Carbon value analysis method and system based on artificial intelligence

Abstract

The invention discloses a carbon value analysis method and system based on artificial intelligence, and belongs to the technical field of environmental engineering. Comprising the steps of inputting green low-carbon activity data and a comprehensive value evaluation target; the carbon value analysis center depicts a green low-carbon scene through an artificial intelligence technology according to the input data and target; potential values of green low-carbon activities are analyzed, and value types and paths capable of being developed and created are given; new content generation based on a standard template and user preference is realized, a project design file of greenhouse gas voluntary emission reduction project development is automatically generated, the development creation direction of sustainable development value and financial value is given by artificial intelligence, and the comprehensive value of green low-carbon activities is evaluated; according to the method and the system, the data of the green low-carbon activities can be comprehensively and intelligently analyzed, a value development and creation scheme and a comprehensive value evaluation result of the green low-carbon activities are given, and the accuracy and the efficiency of analysis are improved by processing the data by utilizing an artificial intelligence technology.

Description

Technical Field

[0001] The present disclosure belongs to the field of environmental engineering technology, and specifically relates to a carbon value analysis method and system based on artificial intelligence. Background Art

[0002] Carbon value refers to the economic, environmental, and social value brought about by carbon reduction / avoidance or carbon removal / removal. Carbon value analysis refers to the process of discovering the potential value of green and low-carbon activities (i.e., specific scenarios of carbon emissions or carbon reductions), optimizing development plans, and comprehensively evaluating their value to support decision-making and management of green and low-carbon activities. Carbon value analysis can help enterprises, governments, society, and other parties identify and utilize the potential value of green and low-carbon activities, and promote low-carbon development and green transformation.

[0003] At present, there are some tools and methods for carbon value analysis, such as carbon value analysis tool (CVAT), carbon risk assessment method, greenhouse gas emission valuation method, etc. These tools and methods mainly conduct quantitative or qualitative evaluation of green and low-carbon activities from a single or multiple dimensions, such as internal rate of return, emission reduction cost, environmental benefit, etc. However, these tools and methods lack a comprehensive, objective, scientific and efficient carbon value analysis framework, and cannot reflect the multi-dimensionality, dynamics and complexity of green and low-carbon activities; they lack carbon value analysis technology based on artificial intelligence, making it difficult to fully explore the value of green and low-carbon activities, difficult to develop the value of green and low-carbon activities at low cost, and unable to improve the accuracy and efficiency of carbon value analysis; therefore, the present invention aims to provide a carbon value analysis method and system based on artificial intelligence, which automatically identifies, intercepts, summarizes and analyzes unstructured data through natural language interpretation and intelligent interaction with customers, and effectively depicts green and low-carbon activity scenarios; analyzes the potential value of green and low-carbon activities, and provides the value types and paths that can be developed and created; realizes the generation of new content based on standard templates and user preferences, automatically generates project design documents for the development of voluntary greenhouse gas emission reduction projects, and provides the development and creation direction of sustainable development value and financial value through artificial intelligence technology; evaluates the five-dimensional value and comprehensive value of green and low-carbon activities, comprehensively and truly reflects the value of green and low-carbon activities, and maximizes the value of green and low-carbon activities. Summary of the invention

[0004] In view of the shortcomings of the prior art, the purpose of the present disclosure is to provide an artificial intelligence-based carbon value analysis method and system, which solves the problem of the single carbon value of green and low-carbon activities in the prior art, solves the problem that the potential carbon value of green and low-carbon activities in the prior art cannot be identified, mined, developed and created, and solves the high cost problem of value development of green and low-carbon activities in the prior art, thereby effectively identifying and utilizing the potential value of green and low-carbon activities and promoting low-carbon development and green transformation.

[0005] The purpose of this disclosure can be achieved through the following technical solutions:

[0006] A carbon value analysis method based on artificial intelligence includes the following steps:

[0007] Input data and comprehensive value evaluation targets of green and low-carbon activities;

[0008] The Carbon Value Analysis Center uses artificial intelligence technology to depict green and low-carbon scenarios based on input data and goals;

[0009] Explore the five-dimensional value of green and low-carbon activities, provide the types of value that can be developed and created and their paths, automatically generate project design documents for the development of voluntary greenhouse gas emission reduction projects, provide the development and creation direction of sustainable development value and financial value through artificial intelligence technology, and evaluate the comprehensive value of green and low-carbon activities;

[0010] The five dimensions of value include: economic value, environmental value, sustainable development value, brand value, and financial value.

[0011] Furthermore, the artificial intelligence technology includes: semantic analysis, matching, natural language processing, image recognition, speech recognition, machine learning, data mining, knowledge discovery, deep learning, optimization algorithms, generation models, and evaluation models.

[0012] An artificial intelligence-based carbon value analysis system, including multiple user terminals and a carbon value analysis center;

[0013] User side: used to send query requests, receive and execute acquisition instructions, send green and low-carbon activity data; receive analysis results, send demand requests based on the results, and receive merchant side information;

[0014] Carbon Value Analysis Center: used to receive query requests, send acquisition instructions according to query requests, and obtain green and low-carbon activity data; explore the five-dimensional value of green and low-carbon activities, provide the value types and paths that can be developed and created, automatically generate project design documents for the development of voluntary greenhouse gas emission reduction projects, and provide the development and creation direction of sustainable development value and financial value through artificial intelligence technology, and evaluate the comprehensive value of green and low-carbon activities, obtain analysis results, and send them; obtain merchant-side information according to demand requests and send them;

[0015] The five dimensions of value include: economic value, environmental value, sustainable development value, brand value, and financial value.

[0016] A readable storage medium, wherein the storage medium stores a carbon value analysis method based on artificial intelligence and a software program, wherein the software program includes software code for a carbon value analysis method based on artificial intelligence.

[0017] A computer processor is configured to run the computer program to perform an artificial intelligence-based carbon value analysis method.

[0018] Beneficial effects of the present disclosure:

[0019] Compared with the existing technology, the present invention can effectively identify the multiple values ​​of green and low-carbon activities, optimize the carbon value development and creation plans of green and low-carbon activities, reduce the cost and risk of green and low-carbon activity value management, shorten the identification and development cycle, and maximize the value of green and low-carbon activities. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 It is a schematic diagram of the system structure of an embodiment of the present disclosure. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0023] Embodiment 1: A carbon value analysis method based on artificial intelligence aims to improve the efficiency and effectiveness of value assessment and conversion of green and low-carbon activities and promote the realization of carbon peak and carbon neutrality goals.

