Carbon emission suggestion generation method, device, equipment and medium

Abstract

The invention discloses a carbon emission suggestion generation method and device, equipment and a medium, and belongs to the technical field of computers. The method comprises the following steps: acquiring a hierarchy identifier of a hierarchy to be predicted, and determining a corresponding process identifier and a material identifier according to the hierarchy identifier; after the data acquisition period arrives, acquiring consumption data of each corresponding target steel material according to the process identifier and the material identifier in allusion to the current period; based on the consumption data of each target steel material, periodic carbon emission corresponding to the level identifier is obtained; obtaining a statistical cycle preset yield of a hierarchical product corresponding to the hierarchical identifier, a cycle actual yield in the current cycle, and a preset statistical cycle quota amount of carbon emission corresponding to the hierarchical identifier; based on the periodic actual yield, the statistical periodic preset yield and the periodic carbon emission, predicting to obtain a statistical periodic carbon emission; and comparing the statistical cycle carbon emission amount with a preset statistical cycle quota amount to generate a carbon emission suggestion.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computers, and particularly relates to a carbon emission suggestion generation method and device, equipment and a medium. BACKGROUND

[0002] As a key carbon emission industry, the carbon emission amount and intensity of the enterprise organization level of a steel enterprise will be an important control target in the process of entering the market and performing the contract of the national carbon market.

[0003] The accounting of the carbon emission amount of the organization level of a steel enterprise is divided into the carbon emission amount accounting of the factory level and the carbon emission amount accounting of the process level, and the carbon emission amount of the entire factory in the process of producing steel or the carbon emission amount of a process in the process of producing steel can be accounted for, but this is calculated after the carbon emission in the process of producing steel is completed, and cannot provide available suggestions for the control of the carbon emission amount of the enterprise in the process of producing steel, so that the enterprise cannot realize the control of the carbon emission amount. SUMMARY

[0004] In view of the above problems, the present application is proposed to provide a carbon emission suggestion generation method, device, equipment and medium which can solve the above problems, and can provide available suggestions for the control of the carbon emission amount of the enterprise in the process of producing steel, and realize the control of the carbon emission amount.

[0005] In a first aspect, the present application provides a carbon emission suggestion generation method, which comprises:

[0006] obtaining a level identifier of a to-be-predicted level, and determining a corresponding process identifier and a material identifier according to the level identifier; wherein the to-be-predicted level comprises any one of a factory level and a process level under the factory level;

[0007] After a data acquisition period arrives, for a current period, obtaining consumption data of each target steel material corresponding to the process identifier and the material identifier;

[0008] obtaining a period carbon emission amount corresponding to the level identifier based on the consumption data of each target steel material;

[0009] obtaining a statistical period preset yield of a level product corresponding to the level identifier and a period actual yield in the current period, and a preset statistical period quota amount of carbon emission corresponding to the level identifier; the statistical period comprises a plurality of data acquisition periods;

[0010] obtaining a statistical period carbon emission amount based on the period actual yield, the statistical period preset yield, and the period carbon emission amount;

[0011] The statistical period carbon emission amount is compared with the preset statistical period quota amount, and a carbon emission suggestion corresponding to the level identifier and for the current period is generated based on a comparison result.

[0012] In one of the embodiments, the period carbon emission amount corresponding to the level identifier is obtained based on the consumption data of each target steel material, including:

[0013] For each target steel material, a carbon emission factor of the target steel material is determined;

[0014] Based on the consumption data and the carbon emission factor, a period carbon emission amount of the target steel material is obtained;

[0015] Based on the period carbon emission amount of each target steel material, a period carbon emission amount corresponding to the level identifier is determined.

[0016] In one of the embodiments, the data acquisition period includes multiple unit periods, and the carbon emission factor of the target steel material is determined, including:

[0017] For each unit period in the current period, batch low calorific values of the target steel material in multiple batches in each unit period are obtained, and based on the batch low calorific values, a period low calorific value of the target steel material in the unit period is obtained;

[0018] Based on the period low calorific values corresponding to each unit period respectively, a final low calorific value of the target steel material in the current period is obtained;

[0019] A preset unit heat value carbon content and carbon oxidation rate of the target steel material are obtained, and based on the final low calorific value, the unit heat value carbon content and the carbon oxidation rate, a carbon emission factor of the target steel material is calculated.

[0020] In one of the embodiments, the statistical period carbon emission amount is predicted based on the period carbon emission amount, the statistical period preset production amount and the period actual production amount, including:

[0021] Based on the period carbon emission amount and the period actual production amount, a steel material emission intensity corresponding thereto is obtained;

[0022] Based on the statistical period preset production amount, the period actual production amount, the steel material emission intensity and the period carbon emission amount, a statistical period carbon emission amount is predicted.

[0023] In one of the embodiments, the statistical period carbon emission amount is predicted based on the statistical period preset production amount, the period actual production amount, the steel material emission intensity and the period carbon emission amount, including:

[0024] calculating a difference between the preset yield of the statistical period and the actual yield of the period;

[0025] calculating a product of the discharge intensity of the steel material and the difference;

[0026] determining a sum of the product and the carbon discharge amount of the period, and taking the determined sum as the predicted statistical period carbon discharge amount.

[0027] In one of the embodiments, when the level to be predicted is the process level, the period carbon discharge amount corresponding to the level identifier is the period carbon discharge amount corresponding to the process level identifier.

[0028] obtaining a preset statistical period quota of carbon discharge corresponding to the level identifier, comprising:

[0029] determining the period carbon discharge amount corresponding to the factory level identifier, and determining the preset statistical period quota of carbon discharge corresponding to the factory level identifier;

[0030] determining a proportion of the period carbon discharge amount corresponding to the process level identifier in the period carbon discharge amount corresponding to the factory level identifier;

[0031] obtaining the preset statistical period quota of carbon discharge corresponding to the process level identifier based on the proportion and the preset statistical period quota corresponding to the factory level identifier;

[0032] taking the preset statistical period quota of carbon discharge corresponding to the process level identifier as the preset statistical period quota of carbon discharge corresponding to the level identifier.

[0033] In one of the embodiments, after the generating of the carbon discharge suggestion corresponding to the level identifier for the current period based on the comparison result, the method further comprises:

[0034] after the data acquisition period arrives, determining a next period of the current period in the statistical period, and obtaining the consumption data of each target steel material corresponding to the process identifier and the material identifier for the next period; and obtaining the period carbon discharge amount corresponding to the level identifier based on the consumption data of each target steel material.

[0035] The total period obtained by accumulating the current period and the next period is taken as the current period, and the total period carbon emission obtained by accumulating the period carbon emission of the current period and the period carbon emission of the next period is taken as the period carbon emission of the current period, and the step of obtaining the statistical period preset yield of the level product corresponding to the level identifier and the period actual yield of the current period, and the preset statistical period quota of carbon emission corresponding to the level identifier is returned and executed until the current period matches the statistical period.

[0036] In a second aspect, the present application provides a carbon emission suggestion generation device, the device comprising:

[0037] A first obtaining module is configured to obtain a level identifier of a to-be-predicted level, and determine a corresponding process identifier and a material identifier according to the level identifier; wherein the to-be-predicted level includes any one of a factory level and a process level under the factory level.

[0038] A second obtaining module is configured to, after a data obtaining period arrives, obtain consumption data of each target steel material corresponding to the process identifier and the material identifier for a current period;

[0039] A first determining module is configured to obtain a period carbon emission corresponding to the level identifier based on the consumption data of each target steel material.

[0040] A third obtaining module is configured to obtain a statistical period preset yield of a level product corresponding to the level identifier and a period actual yield of the current period, and a preset statistical period quota of carbon emission corresponding to the level identifier; the statistical period includes a plurality of data obtaining periods.

[0041] A second determining module is configured to predict a statistical period carbon emission based on the period actual yield, the statistical period preset yield, and the period carbon emission.

