect information on the company's steel products and the material flow, energy flow, and flow paths of the unit processes in the steel product production process; import the life cycle background database of the material flow and energy flow that have an exchange relationship with the outside of the factory during the production process; and import the carbon emission factor library of the material flow and energy flow in the life cycle process;

[0053] The data management module is used to verify the material flow and energy flow data collected from each unit process in the production process through metal balance and carbon balance methods; update the background database and carbon emission factor library; and classify and store data corresponding to different production paths, different steel grades, and different material and energy flows;

[0054] Model building module, used to determine the carbon footprint calculation functional units, production paths and calculation system boundaries of different types of steel products; select data allocation principles; and establish a life cycle carbon footprint model;

[0055] The carbon footprint analysis module is used to manage the carbon footprint of steel products based on the life cycle carbon footprint model constructed by the model building module.

[0056] Furthermore, the carbon footprint analysis module includes:

[0057] Carbon footprint calculation and analysis module, used to calculate and compare product carbon footprints based on the above carbon footprint calculation model;

[0058] A carbon footprint prediction and analysis module is used to predict the carbon footprint of steel products after production based on the above-mentioned carbon footprint prediction model at the time of energy and raw material input or during the production process, and to analyze the prediction results;

[0059] The carbon footprint optimization analysis module is used to optimize the carbon footprint results of products by adjusting the specific production path of steel products based on the above-mentioned carbon footprint optimization model, and analyze the optimization results.

[0060] Compared with the existing methods, the characteristics and beneficial effects of the present invention are:

[0061] The present invention aims at various types of steel products in steel enterprises characterized by a long blast furnace-converter process, and based on the life cycle assessment method, the transformation and flow relationship of material flow and energy flow and the process units connected thereto, realizes the carbon footprint management of steel products at the production equipment level. In combination with the transformation relationship of material flow and energy flow within the unit process and its flow relationship between different unit processes in the steel production process, as well as the complex characteristics of the sources of input raw materials and the destinations of output products and by-products of the unit process, a carbon footprint calculation and optimization model for steel products was invented. It fully realizes that when the production path of the steel product and the material flow and energy flow input in the unit process are known, the carbon footprint of the steel product after production can be predicted at the raw material input stage or during the production process. It fully realizes that when the original production path of the steel product is known, the carbon footprint of the product can be reduced by adjusting and optimizing the path of this type of steel product. It realizes a variety of carbon footprint management methods such as carbon footprint calculation, analysis, prediction, and optimization. Through the adopted carbon footprint management method, it is possible to accurately assess the impact of changes in production paths on the carbon footprint of steel products throughout their life cycle, making up for the defect of existing management methods that only analyze carbon footprint results, and realizing targeted, chain-like and systematic carbon footprint management of steel products throughout their life cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0063] FIG1 is a flow chart of a carbon footprint management method for steel products based on life cycle assessment in an embodiment of the present invention;

[0064] FIG2 is a structural block diagram of a carbon footprint management system for steel products based on life cycle assessment in an embodiment of the present invention. DETAILED DESCRIPTION

[0065] Life cycle assessment can comprehensively evaluate the carbon footprint of steel products and production processes throughout their entire life cycle, identifying key influencing factors and identifying measures to reduce energy consumption and carbon emissions throughout the entire process, thereby enabling enterprise carbon footprint management. Based on this life cycle assessment, the present invention incorporates the transformation and flow of material and energy flows throughout the life cycle of steel products to develop a carbon footprint management method and management system for steel products.

[0066] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0067] As shown in FIG1 , an embodiment of the present invention provides a carbon footprint management method for steel products based on life cycle assessment, including:

[0068] S1. Collect information on the company's steel products and the material flow, energy flow, and flow paths of the unit processes in the steel product production process; import the life cycle background database of the material flow and energy flow that have an exchange relationship with the outside of the factory during the production process; import the carbon emission factor database of the material flow and energy flow during the life cycle process;

[0069] S2. Verify the material flow and energy flow data collected from each unit process in the production process using metal balance and carbon balance methods; update the background database and carbon emission factor library; and classify and store the corresponding data for different production paths, different steel grades, and different material and energy flows;

[0070] S3. Determine the carbon footprint calculation functional units, production paths, and calculation system boundaries for different types of steel products; select data allocation principles; and establish a life cycle carbon footprint model.

[0071] The life cycle carbon footprint model includes: a life cycle carbon footprint calculation model, a life cycle carbon footprint prediction model and / or a life cycle carbon footprint optimization model;

[0072] Build a life cycle carbon footprint model, including:

[0073] In line with the requirements for calculating the carbon footprint of steel products, the calculation scope and allocation principles are determined. According to the nature, quantity and use of steel products, appropriate functional units are selected. Based on the connection between intermediate products between each unit process in the steel product production process and the conversion relationship between material flow and energy flow within the unit process, a carbon footprint calculation model for the life cycle of steel products is established.

[0074] Based on the carbon footprint calculation model, obtain the historical production path of the steel grade to be predicted and the conversion relationship and efficiency of the material flow and energy flow of the unit process, analyze and select appropriate path information and unit process information as the life cycle carbon footprint prediction model for information and data training; and / or,

[0075] Based on the carbon footprint calculation model of the steel product life cycle, the conversion relationship and efficiency of the material flow and energy flow of the unit process, and the number and corresponding relationship of the intermediate flows between each unit process are obtained. According to the corresponding relationship, conversion relationship and efficiency, the objective function and constraint conditions are constructed to minimize the carbon footprint of the product without changing the production process.

[0076] S4. Manage the carbon footprint of steel products based on the life cycle carbon footprint model.

[0077] There are three management methods:

[0078] (1) Based on the carbon footprint calculation model of the steel product life cycle, the material flow and energy flow data, background data and carbon emission factor data of the corresponding unit process are imported; based on the relevant data of the steel product and the quality of the relevant data, the carbon footprint result data of the steel product and the uncertainty interval of the result are calculated; based on the carbon footprint result data of the steel product, the differences in the carbon footprints of different products and the differences in the contribution of various factors to the carbon footprint results are analyzed; based on the carbon footprint calculation model of the steel product life cycle, the corresponding changes in the carbon footprint when a certain factor changes within the actual production value range are analyzed, so as to obtain the sensitivity of the carbon footprint to the factor; the calculation and analysis results are classified and stored;

[0079] Based on the same carbon footprint calculation model and the carbon footprint results of steel products, we compared and analyzed the carbon footprint results of various steel products of the company, the sub-grades of the same category of steel products, and the same steel grade within different calculation time ranges;

[0080] Based on carbon footprint calculation models with different calculation boundaries, and based on the carbon footprint results of steel products, the carbon footprint results of the same steel grade within different calculation boundaries are compared and analyzed to help companies understand their actual carbon footprint situation;

[0081] Based on the carbon footprint data of steel products, the process contribution of the carbon footprint data of steel products is classified and calculated from three aspects: direct emissions from the production process, indirect emissions from external electricity and heat consumption, and emissions in the supply chain. The composition ratio and potential contribution impact of the carbon footprint data of each link of steel products are demonstrated;

[0082] Based on the carbon footprint results of steel products, during the production process within the factory, the process contribution of the carbon footprint data of steel products is classified and calculated from three dimensions: each production process, the equipment included in each process, and the input and output of each equipment. This shows the composition ratio and potential contribution impact of the carbon footprint data of each link of steel products.

