Method for establishing and treating carbon data structured system of iron and steel enterprise

Abstract

The invention discloses an iron and steel enterprise carbon data structured system establishment and treatment method, and solves the problem that system parameter data is invalid or problem data cannot be traced to the source due to the fact that material and energy data of an existing iron and steel enterprise often have offline interruption, static loss of data and numerical value distortion. According to the steel enterprise carbon data structured system establishment and treatment method, starting from the origin of a steel enterprise carbon system, technological process characteristics, material and energy characteristics, carbon system structure characteristics, sensing point location and network characteristics and the like related to carbon data are systematically combed, and steel enterprise carbon data series attributes are analyzed; establishing a correlation model of a physical system dimension, a function application dimension, a time granularity dimension, a process emission source dimension, a software and hardware system dimension and a background database dimension based on carbon data attributes; establishing a steel enterprise carbon data three-level and multi-dimensional structured system and a treatment method; a basic carbon data base can be built for dual-carbon work of iron and steel enterprises, and a carbon system structure and planning management are optimized.

Description

Technical Field

[0001] The present invention belongs to the technical field of metallurgical carbon data attributes and structured management, and specifically relates to a method for establishing and managing a carbon data structured system for a steel enterprise. Background Art

[0002] The process flow of steel enterprises is complex and the system is huge, and the carbon data presents multi-level and multi-dimensional characteristics. The current carbon data system of steel enterprises is based on the original ERP, MES, EMS and other systems as data sources, and some data are extracted from them to form a data system, which is called a carbon data system. This type of "carbon data system" is not fundamentally designed based on the carbon nature of steel enterprises. Such a system has many problems: the hierarchy and structure of carbon data are unclear, there are many aspects of confusion, carbon data acquisition is incomplete, and problematic and erroneous data frequently appear, and cannot be effectively identified and resolved.

[0003] At present, the carbon management platform established by steel enterprises mainly relies on two types of data, namely: parameters related to activity data and emission factors. Among them, the parameters related to activity data are read through the enterprise's production management system and energy management system, and the emission factors are matched by the background database. However, the actual situation of the enterprise is that material and energy data often experience offline interruptions, static loss, numerical distortion, etc., which leads to invalid system parameter data or the problem data cannot be traced. In addition, the complex process of the metallurgical process also makes it difficult to select emission factors. The same type of material has different performances in different process stages or different emission sources; for example: the same type of coal is burned as fuel or as a distillation process, which has a decisive influence on the selection of emission factors. Therefore, how to ensure that the carbon system of steel enterprises obtains effective data and implements effective identification and traceability of carbon data has become a major problem that plagues the industry's dual carbon work. Therefore, it is necessary to improve the establishment and governance methods of the existing steel enterprise carbon data structured system. Summary of the invention

[0004] The present invention aims to solve the above-mentioned problems and provides a method for establishing and managing a structured carbon data system for steel enterprises, which can implement multi-level, multi-dimensional and systematic structural traceability of carbon data, implement structured management of carbon data of steel enterprises, and support, guarantee and serve the realization of the functions of the upper-level platform of enterprise carbon management.

[0005] The technical solution adopted by the present invention is: the steel enterprise carbon data structured system establishment and governance method includes the following steps:

[0006] Step 1: Establish a correlation model for the carbon data attribute system;

[0007] P={A 物理维度 , B 功能维度 , C时间维度 , D 工艺维度 , E 软硬件维度 , F 背景维度}

[0008] Where: P represents the comprehensive performance of carbon data attributes of steel enterprises;

[0009] A 物理维度 The physical system dimension that represents the carbon data attributes;

[0010] B 功能维度 Functional application dimension representing carbon data attributes;

[0011] C 时间维度 The time granularity dimension representing the carbon data attributes;

[0012] D 工艺维度 The process emission source dimension representing the carbon data attributes;

[0013] E 软硬件维度 The hardware and software system dimensions that represent the carbon data attributes;

[0014] F 背景维度 Background database dimensions representing carbon data attributes;

[0015] Step 2: hierarchical management of the presence and absence of carbon data; establishing the corresponding correlation between the process side parameters of carbon data and the sensor system;

[0016] Step 3: hierarchical management of the correctness and error of carbon data; the correctness and error of carbon data at this level includes the time granularity dimension, process emission source dimension, and background database dimension. These three dimensions ensure that the read carbon data does not deviate from the actual process and jointly guarantee the validity of carbon data;

[0017] Step 4: Level governance of carbon data calculation and use; the levels of carbon data calculation and use include physical and functional dimensions, which are the accounting and application levels based on these two levels; distinguish and process parameter divisions, implement accounting and classify and store carbon data results for use by enterprises;

[0018] Step 5. Carbon data pool based on the carbon data structured system; starting from the origin of the carbon system of steel enterprises, establish a three-level, multi-dimensional structuring and governance system for the carbon data of steel enterprises; based on this, steel enterprises form a basic, comprehensive and comprehensive carbon data pool, thereby supporting the company's carbon emission verification, facility carbon management, carbon asset optimization and product carbon accounting and management work.

