Dynamic adjustment method and response system of carbon quota based on game between government and industry

Abstract

The present disclosure relates to a carbon quota dynamic adjustment method and response system based on the game between the government and the industry, the method comprising: obtaining the dynamic allocation parameters of the current cycle, the dynamic allocation parameters comprising: the total carbon emissions of the previous cycle; analyzing the dynamic allocation parameters to determine the carbon quota factor of the current cycle; based on the total carbon emissions of the previous cycle and the carbon quota factor of the current cycle, determining the carbon emission quota of the current cycle. When determining the carbon emission quota, the method of the present disclosure will no longer be biased towards enterprises with rich historical carbon emission data, and will be fairer to all enterprises. Moreover, the present disclosure only requires the dynamic parameters of the current cycle, which greatly reduces the amount of data required compared to the baseline method, reduces the computational complexity, and is easy to operate, making it very suitable for the scenario of the initial carbon trading market.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to a carbon quota dynamic adjustment method and response system based on the game between the government and the industry. Background Art

[0002] With the rapid development of social economy, carbon emissions have increased year by year. The environmental pollution caused by excessive carbon dioxide emissions has gradually aggravated global climate change. The massive increase of greenhouse gases, mainly carbon dioxide, has led to global warming, which has brought severe challenges to human survival and development. Many countries and regions have issued corresponding strategic goals to limit and reduce carbon dioxide emissions.

[0003] Allocating carbon quotas to various industries can both meet human production needs and limit carbon emissions.

[0004] At present, the common carbon quota allocation methods mainly include the "grandfather method" and the "benchmark method". The grandfather method, also known as the historical method, uses the historical emissions of enterprises as the basis for allocating quotas to ensure that the quotas basically meet the normal production needs of each enterprise. However, since the historical method allocates more quotas to enterprises with high historical emissions. On the contrary, high-tech enterprises may obtain fewer carbon quotas due to the lack of historical emission data, the grandfather method has the disadvantage of unfairness. The benchmark method, also known as the benchmark method, allocates quotas based on the emissions per unit of production activities multiplied by the benchmark value set by the industry. The benchmark value can be the average level of the industry or product. The benchmark method makes up for the unfair allocation defect of the grandfather method and ensures that enterprises in the same industry obtain corresponding carbon quotas according to the same standards. The benchmark method can motivate enterprises to take the initiative to reduce emissions and is conducive to the research and development of low-carbon technologies. However, the benchmark method also has some disadvantages. Setting a carbon emission baseline requires a large amount of data, complex calculations, and high operational difficulty. In the early days of the carbon trading market, the infrastructure and legal policies were imperfect, and it was difficult for the government to determine a reasonable carbon emission baseline. Summary of the invention

[0005] In view of this, the present disclosure proposes a carbon quota dynamic adjustment solution.

[0006] According to one aspect of the present disclosure, a carbon quota adjustment method is provided, comprising: obtaining dynamic allocation parameters of a current period, the dynamic allocation parameters comprising: the total carbon emissions of the previous period; analyzing the dynamic allocation parameters to determine a carbon quota factor of the current period; and determining a carbon emission quota of the current period based on the total carbon emissions of the previous period and the carbon quota factor of the current period.

[0007] In one possible implementation, the analyzing the dynamic allocation parameters to determine the carbon quota factor for the current cycle includes: inputting the dynamic allocation parameters into a first model to obtain the carbon quota factor for the current cycle, wherein the first model is used to characterize the balance relationship between product output and the carbon quota factor; the determining the carbon emission quota for the current cycle based on the total carbon emissions of the previous cycle and the carbon quota factor for the current cycle includes: taking the product of the total carbon emissions of the previous cycle and the carbon quota factor for the current cycle as the carbon emission quota for the current cycle.

[0008] In a possible implementation, the dynamic allocation parameters are input into the first model to obtain the carbon quota factor for the current cycle, including: obtaining a first mapping relationship between industry profits, product output, and carbon quota factors under the constraint of an industry carbon emission cap; obtaining a second mapping relationship between social welfare, product output, and carbon quota factors, wherein the social welfare includes the industry profits; and determining, under the limitation of the dynamic allocation parameters, a target carbon quota factor under the condition of maximum social welfare based on the first mapping relationship and the second mapping relationship, and using the target carbon quota factor as the carbon quota factor for the current cycle.

[0009] In a possible implementation, under the limitation of the dynamic allocation parameters, based on the first mapping relationship and the second mapping relationship, the target carbon quota factor under the condition of maximum social welfare is determined, including: based on the first mapping relationship, according to the dynamic allocation parameters, determining a third mapping relationship between product output and carbon quota factor in the same period while satisfying the industry carbon emission upper limit constraint and maximizing industry profits; based on the second mapping relationship and the third mapping relationship, according to the dynamic allocation parameters, determining the target carbon quota factor.

[0010] In a possible implementation, the dynamic allocation parameters also include: product market capacity of the current cycle, inverse sensitivity factor of product demand to price of the current cycle, production cost of unit product of the current cycle, purchase price of unit carbon emission of the current cycle, carbon emission that can be purchased in the current cycle, and carbon emission of unit product produced in the current cycle; the industry carbon emission upper limit constraint condition is expressed as: carbon emission in one cycle is not greater than the set industry carbon emission upper limit;

[0011] The industry carbon emission cap constraints include: f Q≤T+εE;

[0012] Among them, e f Q represents the carbon emissions in a cycle, Q represents the product output in a cycle, and e fRepresents the carbon emissions per unit of product produced; T+εE represents the industry's carbon emissions cap, T represents the carbon emissions that can be purchased in the current cycle, εE represents the carbon emission quota of the current cycle, ε represents the carbon quota factor of the current cycle, and E represents the total carbon emissions of the previous cycle;

