Industrial park ESG data management method

Abstract

The invention relates to an industrial park ESG data management method, and relates to the technical field of ESG data processing, and the method comprises the steps: extracting a product type sequence and a supply constraint ratio, and obtaining a unit yield carbon emission sequence; carrying out product calculation on the supply quantity constraint ratio and the unit yield carbon emission sequence to obtain a carbon emission constraint ratio; subtracting the corresponding carbon quota of the enterprise carbon quota list from each enterprise total carbon emission in the enterprise carbon emission prediction value list of the preset time zone to obtain an adaptation vector list; when the number of the adaptation vectors greater than 0 is not equal to 0, extracting a tradable adaptation vector set which is not equal to 0; and by taking the park carbon emission constraint total amount and the carbon emission constraint ratio as a limit, carrying out transaction scheme optimization on the tradable adaptation vector set, obtaining preset time zone carbon environment management data, and sending the preset time zone carbon environment management data to an ESG data management end. The technical problem that in the prior art, due to the fact that upstream and downstream enterprise yield supply and demand are not fully considered, the carbon emission management refinement degree is insufficient is solved.

Description

Technical Field

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

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

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

[0004] In view of the technical problem that the existing technology has insufficient refinement in carbon emission management due to the lack of full consideration of the supply and demand of production volume between upstream and downstream enterprises, the present invention provides an ESG data management method for industrial parks to solve this problem.

[0005] The technical solution of the present invention to solve the above technical problems is as follows: The present invention provides an ESG data management method for industrial parks, including: extracting the product type sequence and supply quantity constraint ratio of the park's industrial chain; traversing the product type sequence to count the carbon emissions per unit of production of the same type of product, and obtaining the carbon emissions per unit of production sequence; calculating the product of the supply quantity ratio and the carbon emissions per unit of production corresponding to the supply quantity constraint ratio and the carbon emissions per unit of production sequence one by one to obtain the carbon emission constraint ratio; using each enterprise's total carbon emissions in the enterprise carbon emissions prediction value list in the preset time zone minus the corresponding carbon quota in the enterprise carbon quota list to obtain the adaptation vector list; when the number of adaptation vectors greater than 0 in the adaptation vector list is not equal to 0, extracting the set of tradable adaptation vectors that are not equal to 0; optimizing the trading plan for the set of tradable adaptation vectors within the limit of the total carbon emission constraint of the park and the carbon emission constraint ratio to obtain the carbon environment management data in the preset time zone, and sending it to the ESG data management terminal.

[0006] The beneficial effect of the present invention is: by analyzing the supply and demand balance relationship between the product type sequence and the supply quantity constraint ratio, the carbon emission constraint ratio is obtained; then, each enterprise's total carbon emissions in the enterprise carbon emissions prediction value list in the preset time zone minus the corresponding carbon quota in the enterprise carbon quota list to obtain the adaptation vector list. When carbon trading is required, the carbon emission constraint ratio is considered to avoid carbon quota imbalance, achieving the technical effect of improving the refinement of carbon environment management. Description of the Drawings

[0007] Figure 1 Schematic flow chart of an ESG data management method for industrial parks provided by the present invention; Figure 2 Schematic flow chart for obtaining the carbon emission per unit output sequence of an ESG data management method for industrial parks provided by the present invention. Detailed implementation manners

[0008] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts fall within the protection scope of the present invention.

[0009] In the description of the present invention, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality of" means two or more, unless otherwise specifically defined.

[0010] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration, or explanation". Any embodiment described as "for example" in the present invention is not necessarily construed as being more preferred or more advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the present invention. In the following description, details are set forth for purposes of explanation. It should be understood that those skilled in the art can recognize that the present invention can be implemented without using these specific details. In other instances, well-known structures and processes are not elaborated in detail to avoid unnecessary details from obscuring the description of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.

[0011] As Figure 1 shown, the embodiments of the present invention provide an ESG data management method for industrial parks, including the steps of: S10: Extract the product type sequence and supply quantity constraint ratio of the park's industrial chain; Specifically, the product type sequence refers to the sequence in which the products in the industrial park are arranged according to the upstream and downstream relationships of the industrial chain; the supply quantity constraint ratio refers to the proportional relationship between the supply quantity and the demand quantity of a certain product during the supply and demand production process of the upstream and downstream of the industrial chain, reflecting the supply and demand balance state of the product in the industrial chain, and is an important indicator for measuring the sustainability of production activities.