[0024] The following steps are involved:

[0025] (1) The user terminal establishes a connection with the carbon value analysis center by sending a login request and a query request to obtain instructions and analysis results;

[0026] (2) The user end executes the acquisition instruction through the acquisition unit to collect green and low-carbon activity data and send it to the carbon value analysis center;

[0027] (3) The carbon value analysis center analyzes the green and low-carbon activity data through the analysis unit, obtains the analysis results, and sends them to the user end;

[0028] (4) The user side sends a demand request based on the analysis results and receives information from the merchant side to achieve the value transformation of green and low-carbon activities.

[0029] in,

[0030] The user end refers to the terminal equipment of individuals or organizations that perform green and low-carbon activities;

[0031] The collection unit refers to a module built into or external to the user end for collecting green and low-carbon activity data;

[0032] Green and low-carbon activity data refers to various information reflecting the user's execution of green and low-carbon activities, such as text, voice, image, video, geographic location, time, etc.

[0033] The Carbon Value Analysis Center refers to the cloud platform that provides carbon value analysis services, including servers, databases, networks, etc.;

[0034] The analysis unit refers to the module within the Carbon Value Analysis Center that is responsible for analyzing green and low-carbon activity data, including the search sub-unit, scenario characterization sub-unit, value mining sub-unit, value creation sub-unit and value realization sub-unit;

[0035] The search subunit is to search for relevant historical data in the database according to the query request sent by the user end, and return it to the user end;

[0036] The scenario characterization subunit is to perform semantic analysis, matching and natural language processing on the green and low-carbon activity data sent by the user end, characterize the green and low-carbon scenario, and return it to the user end;

[0037] The value mining sub-unit refers to the green and low-carbon activity scenarios returned by the scenario characterization sub-unit, which are subjected to image recognition, voice recognition, machine learning and data mining to identify and mine the five-dimensional value of green and low-carbon activities, namely economic value, environmental value, sustainable development value, brand value and financial value, and to determine the direction of the value development and creation of green and low-carbon activities, and return it to the user end;

[0038] The value creation sub-unit is to perform knowledge discovery, deep learning and optimization algorithms on the five-dimensional value returned by the value mining sub-unit, create an optimization plan, that is, how to improve the five-dimensional value of green and low-carbon activities, and return it to the user end;

[0039] The value realization sub-unit refers to the generation model and evaluation model based on the optimization plan returned by the value creation sub-unit, evaluating the comprehensive value, that is, the overall benefit of green and low-carbon activities, and returning it to the user end;

[0040] The merchant terminal refers to the terminal equipment of individuals or organizations that provide green and low-carbon products or services;

[0041] Demand request refers to the information sent by the user end to the carbon value analysis center expressing its demand for green and low-carbon products or services based on the analysis results;

[0042] Merchant-side information refers to the information sent by the merchant to the user-side based on demand requests, expressing the green and low-carbon products or services it provides.

[0043] The method of use of the present invention is as follows:

[0044] (1) The user accesses the website or application of the Carbon Value Analysis Center through the Internet, enters the user name and password, and sends a login request;

[0045] (2) The Carbon Value Analysis Center verifies the login request. If successful, it returns a successful login message and an acquisition instruction; if unsuccessful, it returns a failed login message and an error prompt;

[0046] (3) After receiving the successful login information and the acquisition instruction, the user terminal collects the green and low-carbon activity data through the acquisition unit according to the acquisition instruction and sends it to the carbon value analysis center;

[0047] (4) After receiving the green and low-carbon activity data, the carbon value analysis center analyzes it through the analysis unit, obtains the analysis results, and sends them to the user end;

[0048] (5) After receiving the analysis results, the user can view the five-dimensional value and comprehensive value of the green and low-carbon activities they have performed, and send demand requests based on their needs, such as asking which nearby merchants provide green and low-carbon products or services;

[0049] (6) After receiving the demand request, the carbon value analysis center forwards it to the corresponding merchant end and returns the merchant end information to the user end;

[0050] (7) After receiving the information from the merchant, the user can select the green and low-carbon products or services of interest and conduct transactions with the merchant to realize the value transformation of green and low-carbon activities.

[0051] The present invention also provides a carbon value analysis system based on artificial intelligence;

[0052] The system of the present invention comprises the following components:

[0053] User end: the same as the user end in the above method;

[0054] Collection unit: the same as the collection unit in the above method;

[0055] Carbon value analysis center: the same as the carbon value analysis center in the above method;

[0056] Analysis unit: the same as the analysis unit in the above method;

[0057] Search subunit: the same as the search subunit in the above method;

[0058] Scene characterization subunit: the same as the scene characterization subunit in the above method;

[0059] Value mining subunit: the same as the value mining subunit in the above method;

[0060] Value realization subunit: the same as the value realization subunit in the above method;

[0061] Merchant side: Same as the merchant side in the above method.

[0062] The system of the present invention connects various components through a network to realize the functions of the above method.

[0063] The implementation effects of the present invention are as follows:

[0064] The present invention uses artificial intelligence technology to analyze green and low-carbon activity data, evaluates its value from multiple dimensions, and provides optimization solutions, thereby improving the efficiency and quality of green and low-carbon activity value analysis;

[0065] The present invention realizes the value transformation of green and low-carbon activities by establishing interaction between the user end and the merchant end, and promotes the consumption and supply of green and low-carbon products or services.

[0066] Embodiment 2, a carbon value analysis method based on artificial intelligence, comprising the following steps:

[0067] Receive query requests, send acquisition instructions according to the query requests, and obtain green and low-carbon activity data;

[0068] Analyze the green and low-carbon activity data, obtain analysis results, and send them, where the analysis results at least include: data description of green and low-carbon activities, value types that can be developed and created by green and low-carbon activities, value creation plans for green and low-carbon activities, and five-dimensional value evaluation and comprehensive value evaluation of green and low-carbon activities.

[0069] For various green and low-carbon activities, through natural language interpretation and intelligent interaction with customers, unstructured data is automatically identified, intercepted, summarized and analyzed to effectively portray green and low-carbon scenarios; the potential value of green and low-carbon activities is identified and explored, and the types of value that can be developed and created and the direction of development and creation are given; new content generation based on standard templates and user preferences is achieved, and project design documents (pdd files) for the development of voluntary greenhouse gas emission reduction projects are automatically generated. Through artificial intelligence technology, the optimization path of sustainable development value indicators that are lower than the set value is automatically given according to standard templates, as well as plans for the development and creation of financial value, to optimize the development and creation plans of green and low-carbon activities and enhance the carbon value of green and low-carbon activities.

[0070] The carbon scenario characterization is to automatically identify, intercept, summarize and analyze the collected unstructured data and information entered by customers through artificial intelligence technology, and specifically depict the green and low-carbon activity scenarios from multiple aspects such as carbon emission data, energy data, technical data, economic data and sustainable development, and classify them.