[0013] The first mapping relationship is expressed as: industry profit = gross profit - carbon emission cost, wherein the price of a unit product is expressed by the product market capacity, the inverse sensitivity factor of product demand to price, and the product output, the gross profit is expressed by the price of the unit product, the production cost of the unit product, and the product output, and the carbon emission cost is expressed by the purchase price of unit carbon emission, the carbon emission of producing a unit product, the total carbon emission in the previous cycle, the carbon quota factor, and the product output;

[0014] The first mapping relationship includes: π = (P-c0) QP e (e f Q-εE);

[0015] Among them, π represents industry profit, (P-c0)Q represents gross profit, P represents the price of unit product, and P = a-bQ, a represents product market capacity, b represents the inverse sensitivity factor of product demand to price, c0 represents the production cost of unit product, P e (e f Q-εE) represents the carbon emission cost, P e Represents the purchase price per unit of carbon emissions;

[0016] The second mapping relationship is expressed as: social welfare = industry profit + consumer surplus - degree of damage to the environment caused by carbon emissions, wherein the consumer surplus is represented by the inverse sensitivity factor of product demand to price and product output, and the carbon emissions per unit product produced and the product output are used to represent the degree of damage to the environment caused by carbon emissions;

[0017] The second mapping relationship includes:

[0018] Among them, W represents social welfare, Characterizes consumer surplus, Characterizes the degree of damage that carbon emissions cause to the environment.

[0019] In a possible implementation, the method further includes: obtaining an optimal output in a current cycle based on the third mapping relationship and the target carbon quota factor.

[0020] In one possible implementation, the dynamic allocation parameters of the current cycle are obtained, including: obtaining electricity consumption data of the previous cycle, carbon emissions per unit product of the previous cycle, and the carbon quota factor of the previous cycle; determining the output of the previous cycle based on the electricity consumption data of the previous cycle; and taking the product of the output of the previous cycle and the carbon emissions per unit product of the previous cycle as the total carbon emissions of the previous cycle.

[0021] According to another aspect of the present disclosure, a carbon quota dynamic adjustment response system is provided, the response system comprising:

[0022] A dynamic allocation parameter acquisition unit, used to acquire the dynamic allocation parameters of the current cycle, wherein the dynamic allocation parameters include: the total carbon emissions of the previous cycle;

[0023] A carbon quota factor determination unit, configured to analyze the dynamic allocation parameter and determine the carbon quota factor for the current period;

[0024] The carbon emission quota determination unit is used to determine the carbon emission quota of the current period based on the total carbon emissions of the previous period and the carbon quota factor of the current period.

[0025] In a possible implementation, the carbon quota factor determination unit includes:

[0026] A carbon quota factor determination subunit, used for inputting the dynamic allocation parameter into a first model to obtain the carbon quota factor of the current cycle, wherein the first model is used for characterizing the balance relationship between product output and the carbon quota factor;

[0027] The carbon emission amount determination unit is used to:

[0028] The product of the total carbon emissions of the previous period and the carbon quota factor of the current period is used as the carbon emission quota of the current period.

[0029] In a possible implementation, the carbon quota factor determination subunit includes:

[0030] A first mapping relationship acquisition unit, used to acquire a first mapping relationship between industry profit, product output, and carbon quota factor under the industry carbon emission upper limit constraint condition;

[0031] A second mapping relationship acquisition unit, used to acquire a second mapping relationship between social welfare, product output, and carbon quota factor, wherein the social welfare includes the industry profit;

[0032] A target carbon quota factor determination unit is used to determine the target carbon quota factor under the condition of maximum social welfare based on the first mapping relationship and the second mapping relationship under the limitation of the dynamic allocation parameter, and use the target carbon quota factor as the carbon quota factor of the current period.

[0033] In a possible implementation, the target carbon quota factor determination unit is used to:

[0034] Based on the first mapping relationship and according to the dynamic allocation parameter, determine a third mapping relationship between product output and carbon quota factor in the same period while satisfying the industry carbon emission upper limit constraint and maximizing industry profits;

[0035] Based on the second mapping relationship and the third mapping relationship, the target carbon quota factor is determined according to the dynamic allocation parameter.

[0036] In a possible implementation, the dynamic allocation parameters also include: product market capacity of the current cycle, inverse sensitivity factor of product demand to price of the current cycle, production cost of unit product of the current cycle, purchase price of unit carbon emission of the current cycle, carbon emission that can be purchased in the current cycle, and carbon emission of unit product produced in the current cycle; the industry carbon emission upper limit constraint condition is expressed as: carbon emission in one cycle is not greater than the set industry carbon emission upper limit;

[0037] The industry carbon emission cap constraints include: f Q≤T+εE;

[0038] Among them, e f Q represents the carbon emissions in a cycle, Q represents the product output in a cycle, and e f Represents the carbon emissions per unit of product produced; T+εE represents the industry's carbon emissions cap, T represents the carbon emissions that can be purchased in the current cycle, εE represents the carbon emission quota of the current cycle, ε represents the carbon quota factor of the current cycle, and E represents the total carbon emissions of the previous cycle;

[0039] The first mapping relationship is expressed as: industry profit = gross profit - carbon emission cost, wherein the price of a unit product is expressed by the product market capacity, the inverse sensitivity factor of product demand to price, and the product output, the gross profit is expressed by the price of the unit product, the production cost of the unit product, and the product output, and the carbon emission cost is expressed by the purchase price of unit carbon emission, the carbon emission of producing a unit product, the total carbon emission in the previous cycle, the carbon quota factor, and the product output;

[0040] The first mapping relationship includes: π = (P-c0) QP e(e f Q-εE);

[0041] Among them, π represents industry profit, (P-c0)Q represents gross profit, P represents the price of unit product, and P = a-bQ, a represents product market capacity, b represents the inverse sensitivity factor of product demand to price, c0 represents the production cost of unit product, P e (e f Q-εE) represents the carbon emission cost, P e Represents the purchase price per unit of carbon emissions;

[0042] The second mapping relationship is expressed as: social welfare = industry profit + consumer surplus - degree of damage to the environment caused by carbon emissions, wherein the consumer surplus is represented by the inverse sensitivity factor of product demand to price and product output, and the carbon emissions per unit product produced and the product output are used to represent the degree of damage to the environment caused by carbon emissions;

[0043] The second mapping relationship includes:

[0044] Among them, W represents social welfare, Characterizes consumer surplus, Characterizes the degree of damage that carbon emissions cause to the environment.