[0012] Exemplarily, assume that there are three upstream and downstream enterprises, namely A, B, and C, in an industrial park. Enterprise A produces raw materials, enterprise B processes the raw materials into semi-finished products, and enterprise C processes the 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, the product type sequence is obtained: raw materials, semi-finished products, and final products. Calculate the supply quantity constraint ratio: the supply quantity constraint ratio of raw materials is 100:80:70 = 10:8:7.

[0013] By analyzing the product type sequence and the supply quantity constraint ratio, the supply and demand relationships of various products in the park can be clarified, thereby providing support for the refinement of carbon emission management and avoiding the problem of imbalance between the production supply and demand of upstream and downstream enterprises caused by simply controlling carbon emissions.

[0014] S20: Traverse the product type sequence to count the carbon emissions per unit output of the same type of product, and obtain the carbon emissions per unit output sequence; Further, as Figure 2 shown, traverse the product type sequence to count the carbon emissions per unit output of the same type of product, and obtain the carbon emissions per unit output sequence. Step S20 includes the steps: S21: Extract the product type sequence and extract the first product type, where the first product type has an equipment label; S22: Collect the carbon emissions per unit output record data of the first product type produced through the equipment label, calculate the central value of the carbon emissions per unit output record data, and obtain the carbon emissions per unit output of the first product type; S23: Add the carbon emissions per unit output of the first product type to the carbon emissions per unit output sequence.

[0015] Specifically, the carbon emissions per unit output refers to the carbon emissions generated by producing a unit quantity of products, usually expressed in kilograms of carbon dioxide equivalent (kgCO2e). Statistically analyze the historical carbon emissions per unit output of the same product produced by the same equipment to obtain the carbon emissions per unit output sequence. The detailed process is as follows: The equipment label refers to the identifier associated with the production equipment of the first product type in the park, which is used to distinguish different equipment or equipment groups; the first product type refers to any product type in the product type sequence. The carbon emissions per unit output record data refers to the historical carbon emissions per unit output data related to the production of the first product type collected from the production equipment through the equipment label; calculate the central value of the carbon emissions per unit output record data to obtain the carbon emissions per unit output of the first product type, and add it to the carbon emissions per unit output sequence. Further, perform the same processing on other product types in the product type sequence, and output the carbon emissions per unit output sequence when all processing is completed.

[0016] Exemplarily, assume that there are three product types in an industrial park: raw materials, semi-finished products, and final products. Each product type has a corresponding equipment label. The following are the specific steps and data: Extract the product type sequence: Obtain the 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 the unit production carbon emission record data: Through the equipment label "Equipment 1", collect the unit production carbon emission data during the production process of raw materials. Assume the collected data is: [45, 50, 55, 48, 52] kgCO2e / ton; Calculate the central value: Calculate the average value of the above data to obtain the unit production carbon emission of raw materials as 50 kgCO2e / ton; Add to the unit production carbon emission sequence: Add the unit production carbon emission of raw materials, 50 kgCO2e / ton, to the unit production carbon emission sequence to obtain the sequence:

[50] ; Repeat the above steps for semi-finished products and final products respectively. Assume the unit production carbon emission of semi-finished products is 30 kgCO2e / ton and the unit production carbon emission of final products is 20 kgCO2e / ton. The finally obtained unit production carbon emission sequence is: [50, 30, 20].

[0017] Precisely collecting carbon emission data through equipment labels and calculating the central value can ensure more accurate statistics of unit production carbon emissions.

