Enterprise carbon performance evaluation method and device based on subdivision scene

Abstract

The invention provides an enterprise carbon performance evaluation method and device based on a subdivision scene, and the method comprises the steps: carrying out the multi-dimensional clustering of enterprises according to the attribute data of each enterprise, and generating different scales of enterprise type databases under each subdivision scene; generating a monthly carbon performance reference value corresponding to each enterprise type according to the enterprise carbon emission data of the same scale in each subdivision scene in the enterprise type database; according to the enterprise carbon emission data of the to-be-evaluated target enterprise, generating a weekly carbon emission average change rate of the target enterprise in the current quarter; and generating a monthly carbon performance evaluation result of the target enterprise according to the average change rate of the weekly carbon emission and the monthly carbon performance reference value through the corresponding relation of the weekly carbon emission grade coefficients corresponding to the enterprises in each subdivision scene, and performing classified management on the carbon data of the enterprises based on various enterprise types, enterprise scales and the subdivision scenes. Practicality and functionality are improved, and enterprise carbon performance is accurately evaluated.

Description

Technical Field

[0001] The present invention relates to the field of carbon energy technology, and in particular to a method and device for evaluating enterprise carbon performance based on segmented scenarios. Background Art

[0002] Carbon performance rating is a process of comprehensive evaluation and grading of a company's carbon emission performance over a certain period of time, such as monthly, quarterly, or annually. This rating is usually based on the company's actual performance in carbon emission reduction, energy efficiency improvement, and low-carbon technology innovation, to promote its improvement of carbon management level and the realization of sustainable development goals. In related technologies, a company's carbon emission reduction, carbon change rate over the same period, and carbon emissions are usually analyzed from a macro perspective, that is, the company's carbon emission reduction performance is analyzed based on a macro score threshold. However, different types of companies have different corporate scenarios, and it is impossible to accurately evaluate the company's carbon performance, resulting in problems of low practicality and functionality. Summary of the invention

[0003] One object of the present invention is to provide a method for evaluating enterprise carbon performance based on segmented scenarios, which can classify and manage the carbon data of enterprises based on various enterprise types, enterprise scales and segmented scenarios, comprehensively consider the carbon emission reduction performance of enterprises in different scenarios, improve practicality and functionality, and accurately evaluate the carbon performance of enterprises. Another object of the present invention is to provide an enterprise carbon performance evaluation device based on segmented scenarios. Another object of the present invention is to provide a computer-readable medium. Another object of the present invention is to provide a computer device.

[0004] In order to achieve the above objectives, the present invention discloses, on the one hand, a method for evaluating corporate carbon performance based on segmented scenarios, comprising:

[0005] Obtain attribute data of each enterprise within the jurisdiction;

[0006] Perform multi-dimensional clustering of enterprises based on attribute data to generate enterprise type databases in different scales and in different sub-scenarios;

[0007] Generate the monthly carbon performance benchmark value corresponding to each enterprise type based on the carbon emission data of enterprises of the same scale in each subdivided scenario in the enterprise type database;

[0008] Based on the corporate carbon emission data of the target enterprise to be assessed, generate the average change rate of the target enterprise's weekly carbon emissions in the current quarter;

[0009] By pre-generating the corresponding weekly carbon emission level coefficients of enterprises in each segmented scenario, the monthly carbon performance evaluation results of the target enterprise are generated according to the average change rate of the target enterprise's weekly carbon emissions within the quarter and the corresponding monthly carbon performance benchmark value.

[0010] Preferably, the attribute data includes business type, number of employees in the enterprise and floor space;

[0011] Based on the attribute data, enterprises are clustered in multiple dimensions to generate enterprise type databases in different scales and different subdivision scenarios, including:

[0012] Cluster each enterprise according to its business type and generate enterprise type clustering results;

[0013] According to the enterprise type clustering results, the scale is divided according to the number of employees and the area occupied by the enterprise, and the enterprise scale clustering results corresponding to each enterprise type are generated;

[0014] According to the enterprise scale clustering results corresponding to each enterprise type, each enterprise is divided into scenarios, and an enterprise type database under each segmented scenario of different scales is constructed. The dimensions of the enterprise type database include multiple enterprise scales, and each enterprise scale includes at least one segmented scenario.

[0015] Preferably, the monthly carbon performance benchmark value corresponding to each enterprise type is generated based on the carbon emission data of enterprises in each subdivided scenario of the same scale in the enterprise type database, including:

[0016] Based on the carbon emission data of enterprises of the same scale in each subdivided scenario in the enterprise type database, generate the corresponding carbon emission reduction, carbon emission change rate in the same period and current monthly carbon emission of enterprises in each subdivided scenario;

[0017] Based on the carbon emission reduction, the change rate of carbon emissions during the same period and the current monthly carbon emissions, the monthly carbon performance benchmark value corresponding to each enterprise type is generated.

[0018] Preferably, the enterprise types include service-oriented enterprises / trade and finance-oriented enterprises, and the subdivided scenarios include office space energy consumption;

[0019] Based on the carbon emission data of enterprises of the same scale in each subdivided scenario in the enterprise type database, the corresponding carbon emission reduction, carbon emission change rate in the same period and current monthly carbon emission of enterprises in each subdivided scenario are generated, including:

[0020] Extract the current month's carbon emissions and historical carbon emissions data for the same period of the current month;

[0021] Based on the current monthly carbon emissions and the historical carbon emissions data for the same period as the current month, the carbon emissions change rate and carbon emission reduction for the same period are generated.

[0022] Preferably, the enterprise type includes a production enterprise database, and the subdivided scenarios include a production process scenario, an energy use scenario, and a raw material procurement scenario;

[0023] Based on the carbon emission data of enterprises of the same scale in each subdivided scenario in the enterprise type database, the corresponding carbon emission reduction, carbon emission change rate in the same period and current monthly carbon emission of enterprises in each subdivided scenario are generated, including:

[0024] According to the production process scenario, energy use scenario, and raw material procurement scenario, the current month's carbon emissions and the historical carbon emissions data for the same period of the current month are extracted respectively;

[0025] Based on the current monthly carbon emissions corresponding to the production process scenario and the historical carbon emissions data for the same period of the current month, generate the carbon emissions change rate and carbon emission reduction corresponding to the enterprise in the production process scenario;

[0026] Based on the current monthly carbon emissions corresponding to the energy usage scenario and the historical carbon emissions data for the same period of the current month, generate the carbon emissions change rate and carbon emission reduction corresponding to the enterprise in the energy usage scenario;

[0027] Based on the current monthly carbon emissions corresponding to the raw material procurement scenario and the historical carbon emissions data for the same period of the current month, the carbon emissions change rate and carbon emission reduction corresponding to the enterprise in the raw material procurement scenario are generated.

[0028] Preferably, the enterprise types include service-oriented enterprises / trade and finance-oriented enterprises, and the subdivided scenarios include office space energy consumption;

[0029] Based on the carbon emission reduction, the change rate of carbon emissions in the same period and the current monthly carbon emissions, the monthly carbon performance benchmark values ​​corresponding to each enterprise type are generated, including:

[0030] Through the pre-generated carbon emission reduction grade score correspondence relationship, the carbon emission change rate grade score correspondence relationship over the same period and the current monthly carbon emission grade score correspondence relationship, according to the carbon emission reduction, the carbon emission change rate over the same period and the current monthly carbon emission, the carbon emission reduction score, the carbon emission change rate score over the same period and the current monthly carbon emission score are generated. The carbon emission reduction grade score correspondence relationship, the carbon emission change rate grade score correspondence relationship over the same period and the current monthly carbon emission grade score correspondence relationship are obtained by sorting and grading the carbon emission reduction, the carbon emission change rate over the same period and the current monthly carbon emission respectively;

[0031] Through the preset first weight ratio, the monthly carbon performance benchmark value corresponding to the service-oriented enterprise / trade and finance enterprise is generated according to the carbon emission reduction score, the carbon emission change rate score during the same period and the current monthly carbon emission score.

[0032] Preferably, the enterprise type includes a production enterprise database, and the subdivided scenarios include a production process scenario, an energy use scenario, and a raw material procurement scenario;

[0033] Based on the carbon emission reduction, the change rate of carbon emissions in the same period and the current monthly carbon emissions, the monthly carbon performance benchmark values ​​corresponding to each enterprise type are generated, including:

[0034] Through the pre-generated correspondence between the carbon emission reduction grade score corresponding to the production process scenario, the carbon emission change rate grade score corresponding to the same period, and the current monthly carbon emission grade score corresponding to the current monthly carbon emission, the carbon emission reduction score, the carbon emission change rate score in the same period, and the current monthly carbon emission score corresponding to the enterprise under the production process scenario are generated according to the carbon emission reduction, the carbon emission change rate in the same period, and the current monthly carbon emission;

[0035] Through the pre-generated correspondence between the carbon emission reduction grade scores corresponding to the energy usage scenarios, the carbon emission change rate grade scores corresponding to the same period, and the current monthly carbon emission grade scores corresponding to the carbon emission reduction, the carbon emission change rate during the same period, and the current monthly carbon emissions, the carbon emission reduction score, the carbon emission change rate score during the same period, and the current monthly carbon emission score corresponding to the enterprise under the energy usage scenario are generated according to the carbon emission reduction, the carbon emission change rate during the same period, and the current monthly carbon emissions;

[0036] Through the pre-generated correspondence between the carbon emission reduction grade score corresponding to the raw material procurement scenario, the carbon emission change rate grade score corresponding to the same period, and the current monthly carbon emission grade score corresponding to the carbon emission reduction, the carbon emission change rate in the same period, and the current monthly carbon emission, the carbon emission reduction score, the carbon emission change rate score in the same period, and the current monthly carbon emission score corresponding to the enterprise in the raw material procurement scenario are generated according to the carbon emission reduction, the carbon emission change rate in the same period, and the current monthly carbon emission;

[0037] Through the preset second weight ratio, the corresponding comprehensive score of the enterprise under the production process scenario is generated according to the carbon emission reduction score of the enterprise under the production process scenario, the carbon emission change rate score during the same period and the current monthly carbon emission score;

[0038] Through the preset second weight ratio, the corresponding comprehensive score of the enterprise under the energy use scenario is generated according to the carbon emission reduction score of the enterprise under the energy use scenario, the carbon emission change rate score during the same period and the current monthly carbon emission score;

[0039] Through the preset second weight ratio, the corresponding comprehensive score of the enterprise in the raw material procurement scenario is generated according to the carbon emission reduction score of the enterprise in the raw material procurement scenario, the carbon emission change rate score in the same period and the current monthly carbon emission score;

[0040] Through the preset third weight ratio, the monthly carbon performance benchmark value corresponding to the production enterprise is generated according to the comprehensive score of the enterprise in the production process scenario, the comprehensive score of the enterprise in the energy use scenario and the comprehensive score of the enterprise in the raw material procurement scenario.

