Enterprise carbon credit evaluation model method and system based on electric power big data

Abstract

The invention discloses an enterprise carbon credit evaluation model method and system based on electric power big data, and relates to the technical field of electric power big data, and the method comprises the steps of index system construction, data acquisition, rating implementation and grade upgrading. The method comprises the following steps of: analyzing related data of three dimensions of relative level of enterprise carbon account value, relative level of enterprise carbon emission intensity and relative level of enterprise carbon behavior, and performing comprehensive calculation in combination with adjustment items of enterprise bad behaviors to obtain a final rating. The enterprise carbon asset credit rating index system has the beneficial effects that the enterprise carbon asset credit rating index system is innovatively provided, and the method for constructing the enterprise carbon credit rating model based on the electric power big data is provided. In the aspect of index setting, the index of carbon strength level is added to reflect the advancement of the enterprise emission reduction technology, the enterprise carbon behavior credit dimension index is introduced, the original credit record behavior of the enterprise is used as an adjustment item, and a carbon asset credit evaluation index system is jointly established.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electric power big data, in particular to an enterprise carbon asset credit evaluation model method based on electric power big data. BACKGROUND

[0002] Under the global trend of responding to climate change, carbon asset management has become an indispensable part of enterprises, and the value of enterprise carbon accounts and the advancement of carbon reduction technology will directly affect the risks and values of various enterprises. Therefore, it is imperative to measure the carbon asset credit status of enterprises under the double carbon goal and to build a carbon asset credit evaluation system.

[0003] Under the current background of lacking unified carbon credit rating standards, enterprises face challenges in carbon emission management and often have difficulty in accurately grasping their own carbon emission status and level. This uncertainty makes it difficult for enterprises to foresee and identify potential carbon emission risks, and thus it is difficult to respond effectively to external challenges such as changes in policies and regulations and changes in market environment.

[0004] On September 30, 2020, Shanghai Energy Exchange Co., Ltd. and Fudan University Center for Sustainable Development and other units drafted and published the "Enterprise Carbon Asset Credit Evaluation Standard", which introduced a method for evaluating enterprise carbon asset credit. The index system is composed of seven categories of indicators: macro risk, regional risk, industry risk, enterprise status, carbon asset risk, non-carbon asset risk, and enterprise comprehensive strength. The method system is an expansion of the original enterprise credit rating system. In the original method system, carbon asset-related dimensions are introduced, so many secondary indicators defined reflect the overall credit status of the enterprise but have weak relevance to carbon assets themselves. In addition, some indicators of the index system are difficult to quantify and measure, and have weak applicability. SUMMARY

[0005] In order to overcome the shortcomings of the prior art, the present application provides an enterprise carbon asset credit evaluation model method based on electric power big data. Based on the value of the carbon asset account of the enterprise and the carbon reduction technology, the carbon asset credit rating of the enterprise is carried out, and the enterprise carbon behavior credit dimension index is introduced. The original credit record behavior of the enterprise is used as an adjustment item to jointly build a carbon asset credit evaluation index system.

[0006] The present application provides an enterprise carbon asset credit evaluation model method based on electric power big data, which includes index system construction, data acquisition, implementation of rating, and grade upgrade.

[0007] The index system construction includes three dimensions of carbon account, carbon intensity, and carbon behavior, and introduces an adjustment item on this basis.

[0008] The first-level indicators include A carbon account, B carbon intensity, C carbon behavior, and D adjustment item.

[0009] Secondary indicators include: A1 positive assets, A2 negative assets, B1 relative level of carbon intensity, C1 data behavior, C2 compliance behavior, D1 number of times of bank bad records, D2 number of times of administrative penalty records;

[0010] Tertiary indicators include: A11 carbon quota amount (estimated) * carbon trading price, A12 CCER) * CCER trading price, A13 carbon sink amount * carbon sink trading price, A14 green electricity amount (green certificate) * power emission factor (grid supply) * carbon trading price, A21 carbon emission amount * carbon trading price; A21 carbon emission amount * carbon trading price;

[0011] Enterprise carbon emission intensity (calculated) / carbon emission intensity of the industry where the enterprise is located (calculated)

[0012] C11 number of times of incorrect verification data

[0013] C12 number of times of false reporting of purchased data (CCER, green certificate, carbon sink)

[0014] C21 number of times of non-timely compliance of green certificate trading

[0015] C22 number of times of non-timely compliance of carbon trading

[0016] D11 number of times of bank bad records

[0017] D21 number of times of administrative penalty records

[0018] The data acquisition includes enterprise-provided data and rating party-collected data. The enterprise-provided data includes: carbon quota amount, CCER, carbon sink amount, green electricity amount, carbon emission amount, enterprise carbon emission intensity, number of times of incorrect verification data / total number of verifications, number of times of false reporting of purchased data / total number of times, number of times of non-timely / timely compliance of green certificate trading, number of times of non-timely / timely compliance of carbon trading, number of times of bank bad records, number of times of administrative penalty records, etc. The rating party-collected data includes: carbon trading price, CCER trading price, carbon sink trading price, power emission factor, etc.

