An ESG data management method for industrial parks

Abstract

The present invention relates to an ESG data management method for an industrial park, and relates to the technical field of ESG data processing, including: extracting a product type sequence and a supply constraint ratio to obtain a unit output carbon emission sequence; performing multiplication calculation on the supply constraint ratio and the unit output carbon emission sequence to obtain a carbon emission constraint ratio; using a preset time zone enterprise carbon emission forecast value list to deduct the corresponding carbon quota in the enterprise carbon quota list from the total carbon emission of each enterprise to obtain an adaptation vector list; when the number of adaptation vectors greater than 0 is not equal to 0, extracting a set of tradable adaptation vectors that are not equal to 0; using the total carbon emission constraint amount and the carbon emission constraint ratio of the park as a limit, optimizing the trading scheme for the tradable adaptation vector set, obtaining the preset time zone carbon environment management data, and sending it to the ESG data management terminal. This method solves the technical problem that the existing technology does not fully consider the supply and demand of upstream and downstream enterprises, resulting in insufficient refinement of carbon emission management.

Description

Technical Field

[0001] The present invention relates to the technical field of ESG data processing, and in particular to an ESG data management method for an industrial park. Background Art

[0002] Carbon emission management is a key part of ESG data management. Traditional methods mainly control the deviation between the emission and absorption of carbon emissions in the park to ensure that the overall carbon emissions of the park are within a reasonable range.

[0003] However, in modern industrial parks, there are often complex upstream and downstream industrial chain relationships between enterprises. The supply and demand of production between these enterprises need to be balanced to ensure the smooth progress of production. Traditional methods of simply controlling carbon emissions may lead to an imbalance in the supply and demand of production between upstream and downstream enterprises, thereby affecting the overall production efficiency and economic benefits of the park. Summary of the Invention

[0004] The present invention aims to solve the technical problem that the existing technology does not fully consider the production supply and demand of upstream and downstream enterprises, resulting in insufficient refinement of carbon emission management, and provides an industrial park ESG data management method to solve the problem.

[0005] The technical solution of the present invention to solve the above technical problems is as follows:

[0006] The present invention provides an ESG data management method for an industrial park, comprising: extracting a product type sequence and a supply constraint ratio of an industrial park's industrial chain; traversing the product type sequence to count the carbon emissions per unit output of similar products to obtain a unit output carbon emission sequence; multiplying the supply ratio and the unit output carbon emission corresponding to the supply constraint ratio and the unit output carbon emission sequence one by one to obtain a carbon emission constraint ratio; subtracting the corresponding carbon quota in the enterprise carbon quota list from the total carbon emissions of each enterprise in the enterprise carbon emission forecast value list in a preset time zone to obtain an adaptation vector list; when the number of adaptation vectors in the adaptation vector list that is greater than 0 is not equal to 0, extracting a set of tradable adaptation vectors that are not equal to 0; optimizing a trading plan for the tradable adaptation vector set with the total carbon emission constraint of the park and the carbon emission constraint ratio as a limit, obtaining carbon environment management data for the preset time zone, and sending it to an ESG data management terminal.

[0007] The beneficial effects of the present invention are: by analyzing the supply and demand balance relationship between the product type sequence and the supply constraint ratio, the carbon emission constraint ratio is obtained; then the total carbon emissions of each enterprise in the enterprise carbon emission forecast value list of the preset time zone is subtracted from the corresponding carbon quota in the enterprise carbon quota list to obtain an adaptation vector list. If carbon trading is required, the carbon emission constraint ratio is taken into consideration to avoid carbon quota imbalance, thereby achieving the technical effect of improving the degree of refinement of carbon environmental management. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 A flowchart of an ESG data management method for an industrial park provided by the present invention;

[0009] Figure 2 A schematic diagram of the process for obtaining the unit output carbon emission sequence of an industrial park ESG data management method provided by the present invention. DETAILED DESCRIPTION

[0010] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0011] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the specified features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0012] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration or illustration". Any embodiment of the present invention described as "for example" is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any person skilled in the art to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed herein.

[0013] like Figure 1 As shown, an embodiment of the present invention provides an industrial park ESG data management method, including the steps of:

[0014] S10: Extract product type sequence and supply constraint ratio of industrial chain in the park;

[0015] Specifically, the product type sequence refers to the sequence of products in the industrial park arranged according to the upstream and downstream relationships of the industrial chain; the supply constraint ratio refers to the proportional relationship between the supply and demand of a certain product in the upstream and downstream supply and demand production process of the industrial chain. It reflects the supply and demand balance of the product in the industrial chain and is an important indicator to measure whether the production activities are sustainable.