[0019] The step 1, ① the physical system dimension of the carbon data attribute of the steel enterprise refers to the enterprise physical system structure represented by the carbon data, and the corresponding data types specifically include: group-level data, enterprise-level data, division-level data, process-level data, workshop-level data, equipment-level data and product-level data;

[0020] A 物理维度 ={Group level, Enterprise level, Division level, Process level, Equipment level, Product level}

[0021] ②The functional application dimension of carbon data attributes refers to the various functions involved in the carbon management system. The corresponding data types include: organizational carbon data, facility carbon data, product carbon data, and carbon asset data;

[0022] B 功能维度 ={Organizational carbon, Facility carbon, Product carbon, Carbon assets}

[0023] ③The time granularity dimensions of carbon data attributes include: real-time data, accumulated data, statistical data, and offline data;

[0024] C 时间维度 ={real-time data, accumulated data, statistical data, offline data}

[0025] ④ The process emission source dimension of carbon data attributes includes: production system emission source, energy system emission source, inspection and testing system emission source, procurement system emission source, and financial system emission source;

[0026] D 工艺维度 ={production system, energy system, inspection and testing system, procurement system, financial system}

[0027] ⑤ The software and hardware system dimensions of carbon data attributes include: sensor points and network signals for carbon data collection;

[0028] E 软硬件维度 ={sensor point, network signal}

[0029] ⑥Emission factors are also an important category of generalized carbon data. The background database dimensions of carbon data attributes include: organizational carbon emission factors, product carbon emission factors, and life cycle assessment emission factors;

[0030] F 背景库维度 ={organizational carbon emission factor, product carbon emission factor, life cycle assessment emission factor}.

[0031] In step 2, the carbon parameter A represents the basic carbon data parameter for implementing carbon emission calculation, A1, A2, A i and A N represents the sensing point associated with the carbon parameter A, and a1, a2, a i and a N represents a signal network that transmits carbon data;

[0032] The quantitative calculation model of carbon data parameter A and the metering data of each sensor point is established as follows:

[0033] Carbon data A = Carbon data A1 + Carbon data A2 + Carbon data A i +Carbon Data A N

[0034] The values ​​of each "carbon data Ai" in the formula can be positive or negative, indicating energy generation and consumption, energy input and output;

[0035] The determination of whether the i-th path of the carbon parameter is smooth can be calculated by the [0, 1] variable f as follows:

[0036]

[0037] When f i When the value is 1, it means that the i-th data path of carbon parameter A is unblocked, that is, the sensor point is collecting data normally and the network signal transmission is normal; when f i When the value is 0, it means that the i-th data path of the carbon parameter A is blocked, that is, the sensor point cannot collect data normally, or the network signal transmission is abnormal.

[0038] In step 3, the time granularity dimension of carbon data attributes includes real-time data, accumulated data, statistical data, and offline data; among them, accumulated data can be obtained through real-time data, and the time granularity is divided into year, quarter, month, day, and hour; statistical data and offline data are usually not obtained by enterprises through measurement means, or the measurement coverage is temporarily insufficient and cannot be obtained; statistical data and offline data are solved by filling in the manual system to ensure that the data of all time dimensions of the enterprise carbon system can be obtained online;

[0039] The process emission source dimension of carbon data attributes includes the enterprise's internal production system data, energy system data, inspection and testing system data, procurement system data, financial system data, as well as the enterprise's upstream raw material mining data and off-site transportation data; unlike the previous independent operation of various systems in steel enterprises, which were rarely interconnected, the carbon system needs to integrate all system carbon attribute-related data to facilitate the unified and comprehensive management of the time and space dimensions of the carbon data system;

[0040] The major categories of data in the background library dimension of carbon data attributes include: organizational carbon emission factors, product carbon emission factors and life cycle assessment factors; the design major category background library data set is as follows:

[0041]

[0042] Product carbon emission factor = {fossil carbon factor, biomass carbon factor, land use carbon factor}

[0043]

[0044] For each type of raw material and energy of the steel enterprise, a corresponding factor library should be established; the key point is to take into account the use process of each type of material. The same type of raw material will correspond to different factors, and the raw material name, use process, and carbon emission factor must be clearly marked.

[0045] Furthermore, the carbon data association methods include: 1. Association in the same time and space, that is, data in the same region and the same time dimension are associated with each other; 2. Association of the same product output, that is, in order to produce a certain type of product, steel companies implement corresponding production data, energy data, inspection and testing data, and procurement data that are associated with each other.