[0041] Preferably, the monthly carbon performance evaluation results of the target enterprise are generated according to the pre-generated correspondence between the weekly carbon emission level coefficients of the enterprise under each segmented scenario, the average change rate of the weekly carbon emissions of the target enterprise within the quarter and the corresponding monthly carbon performance benchmark value, including:

[0042] Through the pre-generated correspondence between the weekly carbon emission level coefficients of enterprises in each segmented scenario, the coefficients are matched according to the average change rate of weekly carbon emissions of the target enterprise within the quarter to generate the corresponding carbon performance correction coefficient;

[0043] According to the target enterprise’s enterprise type, query the corresponding monthly carbon performance benchmark value;

[0044] Based on the target enterprise’s corresponding monthly carbon performance benchmark value and carbon performance correction coefficient, the target enterprise’s monthly carbon performance assessment results are generated.

[0045] The present invention also discloses a device for evaluating enterprise carbon performance based on segmented scenarios, comprising:

[0046] An attribute data acquisition unit, used to acquire attribute data of each enterprise within the jurisdiction;

[0047] The multi-dimensional clustering unit is used to perform multi-dimensional clustering of enterprises based on attribute data and generate enterprise type databases under different scales and different segmentation scenarios;

[0048] The benchmark value calculation unit is used to generate the monthly carbon performance benchmark value corresponding to each enterprise type based on the carbon emission data of enterprises under each subdivided scenario of the same scale in the enterprise type database;

[0049] The average change rate calculation unit is used to generate the average change rate of weekly carbon emissions of the target enterprise in the current quarter based on the corporate carbon emission data of the target enterprise to be evaluated;

[0050] The carbon performance evaluation unit is used to generate the monthly carbon performance evaluation results of the target enterprise based on the pre-generated correspondence between the weekly carbon emission level coefficients of the enterprise under each segmented scenario, the average change rate of the target enterprise's weekly carbon emissions within the quarter and the corresponding monthly carbon performance benchmark value.

[0051] The present invention also discloses a computer-readable medium on which a computer program is stored. When the program is executed by a processor, the method described above is implemented.

[0052] The present invention also discloses a computer device, including a memory and a processor, wherein the memory is used to store information including program instructions, the processor is used to control the execution of program instructions, and the processor implements the above method when executing the program.

[0053] The present invention also discloses a computer program product, including a computer program / instruction, and the method described above is implemented when the computer program / instruction is executed by a processor.

[0054] The present invention obtains attribute data of each enterprise under its jurisdiction; performs multi-dimensional clustering of enterprises according to the attribute data, and generates an enterprise type database under each segmented scenario of different scales; generates a monthly carbon performance benchmark value corresponding to each enterprise type according to the carbon emission data of enterprises under each segmented scenario of the same scale in the enterprise type database; generates the average change rate of weekly carbon emissions of the target enterprise in the current quarter according to the carbon emission data of the target enterprise to be evaluated; generates the monthly carbon performance evaluation result of the target enterprise according to the average change rate of weekly carbon emissions of the target enterprise in the quarter and the corresponding monthly carbon performance benchmark value through the correspondence relationship of weekly carbon emission grade coefficients corresponding to the enterprise in each segmented scenario generated in advance. The carbon data of the enterprise can be classified and managed based on various enterprise types, enterprise scales and segmented scenarios, comprehensively consider the carbon emission reduction performance of the enterprise in different scenarios, improve practicality and functionality, and accurately evaluate the carbon performance of the enterprise. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0056] Figure 1 A flow chart of a method for evaluating corporate carbon performance based on segmented scenarios provided by an embodiment of the present invention;

[0057] Figure 2 A flowchart of another method for evaluating corporate carbon performance based on segmented scenarios provided in an embodiment of the present invention;

[0058] Figure 3 A schematic diagram of the structure of an enterprise carbon performance assessment device based on segmented scenarios provided by an embodiment of the present invention;

[0059] Figure 4 A schematic diagram of the structure of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] It should be noted that the enterprise carbon performance assessment method and device based on segmented scenarios disclosed in the present application can be used in the field of artificial intelligence technology, and can also be used in any field outside the field of artificial intelligence technology. The application field of the enterprise carbon performance assessment method and device based on segmented scenarios disclosed in the present application is not limited.

[0062] The following takes the enterprise carbon performance evaluation device based on the segmented scenario as an example of the execution subject to illustrate the implementation process of the enterprise carbon performance evaluation method based on the segmented scenario provided by the embodiment of the present invention. It can be understood that the execution subject of the enterprise carbon performance evaluation method based on the segmented scenario provided by the embodiment of the present invention includes but is not limited to the enterprise carbon performance evaluation device based on the segmented scenario.

[0063] Figure 1 A flowchart of a method for evaluating corporate carbon performance based on segmented scenarios provided by an embodiment of the present invention is shown in FIG. Figure 1 As shown, the method includes:

[0064] Step 101: Obtain attribute data of each enterprise within the jurisdiction.

[0065] In an embodiment of the present invention, data of subordinate enterprises are collected, and the enterprises are divided based on their types, and enterprises of the same type are divided into relevant grouping databases, including but not limited to production enterprises, service enterprises, and trade and finance enterprises.

[0066] Step 102: Perform multi-dimensional clustering of enterprises based on attribute data to generate enterprise type databases for different scales and various segmented scenarios.

[0067] Specifically, based on the scale of enterprises in the subordinate databases, enterprises in different grouping databases are grouped into secondary groups, and based on the types of enterprises, enterprises are divided into scenarios.

[0068] Step 103: Generate a monthly carbon performance benchmark value corresponding to each enterprise type based on the carbon emission data of enterprises in each segmented scenario of the same scale in the enterprise type database.

[0069] In an embodiment of the present invention, historical data of similar scenarios of enterprises under different secondary classifications are collected, combined with real-time data of the current month, combined with carbon emission reduction, carbon emission change rate during the same period and carbon emissions to perform a comprehensive score and calculate monthly carbon performance.

[0070] Step 104: Generate the average change rate of weekly carbon emissions of the target enterprise in the current quarter based on the enterprise carbon emission data of the target enterprise to be evaluated.

[0071] Step 105: Generate the monthly carbon performance evaluation result of the target enterprise according to the average change rate of weekly carbon emissions of the target enterprise within the quarter and the corresponding monthly carbon performance benchmark value through the pre-generated correspondence relationship between the weekly carbon emission level coefficients of the enterprise under each segmented scenario.

[0072] In the embodiment of the present invention, the weekly carbon emission change data is integrated to analyze the quarterly carbon emission change trend, and the change results are comprehensively ranked to perform additional carbon performance correction.

[0073] In the technical solution provided by the embodiment of the present invention, the attribute data of each enterprise under the jurisdiction is obtained; the enterprises are clustered in multiple dimensions according to the attribute data to generate an enterprise type database under each segmented scenario of different scales; the monthly carbon performance benchmark value corresponding to each enterprise type is generated according to the carbon emission data of enterprises under each segmented scenario of the same scale in the enterprise type database; the average change rate of weekly carbon emissions of the target enterprise in the current quarter is generated according to the enterprise carbon emission data of the target enterprise to be evaluated; the monthly carbon performance evaluation result of the target enterprise is generated according to the average change rate of weekly carbon emissions of the target enterprise in the quarter and the corresponding monthly carbon performance benchmark value through the correspondence relationship between the weekly carbon emission grade coefficients corresponding to the enterprise in each segmented scenario generated in advance. The carbon data of the enterprise can be classified and managed based on various enterprise types, enterprise scales and segmented scenarios, and the carbon emission reduction performance of the enterprise in different scenarios is comprehensively considered to improve practicality and functionality, and accurately evaluate the carbon performance of the enterprise.

[0074] Figure 2 A flowchart of another method for evaluating corporate carbon performance based on segmented scenarios provided in an embodiment of the present invention is shown in FIG. Figure 2 As shown, the method includes:

[0075] Step 201: Obtain attribute data of each enterprise within the jurisdiction.

[0076] In the embodiment of the present invention, each step is performed by an enterprise carbon performance assessment device based on segmented scenarios.

[0077] In the embodiment of the present invention, the attribute data includes but is not limited to the company name, business scope, business license, business type, number of employees in the company and the area occupied.

[0078] Step 202: Cluster the enterprises according to their business types to generate enterprise type clustering results.

[0079] Specifically, according to the business type, each enterprise is clustered according to the preset enterprise type clustering range to generate an enterprise type clustering result. As an optional solution, the enterprise type clustering range includes production type, service type and trade finance type. The enterprise type clustering result includes multiple production type enterprises corresponding to the production type, multiple service type enterprises corresponding to the service type, and multiple trade finance type enterprises corresponding to the trade finance type.