[0083] (2) When the production path of steel products and the material and energy flows input into the unit process are known, the carbon footprint of steel products after production is predicted through the life cycle carbon footprint prediction model at the time of energy and raw material input or during product production.

[0084] (3) When steel products have not yet been produced or are in the production process, based on the life cycle carbon footprint optimization model, the carbon footprint of the product is minimized by adjusting the path of this type of steel products.

[0085] In the above examples, carbon footprint management of steel products at the production equipment level is implemented for various types of steel products in steel enterprises characterized by a long blast furnace-converter process, based on a life cycle assessment approach that analyzes the transformation and flow relationships of material and energy flows, as well as the process units they connect. This carbon footprint management approach enables precise assessment of the impact of changes in production paths on the carbon footprint of steel products throughout their life cycle, addressing the shortcomings of existing management methods that only analyze carbon footprint results and achieving targeted, integrated, and systematic carbon footprint management of steel products throughout their life cycle.

[0086] As shown in FIG2 , an embodiment of the present invention provides a carbon footprint management system for steel products based on life cycle assessment, including:

[0087] Data Collection Module M1: Collects information on the company's steel products, as well as the material and energy flows and flow paths of the unit processes in the steel product production process; imports and updates the life cycle background database of material and energy flows that have exchange relationships with the outside of the factory during the production process; imports and updates the carbon emission factor library of material and energy flows in the "cradle to gate" life cycle process; collects relevant information on the input data, including data collection time, data source, data calculation type, and other data quality-related information;

[0088] Data Management Module M2: Verifies the material flow and energy flow data of the unit process collected in the data acquisition module M1 through metal balance and carbon balance methods; updates the background database and carbon emission factor library; selects and rejects unit process data based on the principle of selection and rejection; and classifies and stores the corresponding data for different steel grades, different material flows and energy flows;

[0089] Model building module M3: Determine the carbon footprint calculation functional units and calculation system boundaries for different types of steel products; select data allocation principles; establish a life cycle carbon footprint calculation, prediction and optimization model;

[0090] Carbon footprint analysis module M4: used to obtain carbon footprint results of different types of steel products based on the life cycle carbon footprint calculation model, analyze and store the carbon footprint results; when the production path of the steel product and the material flow and energy flow input in the unit process are known, the carbon footprint of the steel product after production can be predicted through the life cycle carbon footprint prediction model; when the original production path of the steel product is known, based on the life cycle carbon footprint optimization model, combined with the historical input and output data of the unit process, the carbon footprint of the product can be reduced by adjusting the path of this type of steel product.

[0091] Among them, the data acquisition module M1 includes: steel product information acquisition module M1.1, production path determination module M1.2, background database import module M1.3 and carbon emission factor library import module M1.4;

[0092] The steel product information collection module M1.1 is specifically used to subdivide all steel products produced within the enterprise into different product types based on their product use, product shape, product processing technology, and product performance information, and collect basic information including product name, product carbon content, and product processing technology.

[0093] The minimum granularity for collecting on-site data is the unit process, that is, the production process of each equipment included in the main process and energy system in the factory; the material flow includes the raw materials input into the unit process (iron ore, iron ore concentrate, alloy, etc.), auxiliary raw materials (limestone, dolomite, refractory materials, etc.), and the products and by-products output by the unit process (molten iron, molten steel, scrap steel, etc.); the energy flow includes the energy input into the unit process (washed coal, anthracite, coke, etc.), energy media (electricity, coke oven gas, industrial water, etc.), and the energy and energy media output from the unit process.

[0094] Within the enterprise, all steel products produced are classified in detail according to the production process (such as cold / hot rolled products), processing technology (hood annealing / continuous return), shape (such as round bar / square bar), size (such as hot-rolled thin steel strip / medium and thick plate), performance (such as plasticity / hardness) and use (such as automotive materials / construction materials).

[0095] The production path determination module M1.2 is specifically used to determine the time granularity of information collection; determine the basic information and key physical quantities of the input and output material flow and energy flow of the unit process in the production process of a certain type of steel product; collect the basic information of all unit processes in the production process; determine all unit processes included in the enterprise's production process and the flow relationship of material flow and energy flow between unit processes; determine the flow path of material flow and energy flow between unit processes in the production process of a certain type of steel product.

[0096] Based on the process flow and metallurgical mechanism in the production process, and according to the input of raw materials and output of products within the unit process, the conversion relationship between the input raw materials and output products within each unit process is determined.

[0097] Based on the technological process and metallurgical mechanism in the production process, all unit processes through which the intermediate flows in the steel product production process pass are traced; among them, the intermediate flows include the products or by-products of the upstream unit process that flow into the downstream unit process as raw materials or auxiliary raw materials, and are usually the main products flowing out of the unit process, such as molten iron as the intermediate flow from blast furnace equipment to converter equipment, and molten steel as the intermediate flow from converter equipment to refining equipment.

[0098] Based on different steel product types, with the unit production process as the collection granularity, all material flows and energy flows in the input and output of the production process of each type of steel product are collected.

[0099] Based on different types of steel products and taking the unit production process as the collection granularity, the inputs and outputs of all carbon-containing material flows and energy flows in the production processes of various types of steel products are collected and identified.

[0100] The time granularity of the collection includes one or more of the following units: year, month, day, shift, hour, furnace, and real-time. The basic information of the input and output material flows and energy flows of the unit process includes the types of material flows and energy flows, the properties of material flows and energy flows, the measurement units of material flows and energy flows, and the constraints of material flows and energy flows. The key physical quantities of the input and output material flows and energy flows of the unit process are consumption, generation, recovery, emission, export, steam pressure, and carbon content. The basic information of all unit processes in the production process is collected, including the status of the equipment in each unit process (stable operation, fluctuation, maintenance, shutdown, etc.), the status of the materials in the unit process (processing, transportation, stoppage, stagnation, etc.), and the furnaces of steelmaking, refining, and continuous casting equipment.

[0101] Based on a certain type of steel product, as well as based on the input and output of each unit process in the production process and the material flow and energy flow between the unit processes, determine the connection between the intermediate products between the unit processes in the production process of a certain type of steel product and the conversion relationship between the material flow and energy flow within the unit process.

