Multi-agent transaction distribution method and device based on electricity-carbon-green market

Abstract

The invention relates to a multi-agent transaction distribution method and device based on an electricity-carbon-green market, and the method comprises the steps: constructing a carbon transaction reward and punishment mechanism according to the relation between a carbon quota and the carbon dioxide emission of an agent, determining the carbon transaction cost of the subject according to a carbon transaction reward and punishment mechanism; aiming at the power generation type main body, determining an income objective function; determining a cost objective function for the power utilization subject; constructing a non-cooperative game model by taking the power generation type subject and the power utilization type subject as game subjects, taking the power selling price of the power generation type subject as a decision space and taking the income objective function and the cost objective function as objective functions; and obtaining a resource transaction scheme, updating the resource transaction scheme in the model until the resource transaction scheme meets the equilibrium state, and taking the resource transaction scheme meeting the equilibrium state as a transaction allocation result. According to the invention, accurate allocation of different market resources is realized.

Description

Technical Field

[0001] This application relates to the field of electric energy, and in particular to a multi-entity trading allocation method and apparatus based on the electricity-carbon-green market. Background Technology

[0002] The carbon market, green certificate market, and electricity market are the three core market-based mechanisms of China's new energy system. The electricity market deals with physical electricity, the carbon market with carbon emission rights, and the green certificate market with green environmental rights. While the commodities traded in these three markets differ, they all contribute to resource allocation within the new energy system, influencing the distribution of power generation resources among environmental stakeholders and among electricity loads. However, achieving precise resource allocation among different stakeholders to prevent resource waste remains a pressing issue. Summary of the Invention

[0003] This application provides a multi-entity trading allocation method and apparatus based on the electricity-carbon-green market, which at least solves the problem in related technologies that it is difficult to achieve accurate resource allocation among different entities.

[0004] In a first aspect, embodiments of this application provide a multi-entity trading allocation method based on the electricity-carbon-green market, including: A carbon trading reward and penalty mechanism is constructed based on the relationship between each entity's carbon quota and carbon dioxide emissions, and the carbon trading cost for each entity is determined based on the carbon trading reward and penalty mechanism. For power generation entities, a revenue objective function is determined based on the aforementioned carbon trading costs and expenses; For the aforementioned electricity-consuming entities, a cost objective function is determined based on the purchase cost and the carbon trading cost; Using the power generation entities and the power consumption entities as the game players, the electricity price of the power generation entities as the decision space, and the revenue objective function and the cost objective function as the objective function set, a non-cooperative game model is constructed. Obtain the set of resource trading schemes for each of the aforementioned game subjects, and solve the non-cooperative game model to obtain all resource trading schemes that satisfy the equilibrium state as the trading allocation result.

[0005] In one embodiment, the power generation entities include a first power generation entity representing fossil fuel power generation and a second power generation entity representing clean energy power generation. The revenue objective function includes a first revenue objective function and a second revenue objective function. The costs include power generation costs, carbon emission costs, and power generation revenue. The step of determining the revenue objective function for each power generation entity based on the carbon trading costs and other costs includes... For the first power generation entity, the electricity sales revenue of the first power generation entity is the power generation revenue, the electricity sales revenue of the first power generation entity and the carbon trading cost are the first revenue item, the power generation cost and the carbon emission cost are the first cost item, and the first revenue item minus the first cost item is the first revenue objective function. For the second type of power generation entity, the power generation revenue is the revenue from selling electricity and the revenue from selling green certificates. The power generation revenue and the revenue from selling green certificates are the second revenue items. The power generation cost is the second cost item. The second revenue item minus the second cost item is used as the second revenue objective function.

[0006] In one embodiment, determining the cost objective function for electricity-consuming entities based on purchase costs and carbon trading costs includes: For the aforementioned electricity-consuming entities, the purchase cost is defined as the cost of purchasing electricity, the cost of purchasing green certificates, and the cost of purchasing carbon. The sum of the purchase cost and the carbon trading cost is used as the objective function for expenses.

[0007] In one embodiment, the decision space is specifically configured as follows: The price of the electricity bundled by the second type of power generation entity is within the first threshold range; The price of unbound electricity for the first power generation entity and the price of unbound electricity for the second power generation entity are within a second threshold range.

[0008] In one embodiment, the step of constructing a carbon trading reward and penalty mechanism based on the relationship between each entity's carbon allowance and carbon dioxide emissions, and determining the carbon trading cost for each entity based on the carbon trading reward and penalty mechanism, includes: If the carbon dioxide emissions of the subject are less than or equal to the difference between the carbon quota and the preset excess threshold, then the carbon trading cost of the subject is the first carbon trading penalty cost. If the carbon dioxide emissions of the subject are greater than the difference between the carbon quota and the preset excess threshold, but less than or equal to the preset excess threshold, then the carbon trading cost of the subject is the second carbon trading penalty cost. If the carbon dioxide emissions of the subject are less than or equal to the sum of the carbon quota and the preset excess threshold, and greater than the preset excess threshold, then the carbon trading cost of the subject is the first carbon trading reward cost. If the carbon dioxide emissions of the subject are less than or equal to k+1 times the preset excess threshold and greater than k times the preset excess threshold, then the carbon trading cost of the subject is the second carbon trading reward cost, wherein the values ​​of the first carbon trading penalty cost and the second carbon trading penalty cost are less than 0, and the values ​​of the first carbon trading reward cost and the second carbon trading reward cost are greater than 0.

[0009] In one embodiment, before constructing the carbon trading reward and penalty mechanism based on the relationship between each entity's carbon allowance and carbon dioxide emissions, the method further includes: If the entity is a power generation entity, the carbon quota shall be allocated based on the annual power generation of the power generation entity; If the entity is an industrial manufacturing entity, the carbon quota shall be allocated based on the annual output of the industrial manufacturing entity. If the entity is a public building, the carbon allowance is allocated based on the average historical carbon emissions of the public building.