[0016] For example, suppose there are three upstream and downstream enterprises A, B, and C in an industrial park. Enterprise A produces raw materials, Enterprise B processes raw materials into semi-finished products, and Enterprise C processes semi-finished products into final products. Enterprise A produces 100 tons of raw materials per month, Enterprise B needs 80 tons of raw materials per month, and Enterprise C needs 70 tons of semi-finished products per month. By extracting data, we get the product type sequence: raw materials, semi-finished products, and final products. The supply constraint ratio is calculated: the supply constraint ratio of raw materials is 100:80:70 = 10:8:7.

[0017] By analyzing the product type sequence and supply constraint ratio, the supply and demand relationship of each product in the park can be clarified, which in turn provides support for the refinement of carbon emission management and avoids the imbalance of supply and demand of upstream and downstream enterprises caused by simply controlling carbon emissions.

[0018] S20: traverse the product type sequence to count the carbon emissions per unit output of similar products to obtain a carbon emissions per unit output sequence;

[0019] Further, such as Figure 2 As shown, the product type sequence is traversed to count the carbon emissions per unit output of similar products to obtain a carbon emissions per unit output sequence. Step S20 includes the following steps:

[0020] S21: Extract the product type sequence, extract the first product type, wherein the first product type has a device tag;

[0021] S22: Collecting carbon emission record data per unit of production of the first product type produced by the device tag, calculating a central value of the carbon emission record data per unit of production, and obtaining carbon emission per unit of production of the first product type;

[0022] S23: Add the carbon emissions per unit output of the first product type to the carbon emissions per unit output sequence.

[0023] Specifically, carbon emissions per unit of production refer to the carbon emissions generated by producing a unit quantity of product, usually expressed in kilograms of carbon dioxide equivalent (kgCO2e). The historical carbon emissions per unit of production of the same product produced by the same equipment are counted to obtain a carbon emissions per unit of production sequence. The detailed process is as follows:

[0024] The equipment tag is an identifier associated with the production equipment of the first product type within the park, used to distinguish different equipment or equipment groups. The first product type refers to any product type in the product type sequence. Unit production carbon emissions record data refers to the historical unit production carbon emissions data related to the production of the first product type, collected from the production equipment using the equipment tag. The unit production carbon emissions of the first product type are calculated by averaging the unit production carbon emissions data and added to the unit production carbon emissions sequence. The same process is then performed on the other product types in the product type sequence, and once all processing is complete, the unit production carbon emissions sequence is output.

[0025] For example, let's assume there are three types of products in an industrial park: raw materials, semi-finished products, and finished products. Each product type has a corresponding equipment tag. The following are the specific steps and data:

[0026] Extract product type sequence: Obtain product type sequence from the production management system: [raw materials, semi-finished products, final products]; Extract the first product type: Extract the first product type - raw materials, whose equipment label is "equipment 1"; Collect unit output carbon emission record data: Through the equipment label "equipment 1", collect unit output carbon emission data in the raw material production process, assuming that the collected data is: [45, 50, 55, 48, 52] kgCO2e / ton; Calculate the concentration value: Calculate the average value of the above data and obtain the unit output carbon emission of raw materials as 50 kgCO2e / ton; Add to the unit output carbon emission sequence: Add the unit output carbon emission of raw materials 50 kgCO2e / ton to the unit output carbon emission sequence to obtain the sequence:

[50] ; Repeat the above steps to process the semi-finished products and final products respectively. Assume that the unit output carbon emission of semi-finished products is 30 kgCO2e / ton and the unit output carbon emission of final products is 20 kgCO2e / ton. The final unit output carbon emission sequence is: [50, 30, 20].

[0027] By accurately collecting carbon emission data through equipment labels and calculating centralized values, we can ensure that the statistics of carbon emissions per unit of output are more accurate.

[0028] S30: Calculating the product of the supply quantity constraint ratio and the unit output carbon emission sequence in one-to-one correspondence between the supply quantity constraint ratio and the unit output carbon emission sequence to obtain the carbon emission constraint ratio;

[0029] Specifically, the carbon emission constraint ratio represents the carbon emission constraint of each product under the consideration of supply and demand balance, and is preferably calculated by multiplying the supply constraint ratio and the carbon emission per unit output sequence by the product of the supply ratio and the carbon emission per unit output. For example, assuming that there are three types of products in an industrial park: raw materials, semi-finished products and final products, the supply constraint ratio is 10:8:7, and the carbon emissions per unit output are 50kgCO2e / ton (raw materials), 30kgCO2e / ton (semi-finished products) and 20kgCO2e / ton (final products), respectively; extract the supply constraint ratio: the supply constraint ratio of raw materials is 10, the supply constraint ratio of semi-finished products is 8, and the supply constraint ratio of final products is 7; extract the carbon emissions per unit output: the carbon emissions per unit output of raw materials is 50kgCO2e / ton, the carbon emissions per unit output of semi-finished products is 30kgCO2e / ton, and the carbon emissions per unit output of final products is 20kgCO2e / ton; perform the product calculation:

[0030] Carbon emission constraint ratio of raw materials = 10 × 50 = 500kgCO2e / ton;

[0031] Carbon emission constraint ratio of semi-finished products = 8 × 30 = 240kgCO2e / ton;

[0032] The carbon emission constraint ratio of the final product = 7 × 20 = 140kgCO2e / ton.

[0033] Developing a carbon emission constraint ratio: Arrange the calculated carbon emission constraint ratios by product type, forming a carbon emission constraint ratio of 500:240:140 = 25:12:7. By calculating the carbon emission constraint ratio, we can clearly define the carbon emission limits for each product during the production process, providing data support for subsequent carbon emission constraint calculations and carbon trading scheme optimization.

[0034] S40: Obtain an adaptation vector list by subtracting the corresponding carbon quota in the enterprise carbon quota list from the total carbon emissions of each enterprise in the enterprise carbon emission prediction value list of the preset time zone;

[0035] Furthermore, the total carbon emissions of each enterprise in the enterprise carbon emission forecast value list of the preset time zone is subtracted from the corresponding carbon quota in the enterprise carbon quota list to obtain the adaptation vector list, which previously included:

[0036] Obtain a list of reported product types and a list of reported outputs of the first enterprise in a preset time zone, perform carbon emission statistics, and obtain a list of predicted carbon emission values ​​for each enterprise;

[0037] Adding the enterprise carbon emission forecast values ​​in the first enterprise carbon emission forecast value list to obtain the total carbon emission forecast value of the first enterprise;

[0038] Adding the first enterprise's carbon emission forecast value list and the first enterprise's total carbon emission forecast value to the first enterprise's carbon emission forecast value;

[0039] The first enterprise carbon emission forecast value is added to the enterprise carbon emission forecast value list.

[0040] Specifically, the preset time zone refers to a pre-set time range used for statistics and forecasting of carbon emissions data, for example, it can be a month, a quarter, or a year. The enterprise carbon emissions forecast value list refers to a list of carbon emissions expected to be generated by each enterprise within the preset time zone. These forecast values ​​are usually calculated based on the enterprise's production plan and historical carbon emissions data. The enterprise carbon quota list refers to a list of carbon emission quotas allocated to each enterprise. The carbon quota is the carbon emission cap allocated by the management unit based on the enterprise's production scale and industry standards. The adaptation vector list refers to a list of differences between each enterprise's total carbon emissions forecast value and its carbon quota. This difference reflects the surplus or deficit of the enterprise's carbon emissions within the preset time zone. The reported product type list and reported output list refer to the product type and output data reported by the enterprise to the industrial park management agency, which are used to calculate the enterprise's carbon emissions.

[0041] The specific process is as follows: Taking the first enterprise as an example, the product type and output data produced by the first enterprise in a preset time zone are obtained from the enterprise's production management system; based on the product type and output reported by the first enterprise, the carbon emissions per unit output of each product type are analyzed using the same analysis method as described above, and the carbon emissions of each product are multiplied by the output to obtain the carbon emissions of each product, forming a list of sub-carbon emission prediction values; all carbon emissions in the sub-carbon emission prediction value list are added together to obtain the total carbon emission prediction value of the first enterprise in the preset time zone; the sub-carbon emission prediction value list and the total carbon emission prediction value are integrated into the carbon emission prediction value of the first enterprise, and the carbon emission prediction value of the first enterprise is added to the enterprise carbon emission prediction value list of the entire industrial park. Furthermore, when all enterprises in the park are analyzed, the enterprise carbon emission prediction value list is output. Furthermore, the total carbon emissions of each enterprise in the enterprise carbon emission prediction value list for the preset time zone are subtracted from the corresponding carbon quota in the enterprise carbon quota list, and the calculation result is stored as an adaptation vector list.