[0042] A comparison is made between the statistical period carbon emission and the preset statistical period quota, and a carbon emission suggestion corresponding to the level identifier for the current period is generated based on a comparison result.

[0043] In a third aspect, the present application provides an electronic device, comprising a memory and a processor, which are communicatively connected with each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the method of the first aspect.

[0044] In a fourth aspect, the present application provides a computer readable storage medium, which stores computer instructions for causing the computer to execute the method of the first aspect.

[0045] The technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0046] The carbon emission suggestion generation method, device, equipment and medium provided by the embodiments of the present application obtain the level identifier of a to-be-predicted level, determine the corresponding process identifier and material identifier according to the level identifier, wherein the level identifier of the to-be-predicted level includes any one of a factory level and a process level under the factory level, so that after a data acquisition period arrives, for a current period, the consumption data of each target steel material can be obtained according to the process identifier and the material identifier, and then the period carbon emission amount corresponding to the level identifier is obtained based on the consumption data of each target steel material, so that the period carbon emission amount corresponding to the level identifier for the current period can be calculated, and then after the statistical period preset output of the level product corresponding to the level identifier and the period actual output in the current period are obtained, and the preset statistical period quota amount of carbon emission corresponding to the level identifier is obtained, the statistical period carbon emission amount can be predicted based on the period actual output, the statistical period preset output and the period carbon emission amount, that is, the statistical period carbon emission amount of the whole year can be predicted based on the period carbon emission amount of the current period, so that the predicted statistical period carbon emission amount and the preset statistical period quota amount are compared, the carbon emission suggestion corresponding to the level identifier for the current period is generated based on the comparison result, and thus a useful suggestion for the control of carbon emission in the steel production process of an enterprise can be provided, and the control of carbon emission of the enterprise can be realized.

[0047] The above description is only a summary of the technical solutions of the present application, in order to enable the technical means of the present application to be more clearly understood, and to be implemented in accordance with the content of the description, and in order to enable the above and other purposes, features and advantages of the present application to be more apparent and easy to understand, the specific embodiments of the present application are described below. BRIEF DESCRIPTION OF DRAWINGS

[0048] Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The accompanying drawings are intended to further assist in understanding the preferred embodiments, and are not considered limiting of the present application. Moreover, like reference numerals denote like parts throughout the several views in the drawings. In the drawings:

[0049] Figure 1 is a flow diagram of a carbon emission suggestion generation method provided by the embodiments of the present application;

[0050] Figure 2 is the accounting boundary and process modeling of the factory level and the process level of the present application;

[0051] Figure 3is a flowchart of another carbon emission suggestion generation method provided by an embodiment of the present application;

[0052] Figure 4 is a flowchart of another carbon emission suggestion generation method provided by an embodiment of the present application;

[0053] Figure 5 is a flowchart of another carbon emission suggestion generation method provided by an embodiment of the present application;

[0054] Figure 6 is a structural diagram of a carbon emission suggestion generation device according to the present application;

[0055] Figure 7 is a structural diagram of an electronic device according to the present application. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solutions and advantages of the present application clearer, the embodiments of the present application will be described in further detail below with reference to the drawings, and it should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solutions of the present application, but not limitations of the technical solutions of the present application, and the technical features in the embodiments of the present application and the embodiments can be combined with each other without conflict.

[0057] Figure 1 is a flowchart of a carbon emission suggestion generation method provided by an embodiment of the present application, as shown in Figure 1 , the method comprises:

[0058] In step S102, the hierarchy identifier of the to-be-predicted hierarchy is obtained, and the corresponding process identifier and material identifier are determined according to the hierarchy identifier; wherein the to-be-predicted hierarchy includes any one of the factory hierarchy and the process hierarchy under the factory hierarchy.

[0059] In the accounting of the carbon emission of an enterprise, the research boundary is divided into the factory hierarchy and the process hierarchy, the factory hierarchy includes multiple process hierarchies, and the carbon emission of the factory corresponding to each factory hierarchy is equal to the sum of the carbon emissions respectively corresponding to the multiple process hierarchies under the factory hierarchy.

[0060] In the prior art, when collecting the consumption data of steel materials, an offline manual reporting method is generally used, which results in low accounting efficiency and high error rate. In the present application, the carbon emission prediction system (hereinafter referred to as the system) periodically collects and stores the consumption data of all steel materials used in the production of steel in one or more factories according to a preset data collection period, and marks each steel material with a process identifier and a material identifier. Thus, the consumption data of the steel materials stored in the system can be directly obtained based on the process identifier and the material identifier without manual reporting, so that the carbon emission of the corresponding material can be calculated based on the consumption data, thereby improving the accounting efficiency and reducing the error rate.

[0061] In the present embodiment, the data collection period has a one-to-one correspondence with the data acquisition period, that is, after the data acquisition period arrives, the consumption data of the steel materials collected in the corresponding data collection period can be obtained, and the end time of the data collection period is greater than the start time of the data acquisition period.

[0062] If the to-be-predicted level includes the factory level, the corresponding process identifier and material identifier are determined according to the level identifier, specifically including: determining the multiple process levels under the factory level and the process identifier corresponding to each process level according to the level identifier of the factory level, determining the multiple material levels under each process level, and determining the material identifier corresponding to each material level.

[0063] If the to-be-predicted level includes the process level, the corresponding process identifier and material identifier are determined according to the level identifier, specifically including: determining the process identifier corresponding to the level identifier according to the level identifier of the process level, determining the multiple material levels under the process level, and determining the material identifier corresponding to each material level. In the present embodiment, one possible case is that the level identifier of the process level is the same as the process identifier, for example, the process level is the sintering process, and the level identifier of the process level and the process identifier are both sintering process identifiers. Then, the material identifiers of the multiple material levels under the sintering process can be determined.

[0064] In step S104, after the data acquisition period arrives, the consumption data of each target steel material is obtained according to the process identifier and the material identifier for the current period.

[0065] The system pre-sets a data acquisition period, and after the data acquisition period arrives, the target steel material corresponding to the determined process identifier and material identifier is determined for the current period, and the consumption data of each target steel material in the current period pre-stored in the system is obtained.

[0066] In the present embodiment, the consumption data of the target steel material can be the consumption amount of the target steel material.

[0067] Step S106, based on the consumption data of each target steel material, obtain the period carbon emission corresponding to the level identifier;

[0068] The period carbon emission of each target steel material is calculated, and the period carbon emission of each target steel material is accumulated to obtain the period carbon emission corresponding to the level identifier. For example, in the current period, material 1 and material 2 are needed for the sintering process, and the period carbon emission of the sintering process is equal to the sum of the period carbon emission of material 1 and the period carbon emission of material 2.

[0069] Step S108, obtaining the statistical period preset production of the level product corresponding to the level identifier and the period actual production in the current period, and the preset statistical period quota of carbon emission corresponding to the level identifier; the statistical period includes multiple data acquisition periods;

[0070] If the level to be predicted is the factory level, the level product corresponding to the level identifier is steel, and if the level to be predicted is the process level, the level product corresponding to the level identifier is the intermediate product before the steel is generated. For example, for the sintering process, the level product corresponding to the level identifier is sinter, and for the pelletizing process, the level product corresponding to the level identifier is pellet.

[0071] In the embodiment, the statistical period includes multiple data acquisition periods, for example, the statistical period can be one year, and the data acquisition period can be one month;

[0072] The system obtains the statistical period preset production of the level product corresponding to the level identifier, which refers to the planned production of the level product in the statistical period preset by the system;

[0073] The system obtains the period actual production of the level product corresponding to the level identifier in the current period, which refers to the actual production of the level product in the current period, which is also collected by the system.