[0102] The production process of an enterprise includes a production system and an energy system; each unit process is each equipment in the production system and the energy system; the unit process in the production system includes one or more of the following: coke oven, dry quenching device, sintering machine, ring cooler, roasting equipment, cooling equipment, blast furnace, hot blast stove, converter, ladle, refining furnace, continuous casting machine, heating furnace, roughing mill, finishing mill, annealing furnace and cold rolling mill; among them, the unit process in the energy system includes one or more of the following: gas generator, combustion chamber, waste heat boiler, coal-fired boiler, gas boiler, generator set, oxygen generator, compressor, blower, pressurizer and water treatment device.

[0103] Among them, the material flow and energy flow between unit processes, from the perspective of the production system, include material flows such as sintered ore, pelletized ore, molten iron, molten steel, steel billets, hot-rolled coils, scrap steel, slag steel, and energy flows such as coke and coke powder; from the perspective of the energy system, include energy flows such as new water, clean circulating water, sewage circulating water, electricity, low-pressure steam, high-pressure steam, oxygen, nitrogen, argon, coke oven gas, blast furnace gas, and converter gas; from the perspective of the flow between the production system and the energy system, include energy flows such as new water, clean circulating water, sewage circulating water, electricity, low-pressure steam, high-pressure steam, oxygen, nitrogen, argon, coke oven gas, blast furnace gas, and converter gas.

[0104] Among them, the flow paths of material flows and energy flows between unit processes include: from which unit processes do the raw materials, auxiliary raw materials, and energy of a certain unit process flow out, the types and corresponding quantities of the outflows from each of these upstream unit processes, and all unit processes into which the product flows and by-product flows of the unit process flow, including the types and corresponding quantities of the flows into these unit processes respectively.

[0105] Of course, in some other embodiments, each unit process also includes: other equipment (lime kiln, slag powder device, etc.), energy (natural gas, diesel, etc.), other systems (waste treatment system, etc.). In actual application, the system, equipment and energy type should be determined according to actual needs, and there is no restriction here.

[0106] The background database import module M1.3 is specifically used to import the background database and data-related information of the material flow and energy flow that have an exchange relationship with the outside of the factory during the production process of different steel products.

[0107] Among them, the material flow that has an exchange relationship with the outside of the factory includes the raw materials and auxiliary raw materials purchased by the enterprise from external manufacturers, and the by-products exported by the enterprise to other enterprises; the energy flow that has an exchange relationship with the outside of the factory includes the energy and energy media purchased by the enterprise from external manufacturers, and the energy and energy media exported by the enterprise to other enterprises.

[0108] Among them, the background database includes all inputs and outputs of the mining and processing processes of various types of energy, and all inputs and outputs of the transportation process.

[0109] Among them, the complete background database related to all external raw materials input by steel enterprises includes all inputs and outputs of the mining, processing and production processes of raw materials, and all inputs and outputs of the transportation process; the complete background database related to the production process of industrial products replaced by exported by-products includes the mining and processing of energy and raw materials required for the production process of the replaced industrial products, and all inputs and outputs of the production process of the industrial products.

[0110] The complete background database for all external energy input by steel enterprises includes all inputs and outputs of energy extraction, processing, and production, as well as all inputs and outputs of transportation. The complete background database for the production process of industrial products replaced by exported secondary energy includes the processing of energy required for the production of industrial products, as well as all inputs and outputs of the production process of industrial products.

[0111] Among them, the background database includes the energy and raw material life cycle inventory factors provided by the enterprise's purchasing manufacturers, the energy and raw material transportation process inventory factors from the purchasing manufacturers to the factory gate provided by the transportation department, and the inventory factors of relevant energy and raw materials imported from each life cycle background database.

[0112] Specifically, the data provided by the enterprise purchasing manufacturers include the data in the upstream product life cycle assessment report provided by the upstream supplier that meets the standard requirements and is independently verified by a third party.

[0113] Specifically, life cycle background data should include public life cycle assessment data representing the domestic average production level and technical data on the production of similar energy and raw materials abroad.

[0114] When the data in the background database needs to be updated, check whether the data in each database has been updated. If so, replace the original data in the database with the updated data to complete the update.

[0115] Specifically, information related to background data should include the detailed source of the background data, such as information provided by upstream suppliers, extracted from the National Bureau of Statistics database, or obtained from the CLCD database. The statistical year of the data: the closer the statistical year of the background data is to the year being calculated, the more accurate the calculation results will be. The type of data calculation, i.e., whether the data is derived from field measurements, calculated using a formula, or estimated based on actual data, should be provided. The geographical representativeness of the data, i.e., whether the data is at the product, enterprise, industry, region, or national level, specifically for a specific product type, enterprise name, industry type, region, or country. If some information is missing, the reason for the omission should be explained.

[0116] Specifically, based on the relevant information in the background database, a data evaluation index system is established. The priority of carbon emission factor selection is established based on the data index system and updated in real time as the background database is updated. The data quality is judged based on the index system to help enterprises select more appropriate background data for product carbon footprint management.

[0117] Among them, the data evaluation index system specifically includes comprehensive consideration of indicators such as data source (field data, literature, background database, etc.), data calculation type (measured, calculated, average, estimated, etc.), data year (real-time, within the past year, within the past five years), and data collection area (within the factory, the province, the country) to comprehensively score the quantity and determine the comprehensive quality of the data in each background database.

[0118] The carbon emission factor library import module M1.4 is specifically used to import the carbon emission factor library of material flows and energy flows in the "cradle to gate" life cycle of different steel products, as well as carbon emission factor data-related information.

[0119] The "cradle-to-gate" life cycle refers to the process of steel products from the extraction of resources and energy to the production and manufacturing of products before they are exported to external manufacturers, including the mining and processing of upstream energy and raw materials for steel products, the transportation of upstream raw materials for steel products, and the production process of steel products. The carbon emission factor is the input of carbon-containing substances in the "cradle-to-gate" life cycle, the carbon released into the system or atmosphere by the use of carbon-containing energy, and the carbon fixed in carbon-containing products and by-products due to the carbon content in their components.

[0120] A library of direct carbon emission factors corresponding to all external carbon-containing energy and raw materials, products, and by-products input and output during the "cradle to gate" life cycle of steel products, including direct carbon emission factors from fuel combustion, carbon emission factors derived from the carbon content of carbon-containing solvents, carbon-containing alloys, recarburizers, etc. in input materials, and carbon emission offset factors derived from the carbon content of carbon-containing products and carbon-containing by-products in the process;

[0121] Specifically, when the fuel composition or carbon content used by the enterprise is available, the carbon emission factor of the fuel is calculated using the carbon emission factor calculation formula for direct fuel combustion. When the carbon content of the carbon-containing materials, carbon-containing products, and by-products used by the enterprise is available, the amount of carbon dioxide produced when the unit material is completely decomposed is calculated based on the element balance to obtain its carbon emission factor. For unavailable parts, the carbon emission factors provided in the National Development and Reform Commission guidelines or the IPCC guidelines integrated in the module can be used.