[0080] Step 203: According to the enterprise type clustering results, the scale is divided according to the number of employees and the area occupied by the enterprise, and the enterprise scale clustering results corresponding to each enterprise type are generated.

[0081] In the embodiment of the present invention, based on the number of employees and land area of ​​production enterprises, the number of employees of service enterprises and the number of employees of trade and finance enterprises, enterprises are grouped into two levels based on the scale classification standard to generate enterprise rule clustering results. The enterprise scale clustering results include small-scale enterprises, medium-scale enterprises and large-scale enterprises.

[0082] For service-oriented enterprises and trade finance enterprises, based on the number of employees n and the first number threshold n 1 , the second number threshold n 2 The enterprise-related enterprises are grouped into two levels, specifically: when the number of employees in an enterprise is less than the preset first number threshold (n<n 1 ), the enterprise is clustered as a small-scale enterprise; when the number of employees in the enterprise is greater than or equal to the first number threshold and less than or equal to the preset second number threshold (n 1 ≤n≤n 2 ), the enterprise is clustered as a medium-sized enterprise; when the number of employees in the enterprise is greater than the second number threshold (n>n 2 ), and cluster the enterprise as a large-scale enterprise.

[0083] For production enterprises, based on the number of employees n and the first number threshold n 1 , the second number threshold n 2 , area d, first area threshold d 1 , the second area threshold d 2 , the relevant enterprises are grouped into two levels, specifically: when the number of employees in the enterprise is less than the preset first number threshold, and the area occupied is less than the preset first area threshold (n<n 1 And d<d 1 ), cluster the enterprise as a small-scale enterprise; when the number of employees in the enterprise is greater than or equal to the first number threshold and less than or equal to the preset second number threshold and the area is greater than or equal to the first area threshold and less than or equal to the preset second area threshold (n 1 ≤n≤n 2 And d 1 ≤d≤d 2), the number of employees in the enterprise is less than the preset first number threshold and the floor area is greater than or equal to the first area threshold and less than or equal to the preset second area threshold (n<n 1 And d 1 ≤d≤d 2 ), the number of employees in the enterprise is greater than or equal to the first number threshold and less than or equal to the preset second number threshold and the floor area is less than the first area threshold (n 1 ≤n≤n 2 And d<d 1 ), the enterprise is clustered as a medium-sized enterprise; when the area is greater than the second area threshold or the number of employees in the enterprise is greater than the second number threshold (d>d 2 And n>n 2 ), and cluster the enterprise as a large-scale enterprise.

[0084] It is worth noting that the first number threshold, the second number threshold, the first area threshold, and the second area threshold need to be flexibly set through comprehensive analysis of historical data, industry standards and requirements, and consultation with experts in related fields. The embodiment of the present invention does not limit this. Different thresholds can be used to divide the enterprise scale actually required in different actual situations.

[0085] In the embodiment of the present invention, by segmenting enterprises based on their types and performing secondary classification based on their sizes, it is ensured that the carbon performance rating is more accurate, fair and instructive, and a scientific carbon performance rating system is provided to help enterprises identify their own carbon emission performance.

[0086] Step 204: According to the enterprise scale clustering results corresponding to each enterprise type, each enterprise is divided into scenarios, and an enterprise type database under each segmented scenario of different scales is constructed.

[0087] In the embodiment of the present invention, the dimensions of the enterprise type database include multiple enterprise scales, and each enterprise scale includes at least one segmented scenario.

[0088] In an embodiment of the present invention, an enterprise type database is established based on a relational database management system, including a production enterprise database, a service enterprise database, and a trade and finance enterprise database. The enterprise scale clustering results corresponding to each enterprise type are summarized into the corresponding database, and an enterprise file is established for scenario division of each enterprise and subsequent query of the monthly carbon performance benchmark value of the target enterprise.

[0089] In the embodiment of the present invention, the scenarios of enterprises are divided based on different enterprise types. Among them, the scenarios of production-oriented enterprises include production process, energy use, and raw material procurement; the scenarios of service-oriented enterprises include office energy consumption; the scenarios of trade and finance enterprises include office energy consumption, and the historical carbon emission data of enterprises are collected and recorded into the relevant enterprise files in the database.

[0090] In an embodiment of the present invention, by dividing different types of enterprises into typical scenarios, a horizontal comparison is made for enterprises of various enterprise sizes based on the carbon emission reduction data under different scenarios, the carbon emission change rate during the same period, and the carbon emissions, so as to obtain a monthly carbon performance benchmark value, and indicators are set for specific scenarios of different types of enterprises to ensure that the carbon performance assessment is more accurate and relevant.

[0091] Step 205: Generate the carbon emission reduction, carbon emission change rate and current monthly carbon emission corresponding to the enterprise in each segmented scenario according to the carbon emission data of enterprises of the same scale in each segmented scenario in the enterprise type database.

[0092] In the embodiment of the present invention, each enterprise type database stores historical carbon emission data for each subdivided scenario under different enterprise scales. Specifically, based on the enterprises of each enterprise scale in the same database, based on the enterprise type, the historical carbon emission data under the subdivided scenario is extracted, and the real-time carbon emission data of the current month is collected at the same time. Based on the historical carbon emission data and the real-time carbon emission data, the carbon emission change rate, carbon emission reduction and carbon emission data for the same period are calculated.

[0093] It is worth noting that the calculation method for the data of service-oriented enterprises and trade and finance-oriented enterprises is the same. For enterprise types including service-oriented enterprises / trade and finance-oriented enterprises, the subdivided scenarios include office space energy consumption; step 205 specifically includes:

[0094] Step 2051: extract the carbon emissions for the current month and the historical carbon emissions data for the same period as the current month.

[0095] In an embodiment of the present invention, for trade finance enterprises, historical carbon emission data on office energy consumption of enterprises of the same enterprise scale are extracted from the trade finance enterprise database, including the monthly office energy consumption carbon emissions of the previous year; the office energy consumption carbon emissions of relevant enterprises in the current month are obtained through real-time data; and the historical carbon emission data for the same period of the current month are extracted from the monthly office energy consumption carbon emissions of the previous year.

[0096] In an embodiment of the present invention, for service-oriented enterprises, historical carbon emission data on office energy consumption of enterprises under the same secondary classification are extracted from a service-oriented enterprise database, including monthly office energy consumption carbon emissions in the previous year; office energy consumption carbon emissions of relevant enterprises in the current month are obtained through real-time data; and historical carbon emission data for the same period of the current month are extracted from monthly office energy consumption carbon emissions in the previous year.

[0097] Step 2052: Generate the carbon emission change rate and carbon emission reduction for the same period according to the current monthly carbon emission and the historical carbon emission data for the same period of the current month.

[0098] In the embodiment of the present invention, based on the current monthly carbon emissions and the historical carbon emissions data for the same period of the current month, the carbon emissions change rate and carbon emission reduction of the enterprise in the same period are calculated, and the algorithm formula is:

[0099]

[0100] Among them, ΔC is the change rate of carbon emissions of the enterprise during the same period; C 0 is the historical carbon emission data of office energy consumption in the same period of the current month; C 1 It is the carbon emission of office energy consumption in the current month.

[0101] At the same time, the carbon emission reduction of enterprises under the office energy consumption scenario is calculated, and the algorithm formula is:

[0102] C 减 =C 0 -C 1

[0103] Among them, C 减 is the carbon emission reduction of the enterprise under the office energy consumption scenario; C 0 is the historical carbon emission data of office energy consumption in the same period of the current month; C 1 It is the carbon emission of office energy consumption in the current month.

[0104] Furthermore, the carbon emission reduction of office energy consumption, the change rate of carbon emissions in the same period, and the current monthly carbon emissions of each enterprise scale in the trade and finance enterprise database and the service enterprise database are arranged in descending order, and the arranged data are divided into 10 levels in equal proportion, with level 1 representing the data in the top 10%, level 2 representing the data between the top 10% and 20%, and so on. For the change rate of carbon emissions in the same period, levels 1 to 10 are set to correspond to 100, 90 points, ..., 10 points, respectively, to generate the corresponding level score correspondence of the carbon emission change rate in the same period under the subdivided scenario; for carbon emission reduction, levels 1 to 10 are set to correspond to 100, 90 points, ..., 10 points, respectively, to generate the corresponding level score correspondence of carbon emission reduction in the subdivided scenario; for the current monthly carbon emissions, levels 1 to 10 are set to correspond to 10 points, 20 points, ..., 100 points, respectively, to generate the corresponding level score correspondence of the current monthly carbon emissions in the subdivided scenario.

[0105] For enterprise types including a production enterprise database, the subdivided scenarios include production process scenarios, energy use scenarios, and raw material procurement scenarios; step 205 specifically includes:

[0106] Step 3051: According to the production process scenario, energy use scenario, and raw material procurement scenario, the current monthly carbon emissions and the historical carbon emissions data for the same period as the current month are extracted respectively.

[0107] In an embodiment of the present invention, for manufacturing enterprises, historical carbon emission data on production process, energy use, and raw material purchase of enterprises of the same enterprise scale are extracted from the manufacturing enterprise database, including the monthly carbon emissions from production process, energy use, and raw material purchase in the previous year; the carbon emissions from production process, energy use, and raw material purchase of relevant enterprises in the current month are obtained through real-time data; and the historical carbon emission data on production process, energy use, and raw material purchase in the same period of the current month are extracted from the monthly carbon emissions from production process, energy use, and raw material purchase in the previous year.

[0108] Step 3052: Generate the carbon emission change rate and carbon emission reduction corresponding to the enterprise in the production process scenario according to the current monthly carbon emissions corresponding to the production process scenario and the historical carbon emission data for the same period of the current month.

[0109] In the embodiment of the present invention, based on the current monthly carbon emissions corresponding to the production process scenario and the historical carbon emissions data for the same period of the current month, the carbon emissions change rate and carbon emission reduction corresponding to the enterprise in the production process scenario are calculated, and the algorithm formula is:

[0110]

[0111] Among them, ΔD is the change rate of carbon emissions of the enterprise in the same period under the production process scenario; D0 D is the historical carbon emission data of the production process in the same period of the current month; 1 Carbon emissions from the production process in the current month.

