A big data-based carbon trading market intelligent analysis method and system

Abstract

The application provides a kind of carbon trading market intelligent analysis method and system based on big data, including data collection module, data calculation module, carbon trading module and data analysis module. The emission right trading price is calculated by the data calculation module according to the average marginal abatement cost estimation of the whole industry, and then the carbon trading module controls the emission right trading price, and the data analysis module evaluates the abatement scheme made by enterprises, encourages enterprises to optimize energy structure and improve energy efficiency to achieve abatement. The application effectively improves the economic efficiency of carbon trading in the field.

Description

Technical Field

[0001] This invention relates to the field of data processing system technology, and in particular to an intelligent analysis method and system for carbon trading markets based on big data. Background Technology

[0002] Carbon trading is a general term for the trading of greenhouse gas emission rights, and it is a market-based mechanism for achieving carbon neutrality. The pathways to carbon neutrality include reducing carbon emissions, carbon removal, and negative emissions. Since carbon emissions are a comprehensive reflection of human economic and social activities, achieving carbon neutrality requires collaboration across multiple sectors, including population, economy, industry, energy, and technology. It necessitates accelerating the construction of a clean, low-carbon, safe, and efficient energy system to reduce total energy consumption and energy carbon intensity; and it requires accelerating the construction of a green, low-carbon, and circular economic system, increasing carbon capture while developing negative emission technologies.

[0003] This research team has long been reviewing and studying a large amount of relevant data on big data analysis and carbon trading market technologies. Simultaneously, relying on relevant resources and conducting numerous experiments, extensive searches revealed existing technologies such as US20100057582A1, JP2007080299A, and CN114493054A. For example, CN109272405B describes a carbon asset trading method and system, including: a quota management system, an emission reduction project management system, and a carbon emission management system; this system obtains carbon emission quotas from each power plant within a group power company. The system calculates the carbon emission reduction issuance and actual carbon emissions for each power plant. Based on each power plant's carbon emission allowance, issuance, and actual emissions, the allowance profit / loss value is calculated. The sum of the allowance profit / loss values ​​for all power plants is then calculated to obtain the total allowance profit / loss value for the group's power companies. Based on the total allowance profit / loss value for the group's power companies and the allowance profit / loss value for each power plant, the trading volume between the group's power companies and external companies, as well as among internal power plants, is determined according to the unit attributes of each power plant. This application has enabled the group company to achieve its subsidiaries' allowance compliance at a low cost by combining internal and external carbon trading.

[0004] This invention was made to effectively address the problem of the inability to rationally allocate and adjust carbon resources in the market.

[0005] The foregoing description of the background art is intended only to facilitate understanding of the invention. This description does not endorse or acknowledge any common general knowledge in the materials mentioned. Summary of the Invention

[0006] The purpose of this invention is to address the shortcomings of existing technologies by proposing a big data-based intelligent analysis method and system for the carbon trading market.

[0007] To overcome the shortcomings of the prior art, the present invention adopts the following technical solution:

[0008] A big data-based intelligent analysis system for the carbon trading market includes: a data collection module, a data calculation module communicatively connected to the data collection module, a data analysis module communicatively connected to the data collection module and the data calculation module, and a carbon trading module communicatively connected to the data calculation module and the data analysis module.

[0009] The data collection module is used to collect monthly carbon emission intensity data, monthly carbon emission data, and monthly emission reduction quota data of enterprises in the entire industry, and send the data to the data calculation module.

[0010] The data calculation module is used to calculate the average marginal emission reduction cost of the entire industry; based on the monthly carbon emission intensity data, monthly carbon emission data, and monthly allocated emission reduction quota data of each enterprise in the industry, the data calculation module calculates the monthly average carbon emission intensity of the entire industry. Monthly average allocation of emission reduction quotas Average marginal emission reduction cost across the entire industry ,in This is the average emission reduction cost coefficient, which can be obtained through empirical data; assuming the market is in equilibrium, the emission rights trading price is the average marginal emission reduction cost across the entire industry. ;

[0011] The data analysis module is used to evaluate the emission reduction plans formulated by enterprises, select the optimal emission reduction plan, and output the carbon emission reduction amount to be purchased to the carbon trading module. The data analysis module includes an input unit, a processing unit, an output unit, and a display unit. The input unit is used to input the emission reduction cost coefficient of enterprise i under k emission reduction plans. Monthly carbon emission reduction The processing unit is connected to the data calculation module and the input unit, and is used to generate the marginal emission reduction cost under k emission reduction schemes. Select the minimum marginal emission reduction cost by sorting them by size. The emission reduction plan is proposed, and the carbon emission reduction amount to be purchased is calculated. The output unit is used to process the carbon emission reduction amount to be purchased. The data is sent to the carbon trading module; the display unit is used to display the calculation process within the processing unit.