[0122] Some information on carbon emission factors should be recorded in detail in the database management module. Specifically, the detailed source of the carbon emission factors, such as calculations based on formulas, data from the National Development and Reform Commission guidelines, etc. The statistical year of the data, the closer the statistical year of the carbon emission factors is to the calculated year, the more accurate the calculation results will be. The type of data calculation, that is, calculation based on formulas, actual estimates, national averages, etc. The regional representativeness of the data, that is, the data is at the product level, enterprise level, industry level, region level, and national level, and specifically for a certain type of product, a certain name of enterprise, a certain type of industry, a certain region, a certain country, etc. If some information is missing, the reason for the missing information should be explained;

[0123] Among them, the carbon emission factor database is an integration of multiple different databases. During the integration process, the data source, data type, and data collection time of each database should be clarified; when the data in the carbon emission factor database needs to be updated, check whether the data in each database has been updated. If so, replace the original data in the database with the updated data to complete the update;

[0124] Specifically, based on the relevant information of the data in the carbon emission factor library, a data evaluation index system is established, and the data quality is judged according to the index system. The priority of carbon emission factor selection is established according to the data index system and updated in real time as the carbon emission factor library is updated, helping enterprises to select more appropriate carbon emission factor data for product carbon footprint management.

[0125] Among them, the data evaluation index system comprehensively considers indicators such as data source (field data, literature, background database, etc.), data type (measured, calculated, average, estimated, etc.), data year (real-time, within the past year, within the past five years), and data collection area (within the factory, the province, the country) to comprehensively score the quantity and determine the comprehensive quality of the data in each carbon emission factor library.

[0126] Data management module M2, including: data verification and modification module M2.1, data selection module M2.2, data classification and storage module M2.3;

[0127] Among them, the data verification and modification module M2.1 is specifically used to check the problems in the input and output data of each unit process. If problems are found, the problematic data will be fed back to the data acquisition module M1 for re-collection, and the modified data will be updated; check whether the input and output data of each unit process meet the metal balance and carbon balance, and feed back the data problems to the acquisition module M1 for re-collection, and update the modified data; update the background database and carbon emission factor library.

[0128] Among them, the problems existing in the input and output data of each unit process include whether each unit process is representative, that is, whether the production data statistics are carried out in accordance with the unit process data collection scope; whether the field data is complete, whether there is any missing data on some material flows and energy flows of the unit process or key physical quantity information; whether the field data is consistent, including the names of the same types of material flows and energy flows involved in all unit processes should be uniformly processed, and the names of the same types of material flows and energy flows in the background database and the carbon emission factor library should be consistent.

[0129] Among them, whether the input and output data of each unit process meet the metal balance and carbon balance, including metal balance refers to the balance of ferrous flow, that is, judging whether the iron content in the iron-containing materials input and the iron-containing products, by-products and residues output of the unit process is balanced or balanced within the allowable error range; including carbon balance refers to whether the carbon content in the input energy, raw materials and auxiliary raw materials and the carbon content in the output CO2, carbon-containing products, by-products and solid waste are balanced or balanced within the allowable error range.

[0130] Among them, updating the modified data includes updating the data in the background database and the carbon emission factor library according to the collection time requirements of the background database and the carbon emission factor library; wherein, the updating method is, based on the data year information of the background database and the carbon emission factor library in the data evaluation index system, feeding back the data information of the earlier years to M1.

[0131] The data selection module M2.2 is specifically used to identify, analyze, and screen the process data of each unit in the steel product production process according to the steel product input and output data selection principle, and select the input and output data that meet the requirements. The data selection principle refers to the principle of reducing the complexity of the unit process data involved in each unit process of steel product production based on the proportion of raw material and energy input and output to the total amount of that type;

[0132] Among them, the input and output data that meet the requirements of the trade-off principles are selected, including the accurate positioning, precise identification and analysis of raw materials, auxiliary raw materials, energy input data, products, by-products and energy output of the steel product production unit process. According to the trade-off principles formulated according to the input and output ratios of raw materials and energy, the input and output data related to the steel product production unit process are scientifically processed, so as to use the trade-off principles specified in the specifications and standards to simplify complex unit processes composed of multiple materials and multiple outputs.

[0133] The data classification and storage module M2.3 is specifically used to match the collected unit process material flow and energy flow data with the imported background database and carbon emission factor library based on the information of different steel grades, to form a complete data set for this type of steel products, and classify and store it in the module.

[0134] The information on different steel grades includes the key physical quantities of the input and output material and energy flows of the unit processes during the production of a certain type of steel product, as well as the flow paths of the material and energy flows between unit processes during the production of a certain type of steel product. This is combined with the life cycle background database of the material and energy flows that have an exchange relationship with the external world during the production unit process of this type of steel product, the by-products and energy products exported to external companies, and the relevant carbon emission factors of all inputs and outputs during the "cradle to gate" life cycle of this type of steel product, and the comprehensive data quality evaluation results of each data to form the life cycle carbon footprint dataset of this type of steel product.

[0135] Based on the life cycle carbon footprint dataset of the enterprise's steel products, these datasets are classified and stored in this module according to the types of steel products, data collection time granularity, data collection scope, data quality, etc.

[0136] Model construction module M3, including: carbon footprint calculation model module M3.1, carbon footprint prediction model module M3.2, carbon footprint scheduling model module M3.3;

[0137] The carbon footprint calculation model module M3.1 is specifically used to determine the calculation scope and allocation principles based on the requirements of carbon footprint calculation for steel products. It selects appropriate functional units based on the nature, quantity, and use of steel products. It also establishes a carbon footprint calculation model for steel products based on the connection between intermediate products between unit processes in the steel product production process and the conversion relationship between material flow and energy flow within the unit processes.

[0138] The requirements for calculating the carbon footprint of steel products include that before calculating the carbon footprint of steel products, enterprises should clarify the application intention of the carbon footprint results of steel products, the reasons for conducting the calculation and management, how the results will be used and to whom the results will be communicated, etc., so as to determine the classification method and degree of refinement of the steel product types for carbon footprint calculation, which carbon footprint analysis method to use, and whether to conduct specific analysis and evaluation of the carbon footprint results;

[0139] The feasibility of selecting the actual calculation scope is based on the requirements for calculating the carbon footprint of steel products. In combination with the carbon footprint calculation object being a certain type of steel product, the optional scope of the actual carbon footprint calculation boundary is the "gate-to-gate" life cycle process and the "cradle-to-gate" life cycle process. The "gate-to-gate" life cycle process includes in-plant energy production (including coking process, power system, oxygen system, water system, gas system, steam system) and the production stage of steel products (including sintering process, pelletizing process, ironmaking process, steelmaking process, hot rolling process, and cold rolling process). The "cradle-to-gate" life cycle process includes the mining, production and transportation stages of raw and auxiliary materials and energy, and the production stage of steel products, specifically including raw material mining, production, mining of auxiliary materials, production, energy mining, production, scrap steel collection and processing, transportation (transportation of raw materials, energy, auxiliary raw materials, and scrap steel), in-plant energy production, and in-plant steel product production.

