A p2p virtual power plant electric energy sharing service fee pricing method and device based on two-stage game

Abstract

The application discloses a P2P virtual power plant electric energy sharing service fee pricing method and device based on two-stage game, and belongs to the technical field of electric power systems and energy internet. In view of the problem that an existing pricing model does not fully consider the layered communication architecture information interaction constraint and the heterogeneous behavior of producers and consumers, first, the cost and benefit of each party are analyzed; a service quality perception and dynamic trust degree factor is introduced, and a producer and consumer platform selection model is established based on an extended Hotelling model; then, a two-stage game model of the maximum profit of an operator and the maximum utility of the producer and consumer is constructed, and a nonlinear ladder two-part charging strategy is proposed; and an inverse induction method is used to obtain an optimal pricing combination and an optimal platform selection strategy of the producer and consumer. The method effectively improves the profit of the operator and the utility of the producer and consumer, and provides key technical support for market operation of the P2P virtual power plant.

Description

Technical Field

[0001] This application relates to the field of power system technology, specifically to a pricing method and apparatus for P2P virtual power plant power sharing service fees based on two-stage game theory. Background Technology

[0002] With the large-scale integration of distributed photovoltaic, wind power, and energy storage, the power system is undergoing a profound transformation from centralized to distributed, and from unidirectional flow to bidirectional interaction. Against this backdrop, the group of prosumers with both power generation and consumption capabilities is rapidly expanding, and their need for flexible participation in the electricity market is becoming increasingly prominent. Virtual power plants, as an effective technological means of aggregating massive distributed energy resources, achieve coordinated control of dispersed resources through advanced information and communication technologies, providing crucial support for prosumers' participation in the electricity market. In particular, virtual power plants based on point-to-point trading mechanisms can eliminate intermediate links in the traditional power grid, promote direct electricity trading between prosumers and consumers, and significantly improve the local consumption ratio of renewable energy and the economic efficiency of system operation.

[0003] However, the sustainable operation of P2P virtual power plants highly depends on a scientifically sound business model design, with the pricing mechanism for electricity sharing service fees being a core element. Current research in academia and industry mainly focuses on the price formation mechanism of electricity transactions between producers and consumers, paying insufficient attention to the pricing strategies of virtual power plant operators in charging service fees to producers and consumers. Existing service fee pricing models have several shortcomings: First, they fail to fully consider the information interaction characteristics under a layered collaborative communication architecture. In actual systems, there are differentiated communication latency and bandwidth constraints at the large power grid-platform layer, inter-platform layer, and intra-platform layer, which directly affect the timeliness and feasibility of pricing decisions. Second, they ignore the multidimensional heterogeneity of prosumer behavior. Different users have significant differences in their perception of service quality, their level of trust in the platform, and their sensitivity to price. Existing models usually assume homogeneous user behavior, leading to a disconnect between pricing strategies and actual needs. Third, traditional unilateral pricing methods are difficult to adapt to a market environment with multiple competing platforms. In the presence of multiple P2P virtual power plant operators, the platform selection behavior of prosumers will generate complex network externalities, and existing models have failed to establish a two-way interaction mechanism between operators and prosumers. In addition, existing research lacks in-depth exploration of nonlinear tiered two-part charging strategies, making it impossible to dynamically adjust the basic service fee and transaction service fee according to the user's expected and actual transaction volume, and making it difficult to balance operator revenue and user acceptance. Summary of the Invention

[0004] The purpose of this application is to provide a pricing method and device for P2P virtual power plant power sharing service fees based on two-stage game theory. This method can comprehensively consider hierarchical communication constraints, multidimensional heterogeneous user preferences, and multi-platform competition characteristics to achieve scientific determination and dynamic optimization of service fees, thereby improving platform operation efficiency and user participation.

[0005] This application provides a pricing method for P2P virtual power plant energy sharing services based on a two-stage game theory approach. The method includes: S1. Based on a nonlinear tiered two-part pricing strategy, construct an optimization objective function for P2P virtual power plant operators. The optimization objective function includes a first-order profit function based on the cost and revenue factors of P2P virtual power plant operators, and a second-order profit function based on profit changes. S2. Based on the first-order profit function and the second-order profit function, obtain the basic service fees and transaction service fees for each level for the buyer and the seller. S3. Based on the extended Hotelling model, adjust the preferences of producers and consumers for P2P virtual power plant operators according to the basic service fees, transaction service fees, expected transaction volume, and actual transaction volume of each level. S4. Determine whether the two-stage game between the P2P virtual power plant operator and the producer-consumer has reached Nash equilibrium. If equilibrium has not been reached, return to step S2 to obtain the basic service fees and transaction service fees for the buyer and seller. If equilibrium has been reached, proceed to step S5. S5. Output the final pricing scheme; the final pricing scheme includes the optimal basic service fee and optimal transaction service fee for the buyer, the optimal basic service fee and optimal transaction service fee for each tier for the seller, and the optimal platform selection strategy for prosumers.

[0006] Preferably, the first-order profit function is: (1) in, k =1, 2 represent two competing P2P virtual power plant operators; P2P virtual power plant operator k During the period t Profits; P2P virtual power plant operator k Revenue from electricity trading between producers and consumers, The price of electricity traded within the platform of a P2P virtual power plant operator. P2P Virtual Power Plant k Electricity traded with producers and consumers within the platform; P2P virtual power plant operator k Revenue from selling electricity to the grid, For grid connection electricity price, P2P Virtual Power Plant k Electricity sold to the power grid; P2P virtual power plant operator k The cost of purchasing electricity from the grid, The purchase price of electricity from the grid. P2P virtual power plant operator k Purchase electricity from the power grid; P2P virtual power plant operator k Revenue from selling carbon, For carbon emission prices, P2P virtual power plant operator k Carbon emission reductions; P2P virtual power plant operator k The power generation and operation and maintenance costs, The cost of operation and maintenance per unit of electricity generated. P2P virtual power plant operator k During the period t The amount of electricity generated; P2P virtual power plant operator k The total cost of providing services to the buyer, Cost of service for the buyer To join the P2P virtual power plant operator platform k The number of buyers; P2P virtual power plant operator k The total cost of providing services to the seller Service cost for the seller To join the P2P virtual power plant operator platform k The number of sellers.

[0007] Furthermore, the second-order profit function is expressed as: (2) in, Indicates buyer During the period t The two-part payment fee, P2P virtual power plant operator k During the period t To the buyer Basic service fees are charged.

[0008] Furthermore, the basic service fee corresponding to the buyer is based on the buyer's expected transaction volume. The tiering is set as a step function, specifically in the following form: in, P2P virtual power plant operatork For the buyer Tier 1 basic service fee, P2P virtual power plant operator k For the buyer Tier 2 basic service fee, For P2P virtual power plant operators to buyers The threshold for the basic service fee tiers; and Indicates buyer During the period t Transaction service fee, For the buyer During the period t Number of transactions P2P virtual power plant operator k During the period t To the buyer The fee charged per transaction.

[0009] Furthermore, the transaction fee for the buyer is based on the buyer's actual transaction volume. Set as a piecewise continuous function, specifically in the form of: in, P2P virtual power plant operator k For the buyer The first tier of the benchmark rate function, P2P virtual power plant operator k For the buyer The second tier of the benchmark rate function, and These are the attenuation coefficients for level 1 and level 2, respectively. and P2P virtual power plant operators k For the buyer The minimum transaction fees for Tier 1 and Tier 2, Platform for P2P virtual power plant operators k For the buyer The threshold values ​​for the first and second tiers of transaction service fees; Indicates the seller During the period t The two-part payment fee, P2P virtual power plant operator During the period t To the seller Basic service fees are charged.

