Enterprise carbon credit one-stop service system based on carbon credit multi-dimensional evaluation method

Abstract

The invention discloses an enterprise carbon credit one-stop service system based on a carbon credit multi-dimensional evaluation method, and the system comprises the steps: constructing a quantitative evaluation system which comprises the three indexes of climate change, policy influence, industry technology and the like, and integrating the four function modules: data collection, model management, intelligent evaluation and visual analysis. And dynamic evaluation and real-time feedback optimization of carbon credit are realized. A hierarchical computing architecture and a machine learning algorithm are utilized, evaluation parameters are dynamically corrected, a standardized and precise enterprise carbon efficiency management closed loop is formed, evaluation efficiency and credibility are remarkably improved, and enterprise decarburization decision cost is reduced.

Description

Technical Field

[0001] The present invention relates to the field of carbon accounting technology, and in particular to a one-stop service system for enterprise carbon credit based on a multi-dimensional carbon credit evaluation method. Background Art

[0002] The carbon market plays an increasingly important role in helping businesses and society as a whole achieve net-zero greenhouse gas emissions. The establishment of a carbon credit service system can assist businesses in their decision-making and actions, thereby achieving decarbonization. Traditional carbon credit evaluation methods have the following flaws and shortcomings:

[0003] (1) The credibility of traditional carbon credit evaluation is low. Traditional carbon credit evaluation lacks a standardized evaluation system and algorithm, and lacks digital support and data verification mechanisms in data collection. This leads to doubts about the credibility of the evaluation results and makes it difficult to endorse corporate carbon credit.

[0004] (2) Traditional carbon credit evaluation is costly. Traditional carbon credit evaluation often requires hiring external experts, and the data collection and evaluation process requires a lot of time for repeated data collection, analysis, and verification, resulting in high time and economic costs for a carbon credit evaluation. In the end, only regular static assessment reports can be output, which are less timely and cannot reflect the company's true carbon credit status. Summary of the Invention

[0005] The present invention aims to address at least one of the technical problems existing in the prior art. To this end, one objective of the present invention is to propose a one-stop service system for enterprise carbon credits based on a multidimensional carbon credit evaluation method. This system addresses the pain points of traditional evaluation methods by constructing a multidimensional evaluation model and a digital service platform. The system establishes an evaluation system consisting of three primary indicators, six secondary indicators, and 18 tertiary indicators, develops five core functional modules to achieve fully automated evaluation, and constructs a four-layer technical architecture to ensure efficient system operation.

[0006] In order to solve the above problems, the present invention provides a one-stop service system for enterprise carbon credit based on a multi-dimensional carbon credit evaluation method, comprising:

[0007] Data collection layer: used to aggregate climate change data, policy impact data, industry technology level data, corporate carbon reduction behavior data, corporate asset status data, and corporate technology level data;

[0008] Multi-dimensional evaluation model layer: This includes a three-level evaluation indicator system that generates a comprehensive corporate carbon credit score through the quantitative calculation of external risk indicators (climate change risk Rc, policy impact risk Pmac / Preg / Pind) and internal risk indicators (corporate carbon reduction behavior Ac, asset status As, and technology level Te);

[0009] Service core layer:

[0010] Enterprise model management module: establishes a classified enterprise model library to support model building, classification and empowerment functions;

[0011] Credit indicator management module: maintains dynamic configuration of evaluation topics, primary indicators, and secondary indicators;

[0012] Credit evaluation management module: automatically generates credit rating reports based on a multi-dimensional evaluation model;

[0013] Visualization analysis layer:

[0014] Enterprise portrait module: Build a regional / industry-level enterprise energy and carbon portrait labeling system;

[0015] Comprehensive energy and carbon overview module: provides carbon efficiency rating statistics, industry distribution and energy and carbon data visualization analysis;

[0016] Feedback optimization layer: reversely correct the evaluation model parameters through the evaluation results to form a dynamic iteration mechanism.