[0071] Specifically, data on green and low-carbon activities include carbon emission data, energy data, technical data, economic data, and sustainable development data. Carbon emission data at least include carbon dioxide emissions and time, methane emissions and time, N2O emissions and time, carbon reduction and time, carbon sink and time; energy data at least include total green electricity consumption, total thermal power consumption, total coal consumption, and total natural gas consumption; technical data at least include unit product energy consumption or unit product comprehensive energy consumption or unit energy factor comprehensive energy consumption of energy-consuming equipment. Economic data include industry status, green and low-carbon brand support, operating income from expanding new business, carbon emission reduction cost, carbon removal cost, project investment cost, project payback period, project financing amount and interest rate, and the cost of various carbon credits for project development (including third-party consulting fees and coordination management fees; third-party project review fees; third-party emission reduction verification fees). Sustainable development data include specific data on green and low-carbon activities in local / regional / global environment, social sustainability and development, economic and technological development, etc.

[0072] The carbon emission calculation method refers to the method of the IPCC 2006 National Greenhouse Gas Inventory Guidelines 2019 Revised Edition, and the formula is as follows:

[0073]

[0074] E i NCV represents the physical consumption of the i-th energy, including raw coal, coke, fuel oil, gasoline, kerosene, diesel and natural gas; i Indicates the average low calorific value of energy; CEF iIndicates the carbon content coefficient of energy; COF i Indicates the carbon oxidation coefficient of the energy source.

[0075] For projects that generate carbon emission reductions, the carbon emission reduction calculation formula is as follows:

[0076] ER y =BE y -PE y -L y

[0077] ER y is the emission reduction of the project activity in a certain year y, BE y is the baseline emission, PE y is the project emission, L y Emissions caused by leaks.

[0078] For projects that generate carbon removal, the carbon reduction calculation formula is as follows:

[0079] ΔC AR,t =ΔC ACTURAL,t -ΔC BSL,t -LK t

[0080] in,

[0081] ΔC AR,t = Emission reduction of the project in year t; tCO2

[0082] ΔC ACTURAL,t = Carbon sink of the project in year t; tCO2

[0083] ΔC BSL,t = baseline carbon sink in year t; tCO2

[0084] LK t = leakage emissions generated by project activities in year t

[0085] t = 1, 2, 3, ..., the number of years after the project starts

[0086] Furthermore, the classification of carbon scenarios includes the following 16 areas, namely energy industry, energy distribution, energy demand, manufacturing, chemical industry, construction industry, transportation industry, mineral products, metal production, fugitive emissions from fuels, fugitive emissions from the production and consumption of halogenated carbon compounds and sulfur hexafluoride, solvent use, waste disposal, afforestation and reforestation, agriculture, and carbon capture and storage.

[0087] The identification and mining of the potential value of green and low-carbon activities is to analyze the data of green and low-carbon activities, analyze the specific types of five-dimensional carbon values ​​that may exist in green and low-carbon activities, and determine the direction of value development and creation of green and low-carbon activities. The five-dimensional value refers to economic value, environmental value, sustainable development value, brand value, and financial value.

[0088] Among them, economic value includes net income from the sale of environmental rights and interests, net income from carbon labeling / carbon neutrality certification, net loss reduction brought about by the company's completion of contract performance tasks, net expenditure reduction brought about by energy conservation, government subsidies, etc. Net income from the sale of environmental rights and interests includes net income from the sale of various carbon credits developed from green and low-carbon activities and net income from the sale of green certificates generated from green and low-carbon activities.

[0089] Environmental value refers to the reduction in environmental damage caused by carbon dioxide due to carbon removal and carbon emission reduction, including the monetary value brought about by improvements in ecological environment quality such as the weakening of greenhouse effect, mitigation of climate change, and reduction of extreme weather.

[0090] Sustainable development value is the progress of society, economy and environment in related aspects of the Global Sustainable Development Goals (SDGs) set by the United Nations due to carbon removal and carbon emission reduction.

[0091] Brand value is the sum of the added value of benefits produced by brand-related products, including the added brand value brought about by carbon removal and carbon emission reduction.

[0092] Financial value refers to the reduced financing costs, spot investment income from carbon credits, investment income from carbon financial derivatives, and improved valuation levels that can be obtained from green and low-carbon activities.

[0093] Further, analyze the economic value, sustainable development value, and financial value development and creation plans of green and low-carbon activities.

[0094] Furthermore, the environmental rights and interests in the economic value of green and low-carbon activities are analyzed as follows: whether the projects of green and low-carbon activities can meet the compliance and additionality requirements for the development of voluntary greenhouse gas emission reduction projects. Compliance requirements include subject compliance, legal compliance, and technical compliance. Subject compliance refers to whether the subject applying for the development of voluntary greenhouse gas emission reduction projects meets the requirements of the organization or individual specified in the policy; for fixed asset projects, legal compliance at least includes the approval procedures for fixed asset investment projects, project approval documents, and environmental impact assessment reports. For afforestation and reforestation projects, legal compliance materials at least include forest rights certificates and environmental impact assessment reports. Technical compliance includes whether the project start time meets the start and end time specified in the policy and whether there is an applicable methodology.

[0095] The methodology described above is the methodology for developing voluntary greenhouse gas emission reductions, which can be obtained from the website of the management agency of voluntary greenhouse gas emission reduction trading, such as the website of the management agency of VCS (https: / / verra.org / ) and the website of the management agency of CCER (Ministry of Ecology and Environment of my country).

[0096] Furthermore, additionality means that there will be various obstacles in the absence of additional support for carbon emission reduction, which will make the project unable to be implemented. Additionality analysis is carried out from three aspects: First, whether the carbon emission reduction benefits are considered in advance. Through artificial intelligence technology, the project feasibility study report and the resolutions of the board of directors / general manager's office meeting are automatically searched to prove that the impact of carbon emission reduction benefits on project benefits has been fully considered during the project planning and construction stage. The second is universality analysis. In the area where the project activities are planned to be carried out (generally provinces, autonomous regions and municipalities directly under the central government), similar project activities generally implemented by comparable entities or institutions (such as companies, national governments, local governments, etc.) prove that the proposed project activities are not universal practices. Universality analysis automatically searches for the areas where green and low-carbon activities are located through artificial intelligence technology. If the green and low-carbon activity is not a universal practice in the area where the project activities are planned to be carried out or in similar areas, an obstacle analysis is conducted.

[0097] Furthermore, artificial intelligence technology is used to analyze whether this is a common practice in the following steps:

[0098] Step 1: Take + / -50% of the project design output (capacity) as the applicable output range;

[0099] Step 2: Identify all items that meet the following criteria

[0100] 2.1 The project and the proposed development project are located in the same area;

[0101] 2.2 The project uses the same technology as this project;

[0102] 2.3 If the project activity involves energy conversion, the project and the project activity use the same energy / fuel and raw materials

[0103] 2.4 The project provides the same services / products as this project;

[0104] 2.5 The project’s capacity / output is within the range identified in step 1;

[0105] 2.6 The start time of the project's commercial operation shall be earlier than the earlier of the time when the project's design documents are posted online for public review and the start time of the project's activities.