[0042] For example, assume there are two companies in an industrial park: Company A and Company B. The preset time zone is one month. The following are the specific steps and data:

[0043] Company A reports a list of product types: [Raw materials, Semi-finished products, Final products]; Company A reports a list of production outputs: [100 tons, 80 tons, 70 tons]; Furthermore, the carbon emissions per unit of raw material output is 50 kg CO2e / ton; the carbon emissions per unit of semi-finished product output is 30 kg CO2e / ton; and the carbon emissions per unit of final product output is 20 kg CO2e / ton; Furthermore, Company A's carbon emissions forecast list is: [5000 kg CO2e, 2400 kg CO2e, 1400 kg CO2e]; Adding the carbon emissions forecasts from the first company's carbon emissions forecast list gives the total carbon emissions forecast for the first company: Company A's total carbon emissions forecast = 5000 + 2400 + 1400 = 8800kgCO2e; add the first enterprise's carbon emissions forecast value list and the first enterprise's total carbon emissions forecast value to the first enterprise's carbon emissions forecast value: Enterprise A's carbon emissions forecast value: {carbon emissions forecast value list: [5000, 2400, 1400], total carbon emissions forecast value: 8800}; add the first enterprise's carbon emissions forecast value to the enterprise carbon emissions forecast value list: Enterprise carbon emissions forecast value list: [{Enterprise A: {carbon emissions forecast value list: [5000,2400, 1400], total carbon emissions forecast value: 8800}}]. Assuming that Enterprise A's carbon quota is 8000kgCO2e, then Enterprise A's adaptation vector is: adaptation vector = total carbon emissions forecast value - carbon quota = 8800 - 8000 = 800kgCO2e.

[0044] By calculating the adaptation vector for each enterprise, the surplus or deficit of the enterprise's carbon emissions within the preset time zone can be clearly identified, providing data support for subsequent carbon trading plans. At the same time, the adaptation vector list also provides industrial park managers with an intuitive carbon emission management situation, which helps to identify enterprises with excessive carbon emissions and then take targeted emission reduction measures.

[0045] S50: When the number of adaptation vectors in the adaptation vector list that is greater than 0 is not equal to 0, extracting a set of tradable adaptation vectors that is not equal to 0;

[0046] Specifically, the tradable adaptation vector set refers to a set of enterprises extracted from the adaptation vector list whose adaptation vector values ​​are not equal to 0. These enterprises have a carbon emission deficit (positive value) or surplus (negative value) and can participate in carbon trading. When the number of adaptation vectors greater than 0 in the adaptation vector list is not equal to 0, it means that the enterprises have carbon emissions exceeding the carbon quota and need to optimize carbon emissions. Therefore, extracting the tradable adaptation vector set that is not equal to 0 facilitates the subsequent optimization of trading plans.

[0047] For example, assume that there are three companies in an industrial park: Company A, Company B, and Company C. The preset time zone is one month, and the adaptation vector list is as follows:

[0048] Company A: Adaptation vector = 800kgCO2e (insufficient carbon emissions, need to purchase carbon quotas)

[0049] Company B: Adaptation vector = -500kgCO2e (carbon emission surplus, carbon quota can be sold)

[0050] Company C: Adaptation vector = 0kgCO2e (carbon emissions and quotas are balanced)

[0051] Check the adaptation vector list: traverse the adaptation vector list and check the adaptation vector value of each enterprise; extract adaptation vectors that are not equal to 0: extract enterprises whose adaptation vectors are not equal to 0 to form a tradable adaptation vector set: tradable adaptation vector set: {Enterprise A: 800kgCO2e, Enterprise B: -500kgCO2e}; classify tradable adaptation vectors: classify the enterprises in the tradable adaptation vector set according to the positive or negative value of the adaptation vector: positive tradable adaptation vector set: {Enterprise A: 800kgCO2e} (insufficient carbon emissions, need to purchase carbon quotas); negative tradable adaptation vector set: {Enterprise B: -500kgCO2e} (carbon emissions surplus, can sell carbon quotas).

[0052] By extracting a set of tradable adaptation vectors, we can identify which companies need to participate in carbon trading, providing data support for subsequent optimization of trading plans.

[0053] S60: Based on the total carbon emission constraint of the park and the carbon emission constraint ratio, optimize the trading scheme for the tradable adaptation vector set, obtain the carbon environment management data of the preset time zone, and send it to the ESG data management terminal.

[0054] Furthermore, based on the total carbon emission constraint of the park and the carbon emission constraint ratio, a trading solution optimization is performed on the tradable adaptation vector set to obtain carbon environment management data for a preset time zone, including:

[0055] Grouping the tradable adaptation vector set according to positive and negative numbers to obtain a positive tradable adaptation vector set and a negative tradable adaptation vector set;

[0056] An adaptation vector modulus transaction is performed with the negative tradable adaptation vector set as the delivery party and the positive tradable adaptation vector set as the delivery party. When the sum of the delivery party's sold adaptation vector moduli is greater than or equal to the sum of the delivery party's initial adaptation vector moduli, an initial transaction plan is obtained.