[0045] In a possible implementation, the response system further includes:

[0046] The optimal yield determination unit is used to obtain the optimal yield of the current cycle based on the third mapping relationship and the target carbon quota factor.

[0047] In a possible implementation manner, the dynamic allocation parameter acquisition unit is used to:

[0048] Obtain the electricity consumption data of the previous cycle, the carbon emissions per unit of production of the previous cycle, and the carbon quota factor of the previous cycle;

[0049] Determine the output of the previous cycle according to the electricity consumption data of the previous cycle;

[0050] The product of the output of the previous cycle and the carbon emissions per unit product produced in the previous cycle is taken as the total carbon emissions of the previous cycle.

[0051] According to another aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to implement the above method when executing the instructions stored in the memory.

[0052] According to another aspect of the present disclosure, a non-volatile computer-readable storage medium is provided, on which computer program instructions are stored, wherein the computer program instructions implement the above method when executed by a processor.

[0053] According to another aspect of the present disclosure, a computer program product is provided, including a computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code. When the computer-readable code runs in a processor of an electronic device, the processor in the electronic device executes the above method.

[0054] In the embodiments of the present disclosure, historical data for too long is not required. In fact, historical data only requires the total carbon emissions of the previous cycle, so the accumulation time of historical data on carbon emissions is no longer a determining factor in determining carbon emission quotas. When determining carbon emission quotas, it will no longer be biased towards companies with rich historical carbon emission data, which is more fair to all companies. Moreover, the present disclosure only requires dynamic parameters for the current cycle, which greatly reduces the amount of data required compared to the baseline method, reduces the complexity of calculations, and is easy to operate, making it very suitable for the scenario of the initial carbon trading market.

[0055] Further features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.

[0057] Figure 1 A schematic diagram of a flow chart of a carbon quota dynamic adjustment method provided in an embodiment of the present disclosure;

[0058] Figure 2 A schematic diagram of the structure of a first model provided in an embodiment of the present disclosure;

[0059] Figure 3 This is a schematic diagram of the impact of the total carbon emissions in the previous cycle on the carbon quota factor in the current cycle in Example 1;

[0060] Figure 4 This is a schematic diagram of the mapping relationship between the carbon emissions per unit product produced in the current cycle and the carbon emission quota in the current cycle in Example 1;

[0061] Figure 5 This is a schematic diagram of the impact of the total carbon emissions in the previous cycle on the carbon quota factor in the current cycle in Example 2;

[0062] Figure 6This is a schematic diagram of the mapping relationship between the carbon emissions per unit product produced in the current cycle and the carbon emission quota in the current cycle in Example 2;

[0063] Figure 7 A structural diagram of a carbon quota dynamic adjustment response system provided in an embodiment of the present disclosure;

[0064] Figure 8 A schematic diagram of the structure of an electronic device for dynamic adjustment of carbon quota provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0065] Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0066] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0067] In addition, in order to better illustrate the present disclosure, numerous specific details are given in the following specific embodiments. It should be understood by those skilled in the art that the present disclosure can also be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the main purpose of the present disclosure.

[0068] Figure 1 The following is a flow chart of a method for dynamically adjusting carbon quotas provided in an embodiment of the present disclosure. Figure 1 As shown, the method includes:

[0069] S11, obtaining dynamic allocation parameters of the current cycle, wherein the dynamic allocation parameters include: the total carbon emissions of the previous cycle.

[0070] In the embodiment of the present disclosure, the dynamic allocation parameters may include: economic indicators in a single industry, and / or parameters related to carbon emissions.

[0071] Exemplarily, the dynamic allocation parameters may include economic indicators that characterize carbon emissions, such as the purchase price per unit of carbon emissions.

[0072] By way of example, the dynamic allocation parameters may include economic indicators characterizing products produced in the industry, such as product market capacity, and / or unit product production cost.

[0073] Exemplarily, the dynamic allocation parameters may include parameters related to carbon emissions, such as the total carbon emissions in the previous cycle. Here, the total carbon emissions in the previous cycle may represent the total carbon emissions of a single industry in the previous cycle. The total carbon emissions may be the sum of the carbon emission quota and the carbon emission purchase amount.

[0074] The dynamic allocation parameters of the current cycle can reflect the production level and carbon emissions in a single industry during the current cycle.

[0075] In the disclosed embodiment, the length of a single cycle can be artificially specified. For example, a short cycle such as one month, one quarter, or one year; or a long cycle such as five years or ten years. The disclosed embodiment does not limit the length of a single cycle.

[0076] S12, analyzing the dynamic allocation parameters to determine the carbon quota factor for the current period.

[0077] In the disclosed embodiments, the dynamic allocation parameters can be analyzed from the perspective of achieving a dynamic balance between the economic benefits and carbon emissions of a single industry; or the dynamic allocation parameters can be analyzed from the perspective of maximizing the economic benefits of a single industry and the carbon emissions meeting environmental protection standards to obtain the carbon quota factor for the current period. The carbon quota factor can be an adjustment coefficient.