[0046] In step 4, the physical system dimensions of carbon data attributes include: group level, enterprise level, division level, process level, equipment level and product level; the equipment level refers not only to the main equipment, but also to the auxiliary equipment that helps the equipment to operate, and the auxiliary system that provides conditions for the operation of the main equipment; the product-level carbon data of steel enterprises refers not only to the terminal system brand products, but also to major products, sub-categorized products, and intermediate products;

[0047] The functional application dimensions of carbon data attributes include organizational carbon, facility carbon, carbon assets, and product carbon; among them, the organizational carbon dimension includes carbon emissions from fossil fuel combustion, industrial process carbon emissions, net purchased electricity and heat carbon emissions, and carbon sequestration product carbon emissions; the facility carbon dimension is determined based on the actual situation of each steel company, including major furnace equipment; carbon assets include the group or company's purchase of carbon quotas, sale of carbon quotas, carry-over of carbon assets, purchase of CCERs, purchase of green certificates, and issuance of carbon quotas, as well as the allocation and management of the proportion of each department and each process according to the time dimension; product carbon includes upstream carbon footprint, off-site transportation carbon footprint, fuel combustion carbon footprint, process emission carbon footprint, waste treatment carbon footprint, and symbiotic product carbon footprint.

[0048] The beneficial effects of the present invention: The establishment and governance method of the steel enterprise carbon data structured system starts from the origin of the steel enterprise's carbon system, systematically sorts out the process flow characteristics, material and energy characteristics, carbon system structure characteristics, sensor points and network characteristics related to carbon data, and analyzes the carbon data series attributes of the steel enterprise; establishes an association model based on the physical system dimension, functional application dimension, time granularity dimension, process emission source dimension, software and hardware system dimension, and background database dimension of carbon data attributes; establishes a "three-level, multi-dimensional" structured system and governance method for the steel enterprise's carbon data; can create a basic carbon data foundation for the dual carbon work of steel enterprises and optimize the carbon system structure and planning management. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a supporting relationship diagram of the carbon data attribute dimension of the present invention for the effect of the carbon system.

[0050] Figure 2 It is a three-level, multi-dimensional structured system diagram of carbon data of steel enterprises of the present invention.

[0051] Figure 3 It is a schematic diagram of the association between the carbon data parameters of the present invention and the corresponding sensing points and the transmission network.

[0052] Figure 4 It is a flowchart of the carbon data "presence and absence" hierarchical management algorithm of the present invention.

[0053] Figure 5 This is a diagram of the carbon data-related sensor point system of the present invention (taking coal gas as an example).

[0054] Figure 6 It is a schematic diagram of the method for obtaining the time granularity dimension of carbon data of the present invention.

[0055] Figure 7 It is a schematic diagram of the distribution and integration of carbon data of steel enterprises in various systems according to the present invention.

[0056] Figure 8 It is a flowchart of establishing an emission factor library for steel enterprises based on the metallurgical process technology principle of the present invention.

[0057] Fig. 9 This is a schematic diagram of the carbon data pool of steel enterprises based on “three-level and multi-dimensional” governance of the present invention. DETAILED DESCRIPTION

[0058] The present invention establishes a carbon data attribute system for steel enterprises, a structured carbon data system and a governance method for steel enterprises, and through the implementation of carbon data time granular management, carbon data transmission path management, and complex carbon data system type management, ensures that when data problems occur, the causes can be discovered and identified in a timely manner to support system feedback and timely processing, thereby ensuring the smooth flow of carbon data resolution paths and ensuring the realization of carbon platforms and planning management functions of steel enterprises.

[0059] Carbon data of steel enterprises is different from the raw material data of previous production systems or energy data of energy systems. The carbon data system covers the entire production system, auxiliary system and subsidiary system, as well as upstream raw materials, off-site transportation, gas, solid and liquid hazardous waste treatment, and symbiotic product substitution system in the horizontal aspect of steel enterprises. The carbon data system covers the data acquisition and sensing of material energy, network transmission, emission source parameters, carbon results, carbon indicators, carbon assets, etc. in the vertical aspect of steel enterprises. Steel enterprises need to build a three-dimensional, multi-level, and multi-dimensional structured carbon data system to comprehensively solve the problem of carbon data security.

[0060] After analysis, the scope of carbon data attributes of steel enterprises includes: physical dimension attributes of carbon data, functional dimension attributes of carbon data, time dimension attributes of carbon data, process dimension attributes of carbon data, software and hardware dimension attributes of carbon data, and background dimension attributes of carbon data.