[0106] Step 3: Exclude the projects identified in step 2 that have been registered or are applying for domestic and foreign emission reduction mechanisms, and define the number of remaining projects as N all ;

[0107] Step 4: Identify the remaining projects in step 3 that use different technologies from this project and define the number of such projects as N diff

[0108] Step 5: Calculate the share factor of similar projects to this project F = 1 – D diff / D all

[0109] Conclusion: If F < 0.2 or N all –N diff <3, then this project is not universal.

[0110] The third is barrier analysis, which compares the internal rate of return (IRR) of green and low-carbon activities with the benchmark rate of return. If the internal rate of return is less than the benchmark rate of return (which can be set at 8%), the additionality requirement is met. As mentioned above, the internal rate of return (IRR) of green and low-carbon activities is the discount rate when the total present value of capital inflows is equal to the total present value of capital outflows and the net present value is zero.

[0111]

[0112] The formula for calculating the net present value is:

[0113]

[0114] In this formula, NPV is the net present value, CF i is the cash inflow of each period, CF0 is the initial capital investment, and r is the interest rate level during the period. The compliance and additionality analysis of the development of voluntary greenhouse gas emission reduction projects will output the development and creation direction of the environmental rights and interests value of green and low-carbon activities: for green and low-carbon activities that have passed the compliance and additionality requirements, the development of international carbon credit indicators (at least including VCU, VERs), my country's carbon credit indicators CCER and domestic green certificates will be used as the direction of environmental rights and interests value mining. For green and low-carbon activities that cannot develop international carbon credit indicators (at least including VCU, VERs) and my country's carbon credit indicators CCER, artificial intelligence automatically determines whether they fall within the scope of national green certificate issuance, including national wind power (including distributed wind power and offshore wind power), solar power generation (including distributed photovoltaic power generation and solar thermal power generation), conventional hydropower, biomass power generation, geothermal power generation, and ocean power generation. If so, it will give suggestions for developing green certificates.

[0115] Furthermore, for green and low-carbon activities that can be developed by international carbon credit indicators (including at least VCU and VERs), my country's carbon credit indicators CCER and green certificates, if they do not fall within the scope of national green certificate issuance, then international carbon credit indicators (including at least VCU and VERs) or my country's carbon credit indicators CCER will be developed; if they fall within the scope of national green certificate issuance, then it is analyzed whether to develop green certificates or international carbon credit indicators (including at least VCU and VERs) or my country's carbon credit indicators CCER. Under the same conditions, the principle is to develop environmental rights and interests products with higher economic benefits. The economic benefits of green certificate development are: emission reduction / 0.5703*green certificate price, and the economic benefits of various carbon credit development are: various carbon credit indicators unit price*emission reduction. Compare the size of the benefits of the two and develop products with relatively large benefits. Among them, 0.5703 is based on the national average electricity emission factor of 0.5703 tons CO2 / MWh released by the Ministry of Ecology and Environment in 2022. The subsequent national average electricity emission factor will be automatically obtained from the website of the Ministry of Ecology and Environment through artificial intelligence technology after the update. The price of green certificates is taken from the green certificate subscription platform (www.greenenergy.org.cn), and the unit prices of various carbon credit indicators are taken from the prices published by authoritative trading institutions of various carbon credit indicators.

[0116] For carbon emission reduction projects, the carbon emission reduction calculation formula is as follows:

[0117] ER y =BE y -PE y -L y

[0118] ER y is the emission reduction of the project activity in a certain year y, BE y is the baseline emission, PE y is the project emission, L y Emissions caused by leaks.

[0119] For carbon removal projects, the carbon emission reduction calculation formula is as follows:

[0120] ΔC AR,t =ΔC ACTURAL,t -ΔC BSL,t -LK t

[0121] in,

[0122] ΔC AR,t = Emission reduction of the project in year t; tCO2

[0123] ΔC ACTURAL,t = Carbon sink of the project in year t; tCO2

[0124] ΔC BSL,t = baseline carbon sink in year t; tCO2

[0125] LK t = leakage emissions generated by project activities in year t

[0126] t = 1, 2, 3, ..., the number of years after the project starts

[0127] Furthermore, the net income from carbon labeling / carbon neutrality certification in the economic value of green and low-carbon activities is calculated as follows: Green and low-carbon activities produce end-consumer goods, and the net income from carbon labeling is calculated according to the following formula.

[0128] Y1 = (1 + premium ratio) * product sales revenue before labeling - carbon label certification unit price * product quantity

[0129] Among them, Y1 is the net income of carbon labeling, the premium ratio is 15% and is regularly updated through artificial intelligence technology. The unit price of carbon label certification is regularly taken from the quotations of major carbon label certification companies in the market through artificial intelligence technology.

[0130] Green and low-carbon activities produce industrial products, and the net income of carbon neutral certification is calculated according to the following formula

[0131] Y2 = (1 + cost reduction ratio) * product sales revenue before labeling - carbon neutral certification unit price * number of factories

[0132] Among them, Y2 is the net income of carbon neutrality certification, the cost reduction ratio is 5% and is regularly updated through artificial intelligence technology. The unit price of carbon neutrality certification is regularly taken from the quotations of major carbon neutrality certification companies in the market through artificial intelligence technology.

[0133] If Y1>0, AI will give suggestions for carbon label certification; if Y2>0, AI will give suggestions for carbon neutral certification;

[0134] Furthermore, the sustainable development value mining of green and low-carbon activities is analyzed as follows. Referring to the Gold Standard for the development of voluntary emission reductions, the list of indicators and the scoring system for the evaluation of green and low-carbon activities are determined, as shown in the following table. Based on the input sustainable development data, the green and low-carbon activities are scored from -2 (greater negative impact) to +2 (greater positive impact) to evaluate these indicators. Artificial intelligence automatically gives specific sustainable development indicators with a score of less than 2 points, indicating the direction of development and creation of sustainable development value.

[0135]

[0136] Furthermore, the financial value of green and low-carbon activities is analyzed as follows: the financial value of various green and low-carbon activities is analyzed to provide direction for the development and creation of green financial value. As mentioned above, financial means are to evaluate the quality of green and low-carbon projects. High-quality green and low-carbon projects can reduce financing costs. With reference to the national group standard "Corporate Carbon Credit Evaluation Specification" (T / CECA-G0189-2022), the "Core Carbon Principles" issued by the Integrity Council for the Voluntary Carbon Market (ICVCM) in 2023, and the carbon credit rating system of Sylvera, a US carbon credit rating company, combined with the evaluation of credit risk by Chinese commercial banks, a green index for the project is established, the carbon risk of the project is evaluated, and the corresponding rating is given.