[0018] S30: Calculate the product of the supply quantity constraint ratio and the supply quantity ratio and unit production carbon emission corresponding one by one in the unit production carbon emission sequence to obtain the carbon emission constraint ratio; Specifically, the carbon emission constraint ratio characterizes the carbon emission constraint situation of each product when considering the supply-demand balance. Preferably, it is obtained by calculating the product of the supply quantity constraint ratio and the supply quantity ratio and unit production carbon emission corresponding one by one in the unit production carbon emission sequence. Exemplarily, assume that there are three product types in an industrial park: raw materials, semi-finished products, and final products, the supply quantity constraint ratio is 10:8:7, and the unit production carbon emissions are 50 kgCO2e / ton (raw materials), 30 kgCO2e / ton (semi-finished products), and 20 kgCO2e / ton (final products) respectively; Extract the supply quantity constraint ratio: The supply quantity constraint ratio of raw materials is 10, the supply quantity constraint ratio of semi-finished products is 8, and the supply quantity constraint ratio of final products is 7; Extract the unit production carbon emission: The unit production carbon emission of raw materials is 50 kgCO2e / ton, the unit production carbon emission of semi-finished products is 30 kgCO2e / ton, and the unit production carbon emission of final products is 20 kgkgCO2e / ton; Perform the product calculation: Carbon emission constraint ratio of raw materials = 10 × 50 = 500 kgCO2e / ton; Carbon emission constraint ratio of semi-finished products = 8 × 30 = 240 kgCO2e / ton; Carbon emission constraint ratio of final products = 7 × 20 = 140 kgCO2e / ton.

[0019] Form the carbon emission constraint ratio: Arrange the calculated carbon emission constraint ratios in the order of the product type sequence to form the carbon emission constraint ratio: 500:240:140 = 25:12:7. By calculating the carbon emission constraint ratio, the carbon emission limit situation of each product in the production process can be clarified, providing data support for subsequent carbon emission constraint calculation and carbon trading scheme optimization.

[0020] S40: Subtract the corresponding carbon quota in the enterprise carbon quota list from the total carbon emission of each enterprise in the enterprise carbon emission prediction value list of the preset time zone to obtain the adaptation vector list; Further, subtracting the corresponding carbon quota in the enterprise carbon quota list from the total carbon emission of each enterprise in the enterprise carbon emission prediction value list of the preset time zone to obtain the adaptation vector list previously included: Obtain the reported product type list and reported output list of the first enterprise in the preset time zone, conduct carbon emission statistics, and obtain the first enterprise's sub-carbon emission prediction value list; Sum up the enterprise carbon emission prediction values in the first enterprise's carbon emission prediction value list to obtain the first enterprise's total carbon emission prediction value; Add the first enterprise's sub-carbon emission prediction value list and the first enterprise's total carbon emission prediction value to the first enterprise's carbon emission prediction value; Add the first enterprise's carbon emission prediction value to the enterprise carbon emission prediction value list.

[0021] Specifically, the preset time zone refers to the pre-set time range for carbon emission data statistics and prediction. For example, it can be a month, a quarter, or a year; the enterprise carbon emission prediction value list refers to the list of the expected carbon emissions of each enterprise within the preset time zone, and these prediction values are usually calculated based on the enterprise's production plan and historical carbon emission data; the enterprise carbon quota list refers to the list of carbon emission quotas allocated to each enterprise, and the carbon quota is the upper limit of carbon emissions allocated by the management unit according to the enterprise's production scale and industry standards; the adaptation vector list refers to the list of differences obtained by subtracting the carbon quota from the total carbon emission prediction value of each enterprise. This difference reflects the surplus or deficiency 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 for calculating the enterprise's carbon emissions.

[0022] The specific process is as follows: Taking the first enterprise as an example, obtain the product types and production volume data of the first enterprise produced within the preset time zone from the enterprise's production management system; according to the product types and production volume reported by the first enterprise, use the same analysis method as mentioned above to analyze the carbon emission per unit production volume data of each product type, multiply it by the production volume, obtain the carbon emissions of each product, and form a list of predicted sub-carbon emission values; add up all the carbon emissions in the list of predicted sub-carbon emission values to obtain the predicted total carbon emission value of the first enterprise within the preset time zone; integrate the list of predicted sub-carbon emission values and the predicted total carbon emission value into the predicted carbon emission value of the first enterprise, and add the predicted carbon emission value of the first enterprise to the list of predicted carbon emission values of enterprises in the entire industrial park. Further, when the analysis of all enterprises in the park is completed, output the list of predicted carbon emission values of enterprises. Even further, subtract the corresponding carbon quota in the enterprise carbon quota list from the total carbon emission of each enterprise in the list of predicted carbon emission values of enterprises in the preset time zone, and store the calculation result as a list of adaptation vectors.