[0061] The specific steps of the present invention are described in detail. The steel enterprise carbon data structured system establishment and management method includes:

[0062] Step 1: Establish a correlation model for the carbon data attribute system.

[0063] P={A 物理维度 , B 功能维度 , C 时间维度 , D 工艺维度 , E 软硬件维度 , F 背景维度}

[0064] Where: P represents the comprehensive performance of carbon data attributes of steel enterprises;

[0065] A 物理维度 The physical system dimension that represents the carbon data attributes;

[0066] B 功能维度 Functional application dimension representing carbon data attributes;

[0067] C 时间维度 The time granularity dimension representing the carbon data attributes;

[0068] D 工艺维度 The process emission source dimension representing the carbon data attributes;

[0069] E 软硬件维度 The hardware and software system dimensions that represent the carbon data attributes;

[0070] F 背景维度 Background database dimension representing carbon data attributes.

[0071] (1) Physical system dimension of carbon data attributes

[0072] The physical system dimension of the carbon data attributes of steel enterprises refers to the physical system structure of the enterprise represented by the carbon data. The corresponding data types include: group-level data, enterprise-level data, business unit-level data, process-level data, workshop-level data, equipment-level data and product-level data.

[0073] A 物理维度 ={Group level, Enterprise level, Division level, Process level, Equipment level, Product level}

[0074] (2) Functional application dimension of carbon data attributes

[0075] The functional application dimension of carbon data attributes refers to the various functions involved in the carbon management system. The corresponding data types include: organizational carbon data, facility carbon data, product carbon data, carbon asset data, etc.

[0076] B 功能维度 ={Organizational carbon, Facility carbon, Product carbon, Carbon assets}

[0077] (3) The time granularity dimension of carbon data attributes

[0078] The time granularity dimensions of carbon data attributes include: real-time data, accumulated data, statistical data, offline data (such as receipts, reports, etc.), etc.

[0079] C 时间维度 ={real-time data, accumulated data, statistical data, offline data}

[0080] (4) Process emission source dimension of carbon data attributes

[0081] The process emission source dimension of carbon data attributes includes: production system emission source, energy system emission source, inspection and testing system emission source, procurement system emission source, financial system emission source, etc.; the data range includes the whole process from "cradle to gate". Among them, the financial system implements cost accounting and balance accounting for all materials in the procurement link and the whole factory production process, and involves output value of 10,000 yuan.

[0082] D 工艺维度 ={production system, energy system, inspection and testing system, procurement system, financial system}

[0083] (5) Software and hardware system dimensions of carbon data attributes

[0084] The hardware and software system dimension of carbon data attributes means that all types of carbon data in steel enterprises are associated with corresponding collection points. When carbon data cannot be identified, it may be caused by problems with the sensor points corresponding to the carbon data or the transmission network signal. Therefore, the hardware and software system dimension corresponding to carbon data directly determines whether carbon data exists or not. The hardware and software system dimensions of carbon data attributes include: sensor points for carbon data collection, network signals, etc.

[0085] E 软硬件维度 ={sensor point, network signal}

[0086] (6) Background database dimensions of carbon data attributes

[0087] All types of carbon accounting require emission factors. Currently, most industries use emission factors from authoritative databases. Emission factors are also an important category of broad carbon data. The background database dimensions of carbon data attributes include: organizational carbon emission factors, product carbon emission factors, life cycle assessment emission factors, etc.

[0088] F 背景库维度 ={organizational carbon emission factor, product carbon emission factor, life cycle assessment emission factor}.

[0089] In addition, in order to make the enterprise carbon data good and effective, it is necessary to solve the three-level problems of "existence and non-existence", "correctness and error", and "calculation and use" of carbon data, and build a three-level, multi-dimensional carbon data structured system and governance method. Only in this way can we ensure the acquisition of effective carbon data and carbon results, and then support steel enterprises in implementing carbon management.

[0090] The supporting relationship diagram of the carbon data attribute dimension for the effect of the carbon data system, such as Figure 1 shown.

[0091] ①The software and hardware system dimensions determine the existence or non-existence of carbon data. The carbon data system needs to have monitoring functions for sensor points, signal network smoothness and interruption, etc., and timely discover problems to ensure carbon data connectivity.

[0092] ② The time dimension, process emission source dimension, and background database dimension jointly determine the "rightness or wrongness" of carbon data. For example, issues such as the time matching degree of carbon data, the "one-to-many or many-to-one" of process emission sources, and the rationality of background data selection will all lead to deviations or errors in carbon data.

[0093] ③ The physical dimension and functional dimension determine the calculation logic and usage scenarios of carbon data. For example, the statistical scope and parameter types required for enterprise-level, process-level, and equipment-level carbon accounting are different; organizational carbon, product carbon, and carbon assets, even for the same material, require different calculation methodologies and accounting results.