[0010] In one embodiment, obtaining the set of resource trading schemes for each of the game players and solving the non-cooperative game model to obtain all resource trading schemes that satisfy the equilibrium state as the trading allocation result includes: Obtain the resource transaction scheme set for each of the game entities. In the non-cooperative game model, update the resource transaction scheme currently used by each of the game entities for the game according to the preset update rules until the updated resource transaction scheme satisfies the equilibrium state. Take all resource transaction schemes that satisfy the equilibrium state as the transaction allocation result.

[0011] In one embodiment, obtaining the resource trading scheme set for each of the game entities, and updating the resource trading scheme currently used by each of the game entities in the non-cooperative game model according to a preset update rule until the updated resource trading scheme satisfies an equilibrium state includes: The ideal equilibrium state is obtained by solving the non-cooperative game model using a preset algorithm, and a set of resource trading schemes for each of the game subjects is obtained. In the non-cooperative game model, the ideal equilibrium state is used as a reference target, and the current resource trading scheme used for the game is updated according to a preset update rule until the updated resource trading scheme satisfies the reference target.

[0012] Secondly, embodiments of this application provide a multi-entity trading and allocation device based on the electricity-carbon-green market, including: A carbon trading cost determination module is used to construct a carbon trading reward and penalty mechanism based on the relationship between each entity's carbon quota and carbon dioxide emissions, and to determine the carbon trading cost for each entity based on the carbon trading reward and penalty mechanism. The module for determining the revenue objective function is used to determine the revenue objective function for power generation entities based on the carbon trading costs and expense costs. The module for determining the cost objective function is used to determine the cost objective function for the electricity-consuming entities based on the purchase cost and the carbon trading cost. A model construction module is used to construct a non-cooperative game model with the power generation entity and the power consumption entity as the game entities, the electricity price of the power generation entity as the decision space, and the revenue objective function and the cost objective function as the objective function set. The allocation module is used to obtain the set of resource trading schemes for each of the game subjects, and solve the non-cooperative game model to obtain all resource trading schemes that satisfy the equilibrium state as the trading allocation result.

[0013] Thirdly, embodiments of this application provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the multi-entity trading allocation method based on the electricity-carbon-green market as described in the first aspect above.

[0014] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the multi-entity trading allocation method based on the electricity-carbon-green market as described in the first aspect above.

[0015] The multi-entity trading allocation method and apparatus based on the electricity-carbon-green market provided in this application embodiment have at least the following technical effects: A carbon trading reward and penalty mechanism is constructed based on the relationship between carbon quotas and carbon dioxide emissions to determine the carbon trading costs for each entity. Objective functions are then constructed for different power generation and consumption entities based on varying costs and carbon trading costs. A non-cooperative game model is built and solved to achieve equilibrium, meaning no single entity can gain greater benefits by adjusting its strategy. This determines the trading allocation scheme for different entities, achieving precise allocation of different market resources.

[0016] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1This is a flowchart illustrating a multi-entity trading allocation method based on an exemplary embodiment of the electricity-carbon-green market; Figure 2 This is a schematic diagram illustrating the fluctuation of bundled electricity prices according to an exemplary embodiment; Figure 3 This is a schematic diagram illustrating the fluctuation of unbundled electricity prices according to an exemplary embodiment; Figure 4 This is a schematic diagram illustrating carbon price changes in a carbon market according to an exemplary embodiment; Figure 5 This is a schematic diagram illustrating the trading volume of electricity at different carbon prices according to an exemplary embodiment; Figure 6 This is a schematic diagram of a multi-entity trading and allocation device based on an exemplary embodiment of an electricity-carbon-green market; Figure 7 This is a block diagram of an electronic device according to an exemplary embodiment. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the application is described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application.

[0019] Obviously, the accompanying drawings described below are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar scenarios based on these drawings without any inventive effort. Furthermore, it is understood that although the efforts made in this development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, any changes to design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as insufficient disclosure of the content of this application.

[0020] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that is mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0021] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms “connected,” “linked,” “coupled,” and similar words used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. “Multiple” used in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following objects are in an "or" relationship. The terms "first," "second," and "third" used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0022] Firstly, embodiments of this application provide a multi-entity trading allocation method based on the electricity-carbon-green market. Figure 1 This is a flowchart illustrating a multi-entity trading allocation method based on an exemplary embodiment of the electricity-carbon-green market, such as... Figure 1 As shown, the multi-partner trading allocation method based on the electricity-carbon-green market includes: Step S101: Construct a carbon trading reward and punishment mechanism based on the relationship between each entity's carbon quota and carbon dioxide emissions, and determine the carbon trading cost for each entity based on the carbon trading reward and punishment mechanism.

[0023] The pre-defined carbon allowance allocation rules are based on the total annual carbon allowance quota, whereby relevant carbon market institutions allocate free carbon allowances to different entities. Entities refer to companies from different industries participating in the trading, indicating a specific type of enterprise without limiting the number of companies. When an entity's allocated carbon allowances are insufficient to meet its production needs, it will purchase carbon emission rights from the carbon market to satisfy those needs. If an entity's actual carbon emissions are lower than its allocated carbon allowances, it will place the excess carbon allowances on the carbon market to generate revenue.

[0024] The free carbon allowances for each entity are determined based on carbon allowance allocation rules. The carbon trading cost for each entity is determined by comparing its CO2 emissions during production with its free carbon allowances. Specifically, if an entity's CO2 emissions exceed its free carbon allowances, it must purchase additional carbon allowances from the carbon market, incurring penalties and a premium, thus increasing its carbon trading cost. The greater the excess over the free allowances, the higher the carbon trading cost. Conversely, if an entity's CO2 emissions are less than its free carbon allowances, it can sell the excess allowances to the carbon market to generate revenue. The carbon trading reward and penalty mechanism determines the carbon trading cost by satisfying the following conditions: If an entity's carbon dioxide emissions are less than or equal to the difference between its carbon allowance and the preset excess threshold, then the entity's carbon trading cost is the first carbon trading penalty cost.