[0074] The system obtains the preset statistical period quota of carbon emission corresponding to the level identifier, which is the quota of carbon emission of the level product corresponding to the level identifier in the statistical period preset by the system;

[0075] In the embodiment, if the level to be predicted is the factory level, the preset statistical period quota is the quota of carbon emission in the statistical period preset for the entire factory; if the level to be predicted is the process level, the preset statistical period quota is the quota of carbon emission in the statistical period preset for a certain process, wherein the quota corresponding to the process level can be calculated based on the quota corresponding to the factory level, and the specific calculation method will be described in the following embodiments.

[0076] Step S110, based on the period actual output, the statistical period preset output, and the period carbon emission, a statistical period carbon emission is predicted;

[0077] In the embodiment, the carbon emission of the entire statistical period can be predicted based on the period carbon emission of the current period. Thus, the carbon emission of the entire statistical period can provide a reference for the enterprise to control the carbon emission, and ensure that the enterprise timely realizes the carbon emission control.

[0078] Step S112, comparing the statistical period carbon emission and the preset statistical period quota, a carbon emission suggestion corresponding to the level identifier and for the current period is generated based on the comparison result.

[0079] The system compares the statistical period carbon emission and the preset statistical period quota. If the statistical period carbon emission is greater than or equal to the preset statistical period quota, it indicates that the carbon emission of the entire statistical period will exceed the preset statistical period quota under the condition of the emission level of the current period. Thus, for the to-be-predicted level, it is suggested that the enterprise strengthen the internal control of the carbon emission of the enterprise. If the statistical period carbon emission is less than the preset statistical period quota, it indicates that the carbon emission of the entire statistical period will be less than the preset statistical period quota under the condition of the emission level of the current period. Thus, for the to-be-predicted level, it is suggested that the enterprise maintain the current emission status.

[0080] It can be seen that in the embodiment, the level identifier of the to-be-predicted level is acquired, and the corresponding process identifier and material identifier are determined according to the level identifier, wherein the to-be-predicted level includes any one of the factory level and the process level under the factory level. Thus, after the data acquisition period arrives, for the current period, the consumption data of each target steel material can be acquired according to the process identifier and the material identifier, and the period carbon emission corresponding to the level identifier is obtained based on the consumption data of each target steel material. In this way, the period carbon emission corresponding to the level identifier and for the current period can be calculated. Thus, after the statistical period preset output of the level product corresponding to the level identifier and the period actual output in the current period are acquired, and the preset statistical period quota of the carbon emission corresponding to the level identifier is acquired, the statistical period carbon emission can be predicted based on the period actual output, the statistical period preset output, and the period carbon emission. That is, the statistical period carbon emission of the entire statistical period can be predicted based on the period carbon emission of the current period. Thus, the predicted statistical period carbon emission and the preset statistical period quota are compared, and a carbon emission suggestion corresponding to the level identifier and for the current period is generated based on the comparison result. Thus, a usable suggestion can be provided for the enterprise to control the carbon emission in the steel production process, and the carbon emission of the enterprise can be controlled.

[0081] Figure 2The accounting boundaries and process modeling of the plant level and the process level in the embodiments of the present application are shown. The enterprise carbon emission data accounting is divided into plant level and process level according to the research boundary. The process level accounting granularity in the present application is defined as coking, sintering, pelletizing, blast furnace, steelmaking, steel processing, power generation, lime and other processes. Compared with the existing processes, the system can ensure that the sum of the carbon emissions of each process level in each data acquisition period is equal to the carbon emissions of the plant level in the data acquisition period, or the sum of the carbon emissions of each process level in the statistical period is equal to the carbon emissions of the plant level in the statistical period, by adding other processes and constructing the hierarchical relationship between the plant level and each process level, so that the corresponding carbon quota index coefficient of each process level can be divided according to the carbon emission proportion of each process level in the subsequent process.

[0082] When the plant level (corresponding to the full field level in the figure) carries out steel production, input energy and resources (i.e. materials for producing steel), such as washed fine coal, bituminous coal, anthracite, electricity, coke, scrap steel, manganese iron, nickel iron, chromium iron, crude steel, limestone, dolomite, are used. Gas emissions will be generated during the smelting of the above steel materials, and thus the carbon emissions need to be calculated;

[0083] The coking process inputs energy and resources, such as electricity, washed fine coal, blast furnace gas, produces coke oven gas, coke, crude benzene, tar, and dry quenching power generation, and carbon-containing gas emissions;

[0084] The sintering process inputs energy and resources, such as electricity, limestone, anthracite, dolomite, and coke fines, produces sinter, sinter waste heat power generation, steam, and carbon-containing gas emissions;

[0085] The pelletizing process inputs energy and resources, such as electricity, anthracite, blast furnace pulverized coal, produces pelletizing and carbon-containing gas emissions;

[0086] The blast furnace process inputs energy and resources, such as electricity, anthracite, bituminous coal, coke, dolomite, coke oven gas, blast furnace gas, produces molten iron, blast furnace gas, water slag waste heat, and carbon-containing gas emissions;

[0087] The steelmaking process inputs energy and resources, such as steelmaking electricity, copper, manganese iron, nickel group, lime, limestone, dolomite, converter gas, produces crude steel, and converter gas emissions;

[0088] The steel processing process inputs energy and resources, such as electricity, coke oven gas, natural gas, produces steel processing products, converter gas, and carbon-containing gas emissions;

[0089] The power generation process inputs energy and resources, such as electricity, coke oven gas, blast furnace gas, converter gas, natural gas, produces self-generation, steam, and carbon-containing gas emissions;

[0090] The lime process inputs energy and resources, such as electricity, limestone, natural gas, produces lime products and carbon-containing gas emissions;

[0091] Other processes input energy and resources, such as other products, produce carbon-containing gas emissions.

[0092] In the carbon emission accounting of the enterprise factory level, process level and organization level, the carbon emission of the steel material is often calculated by using the default value of the low calorific value of the material, for example, corresponding to the combustion of fossil fuels, the low calorific value of bituminous coal, anthracite, coke and other coal types is calculated by default, which may cause the accuracy of the calculated carbon emission of the steel material to be not high. In order to solve the problem, the measured heat value coefficient of the steel material can be used to calculate the carbon emission factor, so as to calculate the carbon emission, and the accuracy of the carbon emission is improved. In the present application, the specific process of carbon emission accounting by the system is as follows:

[0093] In one embodiment, the carbon emission of the target steel material is calculated based on the consumption data of the target steel material, including: determining the carbon emission factor of the target steel material; based on the consumption data and the carbon emission factor, the carbon emission of the target steel material is calculated; based on the carbon emission of each target steel material, the carbon emission of the target steel material corresponding to the level identifier is determined.

[0094] In one embodiment, the data acquisition period includes multiple unit periods, and the determination of the carbon emission factor of the target steel material includes: for each unit period in the current period, the batch low calorific value of the target steel material in multiple batches in each unit period is obtained, and based on the batch low calorific value, the period low calorific value of the target steel material in the unit period is obtained; based on the period low calorific value corresponding to each unit period, the final low calorific value of the target steel material in the current period is obtained; the preset unit heat value carbon content and carbon oxidation rate of the target steel material are obtained, and based on the final low calorific value, the unit heat value carbon content and the carbon oxidation rate, the carbon emission factor of the target steel material is calculated.

[0095] Referring to Figure 3 , the embodiment specifically includes the following steps:

[0096] S31, determine the research boundary of carbon emission accounting of enterprise factory, process organization level, and the process level research boundary is divided into coking, sintering, pelletizing, blast furnace, steelmaking, steel processing, power generation, lime and other processes;

[0097] In this embodiment, the carbon emission accounting boundary of the factory level (corresponding to the enterprise factory level in the figure) is determined, and the carbon emission accounting boundary of the process level (i.e., the process organization level in the figure) is determined;

[0098] S32, the input and output materials corresponding to the enterprise factory level and the process level are coded, so that the system can automatically obtain the monthly activity data of the corresponding emission material items through the code number;

[0099] The monthly activity data is the consumption data of the steel material in the current period, specifically: determining the input and output materials corresponding to the four emission types of fossil fuel combustion, industrial production process, purchased electricity and heat, and carbon sequestration deduction at the factory level or process level. For each process level and each type of emission material such as bituminous coal, bituminous coal, coke, limestone, dolomite, purchased electricity, comprehensive electricity, steam, etc. Create process code (i.e., the above process identifier) and material code (i.e., the above material identifier). The accounting unit of the system can automatically capture the corresponding consumption data in monthly cycles according to the process unit code and the material code, ensuring that the emission data is not lost and improving the calculation efficiency.