[0010] Furthermore, the seller's basic service fee is based on the seller's expected transaction volume. The tiering is set as a step function, specifically in the following form: in, P2P virtual power plant operator k For the seller Tier 1 basic service fee, P2P virtual power plant operator k For the seller Tier 2 basic service fee, For P2P virtual power plant operators to sellers The threshold for the basic service fee tiers; and Indicates the seller Transaction service fees during the time period, For the seller During the period t Number of transactions P2P virtual power plant operator k During the period t To the seller The fee charged per transaction.

[0011] Furthermore, the buyer's single transaction fee is based on the seller's actual transaction volume. Set as a piecewise continuous function (seller level 3), specifically in the following form: in, P2P virtual power plant operator k For the seller The first tier of the benchmark rate function, P2P virtual power plant operator k For the seller The second tier of the benchmark rate function, P2P virtual power plant operator k For the seller The third tier of the benchmark rate function, 、 and These are the attenuation coefficients for levels 1, 2, and 3, respectively. 、 and These are the minimum transaction fees for tier 1, tier 2, and tier 3, respectively. and These are platforms for P2P virtual power plant operators. k For the seller The threshold values ​​for transaction service fees at the first and second tiers, and the second and third tiers.

[0012] Furthermore, the buyer i During the period t The number of transactions is determined by the number of platforms that join the P2P virtual power plant operator. k The number of sellers, the actual electricity transaction volume, and the marginal transaction frequency coefficient are all factors that determine this, specifically as follows: (7) in, This is the marginal transaction frequency coefficient. To join the P2P virtual power plant operator platform k The number of sellers, For the buyer Actual electricity trading volume.

[0013] Furthermore, the seller During the period t The number of transactions is determined by the number of platforms that join the P2P virtual power plant operator. k Number of buyers, number of sellers The cost difference and the marginal transaction frequency coefficient are jointly determined, specifically expressed as follows: (8) in, To join the P2P virtual power plant operator platform k Number of buyers For the seller The actual volume of electricity traded.

[0014] Further, step S3 includes: Based on the extended Hotelling model, this paper introduces a service quality perception factor and a dynamic trust factor, assuming two P2P virtual power plant operators' platforms. Located at opposite ends of the interval [0,1], producers and consumers are evenly distributed across the interval; for those located at position... For any buyer, the utility of joining Platform 1 and Platform 2 of different P2P virtual power plant operators is expressed as follows: (9) (10) in, Indicates producer-consumer The power efficiency function, For producers and consumers During the period t The value coefficient of electrical energy, As a preset constant, For producers and consumers During the period t The actual electricity consumption; Indicates buyer On the platform of P2P virtual power plant operators k Net electricity revenue obtained from the source Platform for P2P virtual power plant operators k For the buyer The operational efficiency coefficient; Indicates buyer Revenue from selling carbon, For the buyer Carbon emission reductions; and Indicates buyer The transportation costs of Platform 1 and Platform 2, both P2P virtual power plant operators, are added separately. For the buyer The unit transportation cost; Indicates buyer For P2P virtual power plant operators' platforms k The perceived utility of service quality The sensitivity coefficient of producers and consumers to electricity trading service fees; Indicates buyer For P2P virtual power plant operators' platforms k Trust utility For the buyer For P2P virtual power plant operators' platforms k Trust coefficient.

[0015] Furthermore, for those located in the position Any seller j The utility of joining Platform 1 and Platform 2 of the P2P virtual power plant operator is expressed as follows: (11) (12) in, Indicates the seller On the platform of P2P virtual power plant operators k Net electricity revenue obtained from the source Platform for P2P virtual power plant operators k For the seller The operational efficiency coefficient; Indicates the seller Revenue from selling carbon, For the seller Carbon emission reductions; and Indicates the seller The transportation costs of Platform 1 and Platform 2, both P2P virtual power plant operators, are added separately. For the seller The unit transportation cost; Indicates the seller For P2P virtual power plant operators' platforms The perceived utility of service quality; Indicates the seller For P2P virtual power plant operators' platforms k Trust utility For the seller For P2P virtual power plant operators' platforms Trust coefficient; For any buyer The utility of joining Platform 1 and Platform 2 of different P2P virtual power plant operators is expressed as follows: (13) (14) in, Indicates buyer On the platform of P2P virtual power plant operators k Platform not considered k For the buyer Net electricity revenue obtained from the operating efficiency coefficient; Platforms representing P2P virtual power plant operators k For the buyer The operational efficiency coefficient, This serves as a benchmark coefficient for the platform operation efficiency of P2P virtual power plant operators. For any seller j, the utility of joining Platform 1 and Platform 2 of different P2P virtual power plant operators is expressed as follows: (15) (16) in, Indicates the seller On the platform of P2P virtual power plant operators k Platform not considered k For the seller Net electricity revenue obtained from the operating efficiency coefficient; Platforms representing P2P virtual power plant operators k For the seller The operational efficiency coefficient; The platform selection behavior of buyers and sellers is subject to the following constraints: buyer Participation constraints: (17) Seller Participation constraints: (18) Transportation cost constraints: (19).

[0016] Furthermore, the solution method for the Nash equilibrium in step S4 is as follows: A two-stage game model is used to study P2P virtual power plant operators. k Describe the two-way interaction between producers and consumers; definition , , P2P virtual power plant operators are eligible to operate under the following conditions. k Prosumers and consumers will achieve Nash equilibrium: : (20) (twenty one) Among them, any buyer among prosumers and the seller Optimal basic service fee Any buyer among prosumers and the seller Optimal platform selection strategy , , .

[0017] Furthermore, backward induction is used to solve the two-stage game.

[0018] Considering the diversity of prosumers and consumers in the actual operation of P2P virtual power plants, they can be divided into buyers and sellers based on the volume of electricity transactions. With the basic service fee and transaction service fee determined, prosumers and consumers choose the platform of the P2P virtual power plant operator to join by maximizing their own utility, thus obtaining the optimal platform selection strategy for prosumers and consumers.

[0019] This application also proposes a pricing device for P2P virtual power plant energy sharing service fees based on a two-stage game, comprising: The hierarchical collaborative communication architecture establishment module is used to establish a hierarchical collaborative communication architecture including the large power grid-platform layer, the inter-platform layer, and the internal platform layer. It determines information interaction and latency constraints, analyzes the cost and benefit factors of P2P virtual power plant operators and prosumers, and determines the optimization objective function and corresponding constraints that take into account the platform's multidimensional heterogeneous selection preferences and nonlinear tiered two-part charging changes. The non-linear tiered two-part fee strategy determination module is used to determine the basic service fees and transaction service fees for each tier for both the buyer and the seller. The producer-consumer platform selection preference adjustment module is used to adjust the producer-consumer's platform selection preference for P2P virtual power plant operators based on the extended Hotelling model, according to the basic service fees and transaction service fees of each level, the producer-consumer's expected transaction volume and actual transaction volume. It introduces service quality perceived utility and trust utility to characterize multidimensional heterogeneous preferences. The Nash equilibrium judgment module is used to determine whether the two-stage game system composed of P2P virtual power plant operators and prosumers has reached Nash equilibrium; if it has not reached equilibrium, it returns to the nonlinear tiered two-part charging strategy determination module for iterative optimization. The pricing scheme output module is used to output the final pricing scheme, including the optimal basic service fee and optimal transaction service fee for the buyer, the optimal basic service fee and optimal transaction service fee for each tier for the seller, and the optimal platform selection strategy for prosumers.