[0140] Among them, functional unit refers to the value of the carbon footprint calculation result expressed as the cumulative amount of all the quantities used in the life cycle process of producing "a given amount of a certain steel product";

[0141] Among them, according to the nature, quantity and use of steel products, the selection of appropriate functional units specifically includes: in order to be able to further subdivide a large category of steel products into different types of steel products, it is necessary to select a comparable functional unit. For example, based on the nature, quantity and use of steel products, 1kg of steel products is usually selected as the functional unit, and the carbon footprint results of different steel products are compared on this basis;

[0142] The reasons for determining the allocation principle are as follows: a unit process may produce two or more products simultaneously, but the input of raw materials and energy are not collected separately; a unit process may have multiple input raw materials but only one output; or a unit process may have multiple input raw materials and produce multiple output products. In these cases, the required unit process input and output data cannot be directly obtained, and the data of these unit processes need to be further recombined and allocated to form a new unit process.

[0143] The allocation principle includes: based on the unit process, when there are multiple products in the unit process, data needs to be allocated; the unit process with multiple products includes similar function unit process and multifunctional unit process; similar function unit process refers to a unit process that outputs multiple products with similar properties and functions; multifunctional unit process refers to a unit process that outputs multiple products with greatly different properties and functions;

[0144] Based on similar functional unit processes, the allocation principle includes the following: first, identifying the existence of similar functional unit processes and other unit processes associated with these unit processes, splitting the unit processes, and allocating the material and energy flows of the unit processes to different products based on the mass, energy, and volume ratios of the unit process products; for the split unit processes, it should be checked whether the sum of the inputs and outputs of the unit processes before and after allocation is equal;

[0145] Based on the multifunctional unit processes, the allocation principle includes including some unit processes producing by-products into the system boundary according to the actual use of the by-products;

[0146] Among them, some unit processes of producing by-products are included in the system boundary according to the actual use of by-products. Specifically, after the by-products are exported to external enterprises, the external enterprises use them as substitutes for certain products. According to the actual use of the substitute products, it is equivalent to reducing the total carbon footprint of the life cycle of its production process. Therefore, when some unit processes of producing by-products are included in the system boundary, it is equivalent to offsetting the carbon footprint of the production of these products. For example, the carbon footprint benefit brought by the sale of blast furnace slag as cement clinker in external enterprises is the carbon footprint generated by the corresponding cement clinker production process it replaces;

[0147] Based on the transformation relationship between each unit process and the material and energy flows within the unit process, as well as the flow relationship between intermediate products in different unit processes, a "gate-to-gate" production process model for steel products is established;

[0148] Based on the steel product production process model and the life cycle background database of material and energy flows related to the production process in the background database, a "cradle to gate" life cycle process model of steel products is constructed;

[0149] Based on the steel product production process model and the "cradle to gate" life cycle process model of steel products, and according to the carbon emission factors of the material flow and energy flow related to the production process, the material flow and energy flow in the process are converted into carbon flow to construct a carbon footprint calculation model for steel products.

[0150] The carbon footprint prediction model M3.2 is specifically used to establish a carbon footprint prediction model for steel products based on the carbon footprint calculation model for steel products and in combination with the historical production path of a specific type of steel product;

[0151] Based on the carbon footprint calculation model module of M3.1, the historical production path of the carbon footprint calculation results of a steel product is obtained, and the appropriate path information is analyzed and selected based on the input material flow, energy flow data and flow unit process and path information;

[0152] Based on the conversion relationship and efficiency of material flow and energy flow in the unit process and path information, as well as the corresponding relationship between the intermediate flow of each unit process and its upstream and downstream, when the type, input quantity, input unit process and production path between unit processes of input energy and raw materials are known, the output of material flow and energy flow of the unit process and the quantity and corresponding relationship of the intermediate flow between each unit process of the entire production process can be obtained;

[0153] Based on the output of the material flow and energy flow of the unit process and the number and corresponding relationship of the intermediate flows between the various unit processes in the entire production process, the conversion relationship and conversion efficiency of the material flow and energy flow of the unit process are obtained;

[0154] Based on the conversion relationship and efficiency of the material flow and energy flow of each unit process, as well as the corresponding relationship between the intermediate flow of each unit process and its upstream and downstream, according to the historical production path of the steel grade to be predicted that is close in time, combined with the basic information of each unit process, the appropriate path and path information are analyzed and selected as information and data to train the carbon footprint prediction model.

[0155] The carbon footprint optimization model M3.3 is specifically used to set the objective function and constraints based on the carbon footprint calculation model of steel products to establish the carbon footprint optimization model of steel products;

[0156] The carbon footprint calculation model based on the unit process introduces the objective function and constraints for the carbon footprint results according to the conversion relationship and conversion efficiency of the material flow and energy flow of the unit process, the number and corresponding relationship of the intermediate flows between each unit process;

[0157] Among them, in the establishment of the carbon footprint optimization model, the objective function of minimizing the product carbon footprint depends on the design variables. Each design variable can be written as a function related to the design variables, which is called the objective function.

[0158] Among them, in the establishment of the carbon footprint optimization model, the selection of each design variable is not arbitrary. For example, the selection of unit processes also has various restrictions, such as the number of unit processes, the distribution of intermediate flows among unit processes, etc. There are certain selection trends and ranges, which are called constraints.

[0159] Based on the carbon footprint calculation model, the historical production path information, production data and carbon footprint result data of a certain steel product that needs to be optimized are obtained. Combined with the objective function and constraints, a carbon footprint prediction model is established.

[0160] The carbon footprint analysis module M4 includes: a carbon footprint calculation analysis module M4.1, a carbon footprint prediction analysis module M4.2, and a carbon footprint optimization analysis module M4.3.

[0161] Carbon footprint calculation and analysis module M4.1: Based on the carbon footprint calculation model for steel products, and according to the relevant data of steel products and the quality of the relevant data, calculate the carbon footprint result data and the uncertainty interval of the results of steel products; based on the carbon footprint result data of steel products, analyze the differences in the carbon footprints of different products and the differences in the contribution of various factors to the carbon footprint results; based on the carbon footprint calculation model for steel products, analyze the corresponding changes in the carbon footprint when a certain factor changes within the actual production value range, so as to obtain the sensitivity of the carbon footprint to the factor; classify the calculation and analysis results and store them in this module.

[0162] Among them, the reason for the uncertainty interval of the calculated carbon footprint results of steel products is due to the problem of inaccurate data in life cycle carbon footprint management; among them, the reasons for the inaccurate data include that some data in the background database come from the life cycle process of similar types of products, and the data collection year, data collection region, and data coverage cannot fully represent the actual data in the industrial chain. Since the carbon emissions of the enterprise unit process cannot be directly measured, its carbon emissions are calculated by combining the input and output of the unit process with the carbon emission factors in the carbon emission factor library through a formula. The process calculated according to the carbon emission formula itself has certain uncertainties. In addition, the types of materials and energy in the carbon emission factor library from various sources cannot fully cover the entire life cycle process of steel production. The collection year, data collection region, and data coverage of carbon emission factors from different sources are different when selected. Therefore, it is necessary to analyze the uncertainty of the carbon footprint results of steel products.