[0100] S33, the low calorific value of the related fossil fuel material is weighted and averaged by day batch, and then the weighted average processing is performed for the number of days to obtain the corresponding measured heat value. Finally, combined with the unit carbon content and the carbon oxidation rate, the measured carbon emission factor is obtained;

[0101] The data acquisition period includes multiple unit periods. For each unit period in the current period, each unit period has multiple batches of target steel material that will generate carbon emissions. The batch low heat of multiple batches of target steel material is obtained, and the batch low heat of multiple batches of target steel material is accumulated to obtain the period low heat of target steel material in the unit period.

[0102] Then the period low heat of target steel material in the unit period is accumulated to obtain the final low heat of target steel material in the current period;

[0103] The system pre-sets the unit heat value carbon content and carbon oxidation rate of the target steel material to the literature value obtained according to the literature record. After obtaining the pre-set unit heat value carbon content and carbon oxidation rate in the system, the product of the unit heat value carbon content and the carbon oxidation rate and the final low heat is calculated to obtain the carbon emission factor of the target steel material.

[0104] For example, the data acquisition period is one month, the unit period is one day, and various fossil fuels such as bituminous coal, anthracite, and coke are weighted and averaged according to the heat value detection coefficient (i.e., the low calorific value) at the time of daily vehicle batch storage, and then further weighted and averaged according to the heat value coefficient under the monthly number of days, and finally combined with the unit heat value carbon content and carbon oxidation rate to obtain the measured carbon emission factor. For example, the coal types of a certain steel enterprise are classified into imported injection coal, Yangquan anthracite, Lu'an anthracite, Shenhua bituminous coal, externally purchased first-grade coke, and externally purchased second-grade coke according to bituminous coal, anthracite, and coke. Corresponding to the monthly measured heat value coefficient of each coal type, the imported injection coal is taken as an example for introduction, and the calculation formula is as follows:

[0105]

[0106] Q 日，进口喷吹煤 is the low calorific value of imported injection coal in a unit period (for example, in days), and the unit is GJ / t;

[0107] is the sum of the low calorific value of imported injection coal in each daily batch, the unit is GJ / t, and n is the batch quantity;

[0108] Q 月，进口喷吹煤 is the low calorific value of imported injection coal in a data acquisition period (for example, in months), and the unit is GJ / t;

[0109] is the sum of the low calorific value of imported injection coal in each monthly day, the unit is GJ / t, and k is the number of days.

[0110] Similarly, the monthly measured heat value heat coefficients of Yangquan anthracite, Lu'an anthracite, Shenhua bituminous coal, externally purchased first-grade coke, and externally purchased second-grade coke can be obtained. Next, according to the unit heat value carbon content and carbon oxidation rate of the corresponding materials, the measured carbon emission factor can be obtained through the calculation formula, and the imported injection coal is taken as an example, as follows:

[0111] C 月，进口喷吹煤排放因子 = Q 月，进口喷吹煤 * H 单位热值含碳量 * R 燃烧碳氧化率 * CO2 / C;

[0112] C 月，进口喷吹煤排放因子 is the carbon emission factor of imported injection coal in a data acquisition period (for example, in monthly units), and the unit is tCO2 / t;

[0113] H 单位热值含碳量 is the unit heat value carbon content of imported injection coal, and the unit is tC / GJ;

[0114] R 燃烧碳氧化率 is the carbon oxidation rate of imported injection coal during combustion, and the unit is %.

[0115] In the present application, " / " represents division sign, and "*" represents multiplication sign.

[0116] Similarly, the monthly carbon emission factors of Yangquan anthracite, Lu'an anthracite, Shenhua bituminous coal, purchased first-grade coke and purchased second-grade coke can be obtained.

[0117] S34, the carbon emission data of the enterprise factory and process organization level is multiplied by the activity data to equal the carbon emission amount.

[0118] The product of the consumption data and the carbon emission factor is calculated to obtain the period carbon emission amount of the target steel material. Taking imported injection coal as an example, the calculation formula is as follows:

[0119] C 月，进口喷吹煤排放量 = AD 月，进口喷吹煤 * C 月，进口喷吹煤排放因子 ;

[0120] Wherein, C 月，进口喷吹煤排放量 is the carbon emission amount of imported injection coal in the data acquisition period (for example, monthly unit), and the unit is tCO2 / t, and "*" represents multiplication sign.

[0121] AD 月，进口喷吹煤 is the activity consumption data of imported injection coal in the data acquisition period (for example, monthly unit), and the unit is t.

[0122] The period carbon emission amounts of all target steel materials in the current period are accumulated to obtain the period carbon emission amount corresponding to the level identifier for the current period.

[0123] According to the above, the period carbon emission amount corresponding to the factory level or the process level can be obtained in turn.

[0124] In the present embodiment, the carbon emission factor of the target steel material is finally calculated based on the actual batch low calorific value of the target steel material in each unit period, so as to calculate the carbon emission amount, instead of using the default low calorific value of the steel material to calculate the carbon emission amount, replacing the background carbon emission factor used by most enterprises, improving the accuracy of carbon emission calculation, and making the accounting result closer to the real situation of enterprises and processes.

[0125] As described above, the present application can predict the entire statistical period carbon emission amount based on the period carbon emission amount of the current period. For example, the carbon emission amount of the factory level (or the process level) for the whole year can be predicted based on the period carbon emission amount of the factory level (or the process level) in January. The specific prediction method of the statistical period carbon emission amount is as follows:

[0126] In one of the embodiments, the statistical-period carbon emission amount is predicted based on the period carbon emission amount and the period actual production amount, including: obtaining the corresponding steel emission intensity based on the period carbon emission amount and the period actual production amount; and predicting the statistical-period carbon emission amount based on the statistical-period preset production amount, the period actual production amount, the steel emission intensity and the period carbon emission amount.

[0127] In the embodiment, the steel emission intensity is equal to the period carbon emission amount divided by the period actual production amount for the current period.

[0128] In one of the embodiments, the statistical-period carbon emission amount is predicted based on the statistical-period preset production amount, the period actual production amount, the steel emission intensity and the period carbon emission amount, including: calculating the difference between the statistical-period preset production amount and the period actual production amount; calculating the product of the steel emission intensity and the difference; and determining the sum of the product and the period carbon emission amount, and taking the determined sum as the predicted statistical-period carbon emission amount.

[0129] In the embodiment, the difference between the statistical-period preset production amount and the period actual production amount is calculated, and the difference is the production amount of the hierarchical product in the statistical period except the current period;

[0130] The product of the steel emission intensity and the difference is calculated, and the product is the predicted carbon emission amount of the hierarchical product in the other period, so as to determine the sum of the product and the period carbon emission amount, and the entire predicted statistical-period carbon emission amount can be obtained.

[0131] In one of the embodiments, after the carbon emission suggestion corresponding to the hierarchical identifier and for the current period is generated based on the comparison result, the method further includes:

[0132] After the data acquisition period arrives, the next period of the current period in the statistical period is determined, and for the next period, the consumption data of each target steel material corresponding to the process identifier and the material identifier is acquired; the period carbon emission amount corresponding to the hierarchical identifier is obtained based on the consumption data of each target steel material; the total period obtained by accumulating the current period and the next period is taken as the current period, the total period carbon emission amount obtained by accumulating the period carbon emission amount of the current period and the period carbon emission amount of the next period is taken as the period carbon emission amount of the current period, and the step of acquiring the statistical-period preset production amount of the hierarchical product corresponding to the hierarchical identifier and the period actual production amount in the current period, and the preset statistical-period quota amount of the carbon emission corresponding to the hierarchical identifier is returned and continued to be executed until the current period matches the statistical period.