[0112] At the same time, the carbon emission reduction of the enterprise in the production process scenario is calculated, and the algorithm formula is:

[0113] D 减 =D 0 -D 1

[0114] Among them, D 减 D is the carbon emission reduction of the enterprise in the production process scenario; 0 D is the historical carbon emission data of the production process in the same period of the current month; 1 Carbon emissions from the production process in the current month.

[0115] Step 3053: Generate the carbon emission change rate and carbon emission reduction corresponding to the enterprise in the energy usage scenario according to the current monthly carbon emissions corresponding to the energy usage scenario and the historical carbon emission data for the same period of the current month.

[0116] In the embodiment of the present invention, based on the current monthly carbon emissions corresponding to the energy use scenario and the historical carbon emissions data for the same period of the current month, the carbon emissions change rate and carbon emission reduction corresponding to the enterprise in the energy use scenario are calculated, and the algorithm formula is:

[0117]

[0118] Among them, ΔF is the change rate of carbon emissions of the enterprise in the same period under the energy use scenario; F 0 The historical carbon emission data of energy use in the same period of the current month; F 1 Carbon emissions for energy use in the current month.

[0119] At the same time, the carbon emission reduction of enterprises under energy use scenarios is calculated, and the algorithm formula is:

[0120] F 减 =F 0 -F 1

[0121] Among them, F 减 F is the carbon emission reduction of the enterprise under the energy use scenario; 0 The historical carbon emission data of energy use in the same period of the current month; F 1 Carbon emissions for energy use in the current month.

[0122] Step 3054: Generate the carbon emission change rate and carbon emission reduction corresponding to the enterprise in the raw material procurement scenario according to the current monthly carbon emissions corresponding to the raw material procurement scenario and the historical carbon emission data for the same period of the current month.

[0123] In the embodiment of the present invention, based on the current monthly carbon emissions corresponding to the raw material procurement scenario and the historical carbon emissions data for the same period of the current month, the carbon emissions change rate and carbon emission reduction corresponding to the enterprise in the raw material procurement scenario are calculated, and the algorithm formula is:

[0124]

[0125] Among them, ΔG is the change rate of carbon emissions of the enterprise in the same period under the raw material procurement scenario; G 0 G is the historical carbon emission data of raw material purchases in the same period of the current month; 1 Carbon emissions from raw material purchases for the current month.

[0126] At the same time, the carbon emission reduction of enterprises in the raw material procurement scenario is calculated, and the algorithm formula is:

[0127] G 减 =G 0 -G 1

[0128] Among them, G 减 G is the carbon emission reduction of the enterprise in the raw material procurement scenario; 0 G is the historical carbon emission data of raw material purchases in the same period of the current month; 1 Carbon emissions from raw material purchases for the current month.

[0129] Furthermore, the carbon emission reduction, carbon emission change rate in the same period, and current monthly carbon emission corresponding to the production process, energy use, and raw material procurement of each enterprise scale in the production enterprise database are arranged in descending order, and the arranged data are divided into 10 levels in equal proportion, with level 1 representing the data in the top 10%, level 2 representing the data between the top 10% and 20%, and so on. For the carbon emission change rate in the same period, levels 1 to 10 are set to correspond to 100, 90 points, ..., 10 points, respectively, to generate the corresponding carbon emission change rate level score correspondence in the same period under the subdivided scenario; for carbon emission reduction, levels 1 to 10 are set to correspond to 100, 90 points, ..., 10 points, respectively, to generate the corresponding carbon emission reduction level score correspondence in the subdivided scenario; for the current monthly carbon emission, levels 1 to 10 are set to correspond to 10 points, 20 points, ..., 100 points, respectively, to generate the corresponding current monthly carbon emission level score correspondence in the subdivided scenario.

[0130] In the embodiment of the present invention, the carbon emission change rate in the same period can measure the change in the carbon emission of the enterprise in the current month compared with the same period last year, reflecting the progress of the enterprise in carbon emission reduction in a relatively short period of time; the carbon emission reduction can directly quantify the reduction in carbon emissions of the enterprise in the past year, and intuitively display the emission reduction results of the enterprise. For production-oriented enterprises, trade and finance-oriented enterprises, and service-oriented enterprises, the carbon emission change rate and carbon emission reduction in the same period are calculated according to the subdivided scenarios, respectively, so as to refine the monthly carbon performance of different enterprises.

[0131] Step 206: Generate a monthly carbon performance benchmark value corresponding to each enterprise type based on the carbon emission reduction, the rate of change of carbon emissions during the same period, and the current monthly carbon emissions.

[0132] For enterprise types including service-oriented enterprises / trade and finance-oriented enterprises, the subdivided scenarios include office space energy consumption; step 206 specifically includes:

[0133] Step 2061, through the pre-generated carbon emission reduction grade score correspondence, the carbon emission change rate grade score correspondence over the same period and the current monthly carbon emission grade score correspondence, generate the carbon emission reduction score, the carbon emission change rate score over the same period and the current monthly carbon emission score according to the carbon emission reduction, the carbon emission change rate over the same period and the current monthly carbon emissions.

[0134] In the embodiment of the present invention, the carbon emission reduction level score correspondence, the carbon emission change rate level score correspondence and the current monthly carbon emission level score correspondence are obtained by sorting and grading the carbon emission reduction, the carbon emission change rate and the current monthly carbon emission. See steps 2052 and 3054 for details, which will not be described in detail in the embodiment of the present invention.

[0135] In an embodiment of the present invention, the carbon emission reduction grade score correspondence relationship includes: the carbon emission reduction grade score correspondence relationship under the energy consumption scenario of the office of a trade and finance enterprise, and the carbon emission reduction grade score correspondence relationship under the energy consumption scenario of the office of a service enterprise.

[0136] Specifically, for the energy consumption scenario of the office of a trade and finance enterprise, the carbon emission reduction in the corresponding sub-scenario calculated in step 205 is matched with the corresponding carbon emission reduction grade score under the energy consumption scenario of the office of the trade and finance enterprise to obtain the carbon emission reduction score.

[0137] Specifically, for the energy consumption scenario of the office space of the service-oriented enterprise, the carbon emission reduction in the corresponding subdivided scenario calculated in step 205 is matched with the corresponding carbon emission reduction grade score under the energy consumption scenario of the office space of the service-oriented enterprise to obtain the carbon emission reduction score.

[0138] In an embodiment of the present invention, the corresponding relationship between the grade scores of the carbon emissions change rate during the same period includes: the corresponding relationship between the grade scores of the carbon emissions change rate during the same period corresponding to the energy consumption scenario of the office of a trade and finance enterprise, and the corresponding relationship between the grade scores of the carbon emissions change rate during the same period corresponding to the energy consumption scenario of the office of a service enterprise.

[0139] Specifically, for the energy consumption scenario of the office of a trade and finance enterprise, the carbon emission change rate in the corresponding subdivided scenario calculated in step 205 is matched with the corresponding carbon emission change rate grade score in the energy consumption scenario of the office of the trade and finance enterprise to obtain the carbon emission change rate score in the same period.

[0140] Specifically, for the energy consumption scenario of the office space of a service-oriented enterprise, the carbon emission change rate in the corresponding subdivided scenario calculated in step 205 is matched with the corresponding carbon emission change rate grade score in the energy consumption scenario of the office space of the service-oriented enterprise to obtain the carbon emission change rate score in the same period.

[0141] In an embodiment of the present invention, the corresponding relationship between the current monthly carbon emission level scores includes: the corresponding relationship between the current monthly carbon emission level scores under the energy consumption scenario of the office of a trade and finance enterprise, and the corresponding relationship between the current monthly carbon emission level scores under the energy consumption scenario of the office of a service enterprise.

[0142] Specifically, for the energy consumption scenario of the office of a trade and finance enterprise, the current monthly carbon emissions in the corresponding subdivided scenario calculated in step 205 are matched with the corresponding current monthly carbon emissions grade score under the energy consumption scenario of the office of the trade and finance enterprise to obtain the current monthly carbon emissions score.

[0143] Specifically, for the energy consumption scenario of the office space of the service-oriented enterprise, the current monthly carbon emissions in the corresponding subdivided scenario calculated in step 205 are matched with the corresponding current monthly carbon emissions grade score under the energy consumption scenario of the office space of the service-oriented enterprise to obtain the current monthly carbon emissions score.

[0144] Step 2062: Generate a monthly carbon performance benchmark value corresponding to the service-oriented enterprise / trade and finance-oriented enterprise through a preset first weight ratio, according to the carbon emission reduction score, the carbon emission change rate score during the same period, and the current monthly carbon emission score.

[0145] Specifically, for the energy consumption scenario of office space of trade and finance enterprises, the carbon emission reduction score, the carbon emission change rate score during the same period and the current monthly carbon emission score are calculated through the first weight ratio to generate the corresponding monthly carbon performance benchmark value of trade and finance enterprises. The algorithm steps are as follows:

[0146]

[0147] in, is the monthly carbon performance benchmark value corresponding to trade finance enterprises; α 1 , α 2 , α 3 is the first weight ratio; a 1 is the carbon emission change rate fraction during the same period; b 1 is the carbon emission reduction fraction; c 1 is the carbon emission fraction of the current month.

[0148] Specifically, for the energy consumption scenario of the office space of a service-oriented enterprise, the carbon emission reduction score, the carbon emission change rate score during the same period, and the current monthly carbon emission score are calculated through the first weight ratio to generate the corresponding monthly carbon performance benchmark value for the service-oriented enterprise. The algorithm steps are as follows:

[0149]

[0150] in, is the monthly carbon performance benchmark value corresponding to service-oriented enterprises; α 1 , α 2 , α 3 is the first weight ratio; a' 1 is the carbon emission change rate fraction during the same period; b' 1 is the carbon emission reduction fraction; c' 1 is the carbon emission fraction of the current month.