[0020] Furthermore, the layered collaborative communication architecture establishment module includes: The large power grid-platform layer communication unit is used to realize information interaction between the large power grid and the platform of the P2P virtual power plant operator; Inter-platform communication unit, used to enable information exchange between competing P2P virtual power plant operators' platforms; The platform's internal communication unit is used to enable information exchange between the P2P virtual power plant operator's platform and the producers and consumers within the platform.

[0021] Furthermore, the module for determining the nonlinear tiered two-part tolling strategy includes: The buyer's basic service fee determination unit is used to determine the first and second tiers of basic service fees in the form of a step function according to the buyer's expected transaction volume. The buyer transaction service fee determination unit is used to determine the first and second tiers of transaction service fees in the form of a piecewise continuous function according to the actual transaction volume of the buyer. The seller's basic service fee determination unit is used to determine the first and second tiers of basic service fees in the form of a step function according to the seller's expected transaction volume. The seller transaction service fee determination unit is used to determine the first, second, and third tiers of transaction service fees in the form of a piecewise continuous function based on the seller's actual transaction volume.

[0022] Furthermore, the consumer platform's preference adjustment module includes: The buyer utility calculation unit is used to calculate the utility of the buyer joining the P2P virtual power plant operator's platform 1 and platform 2 based on the extended Hotelling model. The utility includes electricity utility, net electricity revenue, carbon sales revenue, transportation costs, perceived service quality utility, and trust utility. The seller utility calculation unit is used to calculate the seller's utility in joining Platform 1 and Platform 2 of the P2P virtual power plant operator based on the extended Hotelling model. The utility includes net electricity revenue, carbon sales revenue, transportation costs, perceived service quality utility, and trust utility. The platform selection decision unit is used to determine the optimal platform selection strategy for prosumers based on buyer utility and seller utility.

[0023] Furthermore, the Nash equilibrium determination module includes: The participation constraint verification unit is used to verify whether the buyer participation constraint and the seller participation constraint are satisfied. The transportation cost constraint verification unit is used to verify whether the transportation cost constraint is met. The equilibrium condition judgment unit is used to determine whether the equilibrium conditions for maximizing the profits of P2P virtual power plant operators and maximizing the utility of prosumers are met. The iterative optimization control unit is used to control the return to the nonlinear tiered two-part toll strategy determination module for iterative optimization when equilibrium is not reached.

[0024] This application also proposes an electronic device comprising: One or more processors; Memory is used to store one or more programs.

[0025] This application also proposes a computer-readable storage medium having a computer program stored thereon.

[0026] Compared with the prior art, the beneficial effects of this application are as follows: (1) Based on the bilateral market characteristics of P2P virtual power plants, this invention considers the cost and benefit factors of operators and consumers (buyers and sellers), establishes a two-stage game model with the goal of maximizing operator profits and maximizing consumer utility, and realizes the scientific pricing of service fees; (2) This invention introduces the extended Hotelling model, and uses the service quality perception factor and dynamic trust factor to characterize the multidimensional heterogeneous preferences of consumers for competitive platforms, fully considers the influence of consumers' location distribution, unit transportation cost, service quality perception and dynamic trust on platform selection, and reflects the network externality and user heterogeneity characteristics of the bilateral market; (3) This invention proposes a nonlinear tiered two-part charging strategy, decomposes the service fee into basic service fee and transaction service fee, and solves the problem by tiering through reverse induction, obtains the optimal pricing combination of each tier and the optimal platform selection strategy of consumers, and provides theoretical basis and technical support for the commercial operation of P2P virtual power plants. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of a pricing method for P2P virtual power plant energy sharing service fees based on two-stage game theory, provided for an embodiment of this application.

[0028] Figure 2 A schematic diagram of a pricing device for P2P virtual power plant energy sharing service fees based on two-stage game theory provided in this application embodiment. Detailed Implementation

[0029] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0030] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0031] Traditional pricing methods for P2P virtual power plant (PVP) electricity sharing services primarily focus on pricing electricity transactions between producers and consumers, paying less attention to the pricing mechanism of P2P PVP operators charging service fees to producers and consumers. Existing pricing models do not adequately consider the information interaction constraints under a layered communication architecture and the impact of heterogeneous producer-consumer behavior on pricing strategies. Traditional unilateral pricing methods are difficult to apply to complex market environments with multiple competing P2P PVP operators and bilateral users (buyers and sellers), failing to fully consider the impact of producer-consumer platform selection preferences and network externalities on pricing strategies.

[0032] like Figure 1 As shown, this application proposes a pricing method for P2P virtual power plant energy sharing services based on a two-stage game, which includes: S1. Based on the hierarchical collaborative communication architecture of P2P virtual power plants, a hierarchical collaborative communication architecture including the large power grid-platform layer, the inter-platform layer, and the internal platform layer is established. Information interaction and latency constraints are determined, and the cost and benefit factors of P2P virtual power plant operators and prosumers are analyzed. The optimization objective function and corresponding constraints considering the platform's multidimensional heterogeneous selection preferences and nonlinear tiered two-part charging change strategy are determined. Among them, the optimization objective function includes a first-order profit function based on the cost and benefit factors of P2P virtual power plant operators and a second-order profit function based on profit changes. The setting of the first-order profit function and the second-order profit function is based on the nonlinear tiered two-part charging change strategy, which can be used to provide a basis for subsequent characterization of multidimensional heterogeneous selection preferences. S2. Based on a nonlinear tiered two-part fee strategy, determine the basic service fees and transaction service fees for each level for both the buyer and the seller; wherein, when determining the basic service fees and transaction service fees for each level for both the buyer and the seller, the first-order profit function and the second-order profit function are used. S3. Based on the extended Hotelling model, adjust the platform selection preferences of producers and consumers for P2P virtual power plant operators according to the basic service fees and transaction service fees of each level, the expected transaction volume of producers and consumers and the actual transaction volume, and introduce the perceived utility of service quality and the utility of trust to characterize multidimensional heterogeneous preferences. S4. Determine whether the two-stage game system composed of P2P virtual power plant operators and prosumers has reached Nash equilibrium; if it has not reached equilibrium, return to step S2 for iterative optimization; if it has reached equilibrium, proceed to step S5. S5. Output the final pricing scheme, including the optimal basic service fee and optimal transaction service fee for the buyer, the optimal basic service fee and optimal transaction service fee for each tier for the seller, and the optimal platform selection strategy for prosumers.

[0033] Specifically, in step S1, a layered collaborative communication architecture is established based on the P2P virtual power plant, comprising a large power grid-platform layer, an inter-platform layer, and an internal platform layer. This architecture can be built using standard network protocols and communication hardware. For example, the large power grid-platform layer can exchange data using secure API interfaces, the inter-platform layer can achieve data sharing based on blockchain technology or a federated learning framework, and the internal platform layer can rely on local area network or IoT communication protocols for device interconnection. This determines information interaction and latency constraints, for example, by defining data formats and communication protocols to regulate information interaction and setting latency requirements based on information importance. Furthermore, the cost and benefit factors for P2P virtual power plant operators and prosumers are analyzed. For example, the operator's benefits may include electricity sales revenue, service fee revenue, and carbon emission reduction benefits, while costs cover electricity procurement costs, operation and maintenance costs, and service provision costs. The prosumer's benefits may include savings from self-consumed electricity and surplus electricity sales revenue, while costs include platform service fees. Based on this, an optimization objective function and corresponding constraints are determined, taking into account the platform's multidimensional heterogeneous selection preferences and nonlinear tiered two-part pricing variations. For example, the optimization objective function can be set to maximize operator profits or social welfare, while constraints may include grid operation safety limitations, market transaction rules, and the willingness of producers and consumers to participate.