[0133] After the data acquisition cycle is arrived, the next cycle of the current cycle within the statistical cycle is determined. For the next cycle, according to the same process identification and material identification as the current cycle, the corresponding consumption data of each target steel material is also obtained, and based on the consumption data of each target steel material, the cycle carbon emissions corresponding to the hierarchical identification are obtained. The specific implementation method of this embodiment is similar to the above-mentioned calculation of the cycle carbon emissions corresponding to the current cycle, and will not be repeated here.

[0134] The total cycle obtained by adding the current cycle and the next cycle is taken as the above-mentioned current cycle. For example, if the current cycle is January and the next cycle is February, then January to February are taken as the current cycle. The total cycle carbon emissions obtained by adding the cycle carbon emissions of the current cycle and the cycle carbon emissions of the next cycle are taken as the cycle carbon emissions of the above-mentioned current cycle. For example, the sum of the cycle carbon emissions calculated for January and the cycle carbon emissions calculated for February is taken as the cycle carbon emissions of the current cycle. Return to the loop and execute the following steps: obtain the statistical cycle preset output of the hierarchical product corresponding to the hierarchical identifier and the output of the current cycle. The actual output of the previous cycle, and the preset statistical period quota of carbon emissions corresponding to the level identification; based on the actual output of the period, the preset output of the statistical period, and the period carbon emissions, the carbon emissions of the statistical period are predicted; the carbon emissions of the statistical period and the preset statistical period quota are compared, and based on the comparison results, a carbon emission recommendation for the current cycle corresponding to the level identification is generated, and the cycle stops when the current cycle is equal to the statistical period. For example, if the statistical period is one year, the next cycle determined is the last month of the year, that is, December, and the current cycle is from January to December, and the current cycle is equal to the statistical period.

[0135] In this embodiment, as the accumulated data of actual periodic carbon emissions increases, the statistical periodic carbon emissions predicted for the enterprise factory level or the statistical periodic carbon emissions predicted for the process level can be continuously corrected, which can shorten the error between the predicted statistical periodic carbon emissions and the actual statistical periodic carbon emissions, thereby comparing the statistical periodic carbon emissions with the preset statistical period quota. After generating carbon emission recommendations for the current period corresponding to the level identifier based on the comparison results, more accurate recommendations can be provided for the enterprise to control carbon emissions.

[0136] Figure 4 A schematic diagram of a process for predicting carbon emissions at the factory level in an embodiment of the present application is shown, which includes at least S41 to S46, as detailed below:

[0137] S41: Set the company's annual crude steel production plan and annual plant-level carbon emission quota;

[0138] The statistical cycle preset production of the corresponding hierarchical product of the factory level is set, which can be the annual crude steel plan production AD 年,粗钢计划产量 ;

[0139] The preset statistical cycle quota amount of carbon emission of the corresponding hierarchical product of the factory level is set, which can be the annual factory level carbon emission quota;

[0140] The corresponding hierarchical product of the factory level refers to crude steel or steel material.

[0141] S42: The system multiplies the monthly activity data of each type of material in the actual factory level of the enterprise in January of the year by the carbon emission factor to equal the carbon emission amount, and divides the January factory level emission amount by the actual crude steel production in January to equal the crude steel emission intensity in January.

[0142] In this embodiment, the monthly activity data of the material is the consumption data of the steel material described above.

[0143] After obtaining the carbon emission amount of the corresponding factory level of the enterprise in the current cycle, taking January of the enterprise as an example, the crude steel carbon emission intensity in January is calculated according to the actual crude steel production in January of the enterprise, and the formula is as follows:

[0144] CI 1月,工厂级粗钢排放强度 =C 1月,工厂级碳排放量 ÷AD 1月,粗钢实际产量 ;

[0145] CI 1月,工厂级粗钢排放强度 is the crude steel emission intensity of the enterprise in January of the factory level, with the unit of tCO2 / t; C 1月,工厂级碳排放量 is the actual carbon emission amount of the enterprise in January of the factory level, with the unit of tCO2; AD 1月,粗钢实际产量 is the cycle actual production of crude steel of the enterprise in January, with the unit of t. Similarly, the carbon emission amount of the hierarchical product of the enterprise in each month and the crude steel emission intensity of the factory level can be obtained;

[0146] Step S43: According to the annual crude steel plan production of the enterprise minus the actual crude steel production in January, equal to the crude steel calculation production of the enterprise from the second month to January, multiplied by the actual crude steel emission intensity of the enterprise in January, plus the actual emission amount in January, equal to the annual factory level predicted emission amount of the enterprise.

[0147] The calculation formula is as follows:

[0148] C 企业工厂级碳排放预测量 =(AD 年,粗钢计划产量 -AD 1月,粗钢实际产量 )*CI 1月,工厂级粗钢排放强度 +C 1月,工厂级碳排放量 ;

[0149] C 企业工厂级碳排放预测量The predicted statistical period carbon emission of the factory level is tCO2.

[0150] S44: Compare the annual process level predicted emission of the enterprise with the quota amount. If the annual process level predicted emission exceeds the quota amount, suggest the enterprise to purchase carbon quota. If the annual process level predicted emission is within the quota amount, it indicates that the internal control of the enterprise is good.

[0151] In the embodiment, the level to be predicted is the factory level. The system compares the statistical period carbon emission with the preset statistical period quota amount. If the statistical period carbon emission is greater than or equal to the preset statistical period quota amount, it indicates that the carbon emission of the enterprise in the entire statistical period will exceed the preset statistical period quota amount under the current period emission level. It is suggested that the enterprise should develop a carbon quota trading scheme and strengthen the internal control of the process carbon emission of the enterprise. If the statistical period carbon emission is less than the preset statistical period quota amount, it indicates that the carbon emission of the enterprise in the entire statistical period will be less than the preset statistical period quota amount under the current period emission level. It is suggested that the enterprise should maintain the current emission status and sell the saved carbon emission quota to obtain profit.

[0152] S45: Determine whether the current period is equal to the statistical period.

[0153] At this time, the current period is January and the statistical period is a whole year.

[0154] If yes, end the loop. If no, execute step S46.

[0155] S46: Take January and February as the current period, and take the total period carbon emission obtained by adding the period carbon emission of January and the period carbon emission of February as the period carbon emission of the current period. Return to execute S42 to S46 until the current period is equal to the statistical period.

[0156] After the enterprise produces crude steel in February, the annual crude steel production plan minus the actual crude steel production in January and February is equal to the crude steel production plan of the enterprise in March to December. Multiply the weighted crude steel emission intensity of the enterprise in January and February by the actual emission in January and February, which is equal to the annual factory level predicted emission of the enterprise. Then continuously roll and correct.

[0157] C 企业工厂级碳排放预测量 = (AD 年,粗钢计划产量 - AD (1至2)月,粗钢实际产量 ) * CI (1至2)月,工厂级粗钢排放强度 + C (1至2)月,工厂级碳排放量

[0158] , AD (1至2)月,粗钢实际产量The actual cumulative crude steel output of the enterprise in January and February is the sum of the actual crude steel output in January and the actual crude steel output in February, and the unit is t;

[0159] CI (1至2)月,工厂级粗钢排放强度 The cumulative crude steel emission intensity of the enterprise in January and February is tCO2 / t.

[0160] CI (1至2)月,工厂级粗钢排放强度 = C (1至2)月,工厂级碳排放量 / AD (1至2)月,粗钢实际产量 The " / " is a division sign.

[0161] C (1至2)月,工厂级碳排放量 The cumulative carbon emission of the enterprise in January and February is tCO2.