[0025] If an entity's carbon dioxide emissions are greater than the difference between its carbon quota and the preset excess threshold, but less than or equal to the preset excess threshold, then the entity's carbon trading cost is the second carbon trading penalty cost.

[0026] If an entity's carbon dioxide emissions are less than or equal to the sum of its carbon allowance and a preset excess threshold, but greater than the preset excess threshold, then the entity's carbon trading cost is the first carbon trading reward cost.

[0027] If the carbon dioxide emissions of an entity are less than or equal to k+1 times the preset excess threshold and greater than k times the preset excess threshold, then the entity's carbon trading cost is the second carbon trading reward cost, where the values ​​of the first carbon trading penalty cost and the second carbon trading penalty cost are less than 0, and the values ​​of the first carbon trading reward cost and the second carbon trading reward cost are greater than 0.

[0028] In other words, it satisfies the following formula: in, For carbon trading costs, For reward or punishment coefficients, These are the conversion factors for each entity. Main body Emissions To preset the excess threshold, The free quota obtained by the main body.

[0029] By examining the relationship between a subject's carbon dioxide emissions and free carbon allowances, a carbon trading reward and punishment mechanism can be constructed. From the perspective of the carbon market, the carbon trading costs between different subjects can be determined, the impact of the carbon market on different subjects can be quantified, and it can be determined whether different subjects gain benefits or incur additional costs in the carbon market. This will provide a foundation for more accurate allocation in the future.

[0030] Step S102: For power generation entities, determine the revenue objective function based on carbon trading costs and expenses.

[0031] Power generation entities are categorized into two types: Type I and Type II. Their revenue objective functions include a first revenue objective function and a second revenue objective function. Costs include power generation costs, carbon emission costs, and power generation revenue. Type I power generation entities are fossil fuel power generation companies, including coal-fired and gas-fired power plants. Type II power generation entities are renewable energy power generation companies, including wind power companies and photovoltaic power companies. Different types of power generation companies differ in energy consumption, carbon dioxide emissions, and power generation costs. Therefore, a corresponding revenue objective function is determined for each type of power generation entity to assess its profitability.

[0032] For the first type of power generation entity, the electricity sales revenue of the first type of power generation entity is taken as the power generation revenue, the electricity sales revenue and carbon trading costs of the first type of power generation entity are taken as the first revenue item, and the power generation cost and carbon emission cost are taken as the first cost item. The first revenue item minus the first cost item is taken as the first revenue objective function. The first revenue objective function satisfies the following formula:

[0033] in, The primary revenue objective is for power generation entities. It's the revenue from selling electricity. It is the power generation cost of the first type of power generation entity. It is the cost of carbon emissions. It is the cost of carbon trading.

[0034] More specifically, the first objective function for revenue is determined as follows: The costs of the first type of power generation entity include power generation costs and carbon emission costs. The power generation costs of the first type of power generation entity satisfy the following formula:

[0035]

[0036] in, It is the power generation cost of the first type of power generation entity. As the first type of power generation entity Electricity generation, To clear out prices in the market for unbundled electricity consumption. , , These are real-valued parameters.

[0037] The carbon emission cost of the first type of power generation entity satisfies the following formula:

[0038] in, It is the cost of carbon emissions. It refers to the carbon price in the carbon market. The conversion factor representing the carbon allowance for the primary power generation category. As the first type of power generation entity Free carbon credits.

[0039] The electricity produced by entities in the first category is non-bonded electricity and is not obligated to fulfill renewable energy quotas. Therefore, the revenue of entities in the first category comes from the sale of their non-bonded electricity in the electricity market. The revenue from the sale of electricity by entities in the first category satisfies the following formula:

[0040] in, It's the revenue from selling electricity. , They are respectively the first type of power generation entities to electricity sales company and users The strategy for reporting electricity sales, It is the first type of power generation entity to electricity sales company Contracted electricity volume sold, It is the first type of power generation entity To users Contracted electricity sold Furthermore, if the carbon dioxide emissions generated by a primary power generation entity exceed the free carbon allowances, and the entity needs to purchase carbon allowances from the carbon market for production, then the carbon trading cost belongs to the primary power generation entity. Conversely, if the carbon dioxide emissions generated by a primary power generation entity are less than the free carbon allowances, and the entity sells the excess carbon allowances on the carbon market for profit, then the carbon trading cost belongs to the primary power generation entity.

[0041] Considering the electricity sales revenue, generation costs, carbon emission costs, and carbon trading costs of the first type of power generation entity, the first revenue objective function satisfies the following formula:

[0042] in, It is the revenue from electricity sales of the primary power generation entity. It's the revenue from selling electricity. It is the power generation cost of the first type of power generation entity. It is the cost of carbon emissions. It is the cost of carbon trading.

[0043] Continuing with step S102, for the second type of power generation entity, the power generation revenue is the revenue from selling electricity and the revenue from selling green certificates. The power generation revenue and the revenue from selling green certificates are the second revenue items, and the power generation cost is the second cost item. The second revenue item minus the second cost item is used as the objective function for the second revenue.

[0044] The second category of power generation entities consists of renewable energy power generation companies, such as wind power companies and photovoltaic power companies. These entities utilize renewable energy sources, resulting in very low and negligible carbon emissions, thus their carbon emission costs are negligible. Furthermore, according to the pre-set carbon quota allocation rules, these entities are not allocated free carbon quotas; therefore, their carbon trading costs are zero.

[0045] In other words, the second revenue objective function for the second type of power generation entity does not need to consider carbon trading costs and carbon emission costs. Therefore, the second revenue objective function satisfies the following formula:

[0046] in, It is the second revenue objective of the second type of power generation entity. It is the electricity sales revenue of the second type of power generation entity. It is the revenue from the sale of green certificates by the second type of power generation entity. It is the power generation cost of the second type of power generation entity.