[0034] In step S2, based on a non-linear, tiered two-part fee strategy, the base service fees and transaction service fees for both buyers and sellers are determined. Specifically, this fee strategy can be set to include two parts: a fixed base service fee and a variable transaction service fee. The base service fee can be set to different tiers based on the expected transaction volume of the producers and consumers. For example, a lower base service fee is charged when the expected transaction volume is below a certain threshold, and a higher base service fee is charged when it is above that threshold. The transaction service fee can be set as a piecewise continuous function based on the actual transaction volume. For example, the larger the transaction volume, the lower the unit transaction fee, in order to encourage large-scale transactions.

[0035] In step S3, based on the extended Hotelling model, the platform selection preferences of prosumers for P2P virtual power plant operators are adjusted according to the basic service fees and transaction service fees for each tier, the expected transaction volume of prosumers, and the actual transaction volume. For example, the prosumers' preference for different platforms can be quantified by constructing a utility function that comprehensively considers economic factors such as service fees and transaction volume. Furthermore, perceived service quality utility and trust utility are introduced to characterize multidimensional heterogeneous preferences. For example, perceived service quality utility can be evaluated through indicators such as user satisfaction surveys or platform service response speed, while trust utility can be quantified based on the platform's historical operating data or security mechanisms. These utility values ​​are incorporated into the total utility calculation of prosumers to more comprehensively reflect their selection tendencies.

[0036] In step S4, it is determined whether the two-stage game system consisting of the P2P virtual power plant operator and the prosumers has reached a Nash equilibrium. Specifically, this determination process involves verifying that, under the current pricing scheme and platform selection strategy, no party can obtain higher revenue or utility by unilaterally changing its strategy. If equilibrium has not been reached, the process returns to step S2 for iterative optimization. For example, the operator can fine-tune the basic service fee or transaction service fee based on the prosumers' platform selection feedback to guide the system towards an equilibrium state. If equilibrium has been reached, the process proceeds to step S5.

[0037] In step S5, the final pricing scheme is output, including the optimal basic service fee and optimal transaction service fee for the buyer, the optimal basic service fee and optimal transaction service fee for each tier for the seller, and the optimal platform selection strategy for prosumers. This output provides a decision-making basis for the actual operation of the P2P virtual power plant, ensuring the rationality and market competitiveness of service fee pricing.

[0038] This method improves system efficiency by constructing a hierarchical collaborative communication architecture to effectively manage information interaction and latency constraints. By introducing a nonlinear, tiered two-part pricing strategy and considering the multidimensional heterogeneous selection preferences of prosumers, it achieves scientific pricing for P2P virtual power plant (P2P) energy sharing services. This method fully considers the two-way interaction between P2P P2P P2P operators and prosumers, and through iterative optimization using a two-stage game model, ensures the fairness and stability of the pricing scheme. This effectively solves the problem that traditional pricing methods fail to adequately consider the heterogeneity of prosumer behavior and platform selection preferences in complex market environments.

[0039] In a layered collaborative communication architecture based on P2P virtual power plants, failing to accurately and comprehensively quantify the various costs and benefits of P2P virtual power plant operators when pricing electricity sharing services will lead to an unreasonable profit objective function, thereby affecting the effectiveness of the pricing strategy and the operator's sustainable operating capability. To address this, this application further proposes a first-order profit function based on the cost and benefit factors of P2P virtual power plant operators, with the objective of profit maximization.

[0040] The first-order profit function for a P2P virtual power plant operator is: .

[0041] Specifically, the first-order profit function of P2P virtual power plant operators It is defined as the sum of all revenues minus the sum of all costs. Among them, =1, 2 represent two competing P2P virtual power plant operators; P2P virtual power plant operator k During the period tThe profit function is the core basis for operators' decision-making. By clearly identifying all relevant revenue sources and expenditure items, operators can accurately assess their operating status and formulate strategies to maximize their economic benefits.

[0042] Regarding the factors of income, P2P virtual power plant operator Revenue from electricity trading between producers and consumers is the main source of income for operators from their core business—P2P electricity sharing services—through electricity trading prices within the P2P virtual power plant operator's platform. P2P virtual power plant operator Electricity traded with producers and consumers within the platform It is calculated by multiplying the products. P2P virtual power plant operator Revenue from selling electricity to the grid: When there is an imbalance between power supply and demand within the P2P virtual power plant, the operator can sell excess electricity to the main grid. This revenue is generated through the grid connection price. P2P Virtual Power Plant Electricity sold to the grid It is calculated by multiplying the products. P2P virtual power plant operator Revenue from selling carbon is generated through carbon emission pricing. With P2P virtual power plant operators carbon emission reduction The product of these factors is used to calculate energy efficiency, which incentivizes operators to promote clean energy and energy conservation and emission reduction.

[0043] Regarding cost factors, P2P virtual power plant operator The cost of purchasing electricity from the grid: When the internal power supply of a P2P virtual power plant is insufficient, the operator needs to purchase electricity from the main power grid. This cost is determined by the grid purchase price. With P2P virtual power plant operators Purchase electricity from the power grid It is calculated by multiplying the products. P2P virtual power plant operator k The power generation operation and maintenance cost, measured by the operation and maintenance cost per unit of power generation. With P2P virtual power plant operators During the period t Electricity generation It is calculated by multiplying the products. P2P virtual power plant operator The total cost of providing services to the buyer, expressed as the buyer's unit service cost. Platforms that join P2P virtual power plant operators k Number of buyers It is calculated by multiplying the products. P2P virtual power plant operator The total cost of providing services to the seller, expressed as the seller's unit service cost. Platforms that join P2P virtual power plant operators k Number of sellers It is calculated by multiplying the products.

[0044] In some possible embodiments, P2P virtual power plant operators employ a nonlinear tiered two-part pricing strategy, and the second-order profit function relating to their profit changes is expressed as: .

[0045] in, ,in, Indicates buyer The two-part fee paid during time period t P2P virtual power plant operator During the period t To the buyer The basic service fee charged is based on the buyer's expected transaction volume. The gradation is set as a step function. Indicates buyer During the period t Transaction service fee, For the buyer During the period t Number of transactions P2P virtual power plant operator During the period t To the buyer A single transaction fee is charged. Meanwhile... Indicates the seller During the period t The two-part payment fee, P2P virtual power plant operator During the period t To the seller The basic service fee charged, Indicates the seller Transaction service fees during the time period, For the seller During the period t Number of transactions P2P virtual power plant operator During the period t To the seller The fee charged per transaction.

[0046] This non-linear tiered two-part pricing strategy combines fixed and variable fees to optimize operator revenue through differentiated pricing. "Non-linear tiered" means that fixed fees vary in tiers based on pre-set conditions (such as expected transaction volume), while variable fees may also exhibit non-linear characteristics, such as a decreasing marginal rate as transaction volume increases. This strategy provides operators with more flexible and refined pricing tools to adapt to the needs and behavioral patterns of different types of prosumers, thereby maximizing platform revenue and enhancing market competitiveness.