[0162] By repeatedly executing the above steps, the statistical period carbon emission C 企业工厂级碳排放预测量 predicted by the enterprise factory level is continuously corrected.

[0163] In this embodiment, for the factory level, the present application can predict the statistical period carbon emission of the whole year based on the period carbon emission of the current period, and can predict the carbon emission for the factory level, so as to compare the predicted statistical period carbon emission with the preset statistical period quota, generate a carbon emission suggestion for the whole factory in the current period corresponding to the level identifier based on the comparison result, thereby providing a useful suggestion for the control of carbon emission in the steel production process of the enterprise, and realizing the management and control of the carbon emission of the enterprise.

[0164] Figure 5 The flowchart for predicting the carbon emission of the process level in the embodiment of the present application is shown, which at least includes S51 to S56, and is described in detail as follows:

[0165] In one of the embodiments, when the level to be predicted is the process level, the period carbon emission corresponding to the level identifier is the period carbon emission corresponding to the process level identifier; obtaining the preset statistical period quota of carbon emission corresponding to the level identifier includes: determining the period carbon emission corresponding to the factory level identifier for the current period, and determining the preset statistical period quota of carbon emission corresponding to the factory level identifier; determining the proportion of the period carbon emission corresponding to the process level identifier in the period carbon emission corresponding to the factory level identifier; obtaining the preset statistical period quota of carbon emission corresponding to the process level identifier based on the proportion and the preset statistical period quota of carbon emission corresponding to the factory level identifier; and taking the preset statistical period quota of carbon emission corresponding to the process level identifier as the preset statistical period quota of carbon emission corresponding to the level identifier.

[0166] In the embodiment, the determination of the period carbon emission corresponding to the factory level identifier can refer to the description in the above embodiment, that is, after the data acquisition period arrives, for the current period, the consumption data of each target steel material corresponding to the process identifier and the material identifier is acquired; and based on the consumption data of each target steel material, the period carbon emission corresponding to the factory level identifier is obtained.

[0167] The preset statistical period quota of carbon emission corresponding to the factory level identifier is preset by the system;

[0168] After the proportion of the period carbon emission corresponding to the process level identifier in the period carbon emission corresponding to the factory level identifier is obtained, the preset statistical period quota of carbon emission corresponding to the process level identifier can be obtained by multiplying the preset statistical period quota of carbon emission corresponding to the factory level identifier by the proportion.

[0169] It can be seen that, based on the proportion of the period carbon emission corresponding to the process level identifier in the period carbon emission corresponding to the factory level identifier and the preset statistical period quota of carbon emission corresponding to the factory level identifier, the preset statistical period quota of carbon emission corresponding to the process level identifier is calculated, so that the control of the carbon emission of the process level is finally generated based on the preset statistical period quota of carbon emission corresponding to the process level identifier, and the available suggestions can be provided, and the carbon emission of the enterprise can be controlled.

[0170] Specifically, the method comprises the steps of:

[0171] S51, setting the annual product planned yield of each process of the enterprise, and setting the carbon emission quota corresponding to each process according to the carbon emission of each process in January of the enterprise divided by the factory level emission, that is, the emission proportion coefficient of each process in January;

[0172] Setting the annual product planned yield of each process of the enterprise comprises: setting the statistical period preset yield of the product corresponding to each process identifier, which can be the annual planned yield, for example, the product coke AD of the coking process 年,焦炭计划产量 , the product sinter AD of the sintering process 年,烧结矿计划产量 , the product pellet AD of the pelletizing process 年,球团矿计划产量 , the product hot metal AD of the blast furnace process 年,铁水计划产量 , the product crude steel AD of the steelmaking process 年,粗钢计划产量 , the product steel coil AD of the steel processing process 年,钢卷计划产量 , the product electricity AD of the power generation process 年,发电计划产量 , the product lime AD of the lime process 年,石灰计划产量 .

[0173] When the enterprise's January data occurs, the proportion of each process in the factory's carbon emissions in the month is calculated after calculating the carbon emissions of each process level (such as coking, sintering, pelletizing, blast furnace, steelmaking, steel processing, power generation, lime and other processes) and the carbon emissions of the factory level.

[0174] The proportion coefficient is combined with the annual carbon quota of the enterprise at the factory level (i.e. the above-mentioned preset statistical period quota), and the preset statistical period quota of each process for carbon emissions in the month is obtained, so as to perform internal management and control. The proportion coefficient of each process in the month (i.e. the emission proportion in the table below) and the carbon quota allocation index (i.e. the carbon quota in the table below) can be seen in Table 1.

[0175] Table 1: Proportion coefficient and quota index of carbon emissions of each process of the enterprise in January

[0176]

[0177] In Table 1, because there is output of converter gas in steelmaking and the emission is higher than the carbon emission of the input of carbon-containing substances in this process, so the deduction is negative, but it does not affect the execution of the carbon quota index of this process.

[0178] S52, the carbon emissions of each process level of the enterprise in January divided by the actual output of each process product in January is equal to the emission intensity of the process product of each process in January;

[0179] Taking the sintering process in January as an example, according to the actual sinter output generated by the sintering process in January, the carbon emission intensity of the sinter in January is calculated, and the formula is as follows:

[0180] CI 1月,烧结矿排放强度 =C 1月,烧结工序碳排放量 / AD 1月,烧结矿实际产量 ;

[0181] CI 1月,烧结矿排放强度 is the emission intensity of the sinter in January, with the unit of tCO2 / t; C 1月,烧结工序碳排放量 is the actual carbon emission of the sintering process in January, with the unit of tCO2; AD 1月,烧结矿实际产量 is the actual output of the sinter in January, with the unit of t. Similarly, the carbon emissions of each process of the enterprise in January and the emission intensity of the product under the corresponding process can be obtained;

[0182] S53, the actual output of each process product in January is subtracted from the annual planned output of each process, which is equal to the planned output of the product of each process (2 to 12) months, and then multiplied by the emission intensity of the corresponding product of each process in January, and then added to the actual emission of each process in January, which is equal to the annual emission prediction of each process.

[0183] The calculation formula is as follows:

[0184] C 烧结工序碳排放预测量 = (AD 年,烧结矿计划产量 - AD 1月,烧结矿实际产量 ) * CI 1月,烧结矿排放强度 + C 1月,烧结工序碳排放量 ;

[0185] C 烧结工序碳排放预测量 is the sintering process carbon emission prediction quantity, unit: tCO2;

[0186] S54, compare the process annual emission prediction quantity with the process quota quantity, if it exceeds the quota quantity, perform evaluation: if it is within the quota range, perform reward.

[0187] The system compares the statistical period carbon emission quantity and the preset statistical period quota quantity, if the statistical period carbon emission quantity is greater than or equal to the preset statistical period quota quantity, it means that under the current period emission level condition, the carbon emission quantity of the process in the entire statistical period will exceed the preset statistical period quota quantity, then one is to strengthen the internal control of the process, analyze the reasons for exceeding the standard, and two is to implement evaluation according to the exceeding amount; if the statistical period carbon emission quantity is less than the preset statistical period quota quantity, it means that under the current period emission level condition, the carbon emission quantity of the process in the entire statistical period will be less than the preset statistical period quota quantity, it is recommended that the process one is to maintain the current emission status, and two is to reward the saved carbon quota quantity according to the corresponding cost price.

[0188] S55, judge whether the current period is equal to the statistical period;

[0189] At this time, the current period is January, and the statistical period is a whole year;

[0190] If yes, end the loop, if no, execute step S56;

[0191] S56, take January and February as the current period, and take the total period carbon emission quantity obtained by accumulating the period carbon emission quantity of January and the period carbon emission quantity of February as the period carbon emission quantity of the current period, return to loop and execute S52 to S56 until the current period is equal to the statistical period.