[0137] The specific indicators of the green index are as follows: 1. Sustainable development score; 2. Permanence of emission reduction; 3. Annual emission reduction; 4. Type of emission reduction.

[0138]

[0139] The weights of primary and secondary indicators are determined through the AHP method, and the scores of secondary indicators are determined using the fuzzy comprehensive evaluation method. The scores of the green index are comprehensively obtained, and the corresponding grades are given through artificial intelligence technology. The directions for optimization are given according to the standard template.

[0140] Evaluation score [18,20]

[1517] [12,14] [9,11] [6,8] [3,5] [0,2] Green Level Dark Green Medium Green Light green Light Brown Medium Brown Dark Brown black

[0141] Furthermore, in the carbon value creation link, for green and low-carbon activities that can be developed into carbon credits, artificial intelligence technology is used to automatically generate project design documents (PDDs) based on standard templates and user preferences, thereby reducing the cost of writing project design documents (PDDs), shortening the development cycle, and reducing development risks.

[0142] Furthermore, corresponding project design document specification templates are given based on 16 areas of green and low-carbon activities, namely, energy industry, energy distribution, energy demand, manufacturing, chemical industry, construction industry, transportation industry, mineral products, metal production, fugitive emissions from fuels, fugitive emissions from the production and consumption of halogenated carbon compounds and sulfur hexafluoride, solvent use, waste disposal, afforestation and reforestation, agriculture, and carbon capture and storage.

[0143] Part A of the project design document: Project activity description can be obtained from the project feasibility study report through artificial intelligence technology. The project activity description is an introduction to the project itself, including the project type, project location, related technologies and main equipment used, project business conditions, etc. The content is obtained from the electronic version of the project feasibility study report through artificial intelligence technology.

[0144] Part B: Application of selected baseline and monitoring methodologies. In the analysis of the applicability of methodologies, artificial intelligence technology is used to preliminarily screen methodologies similar in name to the project based on the field to which the green and low-carbon activity project belongs, and then the proposed project is compared one by one with the applicability of each screened methodology. If the applicable conditions of one of the methodologies are suitable for the proposed project, this methodology can be used for project development. When a project is applicable to multiple methodologies, the website of the management agency for voluntary greenhouse gas emission reduction trading is searched through artificial intelligence technology, and the methodology with the largest number of registered projects is selected for project development.

[0145] The methodology described above is the methodology for developing voluntary greenhouse gas emission reductions, which can be obtained from the website of the management agency of voluntary greenhouse gas emission reduction trading, such as the website of the management agency of VCS (https: / / verra.org / ) and the website of the management agency of CCER (Ministry of Ecology and Environment of my country).

[0146] For the project boundary, artificial intelligence technology is used to describe the project boundary and baseline boundary through text and drawings according to the standard template; for the types of greenhouse gases contained in the proposed project scenario, they are searched and obtained from the methodology through artificial intelligence technology.

[0147] Furthermore, the baseline refers to the scenario of providing products and services equivalent to green and low-carbon activities when there are no green and low-carbon activities. If green and low-carbon activities are not carried out, then alternative scenarios for providing the same amount of products or services may include:

[0148] Scenario 1: Continue with the current situation, and the electricity will be provided by existing production or supply enterprises. For example, if no investment is made in renewable energy power plants, the required electricity will be supplied by existing power plants connected to the grid.

[0149] Scenario 2: Investing in new plants but using conventional technology / non-green technology. That is, if you do not invest in renewable energy power plants, the required electricity can be obtained by investing in conventional power generation technologies such as coal power and natural gas power generation technologies, but the premise is that these conventional technologies are in compliance with the current laws, regulations and environmental standards of the country where they are located.

[0150] The additionality argument is based on the additionality analysis previously described in this application.

[0151] The purpose of the monitoring plan is to ensure that the monitoring data of the project after filing can accurately reflect the emission reductions generated by the project. According to the selected methodology, all data that may need to be monitored are listed and specific requirements are made for monitoring equipment, monitoring frequency, etc. Artificial intelligence modifies the monitoring plan based on similar cases and the actual situation of the project.

[0152] Part C: Project operation period and crediting period; the crediting period is the time interval during which carbon emission reduction projects approved by the competent authorities can apply for carbon emission reduction indicators. The emission reduction crediting period of the project is selected on the day it is actually put into operation, and it cannot exceed the life of the project. The initial crediting period is set at 10 years.

[0153] Part D: Environmental Impact;

[0154] The content of the environmental impact analysis is automatically obtained from the project environmental impact assessment report through artificial intelligence technology.

[0155] Part E: Socio-economic impacts; Part F: Stakeholder analysis.

[0156] The opinions of residents around the project were collected through questionnaires, and the conclusion was drawn that local residents support the construction of this project.

[0157] Furthermore, in the carbon value creation link, for the development and creation of sustainable development value, artificial intelligence technology is used to automatically provide an optimization path for indicators that are lower than the set value (which can be initially set to 2 points) based on standard templates.

[0158] Furthermore, in the carbon value creation stage, the financial value of various green and low-carbon activities is analyzed, and different loan interest rates for different green indexes are given to provide solutions for the development and creation of financial value.

[0159]

[0160] For the carbon value creation results output in the third step, a five-dimensional carbon value evaluation is conducted, and a comprehensive carbon value evaluation result is output.

[0161] Specifically, economic value includes net income from the sale of environmental rights, net income from carbon labeling / carbon neutrality certification, net loss reduction from the company's fulfillment of its contractual obligations, net expenditure reduction from energy conservation, government subsidies, etc. Net income from the sale of environmental rights includes net income from the sale of various carbon credits developed from green and low-carbon activities and net income from the sale of green certificates generated from green and low-carbon activities.

[0162] Environmental value refers to the reduction in environmental damage caused by carbon dioxide due to carbon removal and carbon emission reduction, including the monetary value brought about by improvements in ecological environment quality such as the weakening of greenhouse effect, mitigation of climate change, and reduction of extreme weather.

[0163] Sustainable development value is the progress of society, economy and environment in related aspects of the Global Sustainable Development Goals (SDGs) set by the United Nations due to carbon removal and carbon emission reduction.

[0164] Brand value is the sum of the added value of benefits produced by brand-related products, including the added brand value brought about by carbon removal and carbon emission reduction.

[0165] Financial value refers to the reduced financing costs, spot investment income of carbon credits, investment income of carbon financial derivatives, and improved valuation level that can be obtained from green and low-carbon activities.