[0012] The carbon trading module includes a discrimination unit, a buying unit, a selling unit, and a carbon trading platform; the discrimination unit determines the carbon emission reductions to be purchased by enterprise i based on the data analysis module. The system determines whether company i should purchase or sell carbon emission reductions. If it determines that company i should purchase carbon emission reductions, company i will use the purchasing unit on the carbon trading platform at the emission rights trading price. Purchase of carbon emission reductions If it is determined that company i should sell carbon emission reductions, company i will do so at the emission trading price. The carbon emission reductions to be purchased are sold through the selling unit on the carbon trading platform. .

[0013] A big data-based intelligent analysis method for the carbon trading market, applied to the aforementioned big data-based intelligent analysis system for the carbon trading market, includes the following steps in evaluating enterprise i's emission reduction plan:

[0014] Step S1: The processing unit establishes a marginal emission reduction cost function:

[0015] (1)

[0016] (2)

[0017] (3)

[0018] in It is the marginal emission reduction cost of enterprise i. This refers to the company's monthly carbon emission reduction. It is the allocated emission reduction quota. It is an enterprise i-emission reduction The cost of reducing carbon dioxide emissions per unit. It is the carbon emission intensity of enterprise i. It is the proportion of carbon emissions of enterprise i in the entire industry. It is the emission reduction cost coefficient of enterprise i. It is the monthly average carbon emission intensity of the entire industry;

[0019] For formula (2) Taking the first derivative, we obtain the carbon emission reduction function that company i has to purchase in the carbon trading market:

[0020] (4)

[0021] Step S2: The input unit inputs the emission reduction cost coefficient of enterprise i under k emission reduction schemes. Monthly carbon emission reduction And send it to the processing unit;

[0022] Step S3: The processing unit calculates the emission reduction cost coefficients under the k emission reduction schemes. Monthly carbon emission reduction and the average marginal emission reduction cost of the entire industry Substituting into formulas (1), (2), and (3), the marginal emission reduction costs under the k emission reduction schemes are generated. And sort them by size to select the minimum marginal emission reduction cost. The emission reduction plan;

[0023] Step S4: The processing unit will calculate the emission reduction cost coefficient in the emission reduction scheme with the minimum marginal emission reduction cost. The carbon emission reduction amount to be purchased is obtained by inputting it into formula (4). ;

[0024] Step S5: The processing unit will process the carbon emission reductions to be purchased. Send to the output unit;

[0025] Step S6: The output unit will output the carbon emission reduction amount to be purchased. Send to the discrimination unit;

[0026] Step S7: The discrimination unit determines the carbon emission reduction. The sign of the value: if positive, it is sent to the buy unit; if negative, it is sent to the sell unit.

[0027] The beneficial effects achieved by this invention are:

[0028] 1. The emission trading price is calculated based on the average marginal emission reduction cost of the entire industry through the data calculation module. Then, the emission trading price is controlled by the carbon trading module, so that high-carbon emission industries can purchase carbon emission reductions from low-carbon emission industries at fair prices, thereby achieving the effect of mutual adjustment and upgrading among industries.

[0029] 2. By evaluating the emission reduction plans formulated by enterprises through the data analysis module, enterprises are encouraged to optimize their energy structure and improve energy efficiency to achieve emission reduction, thereby optimizing their own marginal emission reduction costs and gaining a competitive advantage in carbon trading.

[0030] 3. By establishing a marginal emission reduction cost function through the processing unit, the marginal emission reduction cost of the emission reduction plan formulated by the enterprise is visually calculated to select the emission reduction plan with the minimum marginal emission reduction cost, and the carbon emission reduction amount to be purchased is output to the carbon trading platform for trading.