[0019] The implementation rating is to analyze the relevant data of the three dimensions of enterprise carbon account value relative level, enterprise carbon emission intensity relative level, and enterprise carbon behavior relative level, and comprehensively calculate the final rating by combining the adjustment items of enterprise bad behavior.

[0020] The rating method includes the following steps:

[0021] First, determine the relative level of enterprise carbon account value, and determine the carbon account level A score according to the relative value Y1 of enterprise carbon account value. The specific calculation process is as follows:

[0022] Second step, determine the relative level of enterprise carbon intensity, and determine the carbon intensity level B score according to the relative value of enterprise carbon intensity Y2;

[0023] Third step, calculate the relative level of enterprise carbon behavior, according to the relative value of enterprise carbon behavior Y3 evaluation level standard to enterprise carbon behavior level C score;

[0024] Fourth step, carbon credit rating, ABC three dimension file dimension reduction, get ABC three dimension enterprise total score level, and according to the D adjustment item result to adjust the score level, determine the final carbon credit evaluation level of enterprise.

[0025] The first step, the specific calculation process and level standard are:

[0026] S1, calculate the value of enterprise carbon account A, add the three level indicators of carbon account directly;

[0027] A=carbon quota amount*carbon trading price+CCER*CCER trading price+carbon sink amount*carbon sink trading price+green electricity amount(green certificate)*power emission factor-carbon emission amount*carbon trading price;

[0028] S2, calculate the relative value of enterprise scale, denoted as X1;

[0029]

[0030] S3, calculate the relative value of industry scale, denoted as X2;

[0031]

[0032] S4, calculate the relative level of enterprise carbon account value, that is, the relative value of enterprise carbon account value Y1;

[0033]

[0034] According to the relative value of enterprise carbon account value Y1, and combining with 9 points scoring method, the level evaluation is given, and the evaluation standard is as follows:

[0035] Aaa:[2-1.30); Aa:[1.30-1.2); A:(1.20-1.10]; BBB:[1.10-1.01); BB:1.01-0.99; B:0.99-0.90; CCC:O.90-0.80; CC:0.80-0.70; C:0.70-0;

[0036] The second step, the specific calculation process and level standard are:

[0037]

[0038] The Y2 relative value evaluation level standard is as follows:

[0039] Aaa: (0.01-0.70]; Aa: (0.70-0.80]; A: (0.80-0.90]; BBB: (0.90-0.99]; BB: (0.99-1.01]; B: (1.01-1.10]; CCC: (1.10-1.20]; CC: (1.20-1.3]; C: >1.30;

[0040] The third step is a specific calculation process and level standard:

[0041] Y3 = (number of times of incorrect verification data + number of times of false reporting of purchase data + number of times of non-timely performance of green certificate transaction + number of times of non-timely performance of carbon transaction) / total number of carbon behaviors;

[0042] The Y3 level division standard is as follows:

[0043] Aaa: 0; Aa: 0-0.01; A: 0.01-0.05; BBB: 0.05-0.06; BB: 0.06-0.08; b: 0.08-0.1; CCC: 0.1-0.12; CC: 0.12-0.15; C: 0.15;

[0044] The fourth step is: A is determined by Y1, B is determined by Y2, and C is determined by Y3; the dimension reduction method of ABC three dimensions is: first, Aaa-C is recorded as 9-1 in turn, second, the scores of the three dimensions are weighted by equal weight method, third, the weighted scores are rounded off, and then the scores are matched back to the nine grades of Aaa-C, fourth, the final carbon credit rating of the enterprise is given considering the adjustment rules of D; on the basis of ABC rating, the total carbon credit rating of the enterprise is given, and the number of times of D is calculated from 0, and the carbon credit rating of the enterprise is reduced by one level each time.

[0045] The carbon credit rating upgrade method is:

[0046] The first step is to simply average Y2 and Y3 to obtain Y4;

[0047] The second step is to divide Y4 and Y1 into 5 grades respectively, Y4 value is row, and Y1 value is column, to make an orthogonal table;

[0048] The third step is to determine the carbon credit rating of each enterprise according to the orthogonal table;

[0049] a, classification evaluation is carried out according to industry, and different industries are evaluated separately;

[0050] b, based on the level position of the enterprise in the orthogonal table, the values of Y1 and Y4 are determined, and the enterprise can only be promoted by one level at a time;

[0051] c, based on the determined Y1 value, find the account value V1 of the enterprise;

[0052] d, the Y1 value is promoted by one level, the lower limit value of the interval is recorded as Y1_D, and Y1_D*the size value of the enterprise is calculated =V2,

[0053] e, V2-V1 is the value of the final enterprise carbon credit promotion by one level;

[0054] f, the promotion of V4 level can refer to V1.

[0055] The application also provides an enterprise carbon credit evaluation model system based on power big data, based on the enterprise carbon credit evaluation model method based on power big data, comprising a data acquisition module, a data processing module and a data analysis module.