[0166] As described above, in the economic value, the net income from the sale of carbon credit indicators = the price of carbon credit indicators * the total amount of certified emission reductions of the project - the cost of project development. The price of carbon credit indicators adopts the price published on the website of the authoritative trading institution corresponding to the carbon credit indicators; the operating income brought by the expansion of new businesses is equal to the expected operating income in the next three years (the economic added value of the park and city in the next three years); referring to the "Interim Regulations on the Management of Carbon Emission Rights Trading", the net loss reduction brought by the completion of the performance task by the enterprise = emission reduction * the price of the national carbon emission quota on December 31 of the year * 5; the net expenditure reduction brought by energy saving = electricity fee reduction * local electricity price. The net income of carbon labeling is calculated according to the following formula: Y1 = (1 + premium ratio) * product sales income before labeling - carbon label certification unit price * product quantity. Among them, Y1 is the net income of carbon labeling, the premium ratio is 15% and is regularly updated through artificial intelligence technology. The unit price of carbon labeling certification is regularly taken from the quotations of major carbon labeling certification companies in the market through artificial intelligence technology. The net income from carbon neutrality certification is calculated as follows: Y2 = (1 + cost reduction ratio) * product sales revenue before labeling - carbon neutrality certification unit price * number of factories. Among them, Y2 is the net income from carbon neutrality certification, the cost reduction ratio is 5% and is regularly updated through artificial intelligence technology. The carbon neutrality certification unit price is regularly taken from the quotations of major carbon neutrality certification companies in the market through artificial intelligence technology.

[0167] As mentioned above, environmental value is equal to the product of carbon emission reduction and LIME (a life cycle impact assessment method based on endpoint model) coefficient. LIME value data comes from the environmental damage comprehensive coefficient calculation table released by Japan on October 4, 2013.

[0168] As described above, the brand value brought to the enterprise by green and low-carbon activities is evaluated by modifying the Interbrand brand value evaluation method. The formula is: V = P × S, where V is the green and low-carbon brand value; P is the brand revenue, and S is the green and low-carbon brand contribution rate.

[0169] The benefits brought by green and low-carbon brands are calculated by discounting the expected operating income in the next three years (the economic added value in the next three years for the park and the city), and the discount rate is the national debt interest rate of that year.

[0170] Among them, the economic added value in the next three years is predicted using the weighted moving average method, and its formula is: F = (3×A1+2×A2+1×A3) / 6

[0171] In the formula, A i is the predicted value for the future i-th year.

[0172] Brand contribution rate (S). The brand contribution rate is evaluated from two aspects: industry status and green and low-carbon brand support. For the calculation of the industry status score in the brand contribution rate, please refer to the brand contribution rate calculation score comparison table 1, and for the calculation of the green and low-carbon brand support score, please refer to the brand contribution rate calculation score comparison table 2. The calculation formula of the brand contribution rate is shown in formula (1):

[0173] Brand contribution rate (S) = industry status * 0.5 * 2% + green and low-carbon brand support * 0.5 * 2%. (1)

[0174] Brand contribution rate calculation score comparison table 1

[0175]

[0176] Brand contribution rate calculation score comparison table 2

[0177]

[0178]

[0179] As described above, the sustainable development score of green and low-carbon activities is evaluated using a five-point scoring system ranging from -2 (greater negative impact) to +2 (greater positive impact) (see the table below).

[0180] Questionnaire for the sustainable development value evaluation system of green and low-carbon activities

[0181]

[0182] According to the method described above, the reduction in financing costs that can be brought about by green and low-carbon activities = financing amount * percentage reduction in loan interest rate; carbon credit spot investment income = carbon credit spot sales income - carbon credit development cost; carbon financial derivative investment income = net income from the sale of carbon financial derivatives; valuation level improvement income is calculated through the increase in the company's owners' equity in the balance sheet of the year brought about by the increase in valuation level.

[0183] The entropy weight method is used to calculate the weight coefficients of economic value, environmental value, sustainable development value, brand value, and financial value, and then the comprehensive value of green and low-carbon activities is obtained by weighting, and the comprehensive value is sent as the evaluation result. Specifically, the comprehensive evaluation formula for the i-th green and low-carbon activity is as follows:

[0184]

[0185] In formula (2), y i is the comprehensive evaluation value of the i-th green and low-carbon activity, z ij is the dimensionless value of the evaluation index, w j Yes ij The weight coefficient

[0186] The present application adopts the entropy weight method to determine the weights in model (2). The entropy weight method is an objective weighting method widely used in various disciplines. Its starting point is to determine the weight coefficient according to the degree of difference between the numerical values ​​of each evaluation indicator. The entropy weight method avoids the interference of subjective factors in the process of determining the weight coefficient and can very objectively reflect the importance of each evaluation indicator in the comprehensive evaluation indicator system.

[0187] The specific steps of the entropy weight method are as follows: (1) Standardize the original data to make it dimensionless and eliminate the influence of dimension and order of magnitude. This application adopts the extreme difference standardization method, and its formula is as follows: (2) Calculate the information entropy of each indicator. Information entropy is a quantity that reflects the degree of order of the system. The smaller its value, the higher the degree of order of the system. The greater the difference between the numerical values ​​of each indicator, the greater the role of this indicator in the comprehensive evaluation. (3) Calculate the information entropy redundancy of each indicator. Information entropy redundancy is a quantity that reflects the importance of the indicator. The larger its value, the greater the role of this indicator in the comprehensive evaluation. The calculation formula of information entropy redundancy is as follows: (4) Calculate the weight coefficient of each indicator. The weight coefficient is a quantity that reflects the proportion of the indicator in the comprehensive evaluation. The larger its value, the greater the proportion of the indicator in the comprehensive evaluation.

[0188] The steps for determining the weight coefficients of the five carbon value indicators of green and low-carbon activities using the entropy weight method are as follows:

[0189] (1) Calculate the ratio of the index value of the i-th green and low-carbon activity to the j-th carbon value index

[0190]

[0191] (2) Calculate the entropy value of the jth carbon value indicator

[0192]

[0193] Where 0≤e j ≤1.

[0194] (3) Calculate carbon value index z ij From formula (4), we can see that for a given j, z ij The smaller the difference, the j The larger the z ij When all are equal, e j =e max =1, then the index z j There is no effect on the comparison between green and low-carbon activities. ij The greater the difference, the j The smaller the index z j The greater the comparison effect between green and low-carbon activities, the greater the difference coefficient g is defined on this basis. j =1-e j , g j The larger the value is, the more attention should be paid to the role of this indicator in the green and low-carbon value evaluation index system.

[0195] (4) Determination of weight coefficient.

[0196] Pick

[0197] This j That is the final weight coefficient of the five green and low-carbon value indicators.