[0151] In the embodiment of the present invention, the first weight ratio can be flexibly set for the weight coefficient according to the specific use environment requirements. The embodiment of the present invention does not limit this. As an optional solution, α 1 , α 2 , α 3 The values ​​of are set to 0.4, 0.4, and 0.2 respectively.

[0152] For enterprise types including a production enterprise database, the subdivided scenarios include production process scenarios, energy use scenarios, and raw material procurement scenarios; step 206 specifically includes:

[0153] Step 3061, through the pre-generated correspondence relationship between the carbon emission reduction grade scores corresponding to the production process scenarios, the correspondence relationship between the carbon emission change rate grade scores during the same period and the correspondence relationship between the carbon emission grade scores of the current month, according to the carbon emission reductions, the carbon emission change rate during the same period and the current monthly carbon emissions, generate the carbon emission reduction score, the carbon emission change rate score during the same period and the current monthly carbon emission score corresponding to the enterprise under the production process scenario.

[0154] In the embodiment of the present invention, the corresponding relationship of the carbon emission reduction level score corresponding to the production process scenario, the corresponding relationship of the carbon emission change rate level score corresponding to the same period, and the corresponding relationship of the current monthly carbon emission level score corresponding to the production process scenario are obtained by sorting and grading the carbon emission reduction, the carbon emission change rate in the same period, and the current monthly carbon emission. See steps 2052 and 3054 for details, which will not be described in detail in the embodiment of the present invention.

[0155] Specifically, for the production process scenario, the carbon emission reduction in the production process scenario calculated in step 205 is matched with the corresponding relationship between the carbon emission reduction grade scores corresponding to the production process scenario to obtain the carbon emission reduction score.

[0156] Specifically, for the production process scenario, the carbon emission change rate in the same period in the production process scenario calculated in step 205 is matched with the corresponding carbon emission change rate grade score of the same period corresponding to the production process scenario to obtain the carbon emission change rate score of the same period.

[0157] Specifically, for the production process scenario, the current monthly carbon emissions in the production process scenario calculated in step 205 are matched with the corresponding relationship between the current monthly carbon emissions grade scores corresponding to the production process scenario to obtain the current monthly carbon emissions score.

[0158] Step 3062: Generate the carbon emission reduction score, carbon emission change rate score and current monthly carbon emission score corresponding to the energy usage scenario through the pre-generated correspondence relationship between the carbon emission reduction grade scores and the carbon emission change rate grade scores corresponding to the energy usage scenario, according to the carbon emission reduction, the carbon emission change rate and the current monthly carbon emissions.

[0159] In the embodiment of the present invention, the carbon emission reduction level score correspondence relationship corresponding to the energy use scenario, the carbon emission change rate level score correspondence relationship and the current monthly carbon emission level score correspondence relationship are obtained by sorting and grading the carbon emission reduction, the carbon emission change rate and the current monthly carbon emission. See steps 2052 and 3054 for details, which will not be described in detail in the embodiment of the present invention.

[0160] Specifically, for the energy usage scenario, the carbon emission reduction in the energy usage scenario calculated in step 205 is matched with the corresponding relationship between the carbon emission reduction grade scores corresponding to the energy usage scenario to obtain the carbon emission reduction score.

[0161] Specifically, for energy usage scenarios, the carbon emission change rate in the same period in the energy usage scenario calculated in step 205 is matched with the corresponding carbon emission change rate grade score of the same period corresponding to the energy usage scenario to obtain the carbon emission change rate score of the same period.

[0162] Specifically, for the energy usage scenario, the current monthly carbon emissions in the energy usage scenario calculated in step 205 are matched with the corresponding relationship between the current monthly carbon emissions grade scores corresponding to the energy usage scenario to obtain the current monthly carbon emissions score.

[0163] Step 3063, through the pre-generated correspondence relationship between the carbon emission reduction grade scores corresponding to the raw material procurement scenarios, the correspondence relationship between the carbon emission change rate grade scores during the same period and the correspondence relationship between the carbon emission grade scores of the current month, according to the carbon emission reduction, the carbon emission change rate during the same period and the current monthly carbon emissions, generate the carbon emission reduction score, the carbon emission change rate score during the same period and the current monthly carbon emission score corresponding to the enterprise under the raw material procurement scenario.

[0164] In the embodiment of the present invention, the carbon emission reduction level score corresponding to the raw material procurement scenario, the carbon emission change rate level score corresponding relationship, and the current monthly carbon emission level score corresponding relationship are obtained by sorting and grading the carbon emission reduction, the carbon emission change rate in the same period, and the current monthly carbon emission. See steps 2052 and 3054 for details, which will not be described in detail in the embodiment of the present invention.

[0165] Specifically, for the raw material procurement scenario, the carbon emission reduction in the raw material procurement scenario calculated in step 205 is matched with the corresponding relationship between the carbon emission reduction grade scores corresponding to the raw material procurement scenario to obtain the carbon emission reduction score.

[0166] Specifically, for the raw material procurement scenario, the carbon emission change rate in the same period in the raw material procurement scenario calculated in step 205 is matched with the corresponding carbon emission change rate grade score of the same period corresponding to the raw material procurement scenario to obtain the carbon emission change rate score of the same period.

[0167] Specifically, for the raw material procurement scenario, the current monthly carbon emissions in the raw material procurement scenario calculated in step 205 are matched with the corresponding relationship between the current monthly carbon emissions grade scores corresponding to the raw material procurement scenario to obtain the current monthly carbon emissions score.

[0168] Step 3064: Generate a comprehensive score corresponding to the enterprise in the production process scenario through a preset second weight ratio, according to the enterprise's corresponding carbon emission reduction score in the production process scenario, the carbon emission change rate score in the same period, and the current monthly carbon emission score.

[0169] Specifically, for the production process scenario of a manufacturing enterprise, the carbon emission reduction score, the carbon emission change rate score in the same period and the current monthly carbon emission score corresponding to the enterprise in the production process scenario are calculated through the second weight ratio to generate the comprehensive score corresponding to the enterprise in the production process scenario. The algorithm steps are as follows:

[0170] P1 =β 1 ·a 2 +β 2 b 2 +β 3 ·c 2

[0171] Among them, P 1 is the comprehensive score of the enterprise in the production process scenario; β 1 , β 2 , β 3 is the second weight ratio; a 2 is the carbon emission change rate fraction during the same period; b 2 is the carbon emission reduction fraction; c 2 is the carbon emission fraction of the current month.

[0172] In the embodiment of the present invention, the second weight ratio can be flexibly set for the weight coefficient according to the specific use environment. The embodiment of the present invention does not limit this. As an optional solution, β 1 , β 2 , β 3 The values ​​of are set to 0.4, 0.4, and 0.2 respectively.

[0173] Step 3065: Generate a comprehensive score corresponding to the enterprise under the energy usage scenario through a preset second weight ratio, according to the enterprise's corresponding carbon emission reduction score under the energy usage scenario, the carbon emission change rate score over the same period, and the current monthly carbon emission score.

[0174] Specifically, for the energy use scenario of production-type enterprises, the carbon emission reduction score, the carbon emission change rate score in the same period and the current monthly carbon emission score corresponding to the energy use scenario are calculated through the second weight ratio to generate the comprehensive score corresponding to the enterprise in the energy use scenario. The algorithm steps are as follows:

[0175] P 2 =β 1 ·a 3 +β 2 b 3 +β 3 ·c 3

[0176] Among them, P 2 is the comprehensive score of the enterprise under the energy use scenario; β 1 , β 2 , β 3 is the second weight ratio; a 3 is the carbon emission change rate fraction during the same period; b 3 is the carbon emission reduction fraction; c 3 is the carbon emission fraction of the current month.

[0177] In the embodiment of the present invention, the second weight ratio can be flexibly set for the weight coefficient according to the specific use environment. The embodiment of the present invention does not limit this. As an optional solution, β 1 , β 2 , β 3 The values ​​of are set to 0.4, 0.4, and 0.2 respectively.

[0178] Step 3066: Generate a comprehensive score corresponding to the enterprise in the raw material procurement scenario through the preset second weight ratio, according to the enterprise's corresponding carbon emission reduction score in the raw material procurement scenario, the carbon emission change rate score in the same period and the current monthly carbon emission score.

[0179] Specifically, for the production-type raw material procurement scenario, the carbon emission reduction score, the carbon emission change rate score in the same period and the current monthly carbon emission score corresponding to the enterprise in the raw material procurement scenario are calculated through the second weight ratio to generate the corresponding comprehensive score of the enterprise in the raw material procurement scenario. The algorithm steps are as follows:

[0180] P 3 =β 1 ·a 4 +β 2 b 4 +β 3 ·c 4

[0181] Among them, P 3 is the comprehensive score of the enterprise in the raw material procurement scenario; β 1 , β 2 , β 3 is the second weight ratio; a 4 is the carbon emission change rate fraction during the same period; b 4 is the carbon emission reduction fraction; c 4 is the carbon emission fraction of the current month.

[0182] In the embodiment of the present invention, the second weight ratio can be flexibly set for the weight coefficient according to the specific use environment. The embodiment of the present invention does not limit this. As an optional solution, β 1 , β 2 , β 3 The values ​​of are set to 0.4, 0.4, and 0.2 respectively.

[0183] Step 3067: Generate a monthly carbon performance benchmark value corresponding to the production enterprise based on the preset third weight ratio and the comprehensive score corresponding to the enterprise in the production process scenario, the comprehensive score corresponding to the enterprise in the energy use scenario, and the comprehensive score corresponding to the enterprise in the raw material procurement scenario.