[0078] S13, determining the carbon emission quota of the current cycle based on the total carbon emissions of the previous cycle and the carbon quota factor of the current cycle.

[0079] In the embodiment of the present disclosure, the carbon quota factor of the current period can be used to adjust the total carbon emissions of the previous period to obtain the adjusted carbon emissions, and the adjusted carbon emissions are used as the carbon emissions quota of the current period.

[0080] In the embodiments of the present disclosure, historical data for too long is not required. In fact, historical data only requires the total carbon emissions of the previous cycle, so the accumulation time of historical data on carbon emissions is no longer a determining factor in determining carbon emission quotas. When determining carbon emission quotas, it will no longer be biased towards companies with rich historical carbon emission data, which is more fair to all companies. Moreover, the present disclosure only requires dynamic parameters for the current cycle, which greatly reduces the amount of data required compared to the baseline method, reduces the complexity of calculations, and is easy to operate, making it very suitable for the scenario of the initial carbon trading market.

[0081] In one possible implementation, the analyzing the dynamic allocation parameters to determine the carbon quota factor for the current cycle includes: inputting the dynamic allocation parameters into a first model to obtain the carbon quota factor for the current cycle, wherein the first model is used to characterize the balance relationship between product output and the carbon quota factor; the determining the carbon emission quota for the current cycle based on the total carbon emissions of the previous cycle and the carbon quota factor for the current cycle includes: taking the product of the total carbon emissions of the previous cycle and the carbon quota factor for the current cycle as the carbon emission quota for the current cycle.

[0082] The total carbon emissions of the previous cycle can reflect the carbon quota that the industry actually needs in the previous cycle. Under the influence of the carbon quota factor of the current cycle, the carbon quota of the actual demand may be changed. The changed carbon quota will be more in line with the carbon quota required by the industry in the current cycle. For example, the product of the total carbon emissions of the previous cycle and the carbon quota factor of the current cycle can be directly used as the carbon emission quota of the current cycle, which is simple to calculate and requires little calculation.

[0083] In the disclosed embodiment, the first model may include a pre-trained game model, such as a Stackelberg game model or a Stackelberg integral game model. The first model may reflect a master-slave game with the carbon quota factor (government) as the leader and the product output (industry) as the follower. The first model may characterize the dynamic equilibrium relationship between the product constant and the carbon quota factor. Thus, the carbon quota factor of the current cycle obtained using the first model not only takes into account the economic benefits within the industry, which can improve the enthusiasm of enterprises for energy conservation and emission reduction, but also takes into account environmental protection requirements and effectively controls the carbon emissions of the industry.

[0084] In a possible implementation, the dynamic allocation parameters are input into the first model to obtain the carbon quota factor for the current cycle, including: obtaining a first mapping relationship between industry profits, product output, and carbon quota factors under the constraint of an industry carbon emission cap; obtaining a second mapping relationship between social welfare, product output, and carbon quota factors, wherein the social welfare includes the industry profits; and determining, under the limitation of the dynamic allocation parameters, a target carbon quota factor under the condition of maximum social welfare based on the first mapping relationship and the second mapping relationship, and using the target carbon quota factor as the carbon quota factor for the current cycle.

[0085] For environmental protection, government departments can formulate carbon emission cap constraints for various industries in a coordinated manner. For example, the carbon emission cap constraint for an industry can be the sum of the carbon emission quota and the carbon emission purchase volume in the same period, which is less than the carbon emission cap for the industry. The carbon emission cap for an industry can be a pre-set value.

[0086] In the disclosed embodiment, product output and carbon quota factor can be used to represent industry profit; product output and carbon quota factor can be used to represent social welfare. Social welfare can include industry profit. When social welfare is maximized, it can be said that industry profit is also maximized. Therefore, it is equivalent to determining the target carbon quota factor when social welfare is maximized and industry profit is maximized. This not only takes into account environmental protection requirements, but also mobilizes the enthusiasm of enterprises for energy conservation and emission reduction, so that the determined carbon quota factor is more in line with actual needs.

[0087] In a possible implementation, under the limitation of the dynamic allocation parameters, based on the first mapping relationship and the second mapping relationship, determining the target carbon quota factor under the condition of maximum social welfare includes: based on the first mapping relationship, according to the dynamic allocation parameters, determining a third mapping relationship between product output and carbon quota factor in the same period under the condition of satisfying the industry carbon emission upper limit constraint and maximizing industry profits; based on the second mapping relationship and the third mapping relationship, determining the target carbon quota factor according to the dynamic allocation parameters.

[0088] When industry profits are maximized, the first mapping relationship can be expressed by product output and carbon quota factor, so the third mapping relationship between product output and carbon quota factor can be obtained. When social welfare is maximized, the second mapping relationship can be expressed by product output and carbon quota factor. Moreover, based on the third mapping relationship, product output can be expressed by carbon quota factor, so the target carbon quota factor can be determined. The whole calculation process has simple steps, small calculation amount, and is easy to implement.

[0089] In a possible implementation, the dynamic allocation parameters also include: the product market capacity of the current cycle, the inverse sensitivity factor of the product demand to the price of the current cycle, the production cost of the unit product of the current cycle, the purchase price of the unit carbon emission of the current cycle, the carbon emission that can be purchased in the current cycle, and the carbon emission of the unit product produced in the current cycle; the industry carbon emission upper limit constraint condition is expressed as: the total carbon emission in a cycle is not greater than the set industry carbon emission upper limit; the first mapping relationship is expressed as: industry profit = gross profit - carbon emission cost, wherein the product market capacity, the inverse sensitivity factor of the product demand to the price, and the carbon emission upper limit are used. and product output, representing the price of unit products, using the price of unit products, the production cost of unit products and product output to represent the gross profit, using the unit carbon emission purchase price, the carbon emissions per unit product, the total carbon emissions in the previous cycle, the carbon quota factor and product output to represent the carbon emission cost; the second mapping relationship is expressed as: social welfare = industry profit + consumer surplus - the degree of damage to the environment caused by carbon emissions, wherein the inverse sensitivity factor of product demand to price and product output are used to represent the consumer surplus, and the carbon emissions per unit product and the product output are used to represent the degree of damage to the environment caused by carbon emissions.