[0023] Exemplarily, assume that there are two enterprises in an industrial park: Enterprise A and Enterprise B, and the preset time zone is one month. The following are the specific steps and data: The list of product types reported by Enterprise A: [raw materials, semi-finished products, final products]; the list of production volumes reported by Enterprise A: [100 tons, 80 tons, 70 tons]; further, the carbon emission per unit production volume of raw materials is 50 kgCO2e / ton; the carbon emission per unit production volume of semi-finished products is 30 kgCO2e / ton; the carbon emission per unit production volume of final products is 20 kgCO2e / ton; further, the list of predicted sub-carbon emission values of Enterprise A: [5000 kgCO2e, 2400 kgCO2e, 1400 kgCO2e]; add up the predicted carbon emission values of the first enterprise in the list of predicted carbon emission values of the first enterprise to obtain the predicted total carbon emission value of the first enterprise: The predicted total carbon emission value of Enterprise A = 5000 + 2400 + 1400 = 8800 kgCO2e; add the list of predicted sub-carbon emission values of the first enterprise and the predicted total carbon emission value of the first enterprise to the predicted carbon emission value of the first enterprise: The predicted carbon emission value of Enterprise A: {list of predicted sub-carbon emission values: [5000, 2400, 1400], predicted total carbon emission value: 8800}; add the predicted carbon emission value of the first enterprise to the list of predicted carbon emission values of enterprises: The list of predicted carbon emission values of enterprises: [{Enterprise A: {list of predicted sub-carbon emission values: [5000, 2400, 1400], predicted total carbon emission value: 8800}}]. Assume that the carbon quota of Enterprise A is 8000 kgCO2e, then the adaptation vector of Enterprise A is: Adaptation vector = predicted total carbon emission value - carbon quota = 8800 - 8000 = 800 kgCO2e.

[0024] By calculating the adaptation vectors of each enterprise, the surplus or deficit of carbon emissions of the enterprise in the preset time zone can be clarified, providing data support for subsequent carbon trading schemes. At the same time, the adaptation vector list also provides an intuitive carbon emission management situation for the industrial park managers, helping to identify enterprises with excessive carbon emissions and then taking targeted emission reduction measures.

[0025] S50: When the number of adaptation vectors greater than 0 in the adaptation vector list is not equal to 0, extract the set of tradable adaptation vectors that are not equal to 0; Specifically, the set of tradable adaptation vectors refers to the set of enterprises extracted from the adaptation vector list with adaptation vector values not equal to 0. These enterprises have a deficit (positive value) or surplus (negative value) of carbon emissions 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 there are enterprises with carbon emissions exceeding the carbon quota and carbon emission optimization is required. Therefore, extracting the set of tradable adaptation vectors not equal to 0 facilitates the subsequent optimization of trading schemes.

[0026] Exemplarily, assume there are three enterprises in an industrial park: Enterprise A, Enterprise B, and Enterprise C. The preset time zone is one month, and the adaptation vector list is as follows: Enterprise A: Adaptation vector = 800 kgCO2e (carbon emission deficit, need to purchase carbon quota) Enterprise B: Adaptation vector = -500 kgCO2e (carbon emission surplus, can sell carbon quota) Enterprise C: Adaptation vector = 0 kgCO2e (carbon emission is balanced with the quota) Check the adaptation vector list: Traverse the adaptation vector list and check the adaptation vector values of each enterprise; Extract the adaptation vectors not equal to 0: Extract the enterprises with adaptation vectors not equal to 0 to form a set of tradable adaptation vectors: Set of tradable adaptation vectors: {Enterprise A: 800 kgCO2e, Enterprise B: -500 kgCO2e}; Classify the tradable adaptation vectors: Classify the enterprises in the set of tradable adaptation vectors according to the positive and negative of the adaptation vectors: Set of positive tradable adaptation vectors: {Enterprise A: 800 kgCO2e} (carbon emission deficit, need to purchase carbon quota); Set of negative tradable adaptation vectors: {Enterprise B: -500 kgCO2e} (carbon emission surplus, can sell carbon quota).

[0027] By extracting the set of tradable adaptation vectors, it can be clarified which enterprises need to participate in carbon trading, providing data support for the subsequent optimization of trading schemes.