[0184] Specifically, the comprehensive scores of enterprises in the production process scenario, the comprehensive scores of enterprises in the energy use scenario, and the comprehensive scores of enterprises in the raw material procurement scenario are calculated through the third weight ratio to generate the monthly carbon performance benchmark value corresponding to the production enterprise. The algorithm steps are as follows:

[0185] O 1 =γ 1 ·P 1 +γ 2 ·P 2 +γ 3 ·P 3

[0186] Among them, O 1 is the monthly carbon performance benchmark value corresponding to production enterprises; γ 1 , γ 2 , γ 3 is the third weight ratio; P 1 is the comprehensive score of the enterprise in the production process scenario; P 2 is the comprehensive score of the enterprise under the energy use scenario; P 3 It is the comprehensive score corresponding to the enterprise in the raw material procurement scenario.

[0187] In the embodiment of the present invention, the third weight ratio can be flexibly set for the weight coefficient according to the specific use environment requirements. The embodiment of the present invention does not limit this. As an optional solution, γ 1 , γ 2 , γ 3 The values ​​of are set to 0.4, 0.3, and 0.3 respectively.

[0188] In the embodiment of the present invention, the emission reduction measures of the production enterprise can be comprehensively evaluated by comprehensively considering the specific carbon emission change rate, carbon emission reduction, and carbon emission of the production enterprise during the production process, energy use, and raw material procurement.

[0189] Step 207: Generate the average change rate of weekly carbon emissions of the target enterprise in the current quarter based on the enterprise carbon emission data of the target enterprise to be evaluated.

[0190] In the embodiment of the present invention, the target enterprise is the enterprise whose carbon performance is to be evaluated in the current month. The enterprise type database corresponding to the target enterprise is used to obtain the enterprise carbon emission data of the target enterprise in each week of the current month, and the change rate of the weekly carbon emissions relative to the previous week is calculated. The algorithm formula is:

[0191]

[0192] Among them, M i is the rate of change of carbon emissions in week i relative to week i-1; W iis the carbon emission in the ith week; W i-1 is the carbon emission in week i-1.

[0193] In the embodiment of the present invention, according to the change rate of weekly carbon emissions relative to the previous week, the average value of all weekly change rates in the current quarter is calculated to evaluate the overall change trend. The specific algorithm formula is:

[0194]

[0195] Among them, M i is the rate of change of carbon emissions in week i relative to week i-1; Q i is the average change rate of weekly carbon emissions of the target enterprise in the current quarter, and n is the number of weeks in the current quarter.

[0196] Step 208: By using the pre-generated correspondence between the weekly carbon emission level coefficients of the enterprise under each segmented scenario, the coefficients are matched according to the average change rate of the weekly carbon emissions of the target enterprise within the quarter to generate the corresponding carbon performance correction coefficient.

[0197] In the embodiment of the present invention, the weekly carbon emission level coefficient correspondence is obtained by sorting the average change rate of weekly carbon emissions of enterprises under each enterprise scale in the previous quarter in descending order and dividing them into grades. Specifically, the average change rate of weekly carbon emissions of enterprises under each enterprise scale in the previous quarter after descending order is divided into 5 grades, and the average change rate of weekly carbon emissions ranked in the top 20% is divided into the first grade and the first correction coefficient λ is set 1 ; Classify the average change rate of weekly carbon emissions in the top 20% to 40% into the second level and set the second correction coefficient λ 2 ; Classify the average change rate of weekly carbon emissions from the top 40% to 60% into the third level and set the third correction coefficient λ 3 ; Classify the average change rate of weekly carbon emissions from the top 60% to 80% into the fourth level and set the fourth correction coefficient λ 4 ; Divide the average change rate of weekly carbon emissions from the top 80% to 100% into the fifth level and set the fifth correction coefficient λ 5 .

[0198] It is worth noting that the correction coefficient can be set according to the specific actual usage situation, and the embodiment of the present invention does not limit this. As an optional solution, λ 1 To 5 Set to 1.1, 1.08, 1.06, 1.04, and 1.02 respectively.

[0199] Specifically, the average change rate of weekly carbon emissions of the target enterprise within a quarter is matched with the correspondence between the weekly carbon emission grade coefficient to match the corresponding correction coefficient; the matched correction coefficient is determined as the carbon performance correction coefficient corresponding to the target enterprise.

[0200] In the embodiment of the present invention, by analyzing the quarterly average change rate of the previous quarter of the current month, it can be analyzed whether the relevant enterprises have taken effective emission reduction measures.

[0201] Step 209: According to the enterprise type of the target enterprise, the corresponding monthly carbon performance benchmark value is queried.

[0202] In the embodiment of the present invention, different enterprise types correspond to different monthly carbon performance benchmark values; the enterprise types are matched to query the monthly carbon performance benchmark value corresponding to the target enterprise.

[0203] Step 210: Generate a monthly carbon performance evaluation result of the target enterprise based on the monthly carbon performance benchmark value and carbon performance correction coefficient corresponding to the target enterprise.

[0204] Specifically, the monthly carbon performance benchmark value corresponding to the target enterprise and the carbon performance correction coefficient are multiplied together to generate the monthly carbon performance assessment result of the target enterprise.

[0205] In an embodiment of the present invention, by segmenting enterprises based on their types and performing secondary classification based on their sizes, it is ensured that carbon performance ratings are more accurate, fair and instructive, and a scientific carbon performance rating system is provided to help enterprises identify their own carbon emission performance; by segmenting scenarios for different types of enterprises, a horizontal comparison is made for enterprises of various sizes based on carbon emission reduction data, carbon emission change rate over the same period and carbon emissions under different scenarios to obtain a monthly carbon performance benchmark value, and indicators are set for specific scenarios of different types of enterprises to ensure that carbon performance evaluation is more accurate and relevant, and the current monthly carbon performance benchmark value is corrected by combining the average change rate of the previous quarter, and for enterprises with a better emission reduction change rate in the previous quarter, the correction coefficient is corrected to obtain a monthly carbon performance correction value, so that the carbon performance evaluation is more dynamic and real-time, and can timely reflect the emission reduction trend and effect of the enterprise.

[0206] The present invention corrects the current monthly carbon performance benchmark value in combination with the average change rate of the previous quarter, and corrects the correction coefficient for enterprises with a better emission reduction change rate in the previous quarter to obtain the monthly carbon performance correction value, so that the carbon performance evaluation is more dynamic and real-time, and can timely reflect the emission reduction trend and effect of the enterprise; by correcting the correction coefficient for enterprises with a better emission reduction change rate in the previous quarter, it can encourage enterprises to continue to implement emission reduction measures and establish positive environmental protection behavior patterns, so that enterprises can more effectively manage carbon emissions and identify and improve deficiencies in emission reduction.

[0207] It is worth noting that the acquisition, storage, use, and processing of data in the technical solution of this application are in compliance with the relevant provisions of laws and regulations. The user information in the embodiments of this application is obtained through legal and compliant channels, and the acquisition, storage, use, and processing of user information are authorized and agreed by the customer.

[0208] It is worth noting that the information collected in this application is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of relevant data comply with the relevant laws, regulations and standards of relevant countries and regions, take necessary confidentiality measures, do not violate public order and good customs, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0209] It is worth noting that the technical solution provided in this application provides users with corresponding operation entrances for them to choose to agree or reject the automated decision-making results; if the user chooses to reject, the expert decision-making process will be entered.

[0210] In the technical solution of the enterprise carbon performance evaluation method based on segmented scenarios provided by the embodiment of the present invention, the attribute data of each enterprise within the jurisdiction is obtained; the enterprises are multi-dimensionally clustered according to the attribute data to generate an enterprise type database under each segmented scenario of different scales; the monthly carbon performance benchmark value corresponding to each enterprise type is generated according to the carbon emission data of enterprises under each segmented scenario of the same scale in the enterprise type database; the average change rate of weekly carbon emissions of the target enterprise in the current quarter is generated according to the enterprise carbon emission data of the target enterprise to be evaluated; through the pre-generated correspondence between the weekly carbon emission grade coefficients corresponding to the enterprise in each segmented scenario, the monthly carbon performance evaluation result of the target enterprise is generated according to the average change rate of weekly carbon emissions of the target enterprise in the quarter and the corresponding monthly carbon performance benchmark value. The carbon data of the enterprise can be classified and managed based on various enterprise types, enterprise scales and segmented scenarios, and the carbon emission reduction performance of the enterprise in different scenarios is comprehensively considered to improve practicality and functionality, and accurately evaluate the carbon performance of the enterprise.

[0211] Figure 3 A schematic diagram of the structure of a device for evaluating enterprise carbon performance based on segmented scenarios provided by an embodiment of the present invention, wherein the device is used to execute the above-mentioned method for evaluating enterprise carbon performance based on segmented scenarios, such as Figure 3 As shown, the device includes: an attribute data acquisition unit 11, a multi-dimensional clustering unit 12, a reference value calculation unit 13, an average change rate calculation unit 14 and a carbon performance evaluation unit 15.

[0212] The attribute data acquisition unit 11 is used to acquire the attribute data of each enterprise within its jurisdiction.

[0213] The multi-dimensional clustering unit 12 is used to perform multi-dimensional clustering on enterprises according to attribute data, and generate enterprise type databases in different scales and in various segmented scenarios.

[0214] The benchmark value calculation unit 13 is used to generate a monthly carbon performance benchmark value corresponding to each enterprise type based on the carbon emission data of enterprises in each subdivided scenario of the same scale in the enterprise type database.

[0215] The average change rate calculation unit 14 is used to generate the average change rate of weekly carbon emissions of the target enterprise in the current quarter according to the enterprise carbon emission data of the target enterprise to be evaluated.

[0216] The carbon performance evaluation unit 15 is used to generate a monthly carbon performance evaluation result for the target enterprise based on the pre-generated correspondence between the weekly carbon emission level coefficients of the enterprise under each segmented scenario, the average change rate of the weekly carbon emissions of the target enterprise within a quarter and the corresponding monthly carbon performance benchmark value.