[0047] Second-order profit function Clearly define the benefits to be gained from the two-part pricing strategy (including payments made by the buyer). and the seller paid Incorporate into P2P virtual power plant operators During the period t Original profit In this study, by updating the operator's profit optimization objective, the optimization algorithm can comprehensively consider the revenue from basic electricity trading and the revenue from two-part service fees, thereby seeking the optimal pricing scheme in the game process to maximize the operator's overall profit.

[0048] buyer During the period t Two-part payment The fee consists of two parts: one is based on the buyer's expected transaction volume. Fixed basic service fee charged Secondly, based on the actual number of transactions by the buyer. and single transaction volume Transaction service fees collected This design aims to lock in the buyer's expected transaction commitment through a fixed fee, while using variable fees to reflect their actual activity and resource consumption on the platform, ensuring that operators can obtain reasonable returns from different dimensions of buyer participation.

[0049] Basic service fee It is a P2P virtual power plant operator To the buyer The fixed fee charged is based on the buyer's... Expected trading volume The tiered system uses a tiered function. This means the platform will divide buyers into different tiers based on their estimated electricity demand or transaction volume, and set different base service fees for each tier. For example, buyers with larger expected transaction volumes may need to pay higher or lower base service fees to incentivize their long-term activity and transaction commitment on the platform.

[0050] Transaction service fee It is a P2P virtual power plant operator To the buyer The variable fee charged is related to the buyer. During the period t actual number of transactions and single transaction fees Related. Single transaction fee According to the buyer Actual transaction volume Calculations can be performed, for example, by designing the system so that the larger the transaction volume, the lower the fee per transaction, thus encouraging large-volume transactions. This design ensures that the operator's revenue is closely linked to the buyer's actual transaction behavior, embodying the "pay-as-you-go" principle, and effectively covering the platform's operating costs incurred in processing actual transactions.

[0051] Seller During the period t Two-part payment Similar to the buyer, the seller also needs to pay a two-part fee. This includes fees based on the seller's expected transaction volume. Fixed basic service fee charged and based on the actual number of transactions by the seller and single transaction volume Transaction service fees collected This design aims to incentivize sellers to provide a stable power supply commitment and charge them a fee based on their actual electricity sales activity on the platform, thereby balancing the operator's revenue with the seller's participation costs.

[0052] Basic service fee It is a P2P virtual power plant operator To the seller The fixed fee charged is based on the seller's... Expected trading volume The tiered pricing structure is a step-by-step function. This means the platform will divide sellers into different tiers based on their estimated power generation or supply capacity, and set different base service fees for each tier. This tiered pricing method helps operators estimate and manage the potential contributions of sellers and provides sellers with clear cost expectations.

[0053] Transaction service fee It is a P2P virtual power plant operator To the seller The variable fee charged is related to the seller. During the period t actual number of transactions and single transaction fees Related. Single transaction fee. According to the seller jActual transaction volume The calculations are performed. This design ensures that the operator's revenue is closely linked to the seller's actual power supply activity, effectively covering the platform's operating costs incurred in matching and settling actual transactions, and encouraging sellers to actively participate in power sharing.

[0054] By introducing a non-linear, tiered, two-part pricing strategy, P2P virtual power plant operators can manage their revenue streams more precisely. The base service fee is tiered based on the expected transaction volume of producers and consumers, providing operators with a stable income guarantee and effectively incentivizing producers and consumers to commit to platform transaction volume. Simultaneously, the transaction service fee is dynamically charged based on actual transaction volume and frequency, ensuring that fees are closely linked to the platform's actual service volume and operating costs, thus achieving a better match between revenue and costs. This differentiated and flexible pricing mechanism effectively attracts producers and consumers of different sizes and trading habits, increasing their participation and expanding the platform's transaction scale, ultimately significantly enhancing the profitability and market competitiveness of P2P virtual power plant operators.

[0055] In some possible embodiments, a tiered function is proposed to set the base service fee according to the buyer's expected transaction volume, specifically in the form of: ; in, P2P virtual power plant operator For the buyer Tier 1 basic service fee, P2P virtual power plant operator For the buyer Tier 2 basic service fee, For P2P virtual power plant operators to sellers The threshold for the basic service fee tiers.

[0056] Specifically, the base service fee is set as a tiered function based on the buyer's expected transaction volume, aiming to cater to different levels of buyer expectations. Expected trading volume This involves dividing transactions into different categories or "tiers," and setting a fixed base service fee for each tier. This approach effectively differentiates buyers of varying transaction sizes, enabling differentiated pricing and avoiding the unfairness or inefficiency that a "one-size-fits-all" fee model might cause. As a P2P virtual power plant operator For the buyer The first tier of basic service fees is for buyers with smaller expected transaction volumes. The fixed fee set. It represents the P2P virtual power plant operator. This refers to the cost compensation and profit charged to these buyers for providing basic services such as platform access and information matching. The specific figure can be determined based on factors such as market research, operating costs, and competitive strategies, with the aim of attracting and serving buyers who are new to or engage in low-frequency transactions. As a P2P virtual power plant operator For the buyer The second tier of basic service fees is for buyers with a larger expected transaction volume. The fixed fee is set. Compared to Tier 1, this fee can be set according to the operator's strategy of reducing unit service costs through economies of scale or obtaining higher profits through high transaction volumes. For example, a higher base service fee can be set to cover the cost of providing higher-level services (such as faster response times and more stable transaction guarantees) to buyers with large transaction volumes, or a lower base service fee can be set to encourage long-term cooperation with large clients. As a P2P virtual power plant operator, the buyer The base service fee tier threshold is a key parameter that defines the buyer's expected transaction volume. The critical point for switching from Tier 1 to Tier 2. P2P virtual power plant operator. This threshold can be determined based on historical data, market analysis, and user behavior prediction to ensure the rationality of the tier divisions and that the buyer groups at different tiers have relatively consistent characteristics, thus enabling the tiered pricing strategy to function effectively. For example, it can be set as a multiple of a certain average transaction volume or dynamically adjusted based on user activity. This piecewise function form clearly defines the calculation rules for the basic service fee: when the buyer... Expected trading volume From 0 Between (including) When applicable, the first tier of basic service fee applies. When the expected trading volume Exceed At that time, the second tier of basic service fee will apply. These clear rules make the charging process transparent, making it easier for buyers to understand and choose, and also facilitating automated management and billing by operators.

[0057] In some possible implementations, a single transaction fee is proposed. According to the buyer Actual trading volume Set as a piecewise continuous function, specifically in the form of: .

[0058] in, P2P virtual power plant operator For the buyer The first tier of the benchmark rate function, P2P virtual power plant operator For the buyer The second tier of the benchmark rate function, and These are the attenuation coefficients for level 1 and level 2, respectively. and P2P virtual power plant operators For the buyer The minimum transaction fees for Tier 1 and Tier 2, Platform for P2P virtual power plant operators For the buyer The threshold values ​​for the first and second tiers of transaction service fees.

[0059] Among them, single transaction fee According to the buyer Actual trading volume Setting it to a piecewise continuous function aims to allow transaction costs to be more precisely matched to the buyer. The actual electricity demand and transaction volume can be used to achieve more reasonable cost allocation and more effective market incentives. This can be achieved by pre-setting different transaction volume ranges (e.g., 0 < 10 ... ≤ and ≤ This is achieved by defining different rate calculation formulas for each interval. These formulas are designed to be continuous to avoid exceeding the tier threshold. The cost changes at certain points, thus ensuring a smooth transition of costs.