[0047] More specifically, the second objective function for revenue is determined as follows: The costs of the second type of power generation entity include power generation costs, which satisfy the following formula:

[0048] in, It is the power generation cost of the second type of power generation entity. For the second type of power generation entity, the power generation function is... The market-clearing price for electricity volume tied to green certificates for the second type of power generation entities. The market clearing price for electricity volume not bundled with green certificates; ( ), , These are the real-valued parameters for the second type of power generation entity.

[0049] The second type of power generation entity produces bundled and unbundled electricity through renewable energy sources and trades the produced electricity in the electricity market. Therefore, the power generation revenue of the second type of power generation entity comes from the revenue from selling bundled and unbundled electricity in the electricity market, and from the revenue from selling green certificates in the green certificate market.

[0050] The power generation revenue of the second type of power generation entity satisfies the following formula:

[0051]

[0052] in, It's the revenue from electricity generation. It is the electricity sales revenue of the second type of power generation entity. It is the revenue from the sale of green certificates by the second type of power generation entity. and They are the second type of power generation entities to electricity sales company and users The pricing strategy for the electricity sold is as follows. It is the electricity sales volume tied to the power grid. This refers to the electricity sold without being bundled with other electricity sources. This refers to the sales volume of the green certificates that are tied to the bundled portion. This refers to the sales volume of the non-binding portion of the green certificates. for The price of green certificates corresponding to green electricity.

[0053] Taking into account the power generation revenue and power generation costs of the second type of power generation entity, the objective function for the second revenue of the second type of power generation entity satisfies the following formula:

[0054] in, The target revenue for the second type of power generation entity is... It is the electricity sales revenue of the second type of power generation entity. It is the revenue from the sale of green certificates by the second type of power generation entity. It is the power generation cost of the second type of power generation entity.

[0055] Based on the different characteristics of power generation entities, the revenues and costs of different power generation entities in the carbon market, electricity market, and green certificate market are determined. The revenue objective functions of the first and second power generation entities are then determined to satisfy the optimal allocation for different power generation entities based on the revenue objective functions.

[0056] Step S103: For electricity-consuming entities, determine the cost objective function based on purchase costs and carbon trading costs.

[0057] Electricity-consuming entities bear varying degrees of mandatory responsibility for consuming renewable energy, resulting in significant differences in their electricity demands. These entities can fulfill their obligations by purchasing green electricity and green certificates. Therefore, the purchase costs for electricity-consuming entities include electricity purchase costs, green certificate purchase costs, and carbon purchase costs. Electricity purchase costs consist of bundled and unbundled electricity purchased from both primary and secondary power generation entities. Bundled electricity is sold along with its corresponding environmental rights (such as green certificates and carbon allowances), while unbundled electricity is purchased separately. Green certificate purchase costs are the expenses incurred in purchasing renewable energy green certificates. Carbon purchase costs are the costs of purchasing carbon allowances required by large electricity users with high carbon emissions. Based on the purchase costs of electricity-consuming entities and carbon trading costs, a cost objective function is determined to identify the costs for power generation entities.

[0058] For the aforementioned electricity-consuming entities, the purchase cost is defined as the cost of purchasing electricity, the cost of purchasing green certificates, and the cost of purchasing carbon credits. The sum of the purchase cost and the carbon trading cost is used as the cost objective function. This cost objective function satisfies the following formula:

[0059] in, The cost targets for electricity-consuming entities. It is the cost of purchasing electricity. It is the cost of purchasing green certificates. It is the cost of purchasing carbon credits. It is the cost of carbon trading.

[0060] Specifically, the cost objective function is determined as follows: The purchase cost for electricity-consuming entities includes the cost of electricity purchase, the cost of green certificates, and the cost of carbon credits. The electricity purchase cost includes the cost of non-bundled electricity purchased by the electricity-consuming entity from the first type of power generator, the cost of non-bundled electricity purchased by the electricity-consuming entity from the second type of power generator, and the cost of bundled electricity purchased by the electricity-consuming entity from the second type of power generator. Therefore, the purchase cost satisfies the following formula:

[0061] in, It is the cost of purchasing electricity. It is the cost of purchasing green certificates; It is the cost of non-bundled electricity purchased by the electricity-consuming entity from the first-generation entity. It is the cost of non-bundled electricity purchased by the electricity-consuming entity from the second-generation entity. It is the cost of bundled electricity purchased by the electricity-consuming entity from the second-generation entity. This refers to the cost of purchasing green certificates, specifically the expenses incurred by electricity-using entities when purchasing green certificates. This refers to the cost of purchasing carbon credits.

[0062] More specifically, the cost of purchasing electricity satisfies the following formula:

[0063] in, Electricity-consuming entities are divided into the first type of power-generating entities. The price of unbundled electricity purchased, Electricity-consuming entities are divided into the first type of power-generating entities. The amount of electricity purchased as unbundled power. Electricity-consuming entities are divided into two categories: electricity-generating entities and electricity-consuming entities. The price of unbundled electricity purchased, The main body of electricity is the second type of power generation body. The amount of electricity purchased as unbundled power; The main body of electricity is the second type of power generation body. The price of the bundled electricity purchased, The main body of electricity is the second type of power generation body. The amount of electricity purchased as part of the bundled power supply.

[0064] The cost of purchasing green certificates for electricity-consuming entities is determined based on the actual number of green certificates purchased. Furthermore, if all electricity-consuming entities have completed or exceeded their mandatory renewable energy consumption targets, the cost of purchasing green certificates satisfies the following formula: The actual number of green certificates purchased by electricity-consuming entities meets the following requirements:

[0065] in, This refers to the actual number of green certificates purchased by electricity-consuming entities. This refers to the total amount of green electricity purchased by electricity-consuming entities from all Category 1 power-generating entities. It represents the total amount of green electricity purchased by electricity-consuming entities from all second-category power-generating entities. This refers to the bundled green electricity purchased by electricity-consuming entities. This refers to the total amount of green electricity sold by electricity-consuming entities. It is 1000.