[0017] Preferably, the multi-dimensional evaluation model layer adopts a hierarchical computing architecture:

[0018] First-level indicators: climate change risk - weight 0.2, policy impact risk - weight 0.5, industry technology level risk - weight 0.3;

[0019] Secondary indicators: including greenhouse gas change risk - weight 0.4, temperature change risk - weight 0.3, air quality change risk - weight 0.3;

[0020] Level 3 indicators: quantitative calculation, including:

[0021] A. The calculation formula for climate change risk Rc is:

[0022]

[0023] R C : Compound annual growth rate of greenhouse gases; WP i : warming potential of greenhouse gas i; E i : the emission of greenhouse gas type i;

[0024] B. Temperature change risk S t The calculation formula is:

[0025]

[0026] S t : annual average temperature growth intensity; y n : The previous year, such as 2023t n : Average temperature of the previous year

[0027] C. The formula for calculating the risk of air quality change is:

[0028] Annual average growth rate of days with good air quality (K aqi )

[0029]

[0030] Kaqi: average annual growth rate of days with good air quality; Dn 优 : the number of days with excellent air quality in the nth year; Dn 良 : the number of days with good air quality in the nth year; D 优 : the total number of days with excellent air quality in all sample years; D 良 : The total number of days with excellent air quality in all sample years; n: the number of sample years.

[0031] Preferably, the following logical relationships exist between the modules of the service core layer:

[0032] The enterprise model management module provides customized evaluation models for the credit evaluation management module;

[0033] The credit index management module dynamically adjusts the input parameters of the credit evaluation management module;

[0034] The output data of the credit evaluation management module drives the analysis and display of the enterprise portrait module and the comprehensive energy and carbon overview module.

[0035] Preferably, the visualization analysis layer implements the following data linkage:

[0036] The comprehensive energy and carbon overview module calls the classification labels of the enterprise portrait module;

[0037] Carbon efficiency rating statistical data feeds back into the model optimization of the enterprise model management module.

[0038] Preferably, the feedback optimization layer includes a model adaptation mechanism:

[0039] Train machine learning models through historical evaluation data and dynamically adjust the weights of evaluation indicators;

[0040] Establish a rule base for identifying abnormal data and automatically trigger the data verification process.

[0041] The advantages of the present invention compared with the prior art are:

[0042] (1) The present invention builds a one-stop carbon credit evaluation service system, provides a standardized carbon credit evaluation process and method, and facilitates enterprises to conduct carbon credit evaluation from multiple dimensions.

[0043] (2) Through the data collection, processing, analysis and display of the platform, the present invention can more comprehensively and accurately grasp the carbon credit status of enterprises and realize the standardization, precision and efficiency of carbon credit evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 This is a diagram of the overall system architecture of the present invention;

[0046] Figure 2 This is a diagram of the system business architecture of the present invention;

[0047] Figure 3 This is a diagram of the system data architecture of the present invention;

[0048] Figure 4 This is a diagram of the system technology architecture of the present invention. DETAILED DESCRIPTION

[0049] The following describes in detail embodiments of the present application. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application and are not to be construed as limiting the present application.

[0050] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "installed," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; they can refer to internal communication between two components or the interaction between two components. Those skilled in the art will understand the specific meanings of the above terms in this application based on the specific circumstances.

[0051] The present invention will be described in further detail below with reference to the accompanying drawings.

[0052] Combine Figures 1 to 4 The present invention provides a one-stop service system for enterprise carbon credit based on a multi-dimensional carbon credit evaluation method, comprising:

[0053] (1) Carbon credit evaluation calculation method based on multi-dimensional evaluation system

[0054] The multi-dimensional carbon credit evaluation system includes both external and internal corporate risks, divided into primary, secondary, and tertiary indicators. External risks include three primary indicators: climate change, policy impact, and industry technology level; internal risks include three primary indicators: corporate carbon reduction behavior, corporate asset status, and corporate technology level. The specific calculation method is as follows:

[0055] 1) Climate Change Risk Calculation Method

[0056] Greenhouse gas change risk (Compound annual growth rate: R c )

[0057]

[0058] R C : Compound annual growth rate of greenhouse gases;

[0059] WPi: warming potential of greenhouse gas i;

[0060] Ei: emission of greenhouse gas type i;

[0061] Temperature change risk (annual average temperature increase intensity S t )

[0062] Conduct impact assessments on temperature changes caused by greenhouse gases.