[0198] Embodiment three, as Figure 1 The present invention also provides a carbon value analysis system based on artificial intelligence, such as Figure 1 As shown, it includes multiple user terminals 110 and a carbon value analysis center 120. Among them, the user terminal 110 is used to send query requests, receive and execute acquisition instructions, send green and low-carbon activity data; receive analysis results, send demand requests based on the results, and receive merchant terminal information. Among them, the carbon value analysis center 120;

[0199] Used to perform the following steps:

[0200] Receive query requests, send acquisition instructions according to the query requests, and obtain green and low-carbon activity data;

[0201] Conduct value analysis on green and low-carbon activity data, obtain analysis results, and send them, where the analysis results at least include: the value type and value of green and low-carbon activities, the value type that can be developed and created by green and low-carbon activities and its optimization plan, carbon value creation plan, and carbon value evaluation results;

[0202] Furthermore, the user terminal 110 at least includes: a transceiver unit 111 , a collection unit 112 and a management unit 113 .

[0203] Among them, the transceiver unit 111 is used to send a login request; send a query request after completing the login; receive an acquisition instruction and send the acquisition instruction to the collection unit 112; receive green and low-carbon activity data, and send the green and low-carbon activity data to the user terminal 110; receive evaluation results, and send the evaluation results to the management unit 113; receive client information, and send the client information to the management unit 113.

[0204] The collection unit 112 is used to execute the acquisition instruction, collect the green and low-carbon activity data, and send the green and low-carbon activity data to the transceiver unit 111. The management unit 113 is used to send a demand request according to the evaluation result and receive the merchant terminal information.

[0205] The carbon value analysis center 120 at least includes: a communication unit 121 , an analysis unit 122 , a push unit 123 and a storage unit 124 .

[0206] Among them, the communication unit 121 is used to receive a login request, complete the login according to the login request, receive a query request after completing the login, send an acquisition instruction according to the query request, receive green and low-carbon activity data, and send the green and low-carbon activity data to the analysis unit 122; receive the analysis results, and send the analysis results to the client; receive demand requests, and send the demand requests to the push unit 123; receive client information, and send the client information to the user end.

[0207] Analysis unit 122: used to analyze green and low-carbon activity data, obtain analysis results, and send the analysis results to the communication unit 121. Push unit 123: used to obtain merchant terminal information according to demand request, and send the merchant terminal information to the communication unit 121. Storage unit 124: used to store green and low-carbon activity data and analysis results as historical data in the historical database; a merchant terminal information database is pre-stored, and the merchant terminal information database includes multiple merchant terminal information.

[0208] Furthermore, the analysis unit 122 includes at least: a search sub-unit 1221, a scenario characterization sub-unit 1222, a value mining sub-unit 1223, a value creation sub-unit 1224, and a value realization sub-unit 1225.

[0209] Among them, the search subunit 1221: determines the historical green and low-carbon activity information and historical carbon value analysis information of green and low-carbon activities according to the information input by the customer. Specifically, after the user enters the query content, the search subunit 1221 searches the historical database for historical green and low-carbon activity information and historical carbon value analysis information that match the query content according to the query content, and sends it to the user end. The historical green and low-carbon activity information at least includes: historical carbon emission data, historical energy data, historical technical data, historical economic data, historical sustainable development data, etc. The historical carbon value analysis information at least includes: historical five-dimensional value analysis, historical comprehensive value analysis, etc.

[0210] Scenario characterization subunit 1222: It uses artificial intelligence technology to automatically identify, intercept, summarize and analyze the collected unstructured data and information input by customers, and specifically depicts green and low-carbon activity scenarios from multiple aspects such as carbon emission data, energy data, technical data, economic data and sustainable development data, and classifies them.

[0211] Value mining subunit 1223: After describing the green and low-carbon activity scenario, identify and mine the potential value of green and low-carbon activities, analyze the data of green and low-carbon activities, analyze the specific types of five-dimensional carbon values ​​that may exist in green and low-carbon activities, and determine the direction of value development and creation of green and low-carbon activities. The five-dimensional value refers to economic value, environmental value, sustainable development value, brand value, and financial value.

[0212] Value creation subunit 1224: For green and low-carbon activities that can be developed into voluntary greenhouse gas emission reduction projects, project design documents (PDD) are automatically generated based on standard templates and user preferences through artificial intelligence technology; optimization paths for sustainable development value indicators that are lower than set values ​​are automatically given based on standard templates through artificial intelligence technology; the financial value of various green and low-carbon activities is analyzed, and different loan interest rates for different green indexes are given to provide solutions for the development and creation of financial value.

[0213] Value realization subunit 1225: It is used to evaluate the value of green and low-carbon activities and obtain carbon values ​​in five aspects, including economic value, environmental value, sustainable development value, brand value and financial value brought about by carbon removal and carbon emission reduction. The entropy weight method is used to calculate the weight coefficient of each indicator, and then the comprehensive value of green and low-carbon activities is obtained by weighting, and the comprehensive value is sent as the analysis result.

[0214] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0215] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. A carbon value analysis method based on artificial intelligence, characterized in that: The following steps are involved: Input data and comprehensive value evaluation targets of green and low-carbon activities; The Carbon Value Analysis Center uses artificial intelligence technology to depict green and low-carbon scenarios based on input data and goals; The Carbon Value Analysis Center analyzes the data of green and low-carbon activities, analyzes the specific types of five-dimensional carbon values ​​that may exist in green and low-carbon activities, and provides directions for the development and creation of value of green and low-carbon activities. The Carbon Value Analysis Center automatically generates project design documents for various voluntary greenhouse gas emission reduction projects through artificial intelligence technology, reduces the development cost of carbon credits, improves economic value, and provides optimization directions for sustainable development value and financial value; The Carbon Value Analysis Center evaluates the five-dimensional value and comprehensive value of green and low-carbon activities, comprehensively and truly reflects the value of green and low-carbon activities, and maximizes the value of green and low-carbon activities. The five dimensions of value include: economic value, environmental value, sustainable development value, brand value, and financial value.

2. The carbon value analysis method based on artificial intelligence according to claim 1 is characterized in that: The artificial intelligence technologies include: one or more of semantic analysis, matching, natural language processing and intelligent interaction, generative artificial intelligence, image and speech recognition, machine learning, data mining, knowledge discovery, deep learning, optimization algorithms, generation models and evaluation models.

3. The carbon value analysis method based on artificial intelligence according to claim 1 is characterized in that: The steps of the carbon value analysis center to depict green and low-carbon scenarios through artificial intelligence technology include: Input data and comprehensive value evaluation targets of green and low-carbon activities; Through artificial intelligence technology, the collected unstructured data and information input by customers are automatically identified, intercepted, summarized and analyzed, and green and low-carbon activity scenarios are specifically depicted and classified from multiple aspects such as carbon emission data, energy data, technical data, economic data and sustainable development.