[0217] In an embodiment of the present invention, attribute data includes business type, number of employees and floor space; the multi-dimensional clustering unit 12 is specifically used to cluster each enterprise according to the business type to generate enterprise type clustering results; according to the enterprise type clustering results, the scale is divided according to the number of employees and floor space, and enterprise scale clustering results corresponding to each enterprise type are generated; according to the enterprise scale clustering results corresponding to each enterprise type, each enterprise is divided into scenarios, and an enterprise type database for each subdivided scenario of different scales is constructed, and the dimensions of the enterprise type database include multiple enterprise scales, and each enterprise scale includes at least one subdivided scenario.

[0218] In an embodiment of the present invention, the benchmark value calculation unit 13 is specifically used to generate the carbon emission reduction, carbon emission change rate over the same period and current monthly carbon emissions corresponding to the enterprise in each segmented scenario based on the carbon emission data of enterprises of the same scale in each segmented scenario in the enterprise type database; and generate the monthly carbon performance benchmark value corresponding to each enterprise type based on the carbon emission reduction, carbon emission change rate over the same period and current monthly carbon emissions.

[0219] In an embodiment of the present invention, enterprise types include service-oriented enterprises / trade and finance-oriented enterprises, and subdivided scenarios include office energy consumption; the benchmark value calculation unit 13 is specifically used to extract the current monthly carbon emissions and the historical carbon emissions data for the same period of the current month; based on the current monthly carbon emissions and the historical carbon emissions data for the same period of the current month, the carbon emissions change rate and carbon emission reduction for the same period are generated.

[0220] In an embodiment of the present invention, the enterprise type includes a production enterprise database, and the subdivided scenarios include a production process scenario, an energy use scenario, and a raw material procurement scenario; the benchmark value calculation unit 13 is specifically used to extract the current monthly carbon emissions and the historical carbon emissions data for the same period of the current month according to the production process scenario, the energy use scenario, and the raw material procurement scenario; according to the current monthly carbon emissions corresponding to the production process scenario and the historical carbon emissions data for the same period of the current month, the corresponding carbon emissions change rate and carbon emission reduction for the same period of the enterprise under the production process scenario are generated; according to the current monthly carbon emissions corresponding to the energy use scenario and the historical carbon emissions data for the same period of the current month, the corresponding carbon emissions change rate and carbon emission reduction for the same period of the enterprise under the energy use scenario are generated; according to the current monthly carbon emissions corresponding to the raw material procurement scenario and the historical carbon emissions data for the same period of the current month, the corresponding carbon emissions change rate and carbon emission reduction for the same period of the enterprise under the raw material procurement scenario are generated.

[0221] In an embodiment of the present invention, enterprise types include service-oriented enterprises / trade and finance-oriented enterprises, and subdivided scenarios include energy consumption in office spaces; the benchmark value calculation unit 13 is specifically used to generate a carbon emission reduction score, a carbon emission change rate score for the same period, and a current monthly carbon emission score according to the carbon emission reduction, the carbon emission change rate for the same period, and the current monthly carbon emissions through a pre-generated carbon emission reduction grade score correspondence relationship, a carbon emission change rate grade score correspondence relationship, and a current monthly carbon emission grade score correspondence relationship, wherein the carbon emission reduction grade score correspondence relationship, the carbon emission change rate grade score correspondence relationship, and the current monthly carbon emission grade score correspondence relationship are obtained by sorting and grading the carbon emission reduction, the carbon emission change rate for the same period, and the current monthly carbon emissions respectively; and a monthly carbon performance benchmark value corresponding to the service-oriented enterprise / trade and finance-oriented enterprise is generated according to the carbon emission reduction score, the carbon emission change rate score for the same period, and the current monthly carbon emission score through a preset first weight ratio.

[0222] In an embodiment of the present invention, the enterprise type includes a production enterprise database, and the subdivided scenarios include production process scenarios, energy use scenarios, and raw material procurement scenarios; the benchmark value calculation unit 13 is specifically used to generate the carbon emission reduction grade score corresponding to the production process scenario, the carbon emission change rate grade score corresponding to the same period, and the current monthly carbon emission grade score corresponding to the current month according to the carbon emission reduction, the carbon emission change rate during the same period, and the current monthly carbon emissions; the carbon emission reduction grade score corresponding to the energy use scenario, the carbon emission change rate grade score corresponding to the same period, and the current monthly carbon emission grade score corresponding to the energy use scenario according to the carbon emission reduction, the carbon emission change rate during the same period, and the current monthly carbon emissions; the carbon emission reduction grade score corresponding to the raw material procurement scenario, the carbon emission reduction grade score corresponding to the same period, and the current monthly carbon emission grade score corresponding to the current month according to the carbon emission reduction, the carbon emission change rate during the same period, and the current monthly carbon emissions. According to the corresponding relationship of scores, the carbon emission reduction score, the carbon emission change rate score during the same period and the current monthly carbon emissions are generated for the enterprise in the raw material procurement scenario; through the preset second weight ratio, according to the carbon emission reduction score, the carbon emission change rate score during the same period and the current monthly carbon emission score corresponding to the enterprise in the production process scenario, the comprehensive score corresponding to the enterprise in the production process scenario is generated; through the preset second weight ratio, according to the carbon emission reduction score, the carbon emission change rate score during the same period and the current monthly carbon emission score corresponding to the enterprise in the energy use scenario, the comprehensive score corresponding to the enterprise in the energy use scenario is generated; through the preset second weight ratio, according to the carbon emission reduction score, the carbon emission change rate score during the same period and the current monthly carbon emission score corresponding to the enterprise in the raw material procurement scenario, the comprehensive score corresponding to the enterprise in the raw material procurement scenario is generated; through the preset third weight ratio, according to the comprehensive score corresponding to the enterprise in the production process scenario, the comprehensive score corresponding to the enterprise in the energy use scenario and the comprehensive score corresponding to the enterprise in the raw material procurement scenario, the monthly carbon performance benchmark value corresponding to the production enterprise is generated.

[0223] In the embodiment of the present invention, the carbon performance evaluation unit 15 is specifically used to generate a corresponding carbon performance correction coefficient by matching the coefficients according to the average change rate of weekly carbon emissions of the target enterprise within the quarter through the pre-generated correspondence relationship between the weekly carbon emission level coefficients corresponding to the enterprise in each segmented scenario; query the corresponding monthly carbon performance benchmark value according to the enterprise type of the target enterprise; and generate the monthly carbon performance evaluation result of the target enterprise according to the corresponding monthly carbon performance benchmark value and carbon performance correction coefficient of the target enterprise.

[0224] In the scheme of the embodiment of the present invention, the attribute data of each enterprise within the jurisdiction is obtained; the enterprises are clustered in multiple dimensions according to the attribute data to generate an enterprise type database under each segmented scenario of different scales; the monthly carbon performance benchmark value corresponding to each enterprise type is generated according to the carbon emission data of enterprises under each segmented scenario of the same scale in the enterprise type database; the average change rate of weekly carbon emissions of the target enterprise in the current quarter is generated according to the enterprise carbon emission data of the target enterprise to be evaluated; the monthly carbon performance evaluation result of the target enterprise is generated according to the average change rate of weekly carbon emissions of the target enterprise in the quarter and the corresponding monthly carbon performance benchmark value through the correspondence relationship between the weekly carbon emission grade coefficients corresponding to the enterprises in each segmented scenario generated in advance. The carbon data of the enterprises can be classified and managed based on various enterprise types, enterprise scales and segmented scenarios, and the carbon emission reduction performance of the enterprises in different scenarios can be comprehensively considered to improve the practicality and functionality, and accurately evaluate the carbon performance of the enterprises.

[0225] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer device, and specifically, the computer device may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0226] An embodiment of the present invention provides a computer device, including a memory and a processor, the memory is used to store information including program instructions, the processor is used to control the execution of the program instructions, and the program instructions, when loaded and executed by the processor, implement the steps of the embodiment of the above-mentioned enterprise carbon performance assessment method based on segmented scenarios. For a specific description, please refer to the embodiment of the above-mentioned enterprise carbon performance assessment method based on segmented scenarios.

[0227] Reference below Figure 4 , which shows a schematic diagram of the structure of a computer device 600 suitable for implementing an embodiment of the present application.

[0228] like Figure 4 As shown, the computer device 600 includes a central processing unit (CPU) 601, which can perform various appropriate operations and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage part 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the computer device 600 are also stored. The CPU 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0229] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including a cathode ray tube (CRT), a liquid crystal feedback device (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed as needed as the storage section 608.

[0230] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program tangibly contained on a machine-readable medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 609, and / or installed from the removable medium 611.

[0231] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0232] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0233] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0234] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0235] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0236] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0237] The acquisition, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0238] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0239] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0240] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0241] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0242] The above is only the embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method for evaluating corporate carbon performance based on segmented scenarios, characterized in that: The method comprises: Obtain attribute data of each enterprise within the jurisdiction; Perform multi-dimensional clustering of enterprises according to the attribute data to generate enterprise type databases under different scales and various subdivided scenarios; Generate the monthly carbon performance benchmark value corresponding to each enterprise type based on the carbon emission data of enterprises of the same scale in each subdivided scenario in the enterprise type database; Based on the corporate carbon emission data of the target enterprise to be assessed, generate the average change rate of the target enterprise's weekly carbon emissions in the current quarter; By pre-generating the corresponding weekly carbon emission level coefficient correspondence between enterprises in each segmented scenario, the monthly carbon performance evaluation result of the target enterprise is generated according to the average change rate of weekly carbon emissions of the target enterprise within the quarter and the corresponding monthly carbon performance benchmark value.