[0090] For ease of understanding, formula (1) can be used to represent the industry carbon emission cap constraint; formula (2) can be used to represent the first mapping relationship; and formula (3) can be used to represent the second mapping relationship.

[0091] e f Q≤T+εE (1)

[0092] Among them, e f Q represents the carbon emissions in a cycle, Q represents the product output in a cycle, and e f Represents the carbon emissions per unit of product produced; T+εE represents the industry's carbon emissions cap, T represents the carbon emissions that can be purchased in the current cycle, εE represents the carbon emissions quota of the current cycle, ε represents the carbon quota factor of the current cycle, and E represents the total carbon emissions of the previous cycle.

[0093] π=(P-c0)QP e (e f Q-εE) (2)

[0094] Among them, π represents industry profit, (P-c0)Q represents gross profit, P represents the price of unit product, and P = a-bQ, a represents product market capacity, b represents the inverse sensitivity factor of product demand to price, c0 represents the production cost of unit product, P e (e f Q-εE) represents the carbon emission cost, P eRepresents the purchase price per unit of carbon emissions.

[0095]

[0096] Among them, W represents social welfare, Characterizes consumer surplus, Characterizes the degree of damage that carbon emissions cause to the environment.

[0097] Based on formulas (1) and (2), we can construct the Lagrangian function L of industry profit. For ease of understanding, we use formula (4) to represent the Lagrangian function of industry profit.

[0098] L=(a-bQ-c0)QP e (e f Q-εE)+λ(e f Q-(T+εE)) (4)

[0099] Here, λ is the Lagrange multiplier.

[0100] According to the Lagrangian function L of industry profit, the derivative function of industry profit to product output is determined to obtain the first partial derivative function; and the derivative function of industry profit to Lagrangian multiplier is determined to obtain the second partial derivative function. When the industry profit rate is maximized, the first partial derivative function and the second partial derivative function are both equal to zero, and then the third mapping relationship can be determined, that is,

[0101] According to the second mapping relationship, the derivative function of social welfare to the carbon quota factor is determined to obtain the third partial derivative function. And according to the third partial derivative function, the derivative function of the derivative function of social welfare to the carbon quota factor is determined to obtain the fourth partial derivative function. It can be obtained that the fourth partial derivative is less than zero, so social welfare has a maximum value. Therefore, the third partial derivative is set equal to zero, and the third mapping relationship is substituted into the third partial derivative to determine the carbon quota factor. This carbon quota is the target carbon quota factor when social welfare is maximized.

[0102] For ease of understanding, the first partial derivative function is represented by formula (5), the second partial derivative function is represented by formula (6), the third partial derivative function is represented by formula (7), and the fourth partial derivative function is represented by formula (8).

[0103]

[0104] In a possible implementation, the method further includes: obtaining an optimal output in a current cycle based on the third mapping relationship and the target carbon quota factor.

[0105] As mentioned above, the third mapping relationship represents the relationship between product output and carbon quota factor, so the target carbon quota factor can be substituted into the third mapping relationship to obtain the optimal output of the current cycle. Enterprises can arrange production in the current cycle based on the optimal output. For enterprises, carbon emissions in a single cycle are not easy to count, but it is easy to count and obtain output, so using the optimal output can more intuitively guide corporate carbon emissions, which is highly operational in practical applications.

[0106] In one possible implementation, the dynamic allocation parameters of the current cycle are obtained, including: obtaining electricity consumption data of the previous cycle, carbon emissions per unit product of the previous cycle, and the carbon quota factor of the previous cycle; determining the output of the previous cycle based on the electricity consumption data of the previous cycle; and taking the product of the output of the previous cycle and the carbon emissions per unit product of the previous cycle as the total carbon emissions of the previous cycle.

[0107] It is not easy to count the output of a single cycle for the tertiary industry, construction industry and infrastructure industry. However, electricity consumption data can reflect the output to a certain extent. The electricity consumption data here can include electricity consumption.

[0108] In the embodiment of the present disclosure, a fourth mapping relationship between electricity consumption data and output can be determined based on historical electricity consumption data and historical output data. In this way, the electricity consumption data of the previous cycle can be combined with the fourth mapping relationship to determine the output of the previous cycle, and then the total carbon emissions of the previous cycle can be obtained.

[0109] In this way, the method of the embodiment of the present disclosure is not only applicable to the product production industry, but can also be applied to more industries to determine carbon emission quotas, thereby broadening the scope of application.

[0110] Figure 2 This is a schematic diagram of the structure of the first model provided in the embodiment of the present disclosure. Figure 2 As shown, the first model includes: a parameter import module, a solution model connected to the parameter import model, and a game model connected to the solution model.

[0111] The parameter import module is used to obtain the dynamic allocation parameters of the current cycle. The game model is used to construct the first mapping relationship, the second mapping relationship, and the third mapping relationship.

[0112] The solution module is used to solve the carbon quota factor and optimal output of the current cycle based on the dynamic allocation parameters of the current cycle, according to the first mapping relationship, the second mapping relationship, the third mapping relationship, and the industry carbon emission upper limit constraint.

[0113] Two embodiments are used below to illustrate the results determined by the first model in practical applications.