[0056] The data acquisition module is used for enterprise users to input data provided by the enterprise and rating parties to import data collected by the rating parties.

[0057] The data input by the enterprise user includes: carbon quota, CCER, carbon sink, green electricity, carbon emission, enterprise carbon emission intensity, number of times of verification data error / total number of verification, number of times of false reporting of purchase data / total number of times, number of times of non-timely / good faith performance of green certificate transaction, number of times of non-timely / good faith performance of carbon transaction, number of times of bank bad records, number of times of administrative penalty records, etc.

[0058] The data imported by the rating party includes: carbon trading price, CCER trading price, carbon sink trading price, power emission factor, etc.

[0059] The data processing module is used for preliminary processing of the data input by the enterprise user and the data imported by the rating party, and calculating the relative value of the enterprise carbon account value, the relative value of the enterprise carbon emission intensity and the relative value of the enterprise carbon behavior.

[0060] The relative value of the enterprise carbon account value Y1 is calculated as follows:

[0061] S1, calculate the enterprise carbon account value A, and directly add the three-level indicators of the carbon account;

[0062] A=carbon quota*carbon trading price+CCER*CCER trading price+carbon sink*carbon sink trading price+green electricity(green certificate)*power emission factor-carbon emission*carbon trading price;

[0063] S2, calculate the relative value of the enterprise size, recorded as X1;

[0064]

[0065] S3, calculate the relative value of the industry size, recorded as X2;

[0066]

[0067] S4, calculate the relative value of the enterprise carbon account value, that is, the relative value Y1 of the enterprise carbon account value;

[0068]

[0069] The relative value Y2 of the enterprise carbon emission intensity is calculated as follows:

[0070]

[0071] The relative value Y3 of the enterprise carbon behavior is calculated as follows:

[0072] Y3 = (number of times of incorrect verification data + number of times of false reporting of purchased data + number of times of non-timely performance of green certificate transactions + number of times of non-timely performance of carbon transactions) / total number of carbon behaviors.

[0073] The data analysis module performs a level evaluation on the data Y1, Y2 and Y3 processed by the data processing module according to the evaluation standard, obtains a score, then reduces the dimensions of the ABC three-dimension grades to obtain a total score of the ABC three-dimension enterprise, and adjusts the score grade according to the result of the D adjustment item to determine the final carbon credit evaluation grade of the enterprise.

[0074] According to the relative value Y1 of the enterprise carbon account value, a level evaluation is given in combination with a 9-grade scoring method, and the evaluation standard is as follows:

[0075] Aaa: [2-1.30); Aa: [1.30-1.2); A: (1.20-1.10]; BBB: [1.10-1.01); BB: 1.01-0.99; B: 0.99-0.90; CCC: 0.90-0.80; CC: 0.80-0.70; C: 0.70-0.

[0076] The relative value Y2 evaluation level standard is as follows:

[0077] Aaa: (0.01-0.70]; Aa: (0.70-0.80]; A: (0.80-0.90]; BBB: (0.90-0.99]; BB: (0.99-1.01]; B: (1.01-1.10]; CCC: (1.10-1.20]; CC: (1.20-1.3]; C: >1.30.

[0078] The Y3 level division standard is as follows:

[0079] Aaa: 0; Aa: 0-0.01; A: 0.01-0.05; BBB: 0.05-0.06; BB: 0.06-0.08; b: 0.08-0.1; CCC: 0.1-0.12; CC: 0.12-0.15; C: 0.15.

[0080] A is determined by Y1, B is determined by Y2, and C is determined by Y3; the dimension reduction method of the three dimensions of ABC: first, record 9-1 from Aaa-C in turn, second, weight the scores of the three dimensions by equal weight method, third, round off the weighted scores, and then refer back to the nine grades of Aaa-C, fourth, give the final carbon credit rating of the enterprise considering the adjustment rules of D; give the total carbon credit rating of the enterprise on the basis of ABC rating, and the number of D is calculated from 0, and each time it is increased, the carbon credit rating is reduced by one level;

[0081] The data analysis module is also responsible for upgrading analysis of the carbon credit rating, specifically:

[0082] First, simply average Y2 and Y3 to get Y4;

[0083] Second, divide Y4 and Y1 into 5 grades respectively, Y4 value as row and Y1 value as column, and make an orthogonal table;

[0084] Third, determine the carbon credit rating of each enterprise according to the orthogonal table;

[0085] a, classification and evaluation according to industry, separate evaluation for different industries;

[0086] b, based on the position of the enterprise in the orthogonal table, determine the values of Y1 and Y4, and the enterprise can only be promoted by one level at a time;

[0087] c, based on the determined Y1 value, find out the account value V1 of the enterprise;

[0088] d, Y1 value is promoted by one grade, the lower limit value of this grade interval is recorded as Y1_D, and V2 is calculated as Y1_D*enterprise scale value;

[0089] e, V2-V1 is the value of the final enterprise carbon credit rating promotion by one grade;

[0090] f, the promotion of V4 level can refer to V1.