[0031] 4. Adjusting emission rights trading prices through carbon trading platforms and the market promotes the allocation of market resources and improves economic efficiency. Attached Figure Description

[0032] The invention will be further understood from the following description taken in conjunction with the accompanying drawings. The components in the drawings are not necessarily drawn to scale, but rather the emphasis is on illustrating the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0033] Figure 1 This is a modular schematic diagram of the intelligent carbon trading market system based on big data according to the present invention.

[0034] Figure 2 This is a modular schematic diagram of the data analysis module of the present invention.

[0035] Figure 3 This is a modular schematic diagram of carbon trading according to the present invention.

[0036] Figure 4 This is a schematic diagram illustrating the process of evaluating the emission reduction scheme of enterprise i according to the present invention.

[0037] Figure 5 This is a schematic diagram illustrating the process of adjusting emission rights trading prices in the carbon trading platform according to Embodiment 3 of the present invention. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to its embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention. Other systems, methods, and / or features of this embodiment will become apparent to those skilled in the art after reviewing the following detailed description. All such additional systems, methods, features, and advantages are intended to be included within this specification, within the scope of the invention, and protected by the appended claims. Further features of the disclosed embodiments are described in the following detailed description, and these features will become apparent from the following detailed description.

[0039] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or component referred to must have a specific orientation or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present patent. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0040] Example 1:

[0041] This embodiment constructs an intelligent carbon trading market intelligent analysis system based on big data;

[0042] A big data-based intelligent analysis system for the carbon trading market includes: a data collection module, a data calculation module communicatively connected to the data collection module, a data analysis module communicatively connected to the data collection module and the data calculation module, and a carbon trading module communicatively connected to the data calculation module and the data analysis module.

[0043] The data collection module is used to collect monthly carbon emission intensity data, monthly carbon emission data, and monthly emission reduction quota data of enterprises in the entire industry, and send the data to the data calculation module.

[0044] The data calculation module is used to calculate the average marginal emission reduction cost of the entire industry; based on the monthly carbon emission intensity data, monthly carbon emission data, and monthly allocated emission reduction quota data of each enterprise in the industry, the data calculation module calculates the monthly average carbon emission intensity of the entire industry. Monthly average allocation of emission reduction quotas Average marginal emission reduction cost across the entire industry ,in This is the average emission reduction cost coefficient, which can be obtained through empirical data; assuming the market is in equilibrium, the emission rights trading price is the average marginal emission reduction cost across the entire industry. ;

[0045] The data analysis module is used to evaluate the emission reduction plans formulated by enterprises, select the optimal emission reduction plan, and output the carbon emission reduction amount to be purchased to the carbon trading module. The data analysis module includes an input unit, a processing unit, an output unit, and a display unit. The input unit is used to input the emission reduction cost coefficient of enterprise i under k emission reduction plans. Monthly carbon emission reduction The processing unit is connected to the data calculation module and the input unit, and is used to generate the marginal emission reduction cost under k emission reduction schemes. Select the minimum marginal emission reduction cost by sorting them by size. The emission reduction plan is proposed, and the carbon emission reduction amount to be purchased is calculated. The output unit is used to process the carbon emission reduction amount to be purchased. The data is sent to the carbon trading module; the display unit is used to display the calculation process within the processing unit.

[0046] The carbon trading module includes a discrimination unit, a buying unit, a selling unit, and a carbon trading platform; the discrimination unit determines the carbon emission reductions to be purchased by enterprise i based on the data analysis module. The system determines whether company i should purchase or sell carbon emission reductions. If it determines that company i should purchase carbon emission reductions, company i will use the purchasing unit on the carbon trading platform at the emission rights trading price. Purchase of carbon emission reductions If it is determined that company i should sell carbon emission reductions, company i will do so at the emission trading price. The carbon emission reductions to be purchased are sold through the selling unit on the carbon trading platform. .