[0114] Since the purchase price per unit of carbon emission will not change frequently in the short term, the purchase price per unit of carbon emission is preset in the first model. Therefore, in the following two embodiments, the purchase price per unit of carbon emission in the current cycle may not be included in the dynamic allocation parameters of the current cycle.

[0115] In these two embodiments, the dynamic allocation parameters of the current cycle include: the product market capacity of the current cycle, the inverse sensitivity factor of the product demand of the current cycle to the price, the production cost of the unit product of the current cycle, the carbon emissions of the production unit product of the current cycle, the carbon emissions that can be purchased in the current cycle, and the total carbon emissions of the previous cycle. In addition, a is used to represent the product market capacity of the current cycle, b is used to represent the inverse sensitivity factor of the product demand of the current cycle to the price, c0 is used to represent the production cost of the unit product of the current cycle, and e is used to represent the carbon emissions of the previous cycle. f Indicates the carbon emissions per unit of product produced in the current cycle. T is used to indicate the carbon emissions that can be purchased in the current cycle. E is used to indicate the total carbon emissions in the previous cycle. T is used to indicate the total carbon emissions in the previous cycle. a Indicates the carbon emission quota for the current period.

[0116] Example 1

[0117] The dynamic allocation parameters of the current cycle of the petrochemical industry in City A are imported into the first model, where a = 40 million tons, b = 0.1, c0 = 2457 yuan, e f =0.1~2 tons, T=0, E=20 million~35 million tons, and multiple carbon quota factors for the current cycle can be obtained.

[0118] Figure 3 Schematic diagram of the impact of the total carbon emissions in the previous cycle on the carbon quota factor in the current cycle in Example 1. Figure 3 As shown in the figure, the carbon quota factor decreases with the increase of the total carbon emissions in the previous period. When the carbon emissions per unit product of the current cycle are 2 tons, when the total carbon emissions in the previous cycle are 20 million to 35 million tons, the carbon quota factor of the current cycle is in the range of 0.5575 to 0.9755. When the total carbon emissions in the previous cycle are 35 million tons and the carbon emissions per unit product of the current cycle are 0.1 to 2 tons, the carbon quota factor of the current cycle is in the range of 0.5575 to 1.8068.

[0119] Figure 4 This is a schematic diagram of the mapping relationship between the carbon emissions per unit product produced in the current cycle and the carbon emission quota of the current cycle in Example 1.

[0120] Among them, taking the total carbon emissions of 3391 in the previous cycle as an example, when the carbon emissions per unit product in the current cycle are 0.1 to 2 tons, the carbon emission quota for the current cycle is in the range of 1951.1 to 6323.7 (10,000 tons).

[0121] Example 2

[0122] The dynamic allocation parameters of the current cycle of the petrochemical industry in City B are imported into the first model, where a = 62.86 million tons, b = 0.1, c0 = 2500 yuan, e f =2~4 tons, T=0, E=12~20 million tons, the carbon quota factor for the current cycle can be obtained.

[0123] Figure 5 Schematic diagram of the effect of the total carbon emissions in the previous cycle on the carbon quota factor in the current cycle in Example 2. Figure 5 As shown in Figure 1, the carbon quota factor decreases with the increase of the total carbon emissions in the previous period. When the total carbon emissions in the previous period were 12 to 200 million tons, the carbon quota factor in the current period was in the range of 0.781 to 1.3.

[0124] Figure 6 This is a schematic diagram of the mapping relationship between the carbon emissions per unit product produced in the current cycle and the carbon emission quota of the current cycle in Example 2.

[0125] Among them, taking the total carbon emissions of 20 million tons in the previous cycle as an example, when the carbon emissions per unit product in the current cycle are 2 to 4 tons, the carbon emission quota for the current cycle is in the range of 10.617 million to 25.662 million tons.

[0126] Figure 7 This is a structural diagram of the carbon quota dynamic adjustment response system provided by the embodiment of the present disclosure. Figure 7 As shown, the response system 20 includes:

[0127] The dynamic allocation parameter acquisition unit 21 is used to acquire the dynamic allocation parameters of the current cycle, and the dynamic allocation parameters include: the total carbon emissions of the previous cycle;

[0128] A carbon quota factor determination unit 22, configured to analyze the dynamic allocation parameter and determine the carbon quota factor for the current period;

[0129] The carbon emission amount determination unit 23 is used to determine the carbon emission quota of the current period based on the total carbon emission of the previous period and the carbon quota factor of the current period.

[0130] In a possible implementation, the carbon quota factor determination unit 22 includes:

[0131] A carbon quota factor determination subunit, used for inputting the dynamic allocation parameter into a first model to obtain the carbon quota factor of the current cycle, wherein the first model is used for characterizing the balance relationship between product output and the carbon quota factor;

[0132] The carbon emission amount determination unit 23 is used to:

[0133] The product of the total carbon emissions of the previous period and the carbon quota factor of the current period is used as the carbon emission quota of the current period.

[0134] In a possible implementation, the carbon quota factor determination subunit includes:

[0135] A first mapping relationship acquisition unit, used to acquire a first mapping relationship between industry profit, product output, and carbon quota factor under the industry carbon emission upper limit constraint condition;

[0136] A second mapping relationship acquisition unit, used to acquire a second mapping relationship between social welfare, product output, and carbon quota factor, wherein the social welfare includes the industry profit;

[0137] A target carbon quota factor determination unit is used to determine the target carbon quota factor under the condition of maximum social welfare based on the first mapping relationship and the second mapping relationship under the limitation of the dynamic allocation parameter, and use the target carbon quota factor as the carbon quota factor of the current period.

[0138] In a possible implementation, the target carbon quota factor determination unit is used to:

[0139] Based on the first mapping relationship and according to the dynamic allocation parameter, determine a third mapping relationship between product output and carbon quota factor in the same period while satisfying the industry carbon emission upper limit constraint and maximizing industry profits;

[0140] Based on the second mapping relationship and the third mapping relationship, the target carbon quota factor is determined according to the dynamic allocation parameter.