[0192] After obtaining the consumption data of the steel material of enterprise 2, the product planned production quantity of each process from March to December is equal to the actual production quantity of each process product from January to February, multiplied by the corresponding product emission intensity of each process from January to February, and then added to the actual emission quantity of each process from January to February, which is equal to the annual emission prediction quantity of each process; the calculation formula is as follows:

[0193] C 烧结工序碳排放预测量 = (AD 年,烧结矿计划产量 - AD (1至2)月,烧结矿实际产量CI (1至2)月,烧结矿排放强度 +C (1至2)月,烧结工序碳排放量

[0194] AD (1至2)月,烧结矿实际产量 is the cumulative output of sintered ore of sintering process 1-2 in February, in t;

[0195] CI (1至2)月,烧结矿排放强度 is the cumulative sintered ore emission intensity of sintering process 1-2 in February, in tCO2 / t;

[0196] CI (1至2)月,烧结矿排放强度 =C (1至2)月,烧结工序碳排放量 / AD (1至2)月,烧结矿实际产量 AD (1至2)月,粗钢实际产量 ;“ / ”

[0197] is a division sign;

[0198] C (1至2)月,烧结工序碳排放量 is the cumulative carbon emission of sintering process 1-2 in February, in tCO2

[0199] In the above manner, i.e. continuously rolling, the carbon emission prediction of coking, pelletizing, blast furnace, steelmaking, steel processing, power generation and other processes is obtained. The above steps are repeated, and the carbon emission of 1-2 months and the periodic quota of 1-2 months are compared.

[0200] For the process level, the present application can predict the statistical periodic carbon emission of the whole year based on the periodic carbon emission of the current period, and can predict the carbon emission for the process level, so as to compare the predicted statistical periodic carbon emission with the preset statistical periodic quota, generate the carbon emission suggestion corresponding to the level identifier for the process in the current period based on the comparison result, thereby providing a useful suggestion for the control of carbon emission in the steel production process of the enterprise, and realizing the management and control of the carbon emission of the enterprise.

[0201] Based on the same application concept, the embodiment of the present application also provides a carbon emission suggestion generation device, Figure 6 is a structural block diagram of a carbon emission suggestion generation device provided by the embodiment of the present application, as Figure 6 shown, the device 600 comprises:

[0202] A first acquisition module 601 is configured to acquire the level identifier of a to-be-predicted level, determine the corresponding process identifier and material identifier according to the level identifier; wherein the to-be-predicted level comprises any one of the factory level and the process level under the factory level.

[0203] A second acquisition module 602 is configured to, after the data acquisition period arrives, acquire the consumption data of each target steel material according to the process identifier and the material identifier for the current period;

[0204] The first determining module 603 is configured to obtain, based on consumption data of each target steel material, a period carbon emission corresponding to the level identifier;

[0205] The third obtaining module 604 is configured to obtain a statistical period preset yield of a level product corresponding to the level identifier, a period actual yield in the current period, and a preset statistical period quota of carbon emission corresponding to the level identifier; the statistical period includes a plurality of data obtaining periods;

[0206] The second determining module 605 is configured to predict, based on the period actual yield, the statistical period preset yield, and the period carbon emission, a statistical period carbon emission.

[0207] The comparison module 606 is configured to compare the statistical period carbon emission and the preset statistical period quota, and generate, based on a comparison result, a carbon emission suggestion corresponding to the level identifier for the current period.

[0208] In one of the embodiments, the first determining module 603 is specifically configured to: for each target steel material, determine a carbon emission factor of the target steel material; obtain, based on the consumption data and the carbon emission factor, a period carbon emission of the target steel material; and determine, based on the period carbon emission of each target steel material, a period carbon emission corresponding to the level identifier.

[0209] In one of the embodiments, the first determining module 603 includes a plurality of unit periods in the data obtaining period, and when determining the carbon emission factor of the target steel material, the first determining module 603 is specifically configured to:

[0210] For each unit period in the current period, obtain a batch low calorific value of a plurality of batches of the target steel material in each unit period, and obtain, based on the batch low calorific value, a period low calorific value of the target steel material in the unit period;

[0211] Obtain, based on the period low calorific value corresponding to each unit period, a final low calorific value of the target steel material in the current period;

[0212] Obtain a preset unit heat value carbon content and carbon oxidation rate of the target steel material, and calculate, based on the final low calorific value, the unit heat value carbon content, and the carbon oxidation rate, the carbon emission factor of the target steel material.

[0213] In one of the embodiments, the second determining module 605 is specifically configured to:

[0214] Obtain, based on the period carbon emission and the period actual yield, a corresponding steel emission intensity;

[0215] Based on the annual statistical cycle preset yield, the cycle actual yield, the steel emission intensity and the cycle carbon emission, the annual statistical cycle carbon emission is predicted.

[0216] In one of the embodiments, the second determining module 605, when predicting the annual statistical cycle carbon emission based on the annual statistical cycle preset yield, the cycle actual yield, the steel emission intensity and the cycle carbon emission, is specifically configured to:

[0217] Calculate the difference between the annual statistical cycle preset yield and the cycle actual yield;

[0218] Calculate the product of the steel emission intensity and the difference;

[0219] Determine the sum of the product and the cycle carbon emission, and take the determined sum as the predicted annual statistical cycle carbon emission.

[0220] In one of the embodiments, when the level to be predicted is the process level, the cycle carbon emission corresponding to the level identifier is the cycle carbon emission corresponding to the process level identifier.

[0221] The third obtaining module 604, when obtaining the preset annual statistical cycle quota of carbon emission corresponding to the level identifier, is specifically configured to:

[0222] Determine the cycle carbon emission corresponding to the factory level identifier for the current cycle, and determine the preset annual statistical cycle quota of carbon emission corresponding to the factory level identifier;

[0223] Determine the proportion of the cycle carbon emission corresponding to the process level identifier in the cycle carbon emission corresponding to the factory level identifier;

[0224] Based on the proportion and the preset annual statistical cycle quota of carbon emission corresponding to the factory level identifier, obtain the preset annual statistical cycle quota of carbon emission corresponding to the process level identifier;

[0225] Take the preset annual statistical cycle quota of carbon emission corresponding to the process level identifier as the preset annual statistical cycle quota of carbon emission corresponding to the level identifier.

[0226] In one of the embodiments, the device further comprises a cycle module configured to, after the comparison module 606 generates the carbon emission suggestion corresponding to the level identifier for the current cycle based on the comparison result, determine a next cycle of the current cycle in the annual statistical cycle after the data acquisition cycle arrives, and acquire the consumption data of each target steel material corresponding to the process identifier and the material identifier for the next cycle; and obtain the cycle carbon emission corresponding to the level identifier based on the consumption data of each target steel material.

[0227] The total cycle obtained by accumulating the current cycle and the next cycle is taken as the current cycle, the total cycle carbon emission obtained by accumulating the cycle carbon emission of the current cycle and the cycle carbon emission of the next cycle is taken as the cycle carbon emission of the current cycle, and the step of acquiring the annual statistical cycle yield of the level product corresponding to the level identifier and the actual yield of the current cycle, and the preset annual statistical cycle quota of carbon emission corresponding to the level identifier is returned and executed until the current cycle matches the statistical cycle.

[0228] It can be understood that the device provided in the above embodiments is only used as an example for the division of the above functional modules, and in actual applications, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the above described functions.

[0229] The embodiment of the present application also provides an electronic device, which refers to Figure 7 The electronic device can include a processor and a memory, wherein the processor and the memory can be connected to each other through a bus or other means.

[0230] The processor can be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application, or can also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. chips, or a combination of the above chips.

[0231] The processor includes an enterprise factory and process level carbon emission data accounting system and an enterprise factory and process level carbon emission data prediction system. The factory and process level carbon emission data accounting system can perform the above-mentioned Figure 3 The enterprise factory and process level carbon emission data prediction system can perform the above-mentioned Figure 4 and Figure 5 embodiment steps shown in any one of the above-mentioned embodiments.