[0028] S60: Taking the total carbon emission constraint of the park and the carbon emission constraint ratio as the limit, optimize the trading scheme for the set of tradable adaptation vectors, obtain the carbon environment management data for the preset time zone, and send it to the ESG data management terminal.

[0029] Further, within the limits of the total carbon emission constraint of the park and the carbon emission constraint ratio, optimize the trading plan for the set of tradable adaptation vectors to obtain the carbon environment management data for the preset time zone, including: Group the set of tradable adaptation vectors according to positive and negative values to obtain a set of positive tradable adaptation vectors and a set of negative tradable adaptation vectors; Use the set of negative tradable adaptation vectors as the delivery party and the set of positive tradable adaptation vectors as the receiving party to conduct adaptation vector modulus trading. When the sum of the sold adaptation vector moduli of the delivery party is greater than or equal to the sum of the initial adaptation vector moduli of the receiving party, obtain the initial trading plan; Adjust 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 park, add the initial trading plan to the candidate trading plans; Optimize the trading plan based on the candidate trading plans to obtain the carbon environment management data for the preset time zone.

[0030] Further, optimize the trading plan based on the candidate trading plans to obtain the carbon environment management data for the preset time zone, including: The candidate trading plans include an updated set of tradable adaptation vectors; Construct a trading plan fitness function, where the trading plan fitness function is used to calculate the sum of positive numbers in the updated set of tradable adaptation vectors; Based on the trading plan fitness function, perform minimum value optimization on the candidate trading plans to obtain the carbon environment management data for the preset time zone.

[0031] Specifically, the total carbon emission constraint of the park refers to the maximum total carbon emission allowed in the preset time zone for the industrial park, and this value is usually set according to the carbon neutrality goal and the actual carbon absorption capacity of the park; trading plan optimization: refers to finding the optimal carbon trading plan under the premise of meeting the total carbon emission constraint of the park and the carbon emission constraint ratio to achieve reasonable allocation of carbon emissions and minimize carbon trading costs; trading plan fitness function: is a function used to evaluate the quality of a trading plan, usually calculating the sum of positive numbers in the updated set of tradable adaptation vectors to determine whether the trading plan is optimal; The specific process is as follows: Classify the enterprises in the tradable adaptation vector set according to the positive and negative of the adaptation vectors: The positive tradable adaptation vector set represents enterprises with insufficient carbon emissions (needing to purchase carbon quotas); the negative tradable adaptation vector set represents enterprises with surplus carbon emissions (able to sell carbon quotas); conduct the trading of the modulus of the adaptation vectors: Use the enterprises in the negative tradable adaptation vector set as the delivery parties and the enterprises in the positive tradable adaptation vector set as the receiving parties to conduct the trading of the modulus of the adaptation vectors; when the sum of the sold adaptation vector moduli of the delivery parties is greater than or equal to the sum of the initial adaptation vector moduli of the receiving parties, obtain the initial trading plan; adjust the enterprise carbon quota list: According to the initial trading plan, adjust the enterprise carbon quota list to obtain the updated enterprise carbon quota list; verify whether the updated enterprise carbon quota list meets the constraint conditions: Check whether the updated enterprise carbon quota list meets the carbon emission constraint ratio and the total park carbon emission constraint; if it meets, add the initial trading plan to the candidate trading plans, and when the number of candidate trading plans is greater than or equal to the user-preset generation quantity, output all the candidate trading plans.

[0032] Furthermore, optimize the trading plan: Construct a trading plan fitness function to calculate the sum of positive numbers in the updated tradable adaptation vector set; based on the trading plan fitness function, perform minimum value optimization on all candidate trading plans to obtain the optimal preset time zone carbon environment management data.

[0033] Exemplarily, assume there are three enterprises in an industrial park: Enterprise A, Enterprise B, and Enterprise C, and the preset time zone is one month. The adaptation vector list is as follows: Enterprise A: Adaptation vector = 800 kgCO2e (insufficient carbon emissions, needing to purchase carbon quotas); Enterprise B: Adaptation vector = -500 kgCO2e (surplus carbon emissions, able to sell carbon quotas); Enterprise C: Adaptation vector = -300 kgCO2e (surplus carbon emissions, able to sell carbon quotas).