[0060] P2P virtual power plant operator For the buyer The first tier of benchmark rate function, P2P virtual power plant operator For the buyer The second tier of benchmark fee rate functions forms the basis for calculating single transaction fees. By setting different benchmark fee rate functions corresponding to different transaction volume tiers, P2P virtual power plant operators... Different fee structures can be set for different transaction volumes. For example, a higher base fee rate can be set for small transaction volumes to cover fixed operating costs, while a lower base fee rate can be set for large transaction volumes to encourage large-scale trading. These functions can be linear functions, exponential functions, or other forms of mathematical expressions, and their parameters can be set based on market research, operating cost analysis, and the desired market incentive effect.

[0061] and These are the decay coefficients for Tier 1 and Tier 2, respectively, which introduce the characteristic that transaction costs decrease as the actual transaction volume increases. This means that as the buyer... Actual transaction volume As the volume of transactions increases, the cost per unit decreases, creating a "small profit, quick turnover" incentive mechanism that encourages buyers. Engage in more electricity trading. The decay factor is typically positive, and its magnitude determines the rate at which costs decrease. A larger decay factor leads to a faster decrease in costs and a stronger incentive for large transactions. These factors can be optimized through historical data analysis, market strategy simulation, and other methods.

[0062] and P2P virtual power plant operators For the buyer The first and second tiers of minimum transaction fees set the minimum transaction fees for the buyer at a specific tier. The fee for a single transaction will not fall below a certain lower limit. This ensures that even when the actual transaction volume is very large, causing the exponential decay term to approach zero, the P2P virtual power plant operator... This also allows them to recover some of the basic service costs and avoid losses. These minimum fees can be determined based on the P2P virtual power plant operator. The fixed operating costs, platform maintenance costs, and other factors are calculated and set.

[0063] Platform for P2P virtual power plant operators For the buyer The threshold values ​​for the first and second tiers of transaction service fees are key parameters for differentiating between fee tiers. When the buyer... Actual transaction volume When this threshold is exceeded, the single transaction fee will switch from the first tier calculation method to the second tier calculation method. This allows P2P virtual power plant operators... It can apply different fee structures based on significant differences in transaction size. Threshold The setting needs to take into account market demand, operator cost structure, competitors' pricing strategies, and expected market segmentation effects.

[0064] In some possible embodiments, a basic service fee is proposed based on the seller. Expected trading volume The tiering is set as a step function, specifically in the following form: .

[0065] in, P2P virtual power plant operator For the seller Tier 1 basic service fee, P2P virtual power plant operator For the seller Tier 2 basic service fee, For P2P virtual power plant operators to sellers The threshold for the basic service fee tiers.

[0066] In this scheme, P2P virtual power plant operators For the seller Basic service fee The collection method is no longer a single fixed value, but rather based on the seller's... Expected trading volume A tiered system is implemented. This tiered function design aims to achieve differentiated management and incentives for sellers of different sizes. Specifically, when a seller... Expected trading volume From 0 to In between, P2P virtual power plant operators A basic service fee of tier 1 will be charged. This tier typically targets sellers with smaller expected trading volumes, and its fees can be set relatively low to lower the initial barrier for sellers to participate in the platform, attracting more small or first-time sellers. When sellers Expected trading volume Exceed At that time, P2P virtual power plant operators A second-tier basic service fee will be charged. This tier is typically for sellers with high expected trading volume. While its fees may be higher in absolute terms than tier 1, it may reflect value and incentives for high-volume sellers by offering better service, lower unit transaction costs, or more flexible trading permissions. Tier Threshold It is a key parameter for different pricing tiers, and its value can be determined based on the P2P virtual power plant operator. The pricing mechanism is flexibly set based on factors such as market strategy, operating costs, target user groups, and historical transaction data to ensure its rationality and effectiveness.

[0067] In some possible embodiments, it is proposed that the single transaction fee be set as a piecewise continuous function based on the seller's actual transaction volume, specifically in the form of: .

[0068] in, P2P virtual power plant operator For the seller The first tier of the benchmark rate function, P2P virtual power plant operator For the seller The second tier of the benchmark rate function, P2P virtual power plant operator For the seller The third tier of the benchmark rate function, 、 and These are the attenuation coefficients for levels 1, 2, and 3, respectively. , and These are the minimum transaction fees for tier 1, tier 2, and tier 3, respectively. and These are platforms for P2P virtual power plant operators. For the seller The threshold values ​​for transaction service fees at the first and second tiers, and the second and third tiers.

[0069] Specifically, the cost of a single transaction is set as a piecewise continuous function based on the seller's actual transaction volume, meaning that the seller... On the platform of P2P virtual power plant operators The cost of each electricity transaction is no longer a fixed value or a simple tiered value, but rather varies depending on the time period. t Actual transaction volume The fee function is dynamically calculated, and while it uses different mathematical expressions across different trading volume ranges, it maintains overall continuity. This design aims to more precisely reflect the service cost and value under varying trading volumes, avoiding drastic fee jumps due to small changes in trading volume, thereby improving the rationality and stability of pricing. This can be achieved by pre-setting multiple trading volume ranges (e.g., 0 to...) in the pricing module. , arrive and greater than This is achieved by defining a specific rate calculation formula for each interval. When receiving a seller's... Actual transaction volume When processing data, the system... Choose the appropriate formula to calculate the interval.

[0070] , and As a P2P virtual power plant operator For the seller The first, second, and third tier base fee rate functions represent the basic calculation of single-transaction fees within different trading volume ranges. These functions can be constants, linear functions, or more complex non-linear functions, used to set the basic fee level for that tier of trading volume. For example, It can be a higher rate, suitable for small transactions, to cover fixed operating costs; and The rates can be gradually reduced to reflect economies of scale. These functions can be pre-stored in the pricing system's database as part of the pricing strategy, and adjusted during actual calculation based on the seller's... Actual transaction volume Call the corresponding function to perform the calculation.

[0071] , and These are the decay coefficients for Tier 1, Tier 2, and Tier 3, used to introduce an exponential decay effect, causing the cost of a single transaction to decrease non-linearly as the actual transaction volume increases. This design can more flexibly simulate economic phenomena of diminishing marginal costs or diminishing marginal revenues, encouraging sellers to engage in larger-scale transactions, because the larger the transaction volume, the more significant the decrease in cost per unit of transaction. These decay coefficients are preset parameters that can be adjusted according to the P2P virtual power plant operator. The operational strategy, market competition, and incentive targets for seller trading behavior are adjusted accordingly. In the calculation process, these are used as parameters of the exponential function, and are correlated with actual trading volume. The degree of cost attenuation is determined jointly.

[0072] , and The minimum transaction fees for Tier 1, Tier 2, and Tier 3 are minimum fees set for each transaction volume tier. Even with exponential decay, the fee for a single transaction will not fall below these preset minimums. This ensures the safety of P2P virtual power plant operators. This ensures that the minimum fixed costs of providing the services are covered, and a certain level of profitability is maintained, especially when transaction volume is very high, leading to a significant attenuation effect. These minimum fee values ​​are also preset parameters stored in the pricing system and are calculated... After the exponentially decaying part, it is compared with the corresponding The values ​​are added together to get the final single transaction fee.