[0066] Constraints:

[0067] in, This refers to the actual number of green certificates purchased by electricity-consuming entities. This refers to the bundled green electricity purchased by electricity-consuming entities. This refers to the bundled green electricity purchased by electricity-consuming entities. Total amount of green electricity sold by electricity-consuming entities It is 1000.

[0068] Based on the above constraints and the formula for the actual number of green certificates purchased, the electricity-consuming entities... The cost of purchasing green certificates follows the formula:

[0069] in, It is the cost of purchasing green certificates. This refers to the actual number of green certificates purchased by electricity-consuming entities. yes The price of green certificates corresponding to green electricity.

[0070] The carbon purchase cost for electricity-consuming entities satisfies the following formula:

[0071] in, The carbon purchase cost for electricity-consuming entities. It refers to the carbon price in the carbon market. It is the conversion factor for carbon quotas of electricity-consuming entities. Electricity-using main body Total amount of products produced, and total amount of electricity purchased Positive correlation It's a carbon quota. This refers to the portion of electricity-consuming entities' output from which carbon allowances are available. The unit product coefficient by which electricity consumers obtain carbon allowances; After determining the costs of electricity purchase, green certificate purchase, and carbon purchase, electricity-consuming entities also need to consider whether they need to purchase carbon allowances from first-tier power-generating entities in the carbon market to meet their production needs. Therefore, the cost objective function for electricity-consuming entities satisfies the following formula:

[0072] in, It is the cost for the electricity user. It is the cost of purchasing electricity. It is the cost of purchasing green certificates. It is the cost of purchasing carbon credits. It is the cost of carbon trading.

[0073] The final cost objective function is determined based on the production needs of the electricity-consuming entities, so as to meet their own cost minimization needs in subsequent game theory.

[0074] Step S104: Using power generation entities and power consumption entities as game subjects, the electricity price of power generation entities as the decision space, and the revenue objective function and the cost objective function as the objective function set, construct a non-cooperative game model.

[0075] A non-cooperative game model is constructed with the first type of power generation entity, the second type of power generation entity, and the electricity consumption entity as the game players, and the objective functions of each entity's respective revenue and cost as the objective function set. The electricity selling price of the power generation entity is used as the decision space.

[0076] In the non-cooperative game model, the prices and electricity quantities declared by each player are as follows: First category of power generation entities The declared price of non-bundled electricity sold is And the corresponding electricity sold is .

[0077] Second type of power generation entity The price of the bundled electricity sold is And the corresponding electricity sold is The price of unbundled electricity is And the corresponding electricity sold is .

[0078] The price at which electricity is declared for purchase by electricity-consuming entities is The purchased electricity amount is .

[0079] The aforementioned declaration content constitutes the initial strategy combination for each game player, specifically denoted as:

[0080]

[0081]

[0082]

[0083] In this context, the bids of the game participants are constrained by the decision space, which is specifically configured as follows: The price of the electricity tied to the second type of power generation entity is within the first threshold range.

[0084] The price of unbound electricity for the first type of power generation entity and the price of unbound electricity for the second type of power generation entity are within the second threshold range.

[0085] Specifically, the decision space satisfies the following:

[0086] in, It is the price of the bundled electricity declared and sold by the second type of power generation entity. It refers to the price of unbundled electricity from the primary power generation entity. The price of unbound electricity for the second type of power generation entity, It is the first threshold for tying electricity prices. It is the first threshold for unbundled electricity prices. It is the second threshold for binding electricity. It is the second threshold for unbound electricity.

[0087] By constructing a non-cooperative game model, each player and its objective function are determined. Under the constraints of the decision space, the game bidding is completed. The model can calculate its own revenue based on the prices and electricity quantities declared by different players and the objective function, and continuously update its own decisions on prices and electricity quantities to achieve a multi-player non-cooperative equilibrium state, thereby achieving the optimal allocation of social resources.

[0088] Step S105: Obtain the set of resource transaction schemes for each game subject, and solve the non-cooperative game model to obtain the complete set of resource transaction schemes that satisfy the equilibrium state as the transaction allocation result.

[0089] Specifically, solving non-cooperative game models includes: Obtain the set of resource trading schemes for each player in the game. In the non-cooperative game model, update the resource trading schemes currently used by each player in the game according to the preset update rules until the updated resource trading schemes satisfy the equilibrium state. Take all resource trading schemes that satisfy the equilibrium state as the transaction allocation result.

[0090] Obtain the resource transaction scheme set for each game entity. The specific different resource transaction schemes in the resource transaction scheme set for each game entity include: the price and total amount of electricity purchased by the electricity-consuming entity; the selling price and total amount of unbound electricity sold by the first power-generating entity; the selling price and total amount of unbound electricity sold by the second power-generating entity; and the selling price and total amount of bound electricity sold by the second power-generating entity.

[0091] Based on a set of resource trading schemes, a non-cooperative game model is used to continuously update the current resource trading schemes used by each player, forming different bidding strategies. This continues until all resource trading schemes meet the equilibrium condition, i.e., the equilibrium state where no player can gain greater benefits by adjusting their resource trading schemes. The resource trading scheme that satisfies the equilibrium state is taken as the transaction allocation result for all players.

[0092] More specifically, the methods for achieving equilibrium in resource trading among the various game participants include: Step S151: Solve the non-cooperative game model using a preset algorithm to obtain the ideal equilibrium state and acquire the resource transaction scheme set for each game subject.

[0093] The pre-constructed non-cooperative game model is solved using a pre-defined algorithm to obtain an ideal equilibrium state. This ideal state serves as the convergence reference for subsequent updates to the non-cooperative game model and represents the equilibrium state that each resource trading scheme is expected to reach. Optionally, the pre-defined algorithm includes an improved firefly algorithm.

[0094] Step S152: In the non-cooperative game model, the ideal equilibrium state is used as the reference target. The resource trading scheme currently used for the game is updated according to the preset update rule until the updated resource trading scheme satisfies the reference target.