[0232] The memory can include a mass storage that stores data or instructions. By way of example and not limitation, the memory can include a Hard Disk Drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a Universal Serial Bus (USB) drive or a combination of two or more of these. Where appropriate, the memory can include removable or non-removable (or fixed) media. Where appropriate, the memory can be internal or external to the electronic device. In certain embodiments, the memory can be a non-volatile solid-state memory.

[0233] In one example, the memory can be a Read Only Memory (ROM). In one example, the ROM can be a mask programmed ROM, a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), an Electrically Alterable ROM (EAROM), or a flash memory, or a combination of two or more of these.

[0234] The processor implements any one of the above-mentioned carbon emission suggestion generation methods by reading and executing computer program instructions stored in the memory.

[0235] In one example, the electronic device can further include a communication interface and a bus. The processor, the memory, and the communication interface are connected through the bus and complete communication with each other. The communication interface is mainly used to realize the communication between the modules, devices, units, and / or equipment in the embodiments of the present application. Where appropriate, the bus can include one or more buses.

[0236] In addition, in combination with the carbon emission suggestion generation method in the above-mentioned embodiments, the embodiments of the present application can provide a computer readable storage medium to realize. The computer readable storage medium has computer program instructions stored thereon; the computer program instructions are executed by the processor to realize any one of the carbon emission suggestion generation methods in the above-mentioned embodiments.

[0237] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD), or a solid-state drive (SSD). The storage medium can also include a combination of the above-mentioned types of memory.

[0238] In the description provided herein, numerous specific details are described. However, it is understood that embodiments of the present invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques are not shown in detail so as not to obscure the understanding of this description.

[0239] Similarly, it should be understood that in order to streamline the present disclosure and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this disclosed method should not be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the claims below, inventive aspects lie in less than all the features of the individual embodiments disclosed above. Accordingly, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of the invention.

[0240] It should be noted that the above embodiments illustrate rather than limit the invention, and that a person skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between brackets should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The present invention may be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names.

Claims

1. A method for generating carbon emission recommendations, characterized in that: The method comprises: Obtaining a level identifier of a level to be predicted, and determining a corresponding process identifier and a material identifier according to the level identifier; wherein the level to be predicted includes a factory level and any one of the process levels under the factory level; After the data acquisition cycle arrives, for the current cycle, the consumption data of each target steel material corresponding to the process identifier and the material identifier is acquired; Based on the consumption data of each target steel material, the periodic carbon emissions corresponding to the level identification are obtained; Obtaining the preset statistical period output of the level product corresponding to the level identifier and the actual period output in the current period, as well as the preset statistical period quota of carbon emissions corresponding to the level identifier; the statistical period includes multiple data acquisition periods; Based on the actual output of the period, the preset output of the statistical period, and the carbon emissions of the period, the carbon emissions of the statistical period are predicted; The carbon emissions of the statistical period are compared with the quota of the preset statistical period, and a carbon emissions recommendation for the current period corresponding to the level identifier is generated based on the comparison result.

2. The method according to claim 1, characterized in that The periodic carbon emissions corresponding to the level identifier are obtained based on the consumption data of each target steel material, including: For each target steel material, determining the carbon emission factor of the target steel material; Based on the consumption data and the carbon emission factor, obtaining the periodic carbon emissions of the target steel material; Based on the periodic carbon emissions of each target steel material, the periodic carbon emissions corresponding to the hierarchical identifier are determined.

3. The method according to claim 2, characterized in that The data acquisition cycle includes multiple unit cycles, and the determining of the carbon emission factor of the target steel material includes: For each unit cycle in the current cycle, obtaining the batch low calorific value of multiple batches of the target steel material in each unit cycle, and obtaining the cycle low calorific value of the target steel material in the unit cycle based on the batch low calorific value; Based on the periodic low calorific value corresponding to each unit cycle, a final low calorific value of the target steel material in the current cycle is obtained; The preset carbon content per unit calorific value and carbon oxidation rate of the target steel material are obtained, and the carbon emission factor of the target steel material is calculated based on the final lower calorific value, the carbon content per unit calorific value and the carbon oxidation rate.

4. The method according to any one of claims 1 to 3, characterized in that The method of predicting the carbon emissions for a statistical period based on the actual output for the period, the preset output for the statistical period, and the carbon emissions for the period includes: Based on the carbon emissions of the period and the actual output of the period, a corresponding steel emission intensity is obtained; Based on the preset output of the statistical period, the actual output of the period, the steel emission intensity and the carbon emissions of the period, the carbon emissions of the statistical period are predicted.

5. The method according to claim 4, characterized in that The carbon emissions for the statistical period are predicted based on the preset output for the statistical period, the actual output for the period, the steel emission intensity, and the carbon emissions for the period, including: Calculating the difference between the preset output of the statistical period and the actual output of the period; Calculating the product of the steel emission intensity and the difference; The sum of the product and the periodic carbon emissions is determined, and the determined sum is used as the predicted statistical periodic carbon emissions.

6. The method according to any one of claims 1 to 3, characterized in that In the case where the level to be predicted is the process level, the periodic carbon emissions corresponding to the level identifier are the periodic carbon emissions corresponding to the process level identifier; Obtaining the preset statistical period quota of carbon emissions corresponding to the level identifier, including: Determine the periodic carbon emissions corresponding to the factory level identification for the current period, and determine the preset statistical period quota for carbon emissions corresponding to the factory level identification; Determine the ratio of the cycle carbon emissions corresponding to the process level identifier to the cycle carbon emissions corresponding to the plant level identifier; Based on the ratio and the preset statistical period quota corresponding to the factory level identifier, obtaining the preset statistical period quota of carbon emissions corresponding to the process level identifier; The preset statistical period quota amount of carbon emissions corresponding to the process level identifier is used as the preset statistical period quota amount of carbon emissions corresponding to the level identifier.

7. The method according to any one of claims 1 to 3, characterized in that After generating the carbon emission recommendation for the current period corresponding to the level identifier based on the comparison result, the method further includes: After the data acquisition period arrives, the next period of the current period within the statistical period is determined, and for the next period, the consumption data of each target steel material corresponding to the process identifier and the material identifier is obtained; based on the consumption data of each target steel material, the carbon emissions of the period corresponding to the hierarchical identifier are obtained; The total cycle obtained by accumulating the current cycle and the next cycle is taken as the current cycle, and the total cycle carbon emissions obtained by accumulating the cycle carbon emissions of the current cycle and the cycle carbon emissions of the next cycle is taken as the cycle carbon emissions of the current cycle. Return to the step of obtaining the statistical period preset output of the level product corresponding to the level identifier and the actual cycle output in the current period, as well as the preset statistical period quota of carbon emissions corresponding to the level identifier, and continue to execute until the current cycle matches the statistical period.

8. A carbon emission suggestion generating device, characterized in that: The device comprises: A first acquisition module is configured to acquire a level identifier of a level to be predicted, and determine a corresponding process identifier and a material identifier according to the level identifier; wherein the level to be predicted includes a factory level and any one of the process levels under the factory level; The second acquisition module is configured to acquire the consumption data of each target steel material according to the process identifier and the material identifier for the current cycle after the data acquisition cycle is reached; A first determination module is configured to obtain a periodic carbon emission amount corresponding to the hierarchical identifier based on the consumption data of each target steel material; The third acquisition module is used to obtain the preset statistical period output of the level product corresponding to the level identifier and the actual period output in the current period, as well as the preset statistical period quota of carbon emissions corresponding to the level identifier; the statistical period includes multiple data acquisition periods; A second determination module is configured to predict the carbon emissions for the statistical period based on the actual output for the period, the preset output for the statistical period, and the carbon emissions for the period; The comparison module is used to compare the carbon emissions of the statistical period with the quota of the preset statistical period, and generate a carbon emission recommendation for the current period corresponding to the level identifier based on the comparison result.

9. An electronic device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method according to any one of claims 1 to 7.

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