[0094] The present invention stipulates that the general principle sequence of multi-level and multi-dimensional systematic management of carbon data is: first "existence and non-existence", then "right and wrong", and finally "calculation and use". Based on this, the present invention establishes a "three-level, multi-dimensional" structured system diagram of carbon data of steel enterprises, such as Figure 2 As shown. The carbon data structured system is divided into three levels to ensure carbon data. The first level ensures the existence of carbon data (also known as the basic level), the second level ensures the correctness of carbon data (i.e. reasonable and effective), and the third level ensures the calculation and use of carbon data and carbon results (i.e. reasonable calculation and use). The three levels of the carbon data structured system are respectively guaranteed by the carbon data attribute dimensions contained therein.

[0095] Each level and dimension of carbon data of steel enterprises has its own unique process flow characteristics, processing difficulties, and key solutions and means. The following will solve and implement targeted introductions for each level and attribute dimension of carbon data (steps 2 to 4).

[0096] Step 2: Governance of the “existence and non-existence” level of carbon data.

[0097] Establish the corresponding relationship between carbon data process side parameters and sensor system, such as Figure 3 The carbon parameter A represents the basic carbon data parameter for implementing carbon emission calculation, A1, A2, A i and A N represents the sensing point associated with the carbon parameter A, Figure 3 a1, a2, a i and a N Represents a signal network that transmits carbon data.

[0098] The quantitative calculation model of carbon data parameter A and the metering data of each sensor point is established as follows:

[0099] Carbon data A = Carbon data A1 + Carbon data A2 + Carbon data A i +Carbon Data A N

[0100] The values ​​of each "carbon data Ai" in the formula can be positive or negative, indicating energy generation and consumption, energy input and output, etc.

[0101] The determination of whether the i-th path of the carbon parameter is smooth can be calculated by the [0, 1] variable f as follows:

[0102]

[0103] When f i When the value is 1, it means that the i-th data path of carbon parameter A is unblocked, that is, the sensor point is collecting data normally and the network signal transmission is normal; when f i When the value is 0, it means that the i-th data path of the carbon parameter A is blocked, that is, the sensor point cannot collect data normally, or the network signal transmission is abnormal.

[0104] To implement the “have or have not” level governance of carbon data, the algorithmic processes implemented are as follows: Figure 4 shown.

[0105] The sensor collection system is the basis for the company to obtain carbon data. The accuracy and coverage of the sensor points, as well as the timely uploading of the sensor collection signals to the carbon system through the network, will affect the smoothness of the acquisition path of the carbon data required by the system. Steel companies have a wide variety of materials and energy. Taking the secondary energy gas as an example, the sensor point system diagram of the gas-related carbon data in each region is as follows: Figure 5 shown.

[0106] The hardware and software system dimensions of carbon data determine the presence or absence of data in the carbon system. As mentioned above, a carbon system association model is established for carbon data, sensor points, and network signals. Taking the coal gas of a steel enterprise as an example, when the carbon data attribute E 软硬件维度 When the monitoring result has an element of "0", it means "there is f iWhen the value is 0, it means that the carbon data sensor fails to collect data or the corresponding signal network is not transmitted smoothly. The result is output in time and maintenance is implemented. 软硬件维度 When all elements of the monitoring results are not "0", it means that the basic sensor collection and uploaded data are normal, there is no problem in this link, and a good foundation has been laid for carbon data collection. Through the governance of carbon data "existence and non-existence" level, the basic guarantee of carbon data security is implemented.

[0107] Step 3: Governance of the “right and wrong” levels of carbon data.

[0108] The correctness and error of carbon data at this level include the time granularity dimension, process emission source dimension, and background database dimension. These three dimensions ensure that the read carbon data does not deviate from the actual process and jointly guarantee the validity of the carbon data.

[0109] (1) The time granularity dimension of carbon data attributes

[0110] The time granularity dimensions of carbon data attributes include real-time data, accumulated data, statistical data, offline data, etc. Among them, accumulated data can be obtained through real-time data, and the time granularity is divided into year, quarter, month, day, and hour; statistical data and offline data are usually not obtained by enterprises through measurement means, or the measurement coverage is temporarily insufficient and cannot be obtained; statistical data and offline data are solved by filling in the manual system to ensure that the data of all time dimensions of the enterprise carbon system can be obtained online, such as Figure 6 shown.

[0111] (2) Process emission source dimension of carbon data attributes

[0112] The current data of steel enterprises are stored in different systems. For example, the production system stores material data, and the energy system stores energy data. However, these data are not directly related to the data dimensions required by the carbon system, and the carbon data structure is slightly chaotic, which is not conducive to the carbon system's data classification, accounting and management.