[0034] Group the tradable adaptation vector set according to positive and negative: Positive tradable adaptation vector set: {Enterprise A: 800 kgCO2e}; Negative tradable adaptation vector set: {Enterprise B: -500 kgCO2e, Enterprise C: -300 kgCO2e}.

[0035] Conduct the trading of the modulus of the adaptation vectors: The sum of the sold adaptation vector moduli of the delivery parties (Enterprise B and Enterprise C) = 500 + 300 = 800 kgCO2e; the sum of the initial adaptation vector moduli of the receiving party (Enterprise A) = 800 kgCO2e. Since the sum of the sold adaptation vector moduli of the delivery parties is equal to the sum of the initial adaptation vector moduli of the receiving party, obtain the initial trading plan: Enterprise B sells 500 kgCO2e to Enterprise A; Enterprise C sells 300 kgCO2e to Enterprise A.

[0036] Adjust the enterprise carbon quota list: The updated enterprise carbon quota list: Enterprise A: The carbon quota increases by 800 kgCO2e; Enterprise B: The carbon quota decreases by 500 kgCO2e; Enterprise C: The carbon quota decreases by 300 kgCO2e.

[0037] Verify whether the updated enterprise carbon quota list meets the constraint conditions: 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, and add the initial trading plan to the alternative trading plans.

[0038] Optimize the trading plan: Construct a trading plan fitness function and calculate the sum of positive numbers in the updated tradable adaptation vector set: Alternative trading plan 1: Enterprise B sells 500 kgCO2e, Enterprise C sells 300 kgCO2e. Alternative trading plan 2: Enterprise B sells 800 kgCO2e (assuming Enterprise B has sufficient surplus).

[0039] Based on the trading plan fitness function, perform minimum optimization on all alternative trading plans: The sum of positive numbers in Plan 1 = 0; The sum of positive numbers in Plan 2 = 0; Select Plan 1 as the optimal trading plan.

[0040] The industrial park manager can ensure the reasonable allocation of carbon emissions, minimize carbon trading costs, and improve the refinement of carbon environment management while meeting the carbon emission constraints of the park.

[0041] Furthermore, within the limit of the total carbon emission constraint of the park and the carbon emission constraint ratio, it previously included: Interact with the ESG data management terminal to obtain the vegetation coverage status and wetland coverage status of the park; Perform prescriptive time zone sampling on the vegetation coverage status and the wetland coverage status to obtain a dataset of the park's carbon absorption record; Conduct a central value evaluation on the dataset of the park's carbon absorption record to obtain a predicted value of the park's carbon absorption, where the total carbon emission constraint of the park is less than or equal to the predicted value of the park's carbon absorption.

[0042] Specifically, the vegetation coverage status refers to the distribution and growth of vegetation in the industrial park, which is usually measured by indicators such as vegetation coverage rate and vegetation type. The vegetation coverage status directly affects the carbon absorption capacity of the park; the wetland coverage status refers to the distribution and area of wetlands in the industrial park. Wetlands are important carbon sinks that can absorb and store large amounts of carbon dioxide; Sampling in a preset time zone: Collect data on the vegetation coverage status and wetland coverage status within a preset time range to obtain relevant data on the carbon absorption amount of the park; Record dataset of the carbon absorption amount of the park: The original data set of the carbon absorption amount of the park obtained through sampling, which is used for subsequent analysis and evaluation; Central value evaluation: Conduct statistical analysis on the record dataset of the carbon absorption amount of the park and calculate its central tendency (such as average value, median, etc.) to obtain the predicted value of the carbon absorption amount of the park.

[0043] The specific process is as follows: Interact with the ESG data management terminal: Obtain the vegetation coverage status and wetland coverage status data of the park from the ESG data management terminal. These data usually include information such as vegetation coverage rate, vegetation type, and wetland area; Sampling in a preset time zone: Sample the vegetation coverage status and wetland coverage 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 carbon absorption amount of the park; Obtain the record dataset of the carbon absorption amount of the park: Organize the sampled data into a record dataset of the carbon absorption amount of the park. These data reflect the carbon absorption of vegetation and wetlands in the park within the preset time zone; Central value evaluation: Conduct statistical analysis on the record dataset of the carbon absorption amount of the park and calculate its central value (such as average value, median, etc.) to obtain the predicted value of the carbon absorption amount of the park. This predicted value reflects the amount of carbon that the park is expected to absorb within the preset time zone; Determine the total carbon emission constraint amount of the park: Determine the total carbon emission constraint amount of the park based on the predicted value of the carbon absorption amount of the park. The total carbon emission constraint amount of the park should be less than or equal to the predicted value of the carbon absorption amount of the park to ensure that the park achieves carbon neutrality within the preset time zone.