[0047] A big data-based intelligent analysis method for the carbon trading market, applied to the big data-based intelligent analysis system for the carbon trading market as described above, wherein the evaluation of enterprise i's emission reduction plan includes the following steps:

[0048] Step S1: The processing unit establishes a marginal emission reduction cost function:

[0049] (1)

[0050] (2)

[0051] (3)

[0052] in It is the marginal emission reduction cost of enterprise i. This refers to the company's monthly carbon emission reduction. It is the allocated emission reduction quota. It is an enterprise i-emission reduction The cost of reducing carbon dioxide emissions per unit. It is the carbon emission intensity of enterprise i. It is the proportion of carbon emissions of enterprise i in the entire industry. It is the emission reduction cost coefficient of enterprise i. It is the monthly average carbon emission intensity of the entire industry;

[0053] For formula (2) Taking the first derivative, we obtain the carbon emission reduction function that company i has to purchase in the carbon trading market:

[0054] (4)

[0055] Step S2: The input unit inputs the emission reduction cost coefficient of enterprise i under k emission reduction schemes. Monthly carbon emission reduction And send it to the processing unit;

[0056] Step S3: The processing unit calculates the emission reduction cost coefficients under the k emission reduction schemes. Monthly carbon emission reduction and the average marginal emission reduction cost of the entire industry Substituting into formulas (1), (2), and (3), the marginal emission reduction costs under the k emission reduction schemes are generated. And sort them by size to select the minimum marginal emission reduction cost. The emission reduction plan;

[0057] Step S4: The processing unit will calculate the emission reduction cost coefficient in the emission reduction scheme with the minimum marginal emission reduction cost. The carbon emission reduction amount to be purchased is obtained by inputting it into formula (4). ;

[0058] Step S5: The processing unit will process the carbon emission reductions to be purchased. Send to the output unit;

[0059] Step S6: The output unit will output the carbon emission reduction amount to be purchased. Send to the discrimination unit;

[0060] Step S7: The discrimination unit determines the carbon emission reduction. The sign of the value: if positive, it is sent to the buy unit; if negative, it is sent to the sell unit.

[0061] Example 2:

[0062] The data analysis module is used to select the optimal emission reduction plan based on the emission reduction plan formulated by the trading evaluation enterprise and output the carbon emission reduction amount to be purchased to the carbon trading module. The data analysis module includes an input unit, a processing unit, an output unit, and a display unit. The input unit is used to input the emission reduction cost coefficient of enterprise i under k emission reduction plans. Monthly carbon emission reduction The processing unit is connected to the data calculation module and the input unit, and is used to generate the marginal emission reduction cost under k emission reduction schemes. Select the minimum marginal emission reduction cost by sorting them by size. The emission reduction plan is proposed, and the carbon emission reduction amount to be purchased is calculated. The output unit is used to process the carbon emission reduction amount to be purchased. The data is sent to the carbon trading module; the display unit is used to display the calculation process within the processing unit.

[0063] The processing unit establishes a marginal emission reduction cost function:

[0064] (1)

[0065] (2)

[0066] (3)

[0067] in It is the marginal emission reduction cost of enterprise i. This refers to the company's monthly carbon emission reduction. It is the allocated emission reduction quota. It is an enterprise i-emission reduction The cost of reducing carbon dioxide emissions per unit. It is the carbon emission intensity of enterprise i. It is the proportion of carbon emissions of enterprise i in the entire industry. It is the emission reduction cost coefficient of enterprise i;

[0068] For formula (2) Taking the first derivative, we obtain the carbon emission reduction function that company i has to purchase in the carbon trading market:

[0069] (4)

[0070] Substituting formulas (2), (3), and (4) into (1) yields:

[0071] (5)

[0072] in, (6)

[0073] (7)

[0074] (8)

[0075] Where I is the investment amount, O is the operation and maintenance cost, B is the energy-saving benefit from emission reduction, and C1 is the unit cost of the allocated emission reduction quota. C2 represents the proportion of carbon emission reduction allowances to be purchased, and C2 represents the technology investment cost; O, B, C1, Both C2 and C2 can be obtained through a limited number of experiments by those skilled in the art; d is the discount rate, and n is the payback period of the investment; here, the discount rate is set to d=20%, and the payback period of the investment is n=5; based on empirical data, this invention has found that the marginal cost of carbon emission reduction is related to the allocated emission reduction quota. Emission reduction ratio There is a positive correlation.