[0113] The process emission source dimension of carbon data attributes includes the enterprise’s internal production system data, energy system data, inspection and testing system data, procurement system data, financial system data, as well as the enterprise’s upstream raw material mining data and off-site transportation data.

[0114] Different from the previous independent operation of various systems in steel enterprises with little interconnection, the carbon system needs to integrate all the system carbon attribute related data to facilitate the unified and comprehensive management of the time and space dimensions of the carbon data system. Therefore, carbon data will be a synchronous integration of production data, energy data, inspection and testing data, procurement data, and financial cost data. The distribution and integration diagram of carbon data in various systems of steel enterprises are shown in the figure below. Figure 7 shown.

[0115] Although the data types in the figure are different, the various types of data are not isolated from each other, but interconnected and interrelated. There are two main ways to associate carbon data: one is the association of the same time and space, that is, the data in the same region and the same time dimension are associated with each other; the other is the association of the same product output, that is, in order to produce a certain type of product, steel companies implement the corresponding production data, energy data, inspection and testing data, procurement data and other data to associate with each other.

[0116] (3) Background data dimensions of carbon data attributes

[0117] The difficulty in considering the background data dimension of carbon data attributes lies in the need to associate background data (such as emission factors) with the actual process of activity data. The actual process refers to where and how such raw materials are used in steel enterprises, as well as the production process used. If the emission factors cannot be associated with the actual production of steel enterprises, the processing results are often inaccurate or even wrong.

[0118] Due to the complex production process, different process flow and principles of steel enterprises, the same type of materials often have completely different process principles in different scenarios, which greatly increases the trouble of selecting background data. Misselection will directly lead to distortion and error of carbon data, but it is not easy to be found, which will lead to deviations in carbon planning of steel enterprises, resulting in waste of human, material and financial resources of enterprises, but failing to achieve the desired results.

[0119] After analysis, the major categories of data in the background library dimension of carbon data attributes include: organizational carbon emission factors, product carbon emission factors and life cycle assessment factors; the design of the major category background library data set is as follows:

[0120]

[0121] Product carbon emission factor = {fossil carbon factor, biomass carbon factor, land use carbon factor}

[0122]

[0123] For each type of raw material, energy, etc. of the steel enterprise, a corresponding factor library is established. The key point is that the use process of each type of material must be taken into account. The same type of raw material will correspond to different factors. It is necessary to clearly mark the raw material name, use process, and carbon emission factor; according to the metallurgical process principle, a flow chart of the emission factor library of the steel enterprise is established, such as Figure 8 shown.

[0124] Step 4: Governance of the “calculation and use” levels of carbon data.

[0125] The levels of calculation and use of carbon data include physical dimensions and functional dimensions, and are based on these two levels of accounting and application. They distinguish and process parameter divisions, implement accounting, and classify and store carbon data results for use by enterprises.

[0126] (1) Physical system dimension of carbon data attributes

[0127] The physical system dimensions of carbon data attributes include: group level, enterprise level, division level, process level, equipment level and product level. The difficulty of this part is to clearly distinguish the physical boundaries. If the division is too fine, it will be unexecutable, but if the division is too rough, it will lead to blurred boundaries and distorted results. Among them, the statistical scope boundaries of the equipment level and product level are often unclear in steel enterprises.

[0128] The equipment level refers not only to the main equipment, but also to the auxiliary equipment that helps the equipment to operate, as well as the auxiliary systems that provide conditions for the operation of the main equipment. Taking the iron-making blast furnace as an example, in addition to the blast furnace, the auxiliary equipment also includes the hot blast stove, TRT unit, and ladle baking device; and the auxiliary systems include the feeding system, combustion system, air distribution system, gas recovery system, circulating water system, ash treatment system, etc.

[0129] The product-level carbon data of steel enterprises refers not only to the terminal system grade products, but also to the major categories of products, sub-categories of products, and intermediate products. For example, coke is the product of the coke oven, sintered ore is the sintering product, molten iron is the ironmaking product, molten steel is the steelmaking product, ingot is the product of the continuous casting process, hot-rolled coil is the product of the hot rolling process, and cold-rolled coil is the product of the cold rolling process. These should be considered as the intermediate products of the long process of steel metallurgy. Although they are not terminal products, they are of great significance to the implementation of carbon management and carbon planning by steel enterprises.

[0130] (2) Functional application dimension of carbon data attributes

[0131] The functional application dimensions of carbon data attributes include organizational carbon, facility carbon, carbon assets, product carbon, etc.

[0132] The organizational carbon dimension includes carbon emissions from fossil fuel combustion, carbon emissions from industrial processes, carbon emissions from net purchased electricity and heat, and carbon emissions from carbon sequestration products.