[0163] The uncertainty range of the results includes obtaining a certain value range of the data in the model based on the comprehensive score of each data in the data evaluation index system, inputting the data in the form of a certain value range into the carbon footprint calculation model of steel products, and converting the uncertainty of each input and output data into the uncertainty of the final carbon footprint value of the steel product.

[0164] Based on the carbon footprint calculation model, according to the carbon footprint result data of steel products, the carbon footprint results of the company's various steel products, the subdivided steel grades of the same major steel products, and the same steel grade within different calculation time ranges are compared and analyzed; based on the carbon footprint calculation model with different calculation boundaries, according to the carbon footprint result data of steel products, the carbon footprint results of the same steel grade within different calculation boundaries are compared and analyzed to help companies understand their actual carbon footprint situation.

[0165] Based on the carbon footprint data of steel products, the process contribution of the carbon footprint data of steel products is classified and calculated from three aspects: direct emissions in the production process, indirect emissions generated by consumption of externally input electricity and heat, and emissions in the supply chain. The composition ratio and potential contribution impact of the carbon footprint of each link of steel products are demonstrated.

[0166] Based on the carbon footprint results of steel products, during the production process within the factory, the process contribution of the carbon footprint data of steel products is classified and calculated from three dimensions: each production process, the equipment included in each process, and the input and output of each equipment. This shows the composition ratio and potential contribution impact of the carbon footprint of each link of steel products.

[0167] Among them, the sensitivity of carbon footprint to a certain factor includes, based on the various factors that contribute to the carbon footprint results and the various combined influencing factors, according to the carbon footprint calculation results of steel products, and the evaluation method based on sensitivity analysis, evaluating the differences in the impact of changes in various factors throughout the life cycle of industrial products on the carbon footprint results, so as to compare the sensitivity of the carbon footprint of steel products to changes in different influencing factors, rank the sensitivity, select influencing factors with higher sensitivity results and analyze their reasons.

[0168] Among them, the combined influencing factors are that, based on the carbon footprint result data of steel products, some of the carbon footprint influencing factors of different aspects and dimensions can be recombined through the conversion relationship, inclusion relationship, and influence relationship between them to form new influencing factor types. These new influence types can reflect some proportional relationships, technical parameters, recycling methods, etc. in the production process of steel products. The carbon footprint of steel products is also sensitive to their changes.

[0169] The evaluation method of sensitivity analysis is to input the range of changes of each assumed factor and each combined influencing factor into the model, so as to obtain the range of the product carbon footprint result. The sensitivity result is expressed according to the change amount or percentage of the carbon footprint result when the influencing factors change within the same range. The assumed data change range is the change of the actual input data in the model within a certain percentage range according to the actual production situation of the data.

[0170] Among them, the calculation and analysis results are classified and stored, including carbon footprint results, factor analysis results, sensitivity analysis results, uncertainty analysis results, etc., which are classified and stored in this module according to the data collection time granularity, system boundary range, steel product type, etc.

[0171] The carbon footprint prediction and analysis module M4.2 is specifically used for: Based on the carbon footprint prediction model of steel products, the carbon footprint of steel products after production can be predicted by the steel product carbon footprint prediction model at the time of energy and raw material input or during the production process of the product.

[0172] Among them, the purpose of predicting the carbon footprint of steel products after production at the time of energy and raw material input or during the production process is that, during the production process of steel products, the update of product orders may lead to changes in the production process scheduling of products, that is, the path of the product production process may be flexible in each link of the production process. Predicting the carbon footprint of steel products after production at the time of energy and raw material input or during the production process can provide information related to the carbon footprint of the process flow when producing this type of steel products using a known path or when the production path changes, which can serve as a reference for the carbon footprint results that may be generated by the production of this type of steel products by the enterprise; provide decision-making goals, references and alternative plans for the production decision of steel products, and ensure that the carbon footprint prediction of steel products can be achieved under the original production path or the adjusted production path; and provide a basis for the rational allocation and effective utilization of resources through prediction;

[0173] When the type, quantity, and unit process of input energy and raw materials are known, and the final steel product has not yet been produced through the production process, the input data of energy and raw materials for a certain type of steel product to be predicted, as well as background data and carbon emission factor data, are imported. Based on the carbon footprint prediction model, the input and output of the material flow and energy flow of each unit process of the steel product, as well as the intermediate flows and corresponding relationships between the various unit processes of the entire production process can be predicted;

[0174] When the path of a certain link in the steel production process changes, the unit process of the link and the downstream unit processes connected to the unit process are adjusted in a timely manner based on the steel product carbon footprint prediction model, realizing real-time updated carbon footprint prediction when the path changes in the production process;

[0175] The corresponding relationships selected in the carbon footprint prediction model are combined with the input and output data of each unit process to obtain the carbon footprint prediction results; the accuracy of the prediction results is compared with the carbon footprint prediction results calculated based on the data collected from each unit process after the production of the steel product; based on the relevant data of the steel product and the quality of the relevant data, the carbon footprint prediction results of the steel product and the uncertainty range of the results are calculated;

[0176] Based on the carbon footprint prediction result data and the uncertainty interval of the results, a comparative analysis is conducted with the carbon footprint calculation results and the uncertainty interval of the results calculated based on the post-production unit process data of the steel product produced through the same production path. After comparing the results, the accuracy of the prediction results is analyzed; after comparing the results within the uncertainty interval, the accuracy of the prediction results within the uncertainty interval is analyzed.

[0177] The carbon footprint optimization analysis module M4.3 is specifically used to obtain the adjusted production path of this type of steel product based on the carbon footprint optimization model of steel products, and compare it with the carbon footprint of the same type of product produced through the original production path to achieve the optimization of the product's carbon footprint.

[0178] The purpose of optimizing the carbon footprint of steel products is to understand that steel production often involves many pieces of equipment with the same function. Different combinations of these pieces of equipment often result in different carbon footprints for steel products. The rationality of production path selection significantly impacts energy efficiency, production rate, and product carbon footprint. Efficient and rational path selection can achieve energy conservation and carbon reduction in steel production. However, the numerous unit processes and complex production paths make it difficult to analyze each path individually. Therefore, establishing a carbon footprint optimization model for steel products allows for the direct solution of the optimal production path.

[0179] The purpose of obtaining the adjustment results of the production path of this type of steel products and the optimization results of the carbon footprint of the products is that, in the steel product production process, the update of product orders determines the production scheduling of the product production process, that is, the path of the product production process may be flexible in each link of the production process. When the product order type is relatively simple and the production between equipment with the same function can be adjusted within a certain range, the carbon footprint of steel product production is optimized during energy and raw material input or during the production process. This can be used as a relevant information basis for the production scheduling of this type of steel products when the type and quantity of energy and raw material inputs are known, and provide a reference for enterprises to select appropriate production paths; provide decision-making goals, references and alternative plans for steel product production decisions, which is conducive to selecting appropriate production paths in production and ensuring the realization of carbon footprint optimization goals; and the path adjustment results and optimization results can provide a basis for achieving rational resource allocation and reducing the carbon footprint of steel products.