[0063]

[0064] S t : annual average temperature growth intensity;

[0065] y n : The previous year, such as 2023

[0066] t n : Average temperature of the previous year

[0067] Risk of changes in air quality

[0068] Conduct an impact assessment of environmental quality under the influence of multiple pollutants, focusing on the number of days with excellent and good air quality.

[0069] Annual average growth rate of days with good air quality (K aqi )

[0070]

[0071] Kaqi: average annual growth rate of days with good air quality;

[0072] Dn 优 : the number of days with excellent air quality in year n;

[0073] Dn良 : the number of days with good air quality in year n;

[0074] D 优 : The total number of days with excellent air quality in all sample years;

[0075] D 良 : The total number of days with excellent air quality in all sample years;

[0076] n: number of year samples.

[0077] 2) Policy impact risk

[0078] Macroeconomic policy impact risk (Pmac)

[0079] Assess the impact of macroeconomic policies, mainly the impact of international and national policy changes on corporate carbon credits.

[0080]

[0081] Pmac: Macroeconomic policy carbon pressure on enterprises;

[0082] an: is the weight ratio of the influencing factors;

[0083] En: eigenvector value corresponding to the policy influencing factor (E1~E5);

[0084] xn: is the constant corresponding to the influencing factor;

[0085] an+1: is the influencing factor of the industry variable.

[0086] Regional policy impact risk (Preg)

[0087] Assess the impact of regional policies, focusing on the impact of provincial and municipal policy changes on corporate carbon credits.

[0088]

[0089] Preg: Carbon pressure on enterprises from regional policies;

[0090] bn: is the weight ratio of the influencing factors;

[0091] Fn: eigenvector value corresponding to the policy influencing factor (F1 to F4);

[0092] yn: the constant corresponding to the influencing factor;

[0093] bn+1: is the influencing factor of the industry variable.

[0094] Industry policy impact risk (Pind)

[0095] Assess the impact of industry policies, focusing on the impact of industry-level policy changes on corporate carbon credits.

[0096]

[0097] Pind: Carbon pressure on companies from industry policies;

[0098] ain: the weight ratio of the influencing factors;

[0099] Ein: Ei1 to Ei5, the eigenvector value corresponding to the quantitative factor;

[0100] xin: is the constant corresponding to the influencing factor;

[0101] Ejn: The impact of qualitative factors on corporate carbon pressure.

[0102] 3) Risk of impact of industry technology level (Ti)

[0103] Consider the impact of the industry's overall technological level from two aspects: product technology level and production technology level, specifically including:

[0104] Product technology level risk (Tpro)

[0105] From the perspective of product energy consumption and carbon emissions, the industry's overall product technology level is evaluated, including two indicators: unit product energy consumption and unit product carbon emissions.

[0106]

[0107] E: total energy consumption of the industry;

[0108] C: total carbon emissions of the industry;

[0109] N: total industry output;

[0110] xn: impact factor corresponding to energy consumption change;

[0111] yn: impact factor corresponding to carbon emission changes;

[0112] zn: Influencing constant variable corresponding to changes in energy consumption and carbon emissions;

[0113] n: year.

[0114] Production technology level risk (Tman)

[0115] Evaluate the industry's overall production technology level from the perspectives of output value, number of employees, proportion of technical personnel, energy consumption, and carbon emissions, including per capita output value, energy consumption per unit of output value, and carbon emissions per unit of output value.

[0116]

[0117] Tm: includes two influencing factors: total energy consumption and total carbon emissions of the industry;

[0118] Tn: includes two influencing factors: the number of employees and the number of technical personnel;

[0119] V: total industry output value;

[0120] an: influencing factor of Tm;

[0121] bn: impact factor of influencing factor Tn;

[0122] c: The influencing variables corresponding to all influencing factors.

[0123] 4) Risk of corporate carbon reduction behavior (Ac)

[0124] An impact assessment of corporate carbon reduction behavior is conducted from four levels: energy structure, energy scale, management system, and market-based transactions.