[0133] The carbon dimension of facilities is determined according to the actual situation of each steel enterprise, including major furnace equipment, such as coke ovens, sintering machines, blast furnaces, roasters, converters, electric furnaces, refining furnaces, continuous casting lines, hot rolling lines, flattening lines, cross-cutting lines, molten iron pretreatment, annealing units, acid rolling lines, galvanizing lines, color coating lines, silicon steel lines, gas purification stations, gas tanks, thermal power plants, power plants, etc.

[0134] Carbon assets include the purchase of carbon quotas, sale of carbon quotas, carry-over of carbon assets, purchase of CCERs, purchase of green certificates and issuance of carbon quotas by groups or enterprises, as well as the allocation and implementation of management in proportion to each department and each process in the time dimension.

[0135] Product carbon includes upstream carbon footprint, off-site transportation carbon footprint, fuel combustion carbon footprint, process emission carbon footprint, waste treatment carbon footprint and co-product carbon footprint. In addition, the life cycle assessment stage includes fossil carbon, biomass carbon, land use carbon, acidification potential carbon, eutrophication potential carbon, convective ozone generation potential, etc.

[0136] Step 5: Carbon data pool based on carbon data structured system.

[0137] Starting from the origin of the carbon system of steel enterprises, this paper establishes a three-level, multi-dimensional structured and governance system for carbon data of steel enterprises; based on this, steel enterprises form a basic, comprehensive and comprehensive carbon data pool, as shown in the schematic diagram Fig. 9 As shown. It can be used by the carbon management system of steel enterprises, support the pre-processing of carbon data problems, ensure the accuracy of carbon data and traceability requirements, etc.; support enterprise carbon emission verification, facility carbon management, carbon asset optimization and product carbon accounting and management.

Claims

1. A method for establishing and managing a carbon data structured system for a steel enterprise, characterized in that: The steps include: Step 1: Establish a correlation model for the carbon data attribute system; P={A 物理维度 ,B 功能维度 ,C 时间维度 ,D 工艺维度 ,E 软硬件维度 ,F 背景维度 } Where: P represents the comprehensive performance of carbon data attributes of steel enterprises; A 物理维度 The physical system dimension that represents the carbon data attributes; B 功能维度 Functional application dimension representing carbon data attributes; C 时间维度 The time granularity dimension representing the carbon data attributes; D 工艺维度 The process emission source dimension representing the carbon data attributes; E 软硬件维度 The hardware and software system dimensions that represent the carbon data attributes; F 背景维度 Background database dimensions representing carbon data attributes; Step 2: hierarchical management of the presence and absence of carbon data; establishing the corresponding correlation between the process side parameters of carbon data and the sensor system; Step 3: hierarchical management of the correctness and error of carbon data; the correctness and error of carbon data at this level includes the time granularity dimension, process emission source dimension, and background database dimension. These three dimensions ensure that the read carbon data does not deviate from the actual process and jointly guarantee the validity of carbon data; Step 4: Level governance of carbon data calculation and use; the levels of carbon data calculation and use include physical and functional dimensions, which are the accounting and application levels based on these two levels; distinguish and process parameter divisions, implement accounting and classify and store carbon data results for use by enterprises; Step 5: Carbon data pool based on carbon data structured system; Starting from the origin of the carbon system of steel enterprises, a three-level, multi-dimensional structuring and governance system for the carbon data of steel enterprises is established; based on this, steel enterprises form a basic, comprehensive and comprehensive carbon data pool, which in turn supports the enterprise's carbon emission verification, facility carbon management, carbon asset optimization and product carbon accounting and management work.

2. The method for establishing and managing a carbon data structured system for steel enterprises according to claim 1 is characterized by: The step 1, ① the physical system dimension of the carbon data attribute of the steel enterprise refers to the enterprise physical system structure represented by the carbon data, and the corresponding data types specifically include: group-level data, enterprise-level data, division-level data, process-level data, workshop-level data, equipment-level data and product-level data; A 物理维度 ={Group level, enterprise level, division level, process level, equipment level, product level} ②The functional application dimension of carbon data attributes refers to the various functions involved in the carbon management system. The corresponding data types include: organizational carbon data, facility carbon data, product carbon data, and carbon asset data; B 功能维度 ={Organizational carbon, Facility carbon, Product carbon, Carbon assets} ③The time granularity dimensions of carbon data attributes include: real-time data, accumulated data, statistical data, and offline data; C 时间维度 ={real-time data, accumulated data, statistical data, offline data} ④ The process emission source dimension of carbon data attributes includes: production system emission source, energy system emission source, inspection and testing system emission source, procurement system emission source, and financial system emission source; D 工艺维度 ={production system, energy system, inspection and testing system, procurement system, financial system} ⑤ The software and hardware system dimensions of carbon data attributes include: sensor points and network signals for carbon data collection; E 软硬件维度 ={sensing point, network signal} ⑥Emission factors are also an important category of generalized carbon data. The background database dimensions of carbon data attributes include: organizational carbon emission factors, product carbon emission factors, and life cycle assessment emission factors; F 背景库维度 ={organizational carbon emission factor, product carbon emission factor, life cycle assessment emission factor}.