[0057] Adjusting the enterprise carbon quota list according to the initial trading plan to obtain an updated enterprise carbon quota list;

[0058] When the updated enterprise carbon quota list meets the carbon emission constraint ratio and the total carbon emission constraint of the industrial park, the initial trading plan is added to the candidate trading plans;

[0059] Optimize the trading options according to the selected trading options to obtain carbon environment management data in a preset time zone.

[0060] Furthermore, the optimal trading scheme is searched based on the selected trading scheme to obtain carbon environment management data in a preset time zone, including:

[0061] The transaction solution to be selected includes updating a set of tradable adaptation vectors;

[0062] Constructing a transaction solution fitness function, wherein the transaction solution fitness function is used to calculate the sum of positive numbers of the updated tradable adaptation vector set;

[0063] Based on the transaction scheme fitness function, the minimum value of the transaction scheme to be selected is optimized to obtain the carbon environment management data of the preset time zone.

[0064] Specifically, the total carbon emission constraint of the industrial park refers to the maximum total carbon emissions allowed by the industrial park within a preset time zone. This value is usually set according to the park's carbon neutrality target and actual carbon absorption capacity; trading scheme optimization refers to finding the optimal carbon trading scheme under the premise of meeting the total carbon emission constraint and carbon emission constraint ratio of the industrial park, so as to achieve a reasonable distribution of carbon emissions and minimize carbon trading costs; trading scheme fitness function is a function used to evaluate the pros and cons of trading schemes, which usually calculates the sum of positive numbers in the updated set of tradable fitness vectors to determine whether the trading scheme is optimal;

[0065] The specific process is as follows: the enterprises in the tradable adaptation vector set are classified according to the positive or negative value of the adaptation vector: the positive tradable adaptation vector set represents enterprises with insufficient carbon emissions (need to purchase carbon quotas); the negative tradable adaptation vector set represents enterprises with surplus carbon emissions (can sell carbon quotas); the adaptation vector modulus transaction is carried out: the enterprises in the negative tradable adaptation vector set are the delivery parties, and the enterprises in the positive tradable adaptation vector set are the delivery parties, and the adaptation vector modulus transaction is carried out; when the sum of the delivery party's sold adaptation vector moduli is greater than or equal to the sum of the initial adaptation vector moduli of the delivery party, the initial transaction plan is obtained; the enterprise carbon quota list is adjusted: according to the initial transaction plan, the enterprise carbon quota list is adjusted to obtain an updated enterprise carbon quota list; verify whether the updated enterprise carbon quota list meets the constraints: check whether the updated enterprise carbon quota list meets the carbon emission constraint ratio and the total carbon emission constraint of the park; if so, the initial transaction plan is added to the candidate transaction plan. When the candidate transaction plan is greater than or equal to the user-preset generation quantity, all the candidate transaction plans are output.

[0066] Furthermore, the trading scheme is optimized: a trading scheme fitness function is constructed to calculate and update the sum of positive numbers in the set of tradable adaptation vectors; based on the trading scheme fitness function, all candidate trading schemes are optimized for the minimum value to obtain the optimal carbon environmental management data for the preset time zone.

[0067] For example, assume that there are three companies in an industrial park: Company A, Company B, and Company C. The preset time zone is one month. The adaptation vector list is as follows: Company A: Adaptation vector = 800kgCO2e (insufficient carbon emissions, need to purchase carbon quotas); Company B: Adaptation vector = -500kgCO2e (carbon emissions surplus, carbon quotas can be sold); Company C: Adaptation vector = -300kgCO2e (carbon emissions surplus, carbon quotas can be sold).

[0068] The tradable adaptation vector set is grouped according to positive and negative: positive tradable adaptation vector set: {Company A: 800kgCO2e}; negative tradable adaptation vector set: {Company B: -500kgCO2e, Company C: -300kgCO2e}.

[0069] Conduct an adaptive vector modulus transaction: the sum of the sold adaptive vector moduli of the delivery parties (Enterprise B and Enterprise C) = 500 + 300 = 800 kgCO2e; the sum of the initial adaptive vector moduli of the consignee (Enterprise A) = 800 kgCO2e. Since the sum of the sold adaptive vector moduli of the delivery parties is equal to the sum of the initial adaptive vector moduli of the consignee, the initial transaction plan is obtained: Enterprise B sells 500 kgCO2e to Enterprise A; Enterprise C sells 300 kgCO2e to Enterprise A.