[0125]

[0126] Ac: The impact of corporate carbon reduction behavior on corporate carbon assessment;

[0127] Ezero: the proportion of zero-carbon energy in the company's total energy;

[0128] E2: Proportion of zero-carbon energy consumption in the industry;

[0129] F3: Difference rate between industry zero-carbon energy consumption and national target value;

[0130] Ei3: Growth rate of zero-carbon energy in the industry’s energy consumption structure;

[0131] Ei4: Proportion of electricity consumption in industry energy consumption;

[0132] Ezero: the proportion of zero-carbon energy in corporate energy consumption;

[0133] E low: the proportion of low-carbon energy in corporate energy consumption;

[0134] Etotal: total energy consumption of the enterprise;

[0135] Sy: the characteristic vector of the enterprise in terms of management system and certification;

[0136] St: the characteristic vector of the enterprise in terms of market-based trading emission reduction;

[0137] a, b, c, d, e: impact factors corresponding to each variable;

[0138] n: number of sample years required for evaluation;

[0139] g: Influencing variables corresponding to corporate carbon reduction behavior.

[0140] 5) Enterprise asset status risk (As)

[0141] Through the development of corporate carbon asset projects, the impact of corporate carbon assets on corporate emission reduction is evaluated.

[0142] The formula for the impact of enterprise asset status:

[0143]

[0144] As: The impact of corporate asset status on corporate carbon assessment;

[0145] Asm: carbon emission rights as the characteristic vector of evaluation;

[0146] Asn: characteristic vector of other carbon assets as evaluation indicators;

[0147] i, j: the impact factors corresponding to each variable;

[0148] l: number of sample years required for evaluation;

[0149] k: The influencing variable corresponding to the enterprise's asset status.

[0150] 6) Enterprise technology level risk (Te)

[0151] Consider the impact of the company's own technical level from two aspects: product technical level and production technical level, and conduct a benchmark analysis with the industry's technical level.

[0152]

[0153] E: total energy consumption of the enterprise;

[0154] C: total carbon emissions of the enterprise;

[0155] Tm: enterprise technology influencing factors, including total energy consumption and total carbon emissions;

[0156] Tn: Enterprise technology influencing factors, including the number of enterprise employees and the number of technical personnel;

[0157] N: product output;

[0158] V: enterprise output value;

[0159] q: the influencing variable corresponding to the impact of enterprise technology level;

[0160] Tpro: industry product technology level;

[0161] Tman: Industry production technology level.

[0162] (2) One-stop service system for corporate carbon credit assessment

[0163] 1) Core Functionality

[0164] The one-stop service system for corporate carbon credit evaluation includes five core functions: corporate model management, credit indicator management, credit evaluation management, corporate profiling, and comprehensive energy and carbon overview, supporting the one-stop evaluation service for corporate carbon credit.

[0165] a. Enterprise Model Management

[0166] To meet the personalized needs of credit evaluation, we implement categorized management for different types of enterprises, establish a standard enterprise model library by enterprise type, and conduct credit evaluations on enterprises based on the evaluation indicators corresponding to the standard enterprise type. This mainly includes three application functions: model building, model classification, and model empowerment.

[0167] Model building: It provides the functions of creating, editing, and deleting enterprise models. Enterprise models can be built according to elements such as enterprise type, indicator category, primary indicator, secondary indicator, indicator weight, indicator description, etc., laying a solid foundation for personalized enterprise credit evaluation.

[0168] Model classification: Provides enterprise model classification editing function, which can classify and manage the built models. According to the conclusions of demand research and expert guidance, enterprise types and evaluation indicators are matched in a many-to-many manner to achieve the application goal of personalized enterprise management.

[0169] Model empowerment: Provides indicator empowerment function, empowers the enterprise model according to the indicator weight analysis conclusion obtained by combining expert subjective weighting method and other correlation evaluation methods, including three-level empowerment functions: evaluation theme empowerment, first-level indicator empowerment and second-level indicator empowerment.

[0170] b. Credit indicator management

[0171] It provides credit indicator management functions, which can maintain evaluation topics, primary indicators, and secondary indicators, including the functions of adding, deleting, modifying and checking credit indicators.