[0141] In a possible implementation, the dynamic allocation parameters also include: product market capacity of the current cycle, inverse sensitivity factor of product demand to price of the current cycle, production cost of unit product of the current cycle, purchase price of unit carbon emission of the current cycle, carbon emission that can be purchased in the current cycle, and carbon emission of unit product produced in the current cycle; the industry carbon emission upper limit constraint condition is expressed as: carbon emission in one cycle is not greater than the set industry carbon emission upper limit;

[0142] The industry carbon emission cap constraints include: fQ≤T+εE;

[0143] Among them, e f Q represents the carbon emissions in a cycle, Q represents the product output in a cycle, and e f Represents the carbon emissions per unit of product produced; T+εE represents the industry's carbon emissions cap, T represents the carbon emissions that can be purchased in the current cycle, εE represents the carbon emission quota of the current cycle, ε represents the carbon quota factor of the current cycle, and E represents the total carbon emissions of the previous cycle;

[0144] The first mapping relationship is expressed as: industry profit = gross profit - carbon emission cost, wherein the price of a unit product is expressed by the product market capacity, the inverse sensitivity factor of product demand to price, and the product output, the gross profit is expressed by the price of the unit product, the production cost of the unit product, and the product output, and the carbon emission cost is expressed by the purchase price of unit carbon emission, the carbon emission of producing a unit product, the total carbon emission in the previous cycle, the carbon quota factor, and the product output;

[0145] The first mapping relationship includes: π = (P-c0) QP e (e f Q-εE);

[0146] Among them, π represents industry profit, (P-c0)Q represents gross profit, P represents the price of unit product, and P = a-bQ, a represents product market capacity, b represents the inverse sensitivity factor of product demand to price, c0 represents the production cost of unit product, P e (e f Q-εE) represents the carbon emission cost, P e Represents the purchase price per unit of carbon emissions;

[0147] The second mapping relationship is expressed as: social welfare = industry profit + consumer surplus - degree of damage to the environment caused by carbon emissions, wherein the consumer surplus is represented by the inverse sensitivity factor of product demand to price and product output, and the carbon emissions per unit product produced and the product output are used to represent the degree of damage to the environment caused by carbon emissions;

[0148] The second mapping relationship includes:

[0149] Among them, W represents social welfare, Characterizes consumer surplus, Characterizes the degree of damage that carbon emissions cause to the environment.

[0150] In a possible implementation, the response system 20 further includes:

[0151] The optimal yield determination unit is used to obtain the optimal yield of the current cycle based on the third mapping relationship and the target carbon quota factor.

[0152] In a possible implementation manner, the dynamic allocation parameter acquisition unit is used to:

[0153] Obtain the electricity consumption data of the previous cycle, the carbon emissions per unit of production of the previous cycle, and the carbon quota factor of the previous cycle;

[0154] Determine the output of the previous cycle according to the electricity consumption data of the previous cycle;

[0155] The product of the output of the previous cycle and the carbon emissions per unit product produced in the previous cycle is taken as the total carbon emissions of the previous cycle.

[0156] In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0157] The embodiment of the present disclosure also provides a computer-readable storage medium on which computer program instructions are stored, and the computer program instructions implement the above method when executed by a processor. The computer-readable storage medium can be a volatile or non-volatile computer-readable storage medium.

[0158] An embodiment of the present disclosure further proposes an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to implement the above method when executing the instructions stored in the memory.

[0159] The embodiments of the present disclosure also provide a computer program product, including a computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code. When the computer-readable code runs in a processor of an electronic device, the processor in the electronic device executes the above method.

[0160] Figure 8 A schematic diagram of the structure of an electronic device for dynamic adjustment of carbon quota provided in an embodiment of the present disclosure. For example, the electronic device 1900 may be provided as a server or a terminal device. Figure 8 , the electronic device 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource represented by a memory 1932 for storing instructions executable by the processing component 1922, such as an application. The application stored in the memory 1932 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 1922 is configured to execute instructions to perform the above method.

[0161] The electronic device 1900 may also include a power supply component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input / output interface 1958 (I / O interface). The electronic device 1900 may operate based on an operating system stored in the memory 1932, such as Windows Server 2003. TM , Mac OS X TM , Unix TM ,Linux TM , FreeBSD TM or similar.

[0162] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions, which can be executed by the processing component 1922 of the electronic device 1900 to perform the above method.

[0163] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0164] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0165] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0166] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0167] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0168] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0169] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0170] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of the module, program segment or instruction includes one or more executable instructions for realizing the specified logical function. In some alternative implementations, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of special hardware and computer instructions.

[0171] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A method for dynamically adjusting carbon quotas, characterized in that: include: Obtaining dynamic allocation parameters for the current cycle, the dynamic allocation parameters including: the total carbon emissions of the previous cycle, the product market capacity of the current cycle, the inverse sensitivity factor of product demand to price in the current cycle, the production cost per unit product in the current cycle, the purchase price per unit carbon emissions in the current cycle, the carbon emissions that can be purchased in the current cycle, and the carbon emissions per unit product produced in the current cycle; Analyzing the dynamic allocation parameters to determine the carbon quota factor for the current period; Determine the carbon emission quota for the current period based on the total carbon emissions of the previous period and the carbon quota factor of the current period; The analyzing the dynamic allocation parameters to determine the carbon quota factor for the current period includes: Inputting the dynamic allocation parameter into a first model to obtain the carbon quota factor of the current cycle, wherein the first model is used to characterize the balance relationship between product output and the carbon quota factor; The determining of the carbon emission quota for the current period based on the total carbon emission in the previous period and the carbon quota factor for the current period includes: The product of the total carbon emissions of the previous period and the carbon quota factor of the current period is used as the carbon emission quota of the current period; The step of inputting the dynamic allocation parameter into the first model to obtain the carbon quota factor of the current period includes: Obtaining the first mapping relationship between industry profit, product output, and carbon quota factor under the industry carbon emission cap constraint; Acquire a second mapping relationship between social welfare, product output, and carbon quota factor, wherein the social welfare includes the industry profit; Under the limitation of the dynamic allocation parameters, based on the first mapping relationship and the second mapping relationship, a target carbon quota factor under the condition of maximum social welfare is determined, and the target carbon quota factor is used as the carbon quota factor of the current period.