[0070] Adjustment of corporate carbon quota list: Updated corporate carbon quota list: Company A: carbon quota increased by 800kgCO2e; Company B: carbon quota decreased by 500kgCO2e; Company C: carbon quota decreased by 300kgCO2e.

[0071] Verify whether the updated enterprise carbon quota list meets the constraints: Assume that the total carbon emission constraint of the park is 10,000 kgCO2e and the carbon emission constraint ratio is [500, 300, 200]. Since 800 / 500 ≈ 500 / 300 and 500 / 300 > 300 / 200, the updated enterprise carbon quota list meets the carbon emission constraint ratio and the total carbon emission constraint of the park. Add the initial trading plan to the candidate trading plan.

[0072] Optimizing the trading plan: Constructing the trading plan fitness function, calculating and updating the sum of positive numbers in the set of tradable adaptation vectors:

[0073] Transaction plan 1: Company B sells 500kgCO2e and Company C sells 300kgCO2e. Transaction plan 2: Company B sells 800kgCO2e (assuming Company B has sufficient surplus).

[0074] Based on the transaction plan fitness function, all candidate transaction plans are optimized for the minimum value: the sum of positive numbers of plan 1 = 0; the sum of positive numbers of plan 2 = 0; plan 1 is selected as the optimal transaction plan.

[0075] Industrial park managers can ensure the rational distribution of carbon emissions, minimize carbon trading costs, and improve the sophistication of carbon environmental management while meeting the park's carbon emission constraints.

[0076] Furthermore, the total amount of the park's carbon emission constraints is limited to the ratio of the carbon emission constraints, which previously included:

[0077] Interact with the ESG data management terminal to obtain the vegetation coverage status and wetland coverage status of the park;

[0078] Sampling the vegetation coverage state and the wetland coverage state in a preset time zone to obtain a park carbon absorption record data set;

[0079] A centralized value evaluation is performed on the park carbon absorption record data set to obtain a park carbon absorption prediction value, wherein the park carbon emission constraint total is less than or equal to the park carbon absorption prediction value.

[0080] Specifically, vegetation coverage status refers to the distribution and growth of vegetation within the industrial park, which is usually measured by indicators such as vegetation coverage rate and vegetation type. Vegetation coverage status directly affects the carbon absorption capacity of the park; wetland coverage status refers to the distribution and area of ​​wetlands within the industrial park. Wetlands are important carbon sinks that can absorb and store large amounts of carbon dioxide; preset time zone sampling: within a preset time range, data on vegetation coverage status and wetland coverage status are collected to obtain relevant data on the park's carbon absorption; park carbon absorption record data set: the original data set of the park's carbon absorption obtained through sampling, which is used for subsequent analysis and evaluation; central value evaluation: statistical analysis is performed on the park's carbon absorption record data set to calculate its central trend (such as mean, median, etc.) to obtain the predicted value of the park's carbon absorption.

[0081] The specific process is as follows: Interacting with the ESG data management terminal: Obtaining the park's vegetation cover and wetland cover status data from the ESG data management terminal. This data typically includes information such as vegetation coverage rate, vegetation type, and wetland area. Preset time zone sampling: Sampling vegetation cover and wetland cover status within a preset time range (such as one month, one quarter, etc.). Sampling can be carried out through remote sensing technology, ground monitoring stations, etc., to obtain relevant data on the park's carbon absorption. Obtaining the park's carbon absorption record data set: Organizing the sampled data into a park carbon absorption record data set. This data reflects the carbon absorption of vegetation and wetlands in the park within the preset time zone. Concentration value assessment: Statistically analyzing the park's carbon absorption record data set and calculating its concentration value (such as mean, median, etc.) to obtain a predicted value for the park's carbon absorption. This predicted value reflects the amount of carbon the park is expected to absorb within the preset time zone. Determining the park's total carbon emission constraint: Determining the park's total carbon emission constraint based on the predicted park carbon absorption value. The total carbon emission constraints of the park should be less than or equal to the predicted value of the park's carbon absorption to ensure that the park achieves carbon neutrality within the preset time zone.

[0082] By interacting with the ESG data management terminal, obtaining the vegetation and wetland coverage status, and performing preset time zone sampling and centralized value assessment, the total carbon emission constraint of the industrial park can be scientifically determined, providing data support for subsequent carbon emission management and carbon trading, and ensuring the sustainable development of the industrial park.