[0091] The beneficial effects of the present application are that the enterprise carbon asset credit rating index system is innovatively provided, and a method for constructing an enterprise carbon asset credit evaluation model based on power big data is provided.

[0092] The carbon intensity level adopts relative intensity, which can reflect the reasonable index of the relative carbon emission level of enterprises between different industries, reflect efficiency and technology, and the reason is that the relative technical difference between industries under the same era background environment will not have a generation difference, so it can be considered that the relative intensity is a reasonable index reflecting the relative carbon emission level of enterprises between different industries.

[0093] The method of the present application can perform carbon asset credit rating on key enterprises, and give carbon asset credit score results, which can improve the competitiveness of enterprises in green finance and green credit application, and higher carbon asset credit rating can convey good environmental risk management ability and sustainable development prospect of enterprises to financial institutions, which helps enterprises to obtain lower loan interest rate and more credit support in the capital market. At the same time, through effective carbon asset credit management, enterprises can not only reduce environmental pollution, but also realize cost saving in energy saving and emission reduction, so as to realize the win-win of economic benefit and environmental benefit.

[0094] According to the enterprise carbon account, the enterprise carbon asset credit score model is constructed, and the systematic carbon asset credit evaluation is carried out, which not only can enhance the transparency of enterprise carbon emission, but also can help to promote the implementation of green and low-carbon development strategy and strengthen the early warning and management of carbon emission risk. Such evaluation model has important practical significance: on the one hand, it provides scientific data support for enterprise carbon asset accounting, financial credit application and other activities; on the other hand, it also provides key micro data analysis basis for government and other relevant departments in regulating enterprise carbon emission and providing financial services, so as to promote the whole society to develop in a more green and sustainable direction. BRIEF DESCRIPTION OF DRAWINGS

[0095] Figure 1 The carbon asset credit rating data reporting flowchart of the present application is shown in the figure;

[0096] Figure 2 The carbon asset credit rating flowchart of the present application is shown in the figure. DETAILED DESCRIPTION

[0097] Embodiment 1, a method for evaluating enterprise carbon asset credit based on power big data, including index system construction, data acquisition, implementation rating and grade upgrading.

[0098] The index system is constructed, and the index system includes three dimensions of carbon account, carbon intensity and carbon behavior, and adjustment item is introduced on this basis, and finally the carbon asset credit rating index system is shown in Table 1:

[0099] Table 1 Carbon asset credit rating index system

[0100]

[0101] Carbon account: is an account that can track and manage carbon emissions of an enterprise. Through the carbon account related indicators, the information related to the carbon assets of the enterprise can be finally mastered. It is composed of two secondary indicators of positive and negative assets, wherein the positive assets contain four tertiary indicators, and the negative assets contain one tertiary indicator.

[0102] Carbon intensity: The carbon intensity level reflects the advancement of the carbon emission reduction technology of the enterprise. The relative intensity value is used to measure the carbon emission reduction technology of the enterprise, and its specific meaning is: the carbon emission intensity of the enterprise / the carbon emission intensity of the industry in which the enterprise is located. The relative intensity is a reasonable indicator reflecting the relative carbon emission level of enterprises in different industries, reflecting the efficiency and technology of carbon emission of the enterprise. Under the same era background environment, the relative technical difference between industries will not have a generation difference, so it can be considered that the relative intensity is a reasonable indicator reflecting the relative carbon emission level of enterprises in different industries.

[0103] Carbon behavior: Carbon behavior is composed of two secondary indicators of data behavior and compliance behavior, wherein data behavior contains two tertiary indicators of incorrect verification data times and false data purchase times; compliance behavior contains two tertiary indicators of green certificate transaction non-timely compliance times and carbon transaction non-timely compliance times.

[0104] Adjustment item: Considering that the credit status of the enterprise will affect the implementation of the carbon trading policy of the enterprise, in general, enterprises with poor credit status and multiple administrative penalty records are more likely to cheat in the performance of carbon trading behavior, while enterprises with good credit status are more likely to perform the relevant behavior as scheduled. Based on this, the project team introduces the adjustment item, which is composed of two indicators of bank bad record times and administrative penalty records.

[0105] The data acquisition is specifically shown in Table 1. The evaluation index system contains 12 tertiary indicators. In each quarterly carbon asset credit rating stage, the enterprise provides the data required for statistical rating according to the filling instruction, and the data must be evidence approved by the relevant department. If the data is estimated by the enterprise itself, the calculation process and basis need to be provided; the evaluation party collects other non-enterprise filling data, such as carbon trading price, CCER trading price, carbon sink trading price, and power emission factor.

[0106] The data acquisition includes enterprise-provided data and rating party-collected data. The enterprise-provided data includes carbon quota amount, CCER, carbon sink amount, green electricity amount, carbon emission amount, enterprise carbon emission intensity, number of times of incorrect verification data / total number of verifications, number of times of false reporting of purchase data / total number of times, number of times of non-timely / good faith compliance of green certificate transaction, number of times of non-timely / good faith compliance of carbon transaction, number of times of bank bad records, number of times of administrative penalty records, etc. The specific reporting process of the enterprise is shown in Figure 1 The evaluation party-collected data includes carbon trading price, CCER trading price, carbon sink trading price, and power emission factor.