[0044] By interacting with the ESG data management terminal, obtaining the vegetation and wetland coverage status, and conducting sampling in a preset time zone and central value evaluation, the total carbon emission constraint amount of the 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.

[0045] Furthermore, sampling the vegetation coverage status and the wetland coverage status in a preset time zone to obtain a record dataset of the carbon absorption amount of the park includes: Sampling with the same coverage status using the vegetation coverage status and the wetland coverage status as the primary constraints to obtain a primary record dataset of the carbon absorption amount of the park. Among them, the primary record dataset of the carbon absorption amount of the park has a primary vegetation coverage status label set and a primary wetland coverage status label set; Traverse the carbon absorption record dataset of the first-level industrial parks, and perform sampling with the same coverage status using the first-level vegetation coverage status label set and the first-level wetland coverage status label set as the secondary constraints to obtain multiple groups of carbon absorption record data for the second-level industrial parks; Traverse the multiple groups of carbon absorption record data for the second-level industrial parks for central value evaluation, obtain multiple carbon absorption record data for the second-level industrial parks, and add them to the carbon absorption record dataset of the first-level industrial parks to obtain the carbon absorption record dataset of the industrial parks.

[0046] Specifically, the first-level constraints refer to the preliminary classification and sampling based on the vegetation coverage status and wetland coverage status during the sampling process. These statuses serve as the first-level constraint conditions for screening out datasets with similar characteristics; the carbon absorption record dataset of the first-level industrial parks refers to the preliminary carbon absorption dataset obtained through sampling with the same coverage status under the first-level constraint conditions. This dataset contains carbon absorption records with similar vegetation and wetland coverage statuses, along with the corresponding vegetation and wetland coverage status labels; the second-level constraints: refer to further sampling based on the vegetation coverage status label set and the wetland coverage status label set on the basis of the first-level dataset. This step is to ensure an adequate amount of data in the carbon absorption dataset participating in the analysis; the carbon absorption record dataset of the second-level industrial parks: refers to the carbon absorption dataset obtained through sampling with the same coverage status under the second-level constraint conditions; the central value evaluation: refers to the statistical analysis of the carbon absorption record data for the second-level industrial parks to calculate their central tendency (such as the average value, median, etc.) to obtain a more accurate carbon absorption evaluation value.

[0047] Through two-level constraint sampling, the amount of data in the carbon absorption record dataset is increased, and the accuracy of the statistical results is improved.

[0048] Furthermore, it also includes: when the number of adaptation vectors greater than 0 in the adaptation vector list is equal to 0, generate a preset time zone carbon environment balance identifier and send it to the ESG data management terminal.

[0049] Specifically, the preset time zone carbon environment balance identifier is a special signal or mark used to indicate that within the preset time zone, the carbon emissions and carbon quotas of all enterprises have reached a balanced state, meaning that no enterprise needs to buy or sell carbon quotas; the ESG data management terminal: refers to the environmental, social, and governance (ESG) data management platform of the industrial park for receiving and processing various ESG-related data and identifiers. By generating the carbon environment balance identifier, it can be clarified whether the industrial park has achieved carbon emission balance within the preset time zone.

[0050] An industrial park ESG data management method provided by an embodiment of the present invention has at least the following technical effects: By analyzing the supply-demand balance relationship between the product type sequence and the supply quantity constraint ratio, the carbon emission constraint ratio is obtained; then, for each total carbon emission of an enterprise in the list of predicted enterprise carbon emissions in the preset time zone, subtract the corresponding carbon quota in the list of enterprise carbon quotas to obtain a list of adaptation vectors. When carbon trading is required, consider the carbon emission constraint ratio to avoid carbon quota imbalance, achieving the technical effect of improving the refinement degree of carbon environment management.