[0083] Furthermore, the vegetation coverage state and the wetland coverage state are sampled in preset time zones to obtain a park carbon absorption record data set, including:

[0084] Performing same-coverage-state sampling with the vegetation cover state and the wetland cover state as first-level constraints to obtain a first-level park carbon absorption record dataset, wherein the first-level park carbon absorption record dataset has a first-level vegetation cover state label set and a first-level wetland cover state label set;

[0085] Traversing the first-level park carbon absorption record data set, performing same-coverage state sampling with the first-level vegetation cover state label set and the first-level wetland cover state label set as second-level constraints, and obtaining multiple sets of second-level park carbon absorption record data;

[0086] The plurality of sets of secondary park carbon absorption record data are traversed to perform centralized value evaluation, and a plurality of secondary park carbon absorption record data are obtained, and the data are added to the primary park carbon absorption record data set to obtain the park carbon absorption record data set.

[0087] Specifically, the first-level constraint refers to the preliminary classification and sampling based on the vegetation cover status and wetland cover status during the sampling process. These statuses serve as first-level constraint conditions and are used to screen out data sets with similar characteristics; the first-level park carbon absorption record data set refers to the preliminary carbon absorption data set obtained by sampling with the same coverage status under the first-level constraint conditions. This data set contains carbon absorption records with similar vegetation and wetland cover status, and is accompanied by corresponding vegetation and wetland cover status labels; the second-level constraint refers to further sampling based on the vegetation cover status label set and the wetland cover status label set on the basis of the first-level data set. This step is to ensure the sufficiency of the data volume of the carbon absorption data set involved in the analysis; the second-level park carbon absorption record data set refers to the carbon absorption data set obtained by sampling with the same coverage status under the second-level constraint conditions; the central value assessment refers to the statistical analysis of the second-level park carbon absorption record data and the calculation of its central trend (such as mean, median, etc.) to obtain a more accurate carbon absorption assessment value.

[0088] Through two-level constrained sampling, the data volume of the carbon absorption record dataset was increased and the accuracy of the statistical results was improved.

[0089] Furthermore, it also includes: when the number of adaptation vectors greater than 0 in the adaptation vector list is equal to 0, generating a preset time zone carbon environment balance identifier and sending it to the ESG data management terminal.

[0090] Specifically, the carbon balance indicator for a preset time zone is a special signal or marker that indicates that within the preset time zone, all companies' carbon emissions and carbon allowances have reached a balance, meaning no company needs to buy or sell carbon allowances. The ESG data management platform refers to the industrial park's environmental, social, and governance (ESG) data management platform, which receives and processes various ESG-related data and indicators. By generating the carbon balance indicator, it is clear whether the industrial park has achieved carbon balance within the preset time zone.

[0091] The embodiment of the present invention provides an industrial park ESG data management method, which has at least the following technical effects:

[0092] By analyzing the supply and demand balance relationship between the product type sequence and the supply constraint ratio, the carbon emission constraint ratio is obtained; then, the total carbon emissions of each enterprise in the enterprise carbon emission forecast value list of the preset time zone is subtracted from the corresponding carbon quota in the enterprise carbon quota list to obtain the adaptation vector list. If carbon trading is required, the carbon emission constraint ratio is taken into consideration to avoid carbon quota imbalance, thereby achieving the technical effect of improving the level of refinement of carbon environmental management.

[0093] It should be noted that, in the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0094] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, approaches, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0095] The present invention is described with reference to flowcharts and / or block diagrams of methods, apparatus (methods), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, 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 computer, 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 flowcharts and / or block diagrams. 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.

[0096] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work 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 The function specified in one or more boxes.

[0097] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0098] Although preferred embodiments of the present invention have been described, additional changes and modifications to these embodiments may occur to those skilled in the art once the basic inventive concepts become known.