[0076] Example 3:

[0077] Combined with appendix Figure 1-5 In addition to the content included in the above embodiments, it also includes:

[0078] The carbon trading platform includes a data acquisition unit, a data processing unit, and a transaction processing unit;

[0079] The trading process of the carbon trading platform also includes the trading price of emission rights. The adjustment process:

[0080] Step S21: The data processing unit sets the unit transaction quantity of the carbon emission reduction to be purchased, with the unit transaction quantity in units of one ton of carbon dioxide equivalent.

[0081] Step S22: The data acquisition unit acquires the transaction data of every enterprise in the entire industry, including the number of units traded in each transaction, the emission rights trading price of each transaction, and the transaction time of each transaction;

[0082] Step S23: The data processing unit acquires the transaction data within the corresponding transaction volume in chronological order according to the number of units traded in each transaction, forming a data combination of N units of transaction volume;

[0083] Step S24: After the data processing unit completes the data combination, it performs statistical calculations on the transaction data within each unit of transaction volume to obtain the historical emission rights transaction price and the real-time emission rights transaction price under that unit of transaction volume; the historical emission rights transaction price is the final price of the previous unit of transaction volume, that is, the last transaction price of the previous unit of transaction volume; the real-time emission rights transaction price is the current transaction price within that unit of transaction volume.

[0084] The discrimination unit determines the carbon emission reduction amount to be purchased by enterprise i based on the data analysis module. The system determines whether company i should purchase or sell carbon emission reductions. If it determines that company i should purchase carbon emission reductions, company i purchases the carbon emission reductions to be purchased on the carbon trading platform at the real-time emission rights trading price through the purchasing unit. If it is determined that company i should sell carbon emission reductions, company i will sell the carbon emission reductions to be purchased on the carbon trading platform through the selling unit at the real-time emission trading price. .

[0085] This invention uses a data calculation module to estimate the emission rights trading price based on the average marginal emission reduction cost across all industries. Then, through a carbon trading module, it controls the emission rights trading price, allowing high-carbon-emission industries to purchase carbon emission reductions from low-carbon-emission industries at fair prices, thereby achieving mutual adjustment and upgrading among industries. A data analysis module evaluates the emission reduction plans formulated by enterprises, encouraging them to optimize their energy structure and improve energy efficiency to achieve emission reductions, thus optimizing their own marginal emission reduction costs and gaining a competitive advantage in carbon trading. Furthermore, a processing unit establishes a marginal emission reduction cost function, visually calculating the marginal emission reduction costs of the emission reduction plans formulated by enterprises to select the emission reduction plan with the lowest marginal emission reduction cost, and outputting the carbon emission reductions to be purchased to the carbon trading platform for trading. This invention effectively improves the economic efficiency of carbon trading in this field.

[0086] While the invention has been described above with reference to various embodiments, it should be understood that many changes and modifications can be made without departing from the scope of the invention. That is, the methods, systems, and devices discussed above are examples. Various configurations can be appropriately omitted, substituted, or added to various processes or components. For example, in alternative configurations, methods can be performed in a different order than those described, and / or various components can be added, omitted, and / or combined. Moreover, features described with respect to certain configurations can be combined in various other configurations, such as different aspects and elements of the configuration can be combined in a similar manner. Furthermore, the elements therein can be updated as the technology develops; that is, many elements are examples and do not limit the scope of this disclosure or the claims.

[0087] Specific details are provided in the specification to offer a thorough understanding of exemplary configurations, including implementations. However, configurations can be practiced without these specific details; for example, well-known circuits, processes, algorithms, structures, and techniques have been shown without unnecessary detail to avoid obscuring the configuration. This description provides only exemplary configurations and does not limit the scope, applicability, or configuration of the claims. Rather, the foregoing description of the configurations will provide those skilled in the art with an enabling description for implementing the described techniques. Various changes can be made to the function and arrangement of the elements without departing from the spirit or scope of this disclosure.

[0088] In summary, the above detailed description is intended to be illustrative rather than restrictive, and it should be understood that these embodiments are for illustrative purposes only and not for limiting the scope of protection of the invention. After reading the description of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent changes and modifications also fall within the scope defined by the claims of this invention.