[0180] Based on the relevant data of steel products and the quality of relevant data, background data and carbon emission factor data are imported to calculate the carbon footprint optimization results of steel products and the uncertainty range of the results.

[0181] When the path of a certain link in the steel production process can be optimized and adjusted during the production process, based on the carbon footprint optimization model, path optimization is achieved in the unit process that can be optimized and adjusted and in the downstream unit processes connected to the unit process, so as to achieve real-time carbon footprint optimization when the path changes during the production process. By comparing the changes in the production path of steel products and the carbon footprint results after the original production path and the adjusted production path, the carbon emission reduction is obtained, thereby analyzing the potential for optimizing the carbon footprint of steel products.

[0182] After the product production process is completed, based on the carbon footprint optimization model, the carbon footprint results after the product path optimization can be compared with the actual results to analyze whether the production path of the product is a low-carbon production path. If there is room for optimization, the optimization potential of the production path can be analyzed.

[0183] Based on the carbon footprint optimization result data and the uncertainty interval of the results, a comparative analysis is conducted with the carbon footprint calculation results and the uncertainty interval of the results of the steel product produced through the original production path. After comparing the results and the results within the uncertainty interval, the effect of reducing the carbon footprint based on the comparison of the results and the optimization results within the uncertainty interval is analyzed.

[0184] In an embodiment of the present invention, the carbon footprint management system combines multiple carbon footprint management methods such as carbon footprint calculation, analysis, prediction, and optimization to accurately evaluate the impact of changes in the production path on the carbon footprint of the steel product life cycle under different conditions before, during, and after product production, thereby making up for the defect of existing management systems that only analyze carbon footprint results.

[0185] In the several embodiments provided by the present invention, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are merely illustrative. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, and can be electrical or other forms.

[0186] The units described as separate components may or may not be physically separate, and 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 units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0187] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0188] If the integrated unit is implemented in the form of 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 the present invention, 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. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program codes.

[0189] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A carbon footprint management method for steel products based on life cycle assessment, It is characterized in that include: Collect information on the company's steel products and the material flow, energy flow and flow path of the unit process in the steel product production process; Import the life cycle background database of material and energy flows that have exchange relations with the outside of the factory during the production process; Import the carbon emission factor library of material and energy flows during the life cycle; Verify the material flow and energy flow data of each unit process in the production process collected by metal balance and carbon balance methods; Updating the background database and the carbon emission factor library; Classify and store the corresponding data of different production paths, different steel grades, different material flows and energy flows; Determine the carbon footprint calculation functional units, production paths and calculation system boundaries for different types of steel products; select data allocation principles; establish a life cycle carbon footprint model; Carbon footprint management is performed on the steel product based on the life cycle carbon footprint model.

2. According to the carbon footprint management method of steel products based on life cycle assessment according to claim 1, It is characterized in that The life cycle carbon footprint model includes: a life cycle carbon footprint calculation model, a life cycle carbon footprint prediction model and / or a life cycle carbon footprint optimization model; The establishing of the life cycle carbon footprint model comprises: Combined with the requirements for calculating the carbon footprint of steel products, the calculation scope and allocation principles are determined. According to the nature, quantity and purpose of steel products, appropriate functional units are selected. Based on the connection between intermediate products between unit processes in the production process of steel products and the conversion relationship between material flow and energy flow within the unit process, a carbon footprint calculation model for the life cycle of steel products is established. Based on the carbon footprint calculation model, the historical production path of the steel grade to be predicted and the conversion relationship and efficiency of the material flow and energy flow of the unit process are obtained, and the appropriate path information and unit process information are analyzed and selected as the life cycle carbon footprint prediction model for information and data training; and / or, Based on the steel product life cycle carbon footprint calculation model, the conversion relationship and efficiency of unit process material flow and energy flow, and the number and corresponding relationship of intermediate flows between unit processes are obtained. According to the corresponding relationship, conversion relationship and efficiency, the objective function and constraint conditions are constructed to minimize the product carbon footprint without changing the production process.

3. According to the carbon footprint management method of steel products based on life cycle assessment according to claim 2, It is characterized in that The establishment of a carbon footprint calculation model for the life cycle of steel products includes: Establish a steel product production process model based on each unit process, the transformation relationship between material flow and energy flow within the unit process, and the flow relationship between intermediate products in different unit processes; Constructing a life cycle process model of steel products based on the steel product production process model and combining the material flow and energy flow related to the production process in the background database; Based on the steel product production process model and the steel product life cycle process model, according to the carbon emission factors of the material flow and energy flow related to the production process, the material flow and energy flow in the process are converted into carbon flow, and a steel product life cycle carbon footprint calculation model is constructed; Establishing the life cycle carbon footprint prediction model includes: Based on the steel product life cycle carbon footprint calculation model, all historical production paths of the steel product carbon footprint calculation results of the steel grade to be predicted are obtained, and appropriate path information is analyzed and selected; Based on the conversion relationship and efficiency of material flow and energy flow in unit process and path information, as well as the corresponding relationship between the intermediate flow of each unit process and its upstream and downstream, when the type, input quantity, unit process to which the input energy and raw materials are applied, and the production path between unit processes are known, the output of the material flow and energy flow of the unit process, as well as the quantity and corresponding relationship of the intermediate flow between each unit process in the entire production process are obtained; Based on the output of material flow and energy flow of unit process and the number and corresponding relationship of intermediate flows between each unit process of the whole production process, the conversion relationship and conversion efficiency of material flow and energy flow of unit process are obtained; Based on the conversion relationship and efficiency of the material flow and energy flow of the unit process, as well as the corresponding relationship between the intermediate flow of each unit process and its upstream and downstream, according to the historical production path of the steel grade to be predicted, combined with the basic information of each unit process, analyze and select the appropriate path and path information as the life cycle carbon footprint prediction model for information and data training; Establishing the life cycle carbon footprint optimization model includes: Based on the life cycle carbon footprint calculation model, according to the conversion relationship and conversion efficiency of the material flow and energy flow of the unit process, and the number and corresponding relationship of the intermediate flows between the various unit processes, the objective function and constraint conditions are set to minimize the product carbon footprint by optimizing the production path without changing the production process; Based on the life cycle carbon footprint calculation model, the historical production path information, production data and carbon footprint result data of a certain steel product that needs to be optimized are obtained, and the carbon footprint optimization model of the steel product is formed by combining the objective function and constraint conditions.