2. The enterprise carbon performance evaluation method based on segmented scenarios according to claim 1 is characterized in that: The attribute data include business type, number of employees in the enterprise and floor space; The multi-dimensional clustering of enterprises according to the attribute data to generate enterprise type databases under different scales and various segmented scenarios includes: Clustering each enterprise according to the business type to generate enterprise type clustering results; According to the enterprise type clustering results, the scale of the enterprise is divided according to the number of employees and the area occupied by the enterprise, and the enterprise scale clustering results corresponding to each enterprise type are generated; According to the enterprise scale clustering results corresponding to the enterprise types, each enterprise is divided into scenarios, and an enterprise type database under each segmented scenario of different scales is constructed. The dimensions of the enterprise type database include multiple enterprise scales, and each enterprise scale includes at least one segmented scenario.

3. The enterprise carbon performance evaluation method based on segmented scenarios according to claim 1 is characterized in that: The monthly carbon performance benchmark value corresponding to each enterprise type is generated based on the carbon emission data of enterprises under each subdivided scenario of the same scale in the enterprise type database, including: Based on the carbon emission data of enterprises of the same scale in each subdivided scenario in the enterprise type database, generate the corresponding carbon emission reduction, carbon emission change rate in the same period and current monthly carbon emission of enterprises in each subdivided scenario; Based on the carbon emission reduction, the rate of change of carbon emissions during the same period and the current monthly carbon emissions, a monthly carbon performance benchmark value corresponding to each enterprise type is generated.

4. The enterprise carbon performance evaluation method based on segmented scenarios according to claim 3 is characterized in that: The enterprise types include service-oriented enterprises / trade and finance-oriented enterprises, and the segmented scenarios include energy consumption in office spaces; The carbon emission data of enterprises under each subdivided scenario of the same scale in the enterprise type database is used to generate the carbon emission reduction amount, the carbon emission change rate over the same period and the current monthly carbon emission amount corresponding to the enterprise under each subdivided scenario, including: Extract the current month's carbon emissions and historical carbon emissions data for the same period of the current month; The carbon emission change rate and carbon emission reduction amount for the same period are generated according to the current monthly carbon emission and the historical carbon emission data for the same period of the current month.

5. The enterprise carbon performance evaluation method based on segmented scenarios according to claim 3 is characterized in that: The enterprise types include a production enterprise database, and the segmented scenarios include a production process scenario, an energy use scenario, and a raw material procurement scenario; The carbon emission data of enterprises under each subdivided scenario of the same scale in the enterprise type database is used to generate the carbon emission reduction amount, the carbon emission change rate over the same period and the current monthly carbon emission amount corresponding to the enterprise under each subdivided scenario, including: According to the production process scenario, energy use scenario, and raw material procurement scenario, the current monthly carbon emissions and the historical carbon emissions data for the same period of the current month are extracted respectively; Generate the carbon emission change rate and carbon emission reduction of the enterprise in the same period under the production process scenario according to the current monthly carbon emission corresponding to the production process scenario and the historical carbon emission data for the same period of the current month; Generate the carbon emission change rate and carbon emission reduction of the enterprise in the same period under the energy usage scenario according to the current monthly carbon emission corresponding to the energy usage scenario and the historical carbon emission data for the same period of the current month; According to the current monthly carbon emissions corresponding to the raw material procurement scenario and the historical carbon emissions data for the same period of the current month, the carbon emissions change rate and carbon emission reduction corresponding to the enterprise in the raw material procurement scenario are generated.

6. The enterprise carbon performance evaluation method based on segmented scenarios according to claim 3 is characterized in that: The enterprise types include service-oriented enterprises / trade and finance-oriented enterprises, and the segmented scenarios include energy consumption in office spaces; The monthly carbon performance benchmark value corresponding to each enterprise type is generated according to the carbon emission reduction, the carbon emission change rate during the same period and the current monthly carbon emission, including: Through the pre-generated carbon emission reduction grade score correspondence relationship, the carbon emission change rate grade score correspondence relationship over the same period and the current monthly carbon emission grade score correspondence relationship, according to the carbon emission reduction, the carbon emission change rate over the same period and the current monthly carbon emission, a carbon emission reduction score, a carbon emission change rate score over the same period and the current monthly carbon emission score are generated, wherein the carbon emission reduction grade score correspondence relationship, the carbon emission change rate grade score correspondence relationship and the current monthly carbon emission grade score correspondence relationship are obtained by sorting and grading the carbon emission reduction, the carbon emission change rate over the same period and the current monthly carbon emission respectively; Through the preset first weight ratio, according to the carbon emission reduction score, the carbon emission change rate score during the same period and the current monthly carbon emission score, a monthly carbon performance benchmark value corresponding to the service-oriented enterprise / trade finance enterprise is generated.

7. The enterprise carbon performance evaluation method based on segmented scenarios according to claim 3 is characterized in that: The enterprise types include a production enterprise database, and the segmented scenarios include a production process scenario, an energy use scenario, and a raw material procurement scenario; The monthly carbon performance benchmark value corresponding to each enterprise type is generated according to the carbon emission reduction, the carbon emission change rate during the same period and the current monthly carbon emission, including: Through the pre-generated correspondence relationship between the carbon emission reduction grade scores corresponding to the production process scenario, the correspondence relationship between the carbon emission change rate grade scores during the same period, and the correspondence relationship between the carbon emission grade scores of the current month, according to the carbon emission reduction, the carbon emission change rate during the same period, and the current monthly carbon emissions, the carbon emission reduction score, the carbon emission change rate score during the same period, and the current monthly carbon emission score corresponding to the enterprise under the production process scenario are generated; Through the pre-generated correspondence relationship between the carbon emission reduction grade scores corresponding to the energy usage scenarios, the correspondence relationship between the carbon emission change rate grade scores during the same period, and the correspondence relationship between the carbon emission grade scores of the current month, according to the carbon emission reduction, the carbon emission change rate during the same period, and the current monthly carbon emissions, the carbon emission reduction score, the carbon emission change rate score during the same period, and the current monthly carbon emission score corresponding to the enterprise under the energy usage scenario are generated; Through the pre-generated corresponding relationship of carbon emission reduction grade scores, carbon emission change rate grade scores and current monthly carbon emission grade scores corresponding to the raw material procurement scenario, according to the carbon emission reduction, carbon emission change rate and current monthly carbon emissions, the corresponding carbon emission reduction score, carbon emission change rate score and current monthly carbon emission score for the enterprise under the raw material procurement scenario are generated; Generate a comprehensive score corresponding to the enterprise in the production process scenario according to the carbon emission reduction score corresponding to the enterprise in the production process scenario, the carbon emission change rate score during the same period, and the current monthly carbon emission score through a preset second weight ratio; Generate a comprehensive score corresponding to the enterprise under the energy usage scenario through a preset second weight ratio according to the carbon emission reduction score corresponding to the enterprise under the energy usage scenario, the carbon emission change rate score during the same period, and the carbon emission score of the current month; Generate a comprehensive score corresponding to the enterprise in the raw material procurement scenario through a preset second weight ratio according to the carbon emission reduction score corresponding to the enterprise in the raw material procurement scenario, the carbon emission change rate score during the same period, and the carbon emission score of the current month; Through the preset third weight ratio, the monthly carbon performance benchmark value corresponding to the production enterprise is generated according to the comprehensive score corresponding to the enterprise in the production process scenario, the comprehensive score corresponding to the enterprise in the energy use scenario and the comprehensive score corresponding to the enterprise in the raw material procurement scenario.

8. The enterprise carbon performance evaluation method based on segmented scenarios according to claim 1 is characterized in that: The monthly carbon performance evaluation result of the target enterprise is generated according to the pre-generated correspondence relationship of the weekly carbon emission level coefficients corresponding to the enterprise in each segmented scenario, and the average change rate of the weekly carbon emissions of the target enterprise within the quarter and the corresponding monthly carbon performance benchmark value, including: Through the pre-generated correspondence between the weekly carbon emission level coefficients of the enterprise under each segmented scenario, the coefficients are matched according to the average change rate of the weekly carbon emissions of the target enterprise within the quarter to generate the corresponding carbon performance correction coefficient; According to the target enterprise’s enterprise type, query the corresponding monthly carbon performance benchmark value; The monthly carbon performance evaluation result of the target enterprise is generated according to the monthly carbon performance benchmark value and carbon performance correction coefficient corresponding to the target enterprise.

9. A device for evaluating enterprise carbon performance based on segmented scenarios, characterized in that: The device comprises: An attribute data acquisition unit, used to acquire attribute data of each enterprise within the jurisdiction; A multi-dimensional clustering unit, used to perform multi-dimensional clustering on enterprises according to the attribute data, and generate enterprise type databases under different scales and various subdivided scenarios; The benchmark value calculation unit is used to generate the monthly carbon performance benchmark value corresponding to each enterprise type based on the carbon emission data of enterprises under each subdivided scenario of the same scale in the enterprise type database; The average change rate calculation unit is used to generate the average change rate of weekly carbon emissions of the target enterprise in the current quarter based on the corporate carbon emission data of the target enterprise to be evaluated; The carbon performance evaluation unit is used to generate the monthly carbon performance evaluation result of the target enterprise according to the average change rate of the weekly carbon emissions of the target enterprise within the quarter and the corresponding monthly carbon performance benchmark value through the pre-generated correspondence between the weekly carbon emission level coefficients of the enterprise under each segmented scenario.

10. A computer readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the enterprise carbon performance assessment method based on segmented scenarios as described in any one of claims 1 to 8 is implemented.

11. A computer device comprising a memory and a processor, wherein the memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions, characterized in that: When the program instructions are loaded and executed by the processor, the enterprise carbon performance assessment method based on segmented scenarios as described in any one of claims 1 to 8 is implemented.

12. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the enterprise carbon performance assessment method based on segmented scenarios as described in any one of claims 1 to 8 is implemented.

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