2. The method according to claim 1, characterized in that The determining of the target carbon quota factor under the condition of maximum social welfare based on the first mapping relationship and the second mapping relationship under the limitation of the dynamic allocation parameter includes: Based on the first mapping relationship and according to the dynamic allocation parameter, determine a third mapping relationship between product output and carbon quota factor in the same period while satisfying the industry carbon emission upper limit constraint and maximizing industry profits; Based on the second mapping relationship and the third mapping relationship, the target carbon quota factor is determined according to the dynamic allocation parameter.

3. The method according to claim 1, characterized in that The industry carbon emission ceiling constraint condition is expressed as: the carbon emissions within a cycle shall not exceed the set industry carbon emission ceiling; The industry carbon emission cap constraints include: f Q≤T+εE; Among them, e f Q represents the carbon emissions in a cycle, Q represents the product output in a cycle, and e f Represents the carbon emissions per unit of product produced; T+εE represents the industry's carbon emissions cap, T represents the carbon emissions that can be purchased in the current cycle, εE represents the carbon emission quota of the current cycle, ε represents the carbon quota factor of the current cycle, and E represents the total carbon emissions of the previous cycle; The first mapping relationship is expressed as: industry profit = gross profit - carbon emission cost, wherein the price of a unit product is expressed by the product market capacity, the inverse sensitivity factor of product demand to price, and the product output, the gross profit is expressed by the price of the unit product, the production cost of the unit product, and the product output, and the carbon emission cost is expressed by the purchase price of unit carbon emission, the carbon emission of producing a unit product, the total carbon emission in the previous cycle, the carbon quota factor, and the product output; The first mapping relationship includes: π = (P-c0) QP e (e f Q-εE); Among them, π represents industry profit, (P-c0)Q represents gross profit, P represents the price of unit product, and P = a-bQ, a represents product market capacity, b represents the inverse sensitivity factor of product demand to price, c0 represents the production cost of unit product, P e (e f Q-εE) represents the carbon emission cost, P e Represents the purchase price per unit of carbon emissions; The second mapping relationship is expressed as: social welfare = industry profit + consumer surplus - degree of damage to the environment caused by carbon emissions, wherein the consumer surplus is represented by the inverse sensitivity factor of product demand to price and product output, and the carbon emissions per unit product produced and the product output are used to represent the degree of damage to the environment caused by carbon emissions; The second mapping relationship includes: Among them, W represents social welfare, Characterizes consumer surplus, Characterizes the degree of damage that carbon emissions cause to the environment.

4. The method according to claim 2, characterized in that: The method further comprises: Based on the third mapping relationship and the target carbon quota factor, the optimal output of the current cycle is obtained.

5. The method according to claim 1, characterized in that The obtaining of the dynamic allocation parameters of the current cycle includes: Obtain the electricity consumption data of the previous cycle, the carbon emissions per unit of production of the previous cycle, and the carbon quota factor of the previous cycle; Determine the output of the previous cycle according to the electricity consumption data of the previous cycle; The product of the output of the previous cycle and the carbon emissions per unit product produced in the previous cycle is taken as the total carbon emissions of the previous cycle.

6. A carbon quota dynamic adjustment response system, characterized in that: include: A dynamic allocation parameter acquisition unit, used to acquire dynamic allocation parameters of the current cycle, the dynamic allocation parameters including: the total carbon emissions of the previous cycle, the product market capacity of the current cycle, the inverse sensitivity factor of the product demand to the price of the current cycle, the production cost of the unit product of the current cycle, the purchase price of the unit carbon emissions of the current cycle, the carbon emissions that can be purchased in the current cycle, and the carbon emissions of the production unit products of the current cycle; A carbon quota factor determination unit, configured to analyze the dynamic allocation parameter and determine the carbon quota factor for the current period; A carbon emission quota determination unit, configured to determine the carbon emission quota for the current period based on the total carbon emissions for the previous period and the carbon quota factor for the current period; The carbon quota factor determination unit includes: A carbon quota factor determination subunit, used for inputting the dynamic allocation parameter into a first model to obtain the carbon quota factor of the current cycle, wherein the first model is used for characterizing the balance relationship between product output and the carbon quota factor; The carbon emission amount determination unit is used to: The product of the total carbon emissions of the previous period and the carbon quota factor of the current period is used as the carbon emission quota of the current period; The carbon quota factor determination subunit includes: A first mapping relationship acquisition unit, used to acquire a first mapping relationship between industry profit, product output, and carbon quota factor under the industry carbon emission upper limit constraint condition; A second mapping relationship acquisition unit, used to acquire a second mapping relationship between social welfare, product output, and carbon quota factor, wherein the social welfare includes the industry profit; A target carbon quota factor determination unit is used to determine the target carbon quota factor under the condition of maximum social welfare based on the first mapping relationship and the second mapping relationship under the limitation of the dynamic allocation parameter, and use the target carbon quota factor as the carbon quota factor of the current period.

7. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to implement the method described in any one of claims 1 to 5 when executing the instructions stored in the memory.

8. A non-volatile computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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