[0073] and These are platforms for P2P virtual power plant operators. For the seller The thresholds for the first and second tiers of transaction service fees, and the second and third tiers, define the seller's actual transaction volume. The boundaries of the respective fee tiers. These are the key points for differentiating P2P virtual power plant operators. Able to be based on the seller The actual transaction volume is used to determine the appropriate benchmark rate function, decay factor, and minimum transaction fee combination. These thresholds are preset by the system and are used to determine the transaction volume when a seller's transaction is received. Actual transaction volume Then, determine which cost calculation formula should be used. For example, if 0 < ≤ If so, then the formula for level 1 is used; if < ≤ If so, then the formula for level 2 is used; if > If the threshold is not met, then the formula for level 3 will be used. These thresholds can be dynamically adjusted based on market research, operating cost analysis, and incentive objectives.

[0074] In some possible embodiments, the buyer is proposed to be in the time period t Number of transactions By joining the P2P virtual power plant operator platform Number of sellers Actual electricity trading volume Together with the marginal transaction frequency coefficient γ, it is determined, specifically as follows: .

[0075] Among them, the buyer during the period t Number of transactions Aiming to quantify buyers During a specific period t Platforms built within P2P virtual power plant operators The frequency of transactions conducted on the platform. Its function is to serve as a key input parameter for calculating the buyer's transaction service fee, directly affecting the fees the buyer needs to pay. In practice, this frequency is not simply counted, but dynamically estimated through a comprehensive model to more comprehensively reflect the buyer's transaction activity. Joining the P2P virtual power plant operator platform. Number of sellers This indicates the platform of a P2P virtual power plant operator. The total number of registered and active sellers on the platform. Its function is to reflect the platform's... The depth and liquidity of the supply-side market. Generally, the more sellers on the platform, the more trading partners and opportunities buyers have to choose from, potentially leading to more transactions. This number can be counted and updated in real time by the platform. Actual electricity trading volume. Buyer During a specific period t The total volume of electricity transactions actually completed on the platform. Its function is to directly measure the actual electricity demand and transaction scale of buyers on the platform. A larger transaction volume usually indicates a higher level of utilization of the platform's services by buyers, and may also correspond to more transaction activities. This transaction volume is accurately recorded through the platform's internal metering and settlement system. The marginal transaction frequency coefficient γ is an adjustable scaling factor used to adjust the degree of influence of the number of sellers and the actual electricity transaction volume on the number of buyer transactions. Its function is to allow P2P virtual power plant operators to flexibly set the sensitivity of transaction frequency based on market characteristics, platform operation strategies, or historical data. For example, this coefficient can reflect the average number of independent transactions that will occur given a given number of sellers and transaction volume. This coefficient can be a preset constant or a parameter dynamically adjusted according to market conditions.

[0076] In some possible embodiments, the seller is proposed to be in the time period t Number of transactions By joining the P2P virtual power plant operator platform Number of buyers Seller Actual electricity trading volume Together with the marginal transaction frequency coefficient γ, it is determined, specifically as follows: .

[0077] Among them, the seller in the time period t Number of transactions Indicates the seller During a specific period t The total number of electricity trading events completed within the platform. In a two-part fee structure, the calculation of the transaction service fee depends on this number of transactions; therefore, its accuracy is crucial to ensuring fairness in fee collection. This number is a key indicator of seller activity on the P2P virtual power plant operator's platform.

[0078] Join the P2P virtual power plant operator platform Number of buyers Refers to the platform of P2P virtual power plant operators The total number of registered and active buyers on the platform. This number directly reflects the potential trading opportunities and market depth offered to sellers. A higher number of buyers generally indicates a greater likelihood and frequency of transactions for sellers. This number can be statistically analyzed and obtained in real-time through the platform's user management system.

[0079] Seller Actual electricity trading volume Seller During the periodt The total amount of electricity actually sold within the platform. This is one of the core indicators for measuring the seller's actual contribution and transaction activity. This transaction volume can be accurately measured through the platform's internal transaction record system and serves as an important input parameter for calculating the number of transactions.

[0080] The marginal transaction frequency coefficient γ is a preset proportional coefficient used to adjust the impact of the number of buyers and the actual electricity transaction volume of the seller on the number of transactions by the seller. This coefficient can be calibrated based on historical transaction data, platform operation strategies, or market characteristics to reflect the average number of transactions that can be facilitated by a unit of electricity transaction volume and a unit of buyers under specific market conditions. For example, this coefficient can be set based on factors such as platform transaction matching efficiency and average transaction size.

[0081] In some possible embodiments, the objective function and constraints for maximizing the prosumer's benefit factors and their utility in step S3 are proposed as follows: Based on the extended Hotelling model, a service quality perception factor and a dynamic trust factor are introduced, assuming two P2P virtual power plant operators' platforms... Located at opposite ends of the interval [0,1], producers and consumers are evenly distributed across the interval; for those located at position... Any buyer Its utility in joining P2P virtual power plant operators' platforms 1 and 2 .

[0082] in, Indicates producer-consumer The power efficiency function, For producers and consumers During the period t The value coefficient of electrical energy, As a preset constant, For producers and consumers During the period t The actual electricity consumption; Indicates buyer On the platform of P2P virtual power plant operators Net electricity revenue obtained from the source Platform for P2P virtual power plant operators For the buyer The operational efficiency coefficient; Indicates buyer Revenue from selling carbon, For the buyer Carbon emission reductions; and Indicates buyer The transportation costs of Platform 1 and Platform 2, both P2P virtual power plant operators, are added separately. For the buyer The unit transportation cost; Indicates buyer For P2P virtual power plant operators' platforms The perceived utility of service quality The sensitivity coefficient of producers and consumers to electricity trading service fees; Indicates buyer For P2P virtual power plant operators' platforms Trust utility For the buyer For P2P virtual power plant operators' platforms Trust coefficient.

[0083] Specifically, the Extended Hotelling Model is a spatial competition model used to describe the choice behavior of prosumers between two competing P2P virtual power plant (PVP) operators' platforms. In this model, the two P2P PVP operators' platforms... The consumers are assumed to be located at both ends of a linear market (e.g., the [0,1] interval), with producers and consumers evenly distributed across this interval. Consumers decide which platform to join based on their location and the "transportation costs" of choosing different platforms, thereby maximizing their utility. This model effectively characterizes the differentiated selection preferences of producers and consumers when faced with multiple platforms.

[0084] Perceived utility of service quality It is a measure of the buyer For P2P virtual power plant operators' platforms The subjective evaluation of service quality. This utility reflects the platform's performance in areas such as transaction efficiency, system stability, customer support response speed, and user interface friendliness. For example, a platform with a high transaction success rate and rapid response typically has a higher perceived service quality utility. This utility can be modeled as a function related to platform performance indicators, and the sensitivity coefficient η of prosumers to electricity trading service fees affects their perception of changes in service quality.

[0085] Trust utility This indicates the buyer. For P2P virtual power plant operators' platforms Trust level is a crucial psychological factor for consumers' long-term participation in platform transactions. It stems from the platform's historical performance, data transparency, security measures, and fulfillment of promises to users. For example, a platform with a good reputation, transparent information disclosure, and effective dispute resolution will have a higher trust utility. Trust utility can be expressed through a trust coefficient. To quantify this, the coefficient reflects the buyer's... For specific platforms The level of trust.

[0086] Producers and consumers Electricity efficiency function Quantified prosumers During the period t From actual electricity consumption The satisfaction or value gained from electricity consumption. This function typically exhibits the characteristic of diminishing marginal utility, meaning that as electricity consumption increases, the increase in utility from each additional unit of electricity gradually decreases. For producers and consumers During the period t The value factor of electricity reflects the importance of electricity to producers and consumers; This is a preset constant used to adjust the shape of the utility function.