Claims

1. A big data-based carbon trading market intelligent analysis system, characterized in that, It includes: a data collection module, a data calculation module communicatively connected to the data collection module, a data analysis module communicatively connected to the data collection module and the data calculation module, and a carbon trading module communicatively connected to the data calculation module and the data analysis module; The data collection module is used to collect monthly carbon emission intensity data, monthly carbon emission data, and monthly emission reduction quota data of enterprises in the entire industry, and send the data to the data calculation module. The data calculation module is used to calculate the average marginal emission reduction cost of the entire industry; based on the monthly carbon emission intensity data, monthly carbon emission data, and monthly allocated emission reduction quota data of each enterprise in the industry, the data calculation module calculates the monthly average carbon emission intensity of the entire industry. Monthly average allocation of emission reduction quotas Average marginal emission reduction cost across the entire industry ,in This is the average emission reduction cost coefficient, which can be obtained through empirical data; assuming the market is in equilibrium, the emission rights trading price is the average marginal emission reduction cost across the entire industry. ; The data analysis module is used to evaluate the emission reduction plans formulated by enterprises, select the optimal emission reduction plan, and output the carbon emission reduction amount to be purchased to the carbon trading module. The data analysis module includes an input unit, a processing unit, an output unit, and a display unit. The input unit is used to input the emission reduction cost coefficient of enterprise i under k emission reduction plans. Monthly carbon emission reduction The processing unit is connected to the data calculation module and the input unit, and is used to generate the marginal emission reduction cost under k emission reduction schemes. Select the minimum marginal emission reduction cost by sorting them by size. The emission reduction plan is proposed, and the carbon emission reduction amount to be purchased is calculated. ; The output unit is used to process the carbon emission reduction amount to be purchased. The data is sent to the carbon trading module; the display unit is used to display the calculation process within the processing unit. The carbon trading module includes a discrimination unit, a buying unit, a selling unit, and a carbon trading platform; the discrimination unit determines the carbon emission reductions to be purchased by enterprise i based on the data analysis module. The system determines whether company i should purchase or sell carbon emission reductions. If it determines that company i should purchase carbon emission reductions, company i will use the purchasing unit on the carbon trading platform at the emission rights trading price. Purchase of carbon emission reductions ; If it is determined that company i should sell carbon emission reductions, company i will do so at the emission trading price. The carbon emission reductions to be purchased are sold through the selling unit on the carbon trading platform. .

2. A big data-based intelligent analysis method for the carbon trading market, applied to the big data-based intelligent analysis system for the carbon trading market as described in claim 1, characterized in that, The evaluation of Company i's emission reduction plan includes the following steps: Step S1: The processing unit establishes a marginal emission reduction cost function: （1） （2） （3） in It is the marginal emission reduction cost of enterprise i. This refers to the company's monthly carbon emission reduction. It is the allocated emission reduction quota. It is an enterprise i-emission reduction The cost of reducing carbon dioxide emissions per unit. It is the carbon emission intensity of enterprise i. It is the proportion of carbon emissions of enterprise i in the entire industry. It is the emission reduction cost coefficient of enterprise i. It is the monthly average carbon emission intensity of the entire industry; For formula (2) Taking the first derivative, we obtain the carbon emission reduction function that company i has to purchase in the carbon trading market: （4） Step S2: The input unit inputs the emission reduction cost coefficient of enterprise i under k emission reduction schemes. Monthly carbon emission reduction And send it to the processing unit; Step S3: The processing unit will calculate the emission reduction cost coefficients under the k emission reduction schemes. Monthly carbon emission reduction and the average marginal emission reduction cost of the entire industry Substituting into formulas (1), (2), and (3), the marginal emission reduction costs under the k emission reduction schemes are generated. And sort them by size to select the minimum marginal emission reduction cost. Emission reduction plan; Step S4: The processing unit will calculate the emission reduction cost coefficient in the emission reduction scheme with the minimum marginal emission reduction cost. The carbon emission reduction amount to be purchased is obtained by inputting it into formula (4). ; Step S5: The processing unit will process the carbon emission reductions to be purchased. Send to the output unit; Step S6: The output unit will output the carbon emission reduction amount to be purchased. Send to the discrimination unit; Step S7: The discrimination unit determines the carbon emission reduction. The sign of the value: if positive, it is sent to the buy unit; if negative, it is sent to the sell unit.

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