3. The method for establishing and managing a carbon data structured system for steel enterprises according to claim 1 is characterized by: In step 2, the carbon parameter A represents the basic carbon data parameter for implementing carbon emission calculation, A1, A2, A i and A N represents the sensing point associated with the carbon parameter A, and a1, a2, a i and a N represents a signal network that transmits carbon data; The quantitative calculation model of carbon data parameter A and the metering data of each sensor point is established as follows: Carbon data A = Carbon data A1 + Carbon data A2 + Carbon data A i +Carbon Data A N The values ​​of each "carbon data Ai" in the formula can be positive or negative, indicating energy generation and consumption, energy input and output; The determination of whether the i-th path of the carbon parameter is smooth can be calculated by the [0, 1] variable f as follows: When f i When the value is 1, it means that the i-th data path of carbon parameter A is unblocked, that is, the sensor point is collecting data normally and the network signal transmission is normal; when f i When the value is 0, it means that the i-th data path of the carbon parameter A is blocked, that is, the sensor point cannot collect data normally, or the network signal transmission is abnormal.

4. The method for establishing and managing a carbon data structured system for steel enterprises according to claim 1 is characterized by: In step 3, the time granularity dimension of carbon data attributes includes real-time data, accumulated data, statistical data, and offline data; among them, accumulated data can be obtained through real-time data, and the time granularity is divided into year, quarter, month, day, and hour; statistical data and offline data are usually not obtained by enterprises through measurement means, or the measurement coverage is temporarily insufficient and cannot be obtained; statistical data and offline data are solved by filling in the manual system to ensure that the data of all time dimensions of the enterprise carbon system can be obtained online; The process emission source dimension of carbon data attributes includes the enterprise's internal production system data, energy system data, inspection and testing system data, procurement system data, financial system data, as well as the enterprise's upstream raw material mining data and off-site transportation data; unlike the previous independent operation of various systems in steel enterprises, which were rarely interconnected, the carbon system needs to integrate all system carbon attribute-related data to facilitate the unified and comprehensive management of the time and space dimensions of the carbon data system; The major categories of data in the background library dimension of carbon data attributes include: organizational carbon emission factors, product carbon emission factors and life cycle assessment factors; the design major category background library data set is as follows: Product carbon emission factor = {fossil carbon factor, biomass carbon factor, land use carbon factor} For each type of raw material and energy of the steel enterprise, a corresponding factor library should be established; the key point is to take into account the use process of each type of material. The same type of raw material will correspond to different factors, and the raw material name, use process, and carbon emission factor must be clearly marked.

5. The method for establishing and managing a carbon data structured system for steel enterprises according to claim 4 is characterized by: The ways of associating carbon data include:

1. association in the same time and space, that is, data in the same region and the same time dimension are associated with each other; 2. association of the same product output, that is, in order to produce a certain type of product, steel companies implement corresponding production data, energy data, inspection and testing data, and procurement data that are associated with each other.

6. The method for establishing and managing a carbon data structured system for steel enterprises according to claim 1 is characterized by: In step 4, the physical system dimensions of carbon data attributes include: group level, enterprise level, division level, process level, equipment level and product level; the equipment level refers not only to the main equipment, but also to the auxiliary equipment that helps the equipment to operate, and the auxiliary system that provides conditions for the operation of the main equipment; the product-level carbon data of steel enterprises refers not only to the terminal system brand products, but also to major products, sub-categorized products, and intermediate products; The functional application dimensions of carbon data attributes include organizational carbon, facility carbon, carbon assets, and product carbon; among them, the organizational carbon dimension includes carbon emissions from fossil fuel combustion, industrial process carbon emissions, net purchased electricity and heat carbon emissions, and carbon sequestration product carbon emissions; the facility carbon dimension is determined based on the actual situation of each steel company, including major furnace equipment; carbon assets include the group or company's purchase of carbon quotas, sale of carbon quotas, carry-over of carbon assets, purchase of CCERs, purchase of green certificates, and issuance of carbon quotas, as well as the allocation and management of the proportion of each department and each process according to the time dimension; product carbon includes upstream carbon footprint, off-site transportation carbon footprint, fuel combustion carbon footprint, process emission carbon footprint, waste treatment carbon footprint, and symbiotic product carbon footprint.

Images