[0107] The implementation rating is to analyze the related data of three dimensions of enterprise carbon account value relative level, enterprise carbon emission intensity relative level, and enterprise carbon behavior relative level, and to comprehensively calculate the final rating by combining the adjustment items of enterprise bad behaviors.

[0108] The rating method includes the following steps:

[0109] Firstly, the relative level of the enterprise carbon account value is determined, and the carbon account grade A score is determined according to the relative value Y1 of the enterprise carbon account value. The specific calculation process is as follows:

[0110] S1, calculate the enterprise carbon account value A, and directly add the three-level indicators of the carbon account;

[0111] A = carbon quota amount * carbon trading price + CCER * CCER trading price + carbon sink amount * carbon sink trading price + green electricity amount (green certificate) * power emission factor - carbon emission amount * carbon trading price;

[0112] S2, calculate the relative value of the enterprise scale, denoted as X1;

[0113]

[0114] S3, calculate the relative value of the industry scale, denoted as X2;

[0115]

[0116] S4, calculate the relative level of the enterprise carbon account value, that is, the relative value Y1 of the enterprise carbon account value;

[0117]

[0118] According to the relative value Y1 of the enterprise carbon account value, and combining the 9-grade scoring method, the grade evaluation is given, and the evaluation standard is as follows:

[0119] Aaa: [2-1.30); Aa: [1.30-1.2); A: (1.20-1.10]; BBB: [1.10-1.01); BB: 1.01-0.99; B: 0.99-0.90; CCC: O.90-0.80; CC: 0.80-0.70; C: 0.70-0.

[0120] Industry account value calculation method: based on the total carbon emissions, carbon quota, CCER, carbon sink of the industry, the industry carbon account value is estimated.

[0121] Industry scale value calculation method: through the product output of the industry, and the price of the product to calculate the scale value (output value) of the industry.

[0122] Verification of industry scale value: based on the data of large category industry (above scale), relevant inventory data, literature data (including securities research reports) for verification.

[0123] Second, determine the relative level of enterprise carbon intensity, and determine the carbon intensity level B score according to the relative value Y2 of enterprise carbon intensity.

[0124]

[0125] Y2 relative value evaluation grade standard as follows:

[0126] Aaa: (0.01-0.70]; Aa: (0.70-0.80]; A: (0.80-0.90]; BBB: (0.90-0.99]; BB: (0.99-1.01]; B: (1.01-1.10]; CCC: (1.10-1.20]; CC: (1.20-1.3]; C: >1.30;

[0127] Third, calculate the relative level of enterprise carbon behavior, and evaluate the grade C of enterprise carbon behavior according to the relative value Y3 of enterprise carbon behavior.

[0128] Y3 = (number of times of checking data error + number of times of false reporting of purchased data + number of times of non timely compliance of green certificate transaction + number of times of non timely compliance of carbon transaction) / total number of times of carbon behavior;

[0129] Y3 grade division standard as follows:

[0130] Aaa: 0; Aa: 0-0.01; A: 0.01-0.05; BBB: 0.05-0.06; BB: 0.06-0.08; b: 0.08-0.1; CCC: 0.1-0.12; CC: 0.12-0.15; C: 0.15;

[0131] Fourthly, carbon credit rating, ABC three-dimensional dimension reduction, get ABC three-dimensional enterprise total score grade, and according to the D adjustment item result to adjust the score grade, determine the final carbon credit evaluation grade of enterprise.

[0132] A item is determined by Y1, B item is determined by Y2, C item is determined by Y3;

[0133] ABC three-dimensional dimension reduction method: first, from Aaa-C is recorded as 9-1 in turn, second, the three-dimensional score is weighted by equal weight method, third, the weighted score is rounded, and then it is returned to the nine grades of Aaa-C, fourth, considering the adjustment rule of D item, the final carbon credit grade of enterprise is given.

[0134] D adjustment item usage instruction: on the basis of ABC rating, the total carbon credit grade of enterprise is given, the D item record number is calculated from 0, and each time it is increased, the carbon credit grade of enterprise is reduced by one. The specific rating process is shown in Figure 2 .

[0135] The carbon credit rating upgrade method comprises the following steps:

[0136] Firstly, Y2 and Y3 are simply weighted and averaged as Y4;

[0137] Secondly, Y4 and Y1 are divided into 5 grades respectively, Y4 value is row, and Y1 value is column, and an orthogonal table is made, as shown in Table 2;

[0138] Thirdly, referring to Table 2, the carbon credit grade of each enterprise is determined;

[0139] Table 2 value evaluation method for enterprise carbon credit rating upgrade

[0140]

[0141] Referring to Table 2, the value evaluation of enterprise grade promotion is as follows:

[0142] a. Classification evaluation is carried out according to industry, and different industries are evaluated separately.