4. The carbon value analysis method based on artificial intelligence according to claim 1 is characterized in that: The steps of the carbon value analysis center to mine the value of green and low-carbon activities through artificial intelligence technology include: Explore the economic value of green and low-carbon activities, including environmental rights and interests, carbon labeling / carbon neutrality certification value, etc.; The environmental rights and interests value described above outputs the development and creation direction of the environmental rights and interests value according to whether the green and low-carbon activity projects meet the compliance and additionality requirements for the development of voluntary greenhouse gas emission reduction projects; If the green and low-carbon activity projects meet the compliance and additionality requirements, but are not within the scope of the national green certificate issuance, then develop carbon credit indicators, which at least include the international carbon credit indicators VCU under the certified carbon standard mechanism, the international carbon credit indicators VERs under the gold standard mechanism, and the carbon credit indicators CCER under my country's voluntary greenhouse gas emission reduction trading mechanism; if they are within the scope of the national green certificate issuance, then use artificial intelligence technology to automatically compare the benefits of developing carbon credit indicators and developing domestic green certificates, and choose to develop environmental rights products with higher economic benefits; If the compliance and additionality requirements are not met, determine whether the green and low-carbon activities fall within the scope of the national green certificate issuance. If so, develop a green certificate; Analysis of the carbon label / carbon neutrality certification value, where artificial intelligence calculates the carbon label / carbon neutrality certification value of end-consumer products and industrial products produced through green and low-carbon activities according to calculation formulas; Explore the sustainable development value of green and low-carbon activities. Artificial intelligence automatically gives specific sustainable development indicators with scores lower than the set values, and points out the direction of development and creation of sustainable development value; Explore the financial value of green and low-carbon activities, establish a green index for projects, evaluate the carbon risks of projects, give corresponding grades through artificial intelligence technology, and provide directions for the development and creation of financial value according to standard models.

5. The carbon value analysis method based on artificial intelligence according to claim 1 is characterized in that: The steps for the carbon value analysis center to create green and low-carbon activity value through artificial intelligence technology include: For green and low-carbon activities that can be developed into voluntary greenhouse gas emission reduction projects, project design documents are automatically generated based on standard templates and user preferences through artificial intelligence technology; For sustainable development value, artificial intelligence technology is used to automatically provide an optimization path for indicators that are lower than the set value based on the standard template; Analyze the financial value of various green and low-carbon activities, provide different loan interest rates for different green indexes, and provide solutions for the development and creation of financial value.

6. The carbon value analysis method based on artificial intelligence according to claim 1 is characterized in that: The comprehensive value is calculated by the following method: the entropy weight method is used to calculate the weight coefficients of economic value, environmental value, sustainable development value, brand value, and financial value, and then the weighted values ​​are used to obtain the comprehensive value of green and low-carbon activities.

7. The carbon value analysis method based on artificial intelligence according to claim 1 is characterized in that: The method includes conducting a value analysis on green and low-carbon activity projects, and the specific steps are as follows: Through artificial intelligence technology, the collected unstructured data and information input by customers are automatically identified, intercepted, summarized and analyzed, and green and low-carbon activity scenarios are specifically described from the aspects of carbon emission data, energy data, technical data, economic data and sustainable development, and they are classified; Analyze whether green and low-carbon activity projects meet the compliance and additionality requirements for the development of voluntary greenhouse gas emission reduction projects through artificial intelligence technology; Automatically compare the benefits of developing carbon credit indicators and developing domestic green certificates through artificial intelligence technology, and the carbon credit indicators include VCU, VERs, and CCER; For green and low-carbon activities that can be developed into voluntary greenhouse gas emission reduction projects, extract the project activity description from the project feasibility study report, including project type, project location, relevant technologies and main equipment used, and project business conditions; According to the field of project activities, select methodologies with similar names to the project, and compare the applicability of the proposed project with each selected methodology one by one, and select one or more methodologies as the methodology for carbon credit development; Based on the selected methodology, determine the project boundary, baseline boundary, greenhouse gas type, additionality demonstration, and monitoring plan content, and describe them in text and drawings; Select the project operation period and crediting period, and make your selection based on the project type and national regulations; Copy the contents of the environmental impact analysis from the environmental impact assessment report and adjust them according to the actual situation of the project; Data on socio-economic impacts and stakeholder analysis were collected through questionnaires, and analyzed and summarized based on the data results.

8. A carbon value analysis system based on artificial intelligence, characterized in that: Includes multiple user terminals and carbon value analysis centers; User side: used to send query requests, receive and execute acquisition instructions, send green and low-carbon activity data; receive analysis results, send demand requests based on the results, and receive merchant side information; Carbon Value Analysis Center: used to receive query requests, send acquisition instructions according to the query requests, and obtain green and low-carbon activity data; analyze the potential value of green and low-carbon activities, provide the value types and paths that can be developed and created, automatically generate project design documents for the development of voluntary greenhouse gas emission reduction projects, provide the development and creation direction of sustainable development value and financial value through artificial intelligence technology, and evaluate the comprehensive value of green and low-carbon activities, obtain analysis results, and send them; Obtain merchant information according to demand request and send it; The five dimensions of value include: economic value, environmental value, sustainable development value, brand value, and financial value.

9. The carbon value analysis system based on artificial intelligence according to claim 8 is characterized in that: The user terminal at least includes: a transceiver unit, a collection unit, and a management unit; Transceiver unit: used to send a login request; send a query request after completing the login; receive an acquisition instruction and send the acquisition instruction to the acquisition unit; receive green and low-carbon activity data and send the green and low-carbon activity data to the user end; receive evaluation results and send the evaluation results to the management unit; receive client information and send the client information to the management unit; Collection unit: used to execute acquisition instructions, collect green and low-carbon activity data, and send the green and low-carbon activity data to the transceiver unit; Management unit: used to send demand requests based on evaluation results and receive merchant-side information.

10. The carbon value analysis system based on artificial intelligence according to claim 8, characterized in that: The carbon value analysis center at least includes: a communication unit, an analysis unit, a push unit and a storage unit; Communication unit: used to receive a login request, complete the login according to the login request, receive a query request after completing the login, send an acquisition instruction according to the query request, receive green and low-carbon activity data, and send the green and low-carbon activity data to the analysis unit; receive the analysis results, and send the analysis results to the client; receive demand requests, and send the demand requests to the push unit; receive client information, and send the client information to the user end; Analysis unit: used to analyze green and low-carbon activity data, obtain analysis results, and send the analysis results to the communication unit; Push unit: used to obtain merchant-side information according to demand requests and send the merchant-side information to the communication unit; Storage unit: used to store green and low-carbon activity data and analysis results as historical data in a historical database; a merchant-side information database is pre-stored, and the merchant-side information database includes multiple merchant-side information.

11. A readable storage medium, characterized in that: The storage medium stores an artificial intelligence-based carbon value analysis method and a software program as described in one of claims 1 to 7, and the software program includes software code for executing the artificial intelligence-based carbon value analysis method as described in one of claims 1 to 7.

12. A computer processor, characterized in that: The processor is configured to run the computer program to execute the artificial intelligence-based carbon value analysis method as described in any one of claims 1 to 7.

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