[0051] It should be noted that in the above embodiments, the descriptions of each embodiment have their own emphases. For the parts not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0052] Those skilled in the art should understand that the embodiments of the present invention can be provided as methods, methods, or computer program products. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take 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.) containing computer-usable program code.

[0053] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (methods), and computer program products according to the embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0054] These computer program instructions can 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 generate a manufactured product including an instruction device, and the instruction device implements the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0055] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Therefore, the instructions executed on the computer or other programmable device provide means for implementing the functions specified in Figure 1One or more processes and / or blocks Figure 1 Steps of the functions specified in one or more blocks.

[0056] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications to these embodiments once they learn the basic inventive concept.

[0057] 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 equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. An industrial park ESG data management method, characterized in that: include: Extract product type sequence and supply constraint ratio of industrial chain of the park; Traversing the product type sequence to count the carbon emissions per unit output of similar products, and obtaining a carbon emissions per unit output sequence; The supply quantity constraint ratio and the carbon emission per unit output sequence are multiplied by the product of the supply quantity ratio and the carbon emission per unit output sequence corresponding to each other to obtain the carbon emission constraint ratio; The total carbon emissions of each enterprise in the enterprise carbon emission prediction value list of the preset time zone are subtracted from the corresponding carbon quota in the enterprise carbon quota list 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 is not equal to 0; Based on the total carbon emission constraint of the 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.

2. The method according to claim 1, characterized in that Traversing the product type sequence to count the carbon emissions per unit output of similar products, and obtaining 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 the carbon emission per unit output recorded data produced by the device tag of the first product type, calculating the centralized value of the carbon emission per unit output recorded data, and obtaining the carbon emission per unit output of the first product type; The carbon emission per unit output of the first product type is added to the carbon emission per unit output sequence.

3. The method according to claim 1, characterized in that 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: Obtain a list of reported product types and a list of reported output of the first enterprise in a preset time zone, perform carbon emission statistics, and obtain a list of predicted carbon emission values ​​for the first enterprise; Add the predicted carbon emission values ​​of the enterprises in the first predicted carbon emission value list to obtain the predicted total carbon emission value of the first enterprise; Adding the first enterprise's carbon emission prediction value list and the first enterprise's total carbon emission prediction value to the first enterprise's carbon emission prediction 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, characterized in that The total amount of the park’s carbon emission constraints shall be limited to the ratio of the carbon emission constraints stated above, which 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 data set of carbon absorption records in the park; 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 amount is less than or equal to the park carbon absorption prediction value.

5. The method according to claim 4, characterized in that The vegetation coverage state and the wetland coverage state are sampled in a preset time zone to obtain a park carbon absorption record data set, including: The vegetation coverage state and the wetland coverage state are used as primary constraints to perform same coverage state sampling, and obtain a primary park carbon absorption record data set, wherein the primary park carbon absorption record data set has a primary vegetation coverage state label set and a primary wetland coverage state label set; Traversing the first-level park carbon absorption record data set, performing same coverage state sampling with the first-level vegetation coverage state label set and the first-level wetland coverage state label set as second-level constraints, and obtaining multiple sets of second-level park carbon absorption record data; The plurality of groups 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 into the primary park carbon absorption record data set to obtain the park carbon absorption record data set.

6. The method according to claim 1, characterized in that Based on the total carbon emission constraint of the 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, including: The tradable adaptation vector set is grouped according to positive and negative numbers to obtain a positive tradable adaptation vector set and a negative tradable adaptation vector set; The negative tradable adaptation vector set is used as the delivery party, and the positive tradable adaptation vector set is used as the consignee to perform adaptation vector modulus value trading. When the sum of the selling adaptation vector modulus values ​​of the delivery party is greater than or equal to the sum of the initial adaptation vector modulus values ​​of the consignee, an initial trading plan is obtained; According to the initial trading plan, the enterprise carbon quota list is adjusted 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 trading plan to be selected; The optimal trading scheme is searched according to the selected trading scheme to obtain the carbon environment management data of the preset time zone.

7. The method according to claim 6, characterized in that The trading scheme is optimized according to the selected trading scheme to obtain carbon environment management data in a preset time zone, including: The transaction solution to be selected includes updating a set of tradable adaptation vectors; Constructing a transaction scheme fitness function, wherein the transaction scheme 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.

8. The method according to claim 1, characterized in that 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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