[0143] b. Based on the grade position of the enterprise (assuming the enterprise is enterprise A) in Table 2 (the enterprise can only be promoted by one grade at a time), the Y1 value and Y4 value are determined.

[0144] c. Based on the determined Y1 value, the account value (V1) of enterprise A is found out.

[0145] d. Y1 value is promoted by one grade, the lower limit value of this grade interval is recorded as Y1_D, and V2 is calculated as Y1_D*enterprise scale value,

[0146] e. V2-V1 is the value of the final enterprise carbon credit promotion by one grade.

[0147] f, the promotion of V4 level can refer to V1.

[0148] Embodiment 2, an enterprise carbon credit evaluation model system based on power big data, based on the enterprise carbon credit evaluation model method based on power big data, comprising a data acquisition module, a data processing module, a data analysis module;

[0149] The data acquisition module is used for enterprise users to input data provided by the enterprise and rating parties to import data collected by the rating parties.

[0150] The data input by the enterprise user includes: carbon quota, CCER, carbon sink, green electricity, carbon emissions, enterprise carbon emission intensity, number of incorrect verification data / total number of verification, number of false data purchase / total number of purchase, number of non-timely / good faith of green certificate transaction, number of non-timely / good faith of carbon transaction, number of bad records in bank, number of administrative penalty records, etc. The specific reporting process of the enterprise is as shown in Figure 1

[0151] The data imported by the rating party includes: carbon trading price, CCER trading price, carbon sink trading price, and power emission factor.

[0152] The data processing module is used for preliminary processing of the data input by the enterprise user and the data imported by the rating party, and calculating the relative value of the enterprise carbon account value, the relative value of the enterprise carbon emission intensity, and the relative value of the enterprise carbon behavior.

[0153] The relative value Y1 of the enterprise carbon account value is calculated as follows:

[0154] S1, calculate the enterprise carbon account value A, and directly add the three-level indicators of the carbon account.

[0155] A=carbon quota*carbon trading price+CCER*CCER trading price+carbon sink*carbon sink trading price+green electricity(green certificate)*power emission factor-carbon emissions*carbon trading price.

[0156] S2, calculate the relative value of enterprise scale, denoted as X1.

[0157]

[0158] S3, calculate the relative value of the industry scale, denoted as X2.

[0159]

[0160] S4, calculate the relative level of the enterprise carbon account value, that is, the relative value Y1 of the enterprise carbon account value.

[0161] ​

[0162] The relative value Y2 of the carbon emission intensity of the enterprise, and the specific calculation process is:

[0163]

[0164] The relative value Y3 of the carbon behavior of the enterprise, and the specific calculation process and the grade standard are:

[0165] Y3 = (the number of times of incorrect verification data + the number of times of false reporting of purchased data + the number of times of non-timely performance of green certificate transactions + the number of times of non-timely performance of carbon transactions) / the total number of carbon behaviors.

[0166] The data analysis module performs grade evaluation on the data Y1, Y2 and Y3 processed by the data processing module according to the evaluation standard, obtains a score, then reduces the dimension of the ABC three-dimension grades, obtains the total score grade of the ABC three-dimension enterprise, and adjusts the score grade according to the D adjustment item result to determine the final carbon credit evaluation grade of the enterprise.

[0167] According to the relative value Y1 of the value of the carbon account of the enterprise, and combining the 9-grade scoring method, the grade evaluation is given, and the evaluation standard is as follows:

[0168] Aaa: [2-1.30); Aa: [1.30-1.2); A: (1.20-1.10]; BBB: [1.10-1.01); BB: 1.01-0.99; B: 0.99-0.90; CCC: 0.90-0.80; CC: 0.80-0.70; C: 0.70-0.

[0169] The relative value Y2 evaluation grade standard is as follows:

[0170] Aaa: (0.01-0.70]; Aa: (0.70-0.80]; A: (0.80-0.90]; BBB: (0.90-0.99]; BB: (0.99-1.01]; B: (1.01-1.10]; CCC: (1.10-1.20]; CC: (1.20-1.3]; C: >1.30.

[0171] The Y3 grade division standard is as follows:

[0172] Aaa: 0; Aa: 0-0.01; A: 0.01-0.05; BBB: 0.05-0.06; BB: 0.06-0.08; b: 0.08-0.1; CCC: 0.1-0.12; CC: 0.12-0.15; C: 0.15.