[0095] In a non-cooperative game model with pre-set initial parameters, the ideal equilibrium state is used as the reference target. Resource trading schemes are updated according to a preset update rule. That is, the players adjust their resource trading schemes based on historical experience and the results of the previous round until the state formed by all resource trading schemes converges to the reference target. When the state of all resource trading schemes converges to the reference target, the composition of the current resource trading schemes represents the final transaction allocation result for all players.

[0096] It should be noted that the ideal equilibrium state is a reference target, representing the equilibrium state that each resource trading scheme hopes to achieve. However, in the actual process of updating resource trading schemes, the final convergence target may not be the ideal equilibrium state. Therefore, during the updating of strategy schemes, if the reference target is used as the final convergence target, and if convergence to another stable state—that is, suboptimal equilibrium convergence—is not achieved, then all resource trading schemes at this point can be considered as the trading allocation result.

[0097] In one embodiment, the first power generation entity is a fossil fuel power generation company, the second power generation entity is a renewable energy power generation company, and the electricity consumption entity is an electricity user. A total of eight entities compete in a game, among which... They are two renewable energy power generation companies. They are two fossil fuel power generation companies. There are 4 electricity users. The non-cooperative game model is set with 10 rounds and 150 rounds per round.

[0098] Table 1 shows the basic parameters of the power generation companies. As shown in Table 1, the power output of different power generation companies can be calculated based on the specific parameters of the four power generation companies.

[0099] Table 1 Basic parameters of the power generation company

[0100] Figure 2 This is a schematic diagram illustrating the fluctuation of bundled electricity prices according to an exemplary embodiment, such as... Figure 2As shown, two renewable energy power generation companies and In the constructed non-cooperative game model, the final bid for the bundled electricity stabilizes at around 570 yuan / (MW·h).

[0101] Figure 3 This is a schematic diagram illustrating the fluctuation of unbundled electricity prices according to an exemplary embodiment, such as... Figure 3 As shown, two renewable energy power generation companies and 2 fossil fuel power generation companies and In the constructed non-cooperative game model, the final bid for unbound electricity stabilizes at around 440 yuan / (MW·h).

[0102] Table 2 shows the trading volume and revenue of each entity at equilibrium. As shown in Table 2, according to the different entities' revenue objective functions, at equilibrium, the trading volume and revenue of different power generation companies satisfy their own profit maximization.

[0103] Table 2. Transaction volume and revenue of each entity at equilibrium.

[0104] In another embodiment, Figure 4 This is a schematic diagram illustrating carbon price changes in a carbon market according to an exemplary embodiment, such as... Figure 4 As shown, carbon price fluctuations in the carbon market have one peak and two troughs, and different carbon prices will affect the total electricity trading volume. Figure 5 This is a schematic diagram illustrating the trading volume of electricity at different carbon prices according to an exemplary embodiment, such as... Figure 5 As shown, during the process of carbon price increasing from 20 yuan / ton to 40 yuan / ton, due to the existence of the carbon trading reward and punishment mechanism and the tradability of carbon quotas, the first category of power generation entities engages in carbon trading based on production needs. Under the constraints of the carbon trading reward and punishment mechanism, they either gain additional revenue or incur additional production costs based on the carbon dioxide emissions during the production process, and then offset these additional production costs by increasing production. The electricity consumption entities undergo a similar process to the first category of power generation entities. The second category of power generation entities is influenced by the first and electricity consumption entities, and their electricity trading also increases. Therefore, during the process of carbon price increasing from 20 yuan / ton to 40 yuan / ton, the volume of electricity traded increases. When the carbon price is greater than 40 yuan / ton, the carbon price becomes a burden for all three categories of entities, and the carbon trading reward and punishment mechanism cannot change this situation. Therefore, the production of all entities decreases, and the traded electricity volume decreases.

[0105] Continuing with step S101, determine that the carbon allowance for each entity meets the following conditions: If the entity is a power generation entity, carbon allowances are allocated based on its annual power generation. That is, the carbon allowances for power generation entities satisfy the following formula:

[0106] in, It's a carbon quota. It is the conversion factor for carbon allowances of power generation entities. This refers to the annual power generation. It should be noted that... It is a benchmark value derived by relevant management departments through calculation and analysis of various factors such as the power generation industry's production capacity, installed capacity, technological level, and emission reduction measures.

[0107] If the entity is an industrial manufacturing entity, carbon allowances are allocated based on its annual production output. In other words, the carbon allowances for industrial manufacturing entities satisfy the following formula:

[0108] in, It is the conversion factor for carbon allowances for industrial manufacturing entities. This refers to the annual output of major industrial manufacturing entities. It should be noted that... It is a benchmark value obtained by relevant management departments through calculation and analysis of various aspects such as the production capacity, carbon emission treatment level, technology level and emission situation of the industrial manufacturing industry over the past three years.

[0109] If the building is a public utility, carbon allowances are allocated based on the average historical carbon emissions of public utility buildings. In other words, carbon allowances for public utility buildings satisfy the following formula:

[0110] in, It is the average of historical carbon emissions.

[0111] Optionally, It is the average carbon emissions of the building over the past three years. The carbon allowance for 2021 is the average carbon emissions of 2018, 2019 and 2020.

[0112] In summary, the multi-entity trading allocation method based on the electricity-carbon-green market provided in this application constructs a carbon trading reward and punishment mechanism based on the relationship between carbon quotas and carbon dioxide emissions, determining the benefits or increased costs each entity receives from the carbon market to quantify the impact of the carbon market on entity production. Furthermore, by constructing a non-cooperative game model, the strategies of the game entities are continuously adjusted to ultimately achieve an equilibrium state, meaning that no single game entity can obtain greater benefits by adjusting its strategy, thus maximizing the interests of all game entities. The obtained strategy combinations then form the trading allocation scheme, achieving precise allocation of resources.