4. The carbon footprint management method for steel products based on life cycle assessment according to claim 2 or 3, It is characterized in that The carbon footprint management of the steel product is performed based on the life cycle carbon footprint model, including: Based on the steel product life cycle carbon footprint calculation model, the material flow and energy flow data, background data and carbon emission factor data of the corresponding unit process are imported; based on the relevant data of the steel product and the relevant data quality, the carbon footprint result data of the steel product and the uncertainty interval of the result are calculated; based on the carbon footprint result data of the steel product, the differences in the carbon footprints of different products and the differences in the contribution of various factors to the carbon footprint results are analyzed; based on the steel product life cycle carbon footprint calculation model, the corresponding changes in the carbon footprint when a certain factor changes within the actual production value range are analyzed, so as to obtain the sensitivity of the carbon footprint to the factor; the calculation and analysis results are classified and stored; Based on the same carbon footprint calculation model, and according to the carbon footprint result data of the steel products, compare and analyze the carbon footprint results of the steel products of the enterprise, the sub-segments of the same category of steel products, and the same steel grade within different calculation time ranges; Based on the carbon footprint calculation model with different calculation boundaries, according to the carbon footprint result data of the steel products, the carbon footprint results of the same steel grade within different calculation boundaries are compared and analyzed to help enterprises understand their actual carbon footprint situation; Based on the carbon footprint result data of steel products, the process contribution of the carbon footprint data of steel products is classified and calculated from three aspects: direct emissions in the production process, indirect emissions from external electricity consumption and heat generation, and emissions in the supply chain, to show the composition ratio and potential contribution impact of the carbon footprint data of each link of steel products; Based on the steel product carbon footprint result data, during the production process within the factory, the process contribution of the steel product carbon footprint data is classified and calculated from three dimensions: each production process, the equipment included in each process, and the input and output of each equipment, to demonstrate the composition ratio and potential contribution impact of the carbon footprint data of each link of steel products.

5. The carbon footprint management method for steel products based on life cycle assessment according to claim 2 or 3, It is characterized in that The carbon footprint management of the steel product is performed based on the life cycle carbon footprint model, including: When the production path of steel products and the material flow and energy flow input in the unit process are known, the carbon footprint of the steel products after production is predicted by the life cycle carbon footprint prediction model based on the energy and raw material input location and input amount or the product production process.

6. The carbon footprint management method for steel products based on life cycle assessment according to claim 5, It is characterized in that Predict the carbon footprint of steel products after production, including: Based on the steel product life cycle carbon footprint prediction model, the carbon footprint of the steel product after production is predicted by the steel product carbon footprint calculation model at the time of energy and raw material input or during the product production process; When the type, quantity and unit process of input energy and raw materials are known, and the final steel product has not yet been produced through the production process, the material footprint of each unit process of the steel product is obtained based on the carbon footprint prediction model. The prediction results of the input and output of flow and energy flow and the intermediate flow and corresponding relationship between each unit process of the whole production process; When the path of a certain link in the steel production process changes, based on the steel product carbon footprint prediction model, the unit process of the link and the downstream unit processes connected to the unit process are adjusted in time to achieve real-time updated carbon footprint prediction when the path changes in the production process; The corresponding relationship selected in the carbon footprint prediction model is combined with the input and output data of each unit process to obtain the carbon footprint prediction result; and the accuracy of the prediction result is compared with the carbon footprint prediction result calculated based on the data collected from each unit process after the production of the steel product; according to the relevant data of the steel product and the quality of the relevant data, the carbon footprint prediction result data and the uncertainty interval of the result of the steel product are calculated; Based on the carbon footprint prediction result data and the uncertainty interval of the results, a comparative analysis is made between the carbon footprint calculation results and the uncertainty interval of the results calculated based on the post-production unit process data of the steel product produced through the same production path. By comparing the results within the uncertainty interval, the accuracy of the prediction results within the uncertainty interval is analyzed.

7. The carbon footprint management method for steel products based on life cycle assessment according to claim 2 or 3, It is characterized in that The carbon footprint management of the steel product is performed based on the life cycle carbon footprint model, including: When the steel product has not yet been produced or is in the production process, the carbon footprint of the product is minimized by adjusting the path of this type of steel product based on the life cycle carbon footprint optimization model.

8. According to the carbon footprint management method of steel products based on life cycle assessment in claim 7, It is characterized in that The adjustments to the path of this type of steel products include: Based on the optimized production path in the carbon footprint optimization model, combined with the input and output data of each unit process, the carbon footprint optimization results are obtained; based on the relevant data of steel products and the quality of relevant data, the carbon footprint optimization result data and the uncertainty interval of the results of steel products are calculated; When the path of a certain link in the steel production process can be optimized and adjusted during the production process, based on the carbon footprint optimization model, the path optimization is implemented in the unit process in the link that can be optimized and adjusted and the downstream unit processes connected to the unit process, so as to achieve real-time carbon footprint optimization when the path changes during the production process, and the carbon footprint result of the steel product production path after the original production path is compared with the adjustment result of the production path to obtain the carbon footprint reduction, thereby analyzing the optimization potential of the carbon footprint of steel products; After the product production process is completed, based on the carbon footprint optimization model, the carbon footprint result after the product path optimization is compared with the actual result to analyze whether the product production path is a low-carbon production path. If there is room for optimization, Analyze the optimization potential of production paths; Based on the carbon footprint optimization result data and the uncertainty interval of the results, a comparative analysis is conducted with the carbon footprint calculation results and the uncertainty interval of the results of the steel product produced through the original production path, and the effect of reducing the carbon footprint based on the comparison of the results and the optimization results within the uncertainty interval is analyzed.

9. A carbon footprint management system for steel products based on life cycle assessment, It is characterized in that include: Data collection module, used to collect information on the company's steel products and the material flow, energy flow and flow path of the unit process in the steel product production process; Import the life cycle background database of material and energy flows that have exchange relations with the outside of the factory during the production process; Import the carbon emission factor library of material and energy flows during the life cycle; A data management module, used to verify the collected material flow and energy flow data of each unit process in the production process by means of metal balance and carbon balance; Updating the background database and the carbon emission factor library; Classify and store data corresponding to different production paths, different steel grades, different material flows and energy flows; Model building module, used to determine carbon footprint calculation functional units, production paths and calculation system boundaries for different types of steel products; select data allocation principles; establish life cycle carbon footprint model; A carbon footprint analysis module is used to manage the carbon footprint of the steel product based on the life cycle carbon footprint model constructed by the model construction module.

10. A carbon footprint management system for steel products based on life cycle assessment according to claim 9, It is characterized in that The carbon footprint analysis module includes: A carbon footprint calculation and analysis module, used to calculate and compare the carbon footprint of a product based on the carbon footprint calculation model as claimed in claim 2; A carbon footprint prediction and analysis module, for predicting the carbon footprint of steel products after production at the time of energy and raw material input or during production based on the carbon footprint prediction model as claimed in claim 2, and analyzing the prediction results; The carbon footprint optimization analysis module is used to optimize the carbon footprint results of the products by adjusting the specific production path of the steel products based on the carbon footprint optimization model as described in claim 2, and analyze the optimization results.

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