[0087] buyer On the platform of P2P virtual power plant operators Net electricity revenue obtained from The buyer i Through the platform The actual economic benefits gained from trading electricity online. This typically includes the buyer's profit from purchasing electricity at below-market prices or on more favorable terms, and may be influenced by the platform of a P2P virtual power plant operator. For the buyer operational efficiency coefficient The coefficient reflects the platform's ability to facilitate transactions and reduce costs.

[0088] buyer Revenue from selling carbon The buyer The economic compensation gained through reducing carbon emissions. This typically occurs when the buyer adopts clean energy or reduces its demand for conventionally high-carbon-emission electricity through energy-saving measures. This benefit is shared by the buyer. carbon emission reduction This is directly related and reflects the incentive mechanism of green energy trading.

[0089] buyer The transportation costs of Platform 1 and Platform 2, respectively, are added to the P2P virtual power plant operator. and In the extended Hotelling model, "cost" does not refer to actual physical transportation costs, but rather to the broader costs or inconveniences incurred by prosumers when choosing different platforms. This may include platform switching costs, adaptation costs to new platform rules, or psychological costs arising from platform characteristics not aligning with their own preferences. These costs are typically associated with the buyer's... Unit transportation cost And its position in the market space.

[0090] In some possible embodiments, it is proposed that for a location Any seller The utility of joining Platform 1 and Platform 2 of the P2P virtual power plant operator is expressed as follows: .

[0091] in, Indicates the seller On the platform of P2P virtual power plant operators Net electricity revenue obtained from the source Platform for P2P virtual power plant operators For the seller The operational efficiency coefficient; Indicates the seller Revenue from selling carbon, For the seller Carbon emission reductions; and Indicates the seller The transportation costs of Platform 1 and Platform 2, both P2P virtual power plant operators, are added separately. For the seller The unit transportation cost; Indicates the seller For P2P virtual power plant operators' platforms The perceived utility of service quality; Indicates the seller For P2P virtual power plant operators' platforms Trust utility For the seller For P2P virtual power plant operators' platforms Trust coefficient.

[0092] Specifically, the seller The utility of joining Platform 1 and Platform 2 as P2P virtual power plant operators ( and () is a measure of the seller A comprehensive indicator of overall satisfaction or benefit gained from participating in P2P virtual power plant energy sharing services. It quantifies the seller's... The sum of economic benefits, service experience, and other non-economic factors obtainable across different platforms. (Seller) Based on the principle of maximizing their own utility, sellers will choose to join platforms of P2P virtual power plant operators that offer higher utility. On the platform of P2P virtual power plant operators Net electricity revenue obtained from Indicates the seller Through the platform of P2P virtual power plant operators The net amount of revenue from the sale of electricity, less related costs. This typically includes electricity sales revenue, platform subsidies, etc., and deducts generation costs, transaction fees, etc. Its calculation is subject to the platform of the P2P virtual power plant operator. For the seller operational efficiency coefficient The coefficient reflects the impact of the platform. The ability to facilitate seller transactions and reduce seller costs. A P2P virtual power plant operator platform. For the seller operational efficiency coefficient Platform for quantifying P2P virtual power plant operators For the seller The level of efficiency in providing services. A high operational efficiency coefficient. This may mean the platform Able to provide for the seller Offering lower transaction costs, more convenient transaction processes, or higher transaction success rates indirectly influences sellers. Net electricity revenue Seller Revenue from selling carbon Indicates the seller Carbon emission reductions achieved through their electricity production or trading activities The sellers then sell these carbon emission reductions in the carbon trading market, generating economic returns. This encourages sellers to adopt clean energy or energy-efficient methods, thereby gaining additional revenue. carbon emission reduction Seller During a specific period t Within the country, this refers to the total amount of carbon emissions reduced relative to a baseline emission level through its electricity generation or consumption behavior. For example, using renewable energy to generate electricity or optimizing electricity consumption through energy storage systems can generate carbon reductions. (Seller) The transportation costs of Platform 1 and Platform 2, respectively, are added to the P2P virtual power plant operator. and In the extended Hotelling model, it is an abstract concept that represents the seller. The costs incurred in "moving" from their current location (or preference) to the platform of a P2P virtual power plant operator. This may include, but is not limited to, platform switching costs, costs of learning to operate a new platform, the degree of deviation from the platform's geographical location or service characteristics, and inconveniences caused by platform differences. Seller Unit transportation cost This quantifies the unit cost of this "movement," and the parameter represents the seller's cost. When selecting a P2P virtual power plant operator's platform, this refers to the cost per "unit distance" or per "unit deviation." It reflects the seller's... Sensitivity to platform flexibility or platform differences. (Seller) For P2P virtual power plant operators' platforms Service quality perceived utility Reflects the seller For P2P virtual power plant operators' platforms The subjective evaluation and perception of the quality of services provided. Service quality may include the ease of transactions, platform stability, customer support responsiveness, information transparency, and settlement efficiency. A higher perceived service quality leads to greater utility. Increase sellers The seller's preference for this platform. For P2P virtual power plant operators' platforms Trust utility Indicates the seller For P2P virtual power plant operators' platforms The psychological or practical benefits derived from the level of trust. Trust utility. Subject to the seller For P2P virtual power plant operators' platforms Trust coefficient The impact of this coefficient on the seller For the platform Confidence in the reliability, fairness, data security, and performance capabilities of the entity. High trust utility. Helps reduce sellers This increases the seller's perception of transaction risks, thereby enhancing their willingness to choose the platform. For P2P virtual power plant operators' platforms Trust coefficient Used for quantitative selling For P2P virtual power plant operators' platforms The level of trust. Trust coefficient. Evaluations can be based on factors such as historical transaction data, platform reputation, user reviews, and regulatory compliance.

[0093] In some possible implementations, a method for solving the Nash equilibrium is proposed. This method first employs a two-stage game model to address the P2P virtual power plant operator... The two-way interaction between producers and consumers is described. A two-stage game model is a sequential game, typically involving a leader and one or more followers. In this application, P2P virtual power plant operators... As a leader, the first step is to formulate a service fee pricing strategy, while producers and consumers (including buyers)... and the seller Consumers, acting as followers, make platform selection decisions based on the operator's pricing strategy. This model effectively captures the order and mutual influence of decision-making between operators and consumers, thus more accurately reflecting market dynamics.

[0094] To ensure the rationality of the game and the active participation of producers and consumers, this application defines buyer participation constraints and seller participation constraints. Buyer Participation constraints: Its core lies in ensuring the buyer The net utility or benefit obtained from participating in the P2P virtual power plant operator's platform shall not be less than the retained utility if it did not participate; that is, the benefit from participation must be greater than or equal to the transaction service fee paid.

[0095] Similarly, the seller Participation constraints: Intended to guarantee the seller The net benefits gained from sharing electricity through the platform must be no less than the retained utility they would have received if they hadn't participated; that is, the benefits must be sufficient to cover the transaction service fees they pay. These constraints are the basis for ensuring that prosumers voluntarily join and remain active on the platform.

[0096] In addition, this application also defines transportation cost constraints: This constraint, within the extended Hotelling model framework, limits the reasonable range of "transportation costs" or switching costs faced by prosumers when choosing between platforms operated by different P2P virtual power plant operators. It ensures that the utility prosumers derive from a platform effectively offsets the "transportation costs" incurred due to factors such as geographical location and service preferences, while guaranteeing a minimum benefit threshold for participation and avoiding unreasonable pricing in extreme cases.