[0172] c. Credit evaluation management

[0173] Based on the carbon credit assessment model, we conduct carbon credit assessments on eligible companies, calculate credit ratings, and generate credit rating analysis reports. We provide functions such as adding, deleting, modifying, and querying companies, selecting company categories, importing indicator data, assigning ratings, and generating analysis reports.

[0174] d. Corporate portrait

[0175] From the perspective of government supervision, we extract profile tags based on credit indicators to form a regional and industry-level enterprise energy and carbon index database, constructing a diverse set of enterprise energy and carbon profiles to meet the refined management and control needs of local governments. This includes label management and enterprise profiling functions.

[0176] Tag management: interacts with the credit index function to provide credit index selection and tag addition, deletion, modification and query functions.

[0177] Enterprise portrait: interacts with the credit rating function to provide enterprise portrait screening and enterprise visual classification display functions.

[0178] e. Comprehensive energy and carbon overview

[0179] Based on the enterprise carbon credit evaluation data, we will build enterprise carbon efficiency rating statistics, industry distribution statistics, and enterprise energy carbon evaluation lists to form a visual analysis function for enterprise energy carbon management.

[0180] 2) Business Architecture

[0181] It includes 5 application modules and 11 sub-modules in total.

[0182] 3) Data Architecture

[0183] The component data architecture mainly brings together climate change data, policy impact data, industry technology level data, corporate carbon reduction behavior data, corporate asset status data, corporate technology level data, etc.

[0184] a. Climate change data: Global climate change data, mainly including data on changes in greenhouse gases such as carbon dioxide, hydrofluorocarbons, and perfluorocarbons;

[0185] b. Policy impact data: International, domestic, regional, and industry-level energy carbon emission policy data, including energy intensity reduction rate, carbon emission intensity reduction rate, carbon peak / carbon neutrality year, thermal power generation efficiency improvement, and clean energy share increase;

[0186] c. Industry technology level data: mainly including data on industry production processes, industry energy efficiency levels, product energy efficiency levels, energy structure changes, etc.;

[0187] d. Data on corporate carbon reduction activities: This primarily includes data on improvements to corporate energy structures, energy efficiency improvements, application of negative carbon technologies, and trading of green electricity and green certificates;

[0188] e. Enterprise asset status data: mainly includes enterprise carbon assets, fixed assets, current assets, annual turnover, gross profit margin, net profit margin, credit rating and other data.

[0189] f. Enterprise technology level data: mainly includes enterprise production technology, energy conservation and emission reduction technology data, etc.

[0190] 4) Technical Architecture

[0191] The platform follows a multi-layer distributed application model, adopts componentized and dynamic software technology, and utilizes a consistent and shareable data model. It implements a multi-layer technical system design according to the data resource layer, support service layer, business logic layer, business service layer and presentation layer. Through various integration methods such as service bus, data exchange platform and data center, it realizes platform interface integration, data integration and application integration to meet various application requirements within the platform's business scope, as well as the information interaction requirements of vertical integration and horizontal integration.

[0192] like Figure 1 The figure shows the overall architecture of the one-stop service system for corporate carbon credit evaluation, which includes five core functions: corporate model management, credit indicator management, credit evaluation management, corporate profiling, and comprehensive energy and carbon overview.

[0193] like Figure 2 The following figure shows the business architecture of the one-stop service system for enterprise carbon credit evaluation. The entire application architecture is designed to provide comprehensive, accurate, and real-time data support and business services for the one-stop service system, thereby improving the accuracy and efficiency of credit evaluation.

[0194] like Figure 3 The following figure shows the data architecture of the one-stop service system for corporate carbon credit assessment. The platform data architecture mainly integrates public platform data and corporate platform data.

[0195] like Figure 4 The technical architecture shown is generally divided into infrastructure layer, data layer, support service layer, service layer, application layer, and presentation layer. Unified security assurance strategies and unified monitoring and logging are implemented throughout all levels of the technical architecture, providing standardized service capabilities and data access services at the platform boundaries.