[0099] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for managing ESG data in an industrial park, characterized in that: include: Extract the product type sequence and supply constraint ratio of the industrial chain of the industrial park. The product type sequence refers to the sequence of products in the industrial park according to the upstream and downstream relationships of the industrial chain. The supply constraint ratio refers to the proportional relationship between the supply and demand of a certain product in the upstream and downstream supply and demand production process of the industrial chain. Traversing the product type sequence to count the carbon emissions per unit output of similar products to obtain a carbon emissions per unit output sequence; Calculating the product of the supply quantity constraint ratio and the unit output carbon emission sequence in one-to-one correspondence between the supply quantity constraint ratio and the unit output carbon emission sequence to obtain the carbon emission constraint ratio; Obtain an adaptation vector list by subtracting the corresponding carbon quota from the total carbon emissions of each enterprise in the enterprise carbon quota list using the enterprise carbon emission forecast value list of the preset time zone; When the number of adaptation vectors in the adaptation vector list that is greater than 0 is not equal to 0, extracting a set of tradable adaptation vectors that is not equal to 0; Based on the total carbon emission constraint of the industrial park and the carbon emission constraint ratio, the trading scheme of the tradable adaptation vector set is optimized to obtain the carbon environment management data of the preset time zone and send it to the ESG data management terminal; The process of optimizing the trading scheme for the set of tradable adaptation vectors based on the total carbon emission constraint of the industrial park and the carbon emission constraint ratio is performed to obtain carbon environment management data for a preset time zone, including: Grouping the tradable adaptation vector set according to positive and negative numbers to obtain a positive tradable adaptation vector set and a negative tradable adaptation vector set; An adaptation vector modulus transaction is performed with the negative tradable adaptation vector set as the delivery party and the positive tradable adaptation vector set as the delivery party. When the sum of the delivery party's sold adaptation vector moduli is greater than or equal to the sum of the delivery party's initial adaptation vector moduli, an initial transaction plan is obtained. Adjusting the enterprise carbon quota list according to the initial trading plan to obtain an updated enterprise carbon quota list; When the updated enterprise carbon quota list meets the carbon emission constraint ratio and the total carbon emission constraint of the industrial park, the initial trading plan is added to the candidate trading plans; Searching for the best trading plan based on the selected trading plans to obtain carbon environment management data for a preset time zone; The process of optimizing the trading scheme according to the selected trading scheme and obtaining the carbon environment management data for the preset time zone includes: The transaction solution to be selected includes updating a set of tradable adaptation vectors; Constructing a transaction solution fitness function, wherein the transaction solution fitness function is used to calculate the sum of positive numbers of the updated tradable adaptation vector set; Based on the transaction scheme fitness function, the minimum value of the transaction scheme to be selected is optimized to obtain the carbon environment management data of the preset time zone.

2. The method according to claim 1, wherein Traverse the product type sequence to count the carbon emissions per unit output of similar products to obtain a carbon emissions per unit output sequence, including: Extracting the product type sequence, extracting a first product type, wherein the first product type has a device tag; Collecting carbon emission record data per unit of output of the first product type produced by the device tag, calculating a central value of the carbon emission record data per unit of output, and obtaining carbon emission per unit of output of the first product type; The carbon emissions per unit of output of the first product type are added to the carbon emissions per unit of output sequence.

3. The method according to claim 1, wherein The adaptation vector list is obtained by subtracting the corresponding carbon quota from the enterprise carbon quota list from the total carbon emissions of each enterprise in the enterprise carbon emission forecast value list of the preset time zone. The previous list includes: Obtain a list of reported product types and a list of reported outputs of the first enterprise in a preset time zone, perform carbon emission statistics, and obtain a list of predicted carbon emission values ​​for each enterprise; Adding the enterprise carbon emission forecast values ​​in the first enterprise carbon emission forecast value list to obtain the total carbon emission forecast value of the first enterprise; Adding the first enterprise's carbon emission forecast value list and the first enterprise's total carbon emission forecast value to the first enterprise's carbon emission forecast value; The first enterprise carbon emission forecast value is added to the enterprise carbon emission forecast value list.

4. The method according to claim 1, wherein The ratio of the total carbon emission constraint of the park to the carbon emission constraint is limited, and previously included: Interact with the ESG data management terminal to obtain the vegetation coverage status and wetland coverage status of the park; Sampling the vegetation coverage state and the wetland coverage state in a preset time zone to obtain a park carbon absorption record data set; A centralized value evaluation is performed on the park carbon absorption record data set to obtain a park carbon absorption prediction value, wherein the park carbon emission constraint total is less than or equal to the park carbon absorption prediction value.

5. The method according to claim 4, wherein The vegetation coverage state and the wetland coverage state are sampled in preset time zones to obtain a park carbon absorption record data set, including: Performing same-coverage-state sampling with the vegetation cover state and the wetland cover state as first-level constraints to obtain a first-level park carbon absorption record dataset, wherein the first-level park carbon absorption record dataset has a first-level vegetation cover state label set and a first-level wetland cover state label set; Traversing the first-level park carbon absorption record data set, performing same-coverage state sampling with the first-level vegetation cover state label set and the first-level wetland cover state label set as second-level constraints, and obtaining multiple sets of second-level park carbon absorption record data; The plurality of sets of secondary park carbon absorption record data are traversed to perform centralized value evaluation, and a plurality of secondary park carbon absorption record data are obtained, and the data are added to the primary park carbon absorption record data set to obtain the park carbon absorption record data set.

6. The method according to claim 1, wherein Also includes: When the number of adaptation vectors greater than 0 in the adaptation vector list is equal to 0, a preset time zone carbon environment balance identifier is generated and sent to the ESG data management terminal.

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