[0173] A is determined by Y1, B is determined by Y2, and C is determined by Y3; the dimension reduction method of ABC three dimensions: first, Aaa-C is recorded as 9-1 in turn, second, the three dimension scores are weighted by equal weight method, third, the weighted scores are rounded, and then referred to the nine grades of Aaa-C, fourth, the final carbon credit rating of the enterprise is given considering the adjustment rules of D; on the basis of ABC rating, the total carbon credit rating of the enterprise is given, and the number of D is counted from 0, and the carbon credit rating of the enterprise is reduced by one level each time;

[0174] The data analysis module is also responsible for upgrading analysis of the carbon credit rating, specifically:

[0175] First, Y2 and Y3 are simply weighted and averaged as Y4;

[0176] Second, Y4 and Y1 are divided into 5 grades respectively, Y4 value is row, and Y1 value is column, and an orthogonal table is made;

[0177] Third, the carbon credit rating of each enterprise is determined according to the orthogonal table;

[0178] a, classification and evaluation according to industry, separate evaluation for different industries;

[0179] b, based on the position of the enterprise in the orthogonal table, determine the value of Y1 and Y4, and the enterprise can only be promoted by one level at a time;

[0180] c, based on the determined Y1 value, find out the account value V1 of the enterprise;

[0181] d, Y1 value is promoted by one grade, the lower limit value of this grade interval is recorded as Y1_D, and V2 is calculated as Y1_D*enterprise scale value;

[0182] e, V2-V1 is the value of the final enterprise carbon credit rating promotion by one grade;

[0183] f, the promotion of V4 level can refer to V1.

Claims

1. A power big data-based enterprise carbon credit evaluation model method, characterized in that, The method comprises index system construction, data acquisition, implementation rating and grade upgrading. 2.The enterprise carbon credit evaluation model based on power big data according to claim 1, characterized in that, The index system construction comprises three dimensions of carbon account, carbon intensity and carbon behavior, and adjustment items are introduced on this basis. The first-level indexes comprise A carbon account, B carbon intensity, C carbon behavior and D adjustment items. The second-level indexes comprise A1 positive assets, A2 negative assets, B1 carbon intensity relative level, C1 data behavior, C2 performance behavior, D1 bank bad record times and D2 administrative penalty record times. 3.The enterprise carbon credit evaluation model based on power big data according to claim 2, characterized in that, The data acquisition comprises enterprise-provided data and rating party collected data. 4.The enterprise carbon credit evaluation model based on power big data according to claim 3, characterized in that, The enterprise-provided data comprises carbon quota amount, CCER, carbon sink amount, green electricity amount, carbon emission amount, enterprise carbon emission intensity, verification data error times / verification total times, purchase data false reporting times / total times, green certificate transaction non-timely / timely performance times, carbon transaction non-timely / timely performance times, bank bad record times and administrative penalty record times. 5.The enterprise carbon credit evaluation model based on power big data according to claim 4, characterized in that, The rating party collected data comprises carbon transaction price, CCER transaction price, carbon sink transaction price and power emission factor. The implementation rating is to analyze the relative data of three dimensions of enterprise carbon account value relative level, enterprise carbon emission intensity relative level and enterprise carbon behavior relative level, and to comprehensively calculate the final rating by combining the adjustment items of enterprise bad behavior. The implementation rating comprises the following steps: In the first step, the enterprise carbon account value relative level is determined, and the carbon account grade A score is determined according to the enterprise carbon account value relative value Y1. In the second step, the enterprise carbon emission intensity relative level is determined, and the carbon emission intensity grade B score is determined according to the enterprise carbon emission intensity relative value Y2. 6.The enterprise carbon credit evaluation model based on power big data according to claim 5, characterized in that, In the third step, the enterprise carbon behavior relative level is calculated, and the enterprise carbon behavior grade C is scored according to the enterprise carbon behavior relative value Y3. In the fourth step, the carbon credit rating is to reduce the dimension of ABC three-dimension grades, to obtain the total score grade of ABC three-dimension enterprises, and to adjust the score grade according to the D adjustment item result to determine the final carbon credit evaluation grade of the enterprise. In the first step, the specific calculation process and grade standard are as follows: S1, the enterprise carbon account value A is calculated by directly adding the three-level indexes of carbon account. A=carbon quota amount*carbon transaction price+CCER*CCER transaction price+carbon sink amount*carbon sink transaction price+green electricity amount*power emission factor-carbon emission amount*carbon transaction price. S2, the enterprise scale relative value is calculated, which is denoted as X1. S3, the industry scale relative value is calculated, which is denoted as X2. S4, the enterprise carbon account value relative level is calculated, which is denoted as Y1. B：0.99-0.90； According to the enterprise carbon account value relative value Y1, the grade evaluation is given by combining the 9-grade scoring method, and the evaluation standard is as follows: Aaa:[2-1.30); Aa:[1.30-1.2); A:(1.20-1.10]; BBB:[1.10-1.01); BB:1.01-0.99; C：0.70-0。 7.The enterprise carbon credit evaluation model based on power big data according to claim 6, wherein, CCC:0.90-0.80; CC:0.80-0.70; In the second step, the specific calculation process and grade standard are as follows: The Y2 relative value evaluation grade standard is as follows: Aaa: (0.01-0.70]; Aa: (0.70-0.80]; A: (0.80-0.90]; BBB: (0.90-0.99]; BB: (0.99-1.01]; B: (1.01-1.10]; CCC: (1.10-1.20]; CC: (1.20-1.3]; C: >1.30; The third step, the specific calculation process and the grade standard are: Y3 = (the number of times of incorrect verification data + the number of times of false reporting of purchase data + the number of times of non-timely performance of green certificate transaction + the number of times of non-timely performance of carbon transaction) / the total number of carbon behaviors; The Y3 grade division standard is as follows: Aaa: 0; Aa: 0-0.01; A：0.01-0.05； BBB: 0.05-0.06; BB: 0.06-0.08; b：0.08-0.1； CCC: 0.1-0.12; CC: 0.12-0.15; C：0.15。 8.The enterprise carbon credit evaluation model based on power big data according to claim 7, characterized in that, The fourth step is: A is determined by Y1, B is determined by Y2, and C is determined by Y3; the dimension reduction method of ABC three dimensions is: first, Aaa-C is sequentially recorded as 9-1 points, second, the three dimension scores are weighted by the equal weight method, third, the weighted score is rounded, and then it is matched back to the nine grades of Aaa-C, and fourth, the final carbon credit rating of the enterprise is given according to the adjustment rules of D; On the basis of ABC rating, the total carbon credit rating of the enterprise is given, and the number of times of D is calculated from 0, and the carbon credit rating of the enterprise is reduced by one level each time. 9.The enterprise carbon credit evaluation model based on power big data according to claim 8, characterized in that, The carbon credit rating upgrade method is: The first step is to simply weight Y2 and Y3 as Y4; The second step is to divide Y4 and Y1 into 5 grades respectively, Y4 value is row, and Y1 value is column, to make an orthogonal table; The third step is to determine the carbon credit rating of each enterprise according to the orthogonal table; a, classification evaluation is carried out according to industries, and different industries are evaluated separately; b, based on the grade position of the enterprise in the orthogonal table, the Y1 value and the Y4 value are determined, and the enterprise can only be promoted by one level at a time; c, based on the determined Y1 value, the account value V1 of the enterprise is found out; d, the Y1 value is promoted by one grade, the lower limit value of this grade interval is recorded as Y1_D, and V2 is calculated as Y1_D*enterprise scale value; e, V2-V1 is the value of the final enterprise carbon credit rating promotion by one grade; f, the promotion of V4 level can refer to V1.