[0113] Secondly, embodiments of this application provide a multi-entity trading and allocation device based on the electricity-carbon-green market. Figure 6 This is a schematic diagram of a multi-entity trading and allocation device based on an exemplary embodiment of an electricity-carbon-green market, as shown below. Figure 6 As shown, the multi-entity trading and allocation device based on the electricity-carbon-green market includes: The carbon trading cost determination module is used to construct a carbon trading reward and penalty mechanism based on the relationship between each entity's carbon quota and carbon dioxide emissions, and to determine the carbon trading cost for each entity based on the carbon trading reward and penalty mechanism. The module for determining the revenue objective function is used to determine the revenue objective function for power generation entities based on carbon trading costs and expenses. The module for determining the cost objective function is used to determine the cost objective function for electricity-consuming entities based on purchase costs and carbon trading costs. A model building module is used to construct a non-cooperative game model with power generation entities and power consumption entities as the game entities, the electricity price of power generation entities as the decision space, and the revenue objective function and cost objective function as the objective function set. The allocation module is used to obtain the set of resource transaction schemes for each game player, and solve the non-cooperative game model to obtain the complete set of resource transaction schemes that satisfy the equilibrium state as the transaction allocation result.

[0114] In summary, the multi-entity trading and allocation device based on the electricity-carbon-green market provided in this application determines the carbon trading cost for each entity by constructing a carbon trading reward and punishment mechanism based on the relationship between carbon quotas and carbon dioxide emissions. It also constructs objective functions for different power generation and consumption entities based on varying costs and carbon trading costs, and builds and solves a non-cooperative game model to achieve equilibrium, meaning no single entity can gain greater benefits by adjusting its strategy. This determines the trading allocation schemes for different entities, achieving precise allocation of different market resources.

[0115] It should be noted that the multi-entity trading and allocation device based on the electricity-carbon-green market provided in this embodiment is used to implement the above-described embodiments, and details already described will not be repeated. As used above, terms such as "module," "unit," and "subunit" can refer to combinations of software and / or hardware that perform predetermined functions. Although the device described in the above embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0116] Thirdly, embodiments of this application provide an electronic device, Figure 7 This is a block diagram illustrating an electronic device according to an exemplary embodiment. (e.g.) Figure 7 As shown, the electronic device may include a processor 81 and a memory 82 storing computer program instructions.

[0117] Specifically, the processor 81 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0118] The memory 82 may include a mass storage device for data or instructions. For example, and not limitingly, the memory 82 may include a hard disk drive (HDD), a floppy disk drive, a solid-state drive (SSD), flash memory, an optical disk drive, a magneto-optical disk drive, magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 82 may include removable or non-removable (or fixed) media. Where appropriate, the memory 82 may be internal or external to a data processing device. In a particular embodiment, the memory 82 is non-volatile memory. In a particular embodiment, the memory 82 includes read-only memory (ROM) and random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), an electrically alterable read-only memory (EAROM), or flash memory, or a combination of two or more of these. Where appropriate, the RAM can be Static Random-Access Memory (SRAM) or Dynamic Random-Access Memory (DRAM). DRAM can be Fast Page Mode Dynamic Random-Access Memory (FPMDRAM), Extended Data Out Dynamic Random-Access Memory (EDODRAM), Synchronous Dynamic Random-Access Memory (SDRAM), etc.

[0119] The memory 82 can be used to store or cache various data files that need to be processed and / or communicated, as well as possible computer program instructions executed by the processor 81.

[0120] The processor 81 reads and executes computer program instructions stored in the memory 82 to implement any of the multi-entity trading allocation methods based on the electricity-carbon-green market in the above embodiments.

[0121] In one embodiment, the multi-entity trading and allocation device based on the electricity-carbon-green market may further include a communication interface 83 and a bus 80. Wherein, as Figure 7 As shown, the processor 81, memory 82, and communication interface 83 are connected through bus 80 and complete communication with each other.

[0122] The communication interface 83 is used to enable communication between the various modules, devices, units, and / or equipment in the embodiments of this application. The communication interface 83 can also enable data communication with other components such as external devices, image / data acquisition devices, databases, external storage, and image / data processing workstations.

[0123] Bus 80 includes hardware, software, or both, that couples together components of a multi-entity trading and allocation device based on the electricity-carbon-green market. Bus 80 includes, but is not limited to, at least one of the following: data bus, address bus, control bus, expansion bus, and local bus. For example, and not as a limitation, bus 80 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 80 may include one or more buses. Although specific buses are described and illustrated in the embodiments of this application, this application considers any suitable bus or interconnection.

[0124] Fourthly, embodiments of this application provide a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the multi-entity trading allocation method based on the electricity-carbon-green market provided in the first aspect.

[0125] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0126] In a possible implementation, the invention can also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform steps implementing the multi-entity trading allocation method based on the electricity-carbon-green market provided in the first aspect.

[0127] The program code for executing the present invention can be written in any combination of one or more programming languages. The program code can be executed entirely on the user device, partially on the user device, as a standalone software package, partially on the user device and partially on a remote device, or entirely on a remote device.

[0128] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0129] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A multi-entity trading allocation method based on the electricity-carbon-green market, characterized in that, include: A carbon trading reward and penalty mechanism is constructed based on the relationship between each entity's carbon quota and carbon dioxide emissions, and the carbon trading cost for each entity is determined based on the carbon trading reward and penalty mechanism. For power generation entities, a revenue objective function is determined based on the aforementioned carbon trading costs and expenses; For electricity-consuming entities, the cost objective function is determined based on the purchase cost and the carbon trading cost. Using the power generation entities and the power consumption entities as the game players, the electricity price of the power generation entities as the decision space, and the revenue objective function and the cost objective function as the objective function set, a non-cooperative game model is constructed. Obtain the set of resource trading schemes for each of the aforementioned game subjects, and solve the non-cooperative game model to obtain all resource trading schemes that satisfy the equilibrium state as the trading allocation result.