[0196] Table 1 Carbon credit evaluation system

[0197]

[0198]

[0199] Finally, all parts not fully described in the present invention adopt mature equipment and mature technical means in the prior art.

[0200] The present invention and its embodiments are described above. This description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if a person skilled in the art is inspired by this and, without departing from the purpose of the present invention, designs structures and embodiments similar to this technical solution without inventiveness, they shall fall within the scope of protection of the present invention.

Claims

1. A one-stop service system for corporate carbon credit based on a multi-dimensional carbon credit evaluation method, characterized by: include: Data collection layer: used to aggregate climate change data, policy impact data, industry technology level data, corporate carbon reduction behavior data, corporate asset status data, and corporate technology level data; Multi-dimensional evaluation model layer: This includes a three-level evaluation indicator system that generates a comprehensive corporate carbon credit score through the quantitative calculation of external risk indicators (climate change risk Rc, policy impact risk Pmac / Preg / Pind) and internal risk indicators (corporate carbon reduction behavior Ac, asset status As, and technology level Te); Service core layer: Enterprise model management module: establishes a classified enterprise model library to support model building, classification and empowerment functions; Credit indicator management module: maintains dynamic configuration of evaluation topics, primary indicators, and secondary indicators; Credit evaluation management module: automatically generates credit rating reports based on a multi-dimensional evaluation model; Visualization analysis layer: Enterprise portrait module: Build a regional / industry-level enterprise energy and carbon portrait labeling system; Comprehensive energy and carbon overview module: provides carbon efficiency rating statistics, industry distribution and energy and carbon data visualization analysis; Feedback optimization layer: reversely correct the evaluation model parameters through the evaluation results to form a dynamic iteration mechanism.

2. The one-stop service system for enterprise carbon credit based on the multi-dimensional carbon credit evaluation method according to claim 1 is characterized by: The multi-dimensional evaluation model layer adopts a hierarchical computing architecture: First-level indicators: climate change risk - weight 0.2, policy impact risk - weight 0.5, industry technology level risk - weight 0.3; Secondary indicators: including greenhouse gas change risk - weight 0.4, temperature change risk - weight 0.3, air quality change risk - weight 0.3; Level 3 indicators: quantitative calculation, including: A. The calculation formula for climate change risk Rc is: R C : Compound annual growth rate of greenhouse gases; WP i : warming potential of greenhouse gas i; E i : the emission of greenhouse gas type i; B. Temperature change risk S t The calculation formula is: S t : annual average temperature growth intensity; y n : The previous year, such as 2023t n : Average temperature of the previous year C. The formula for calculating the risk of air quality change is: Annual average growth rate of days with good air quality (K aqi ) Kaqi: average annual growth rate of days with good air quality; Dn 优 : the number of days with excellent air quality in the nth year; Dn 良 : the number of days with good air quality in the nth year; D 优 : the total number of days with excellent air quality in all sample years; D 良 : The total number of days with excellent air quality in all sample years; n: number of year samples.

3. The one-stop service system for enterprise carbon credit based on the multi-dimensional carbon credit evaluation method according to claim 1 is characterized by: The following logical relationships exist between the modules in the service core layer: The enterprise model management module provides customized evaluation models for the credit evaluation management module; The credit index management module dynamically adjusts the input parameters of the credit evaluation management module; The output data of the credit evaluation management module drives the analysis and display of the enterprise portrait module and the comprehensive energy and carbon overview module.

4. The one-stop service system for enterprise carbon credit based on the multi-dimensional carbon credit evaluation method according to claim 1 is characterized by: The visualization analysis layer implements the following data linkage: The comprehensive energy and carbon overview module calls the classification labels of the enterprise portrait module; Carbon efficiency rating statistical data feeds back into the model optimization of the enterprise model management module.

5. The one-stop service system for enterprise carbon credit based on the multi-dimensional carbon credit evaluation method according to claim 1 is characterized by: The feedback optimization layer includes a model adaptation mechanism: Train machine learning models through historical evaluation data and dynamically adjust the weights of evaluation indicators; Establish a rule base for identifying abnormal data and automatically trigger the data verification process.

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