10. A power big data-based enterprise carbon credit evaluation model system based on the power big data-based enterprise carbon credit evaluation model method of any one of claims 1-9, characterized in that, It comprises a data acquisition module, a data processing module and a data analysis module; The data acquisition module is used for enterprise users to input data required by the enterprise and for rating parties to import collected data by the rating parties; The data input by the enterprise users includes carbon quota, CCER, carbon sink, green electricity, carbon emission, enterprise carbon emission intensity, number of times of incorrect verification data / total number of times of verification, number of times of false reporting of purchase data / total number of times, number of times of non-timely / timely performance of green certificate transaction, number of times of non-timely / timely performance of carbon transaction, number of times of bank bad records, number of times of administrative penalty records and the like; The data imported by the rating parties includes carbon trading price, CCER trading price, carbon sink trading price, power emission factor and the like; The data processing module is used to perform preliminary processing on the data entered by enterprise users and the data imported by the rating agency, and to calculate the relative value of the enterprise's carbon account, the relative value of the enterprise's carbon emission intensity, and the relative value of the enterprise's carbon behavior. The data analysis module evaluates the data (Y1, Y2, Y3) processed by the data processing module according to the evaluation criteria, and obtains a score. Then, it performs dimensionality reduction on the three dimensions (A, B, C) to obtain the overall corporate score level across these three dimensions. The score level is then adjusted based on the results of the adjustment item (D) to determine the final carbon credit rating of the enterprise. The dimensionality reduction method for the three dimensions (A, B, C) is as follows: First, scores are assigned sequentially from Aaa to C as 9-1 points. Second, the scores of the three dimensions are weighted using an equal-weighting method. Third, the weighted scores are rounded and then mapped back to the nine levels from Aaa to C. Fourth, the adjustment rules for item D are considered to give the final carbon credit rating of the enterprise. Based on the ABC rating, the overall carbon credit rating of the enterprise is given. The number of records for item D starts from 0, and each additional record lowers the carbon credit rating by one level. The data analysis module is also responsible for upgrading carbon credit ratings, specifically: The first step is to simply take a weighted average of Y2 and Y3 to obtain Y4; The second step is to divide Y4 and Y1 into 5 categories each, with Y4 values ​​being rows and Y1 values ​​being columns, to create an orthogonal table; The third step is to determine the carbon credit rating of each company using an orthogonal table. a) Classify and evaluate by industry, with different industries evaluated separately; b. Based on the enterprise's position in the orthogonal table, determine the Y1 and Y4 values. An enterprise can only be promoted by one level at a time. c. Based on the determined Y1 value, find the company's account value V1; d, the value of Y1 is increased by one level, and the lower limit of this level is denoted as Y1_D. Calculate Y1_D * the size value of the enterprise = V2; e, V2-V1 represents the value of upgrading a company's carbon credit rating by one level; f. For V4 level upgrades, refer to V1.

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