2. The multi-entity trading allocation method based on the electricity-carbon-green market according to claim 1, characterized in that, The power generation entities include a first type of power generation entity representing fossil fuel power generation and a second type of power generation entity representing clean energy power generation. The revenue objective function includes a first revenue objective function and a second revenue objective function. The costs include power generation costs, carbon emission costs, and power generation revenue. For each power generation entity, the revenue objective function is determined based on the carbon trading costs and other costs. For the first power generation entity, the electricity sales revenue of the first power generation entity is the power generation revenue, the electricity sales revenue of the first power generation entity and the carbon trading cost are the first revenue item, the power generation cost and the carbon emission cost are the first cost item, and the first revenue item minus the first cost item is the first revenue objective function. For the second type of power generation entity, the power generation revenue is the revenue from selling electricity and the revenue from selling green certificates. The power generation revenue and the revenue from selling green certificates are the second revenue items. The power generation cost is the second cost item. The second revenue item minus the second cost item is used as the second revenue objective function.

3. The multi-entity trading allocation method based on the electricity-carbon-green market according to claim 1, characterized in that, The aforementioned method for determining the cost objective function for electricity-consuming entities, based on the purchase cost and the carbon trading cost, includes: For the aforementioned electricity-consuming entities, the purchase cost is defined as the cost of purchasing electricity, the cost of purchasing green certificates, and the cost of purchasing carbon. The sum of the purchase cost and the carbon trading cost is used as the objective function for expenses.

4. The multi-entity trading allocation method based on the electricity-carbon-green market according to claim 2, characterized in that, The decision space is specifically configured as follows: The price of the electricity bundled by the second type of power generation entity is within the first threshold range; The price of unbound electricity for the first power generation entity and the price of unbound electricity for the second power generation entity are within a second threshold range.

5. The multi-entity trading allocation method based on the electricity-carbon-green market according to claim 1, characterized in that, The carbon trading reward and penalty mechanism is constructed based on the relationship between each entity's carbon allowance and its carbon dioxide emissions. The carbon trading cost for each entity is determined according to this mechanism, including: If the carbon dioxide emissions of the subject are less than or equal to the difference between the carbon quota and the preset excess threshold, then the carbon trading cost of the subject is the first carbon trading penalty cost. If the carbon dioxide emissions of the subject are greater than the difference between the carbon quota and the preset excess threshold, but less than or equal to the preset excess threshold, then the carbon trading cost of the subject is the second carbon trading penalty cost. If the carbon dioxide emissions of the subject are less than or equal to the sum of the carbon quota and the preset excess threshold, and greater than the preset excess threshold, then the carbon trading cost of the subject is the first carbon trading reward cost. If the carbon dioxide emissions of the subject are less than or equal to k+1 times the preset excess threshold and greater than k times the preset excess threshold, then the carbon trading cost of the subject is the second carbon trading reward cost, wherein the values ​​of the first carbon trading penalty cost and the second carbon trading penalty cost are less than 0, and the values ​​of the first carbon trading reward cost and the second carbon trading reward cost are greater than 0.

6. The multi-entity trading allocation method based on the electricity-carbon-green market according to claim 5, characterized in that, Before constructing the carbon trading reward and penalty mechanism based on the relationship between each entity's carbon allowance and carbon dioxide emissions, the method further includes: If the entity is a power generation entity, the carbon quota shall be allocated based on the annual power generation of the power generation entity; If the entity is an industrial manufacturing entity, the carbon quota shall be allocated based on the annual output of the industrial manufacturing entity. If the entity is a public building, the carbon allowance is allocated based on the average historical carbon emissions of the public building.

7. The multi-entity trading allocation method based on the electricity-carbon-green market according to claim 1, characterized in that, The step of obtaining the set of resource trading schemes for each of the game participants and solving the non-cooperative game model to obtain all resource trading schemes that satisfy the equilibrium state as the trading allocation result includes: Obtain the resource transaction scheme set for each of the game entities. In the non-cooperative game model, update the resource transaction scheme currently used by each of the game entities for the game according to the preset update rules until the updated resource transaction scheme satisfies the equilibrium state. Take all resource transaction schemes that satisfy the equilibrium state as the transaction allocation result.

8. The multi-entity trading allocation method based on the electricity-carbon-green market according to claim 1, characterized in that, The step of obtaining a set of resource trading schemes for each of the game entities, and updating the current resource trading schemes used by each of the game entities in the non-cooperative game model according to a preset update rule until the updated resource trading schemes satisfy an equilibrium state, includes: The ideal equilibrium state is obtained by solving the non-cooperative game model using a preset algorithm, and a set of resource trading schemes for each of the game subjects is obtained. In the non-cooperative game model, the ideal equilibrium state is used as a reference target, and the current resource trading scheme used for the game is updated according to a preset update rule until the updated resource trading scheme satisfies the reference target.

9. A multi-entity trading and allocation device based on the electricity-carbon-green market, characterized in that, include: A carbon trading cost determination module is used to construct a carbon trading reward and penalty mechanism based on the relationship between each entity's carbon allowance and the entity's carbon dioxide emissions, and to determine the carbon trading cost for each entity based on the carbon trading reward and penalty mechanism. The module for determining the revenue objective function is used to determine the revenue objective function for power generation entities based on the carbon trading costs and expense costs. The module for determining the cost objective function is used to determine the cost objective function for electricity-consuming entities based on the purchase cost and the carbon trading cost. A model construction module is used to construct a non-cooperative game model with the power generation entity and the power consumption entity as the game entities, the electricity price of the power generation entity as the decision space, and the revenue objective function and the cost objective function as the objective function set. The allocation module is used to obtain the set of resource trading schemes for each of the game subjects, and solve the non-cooperative game model to obtain all resource trading schemes that satisfy the equilibrium state as the trading allocation result.

10. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor, when executing the computer program, implements the multi-entity trading allocation method based on the electricity-carbon-green market as described in any one of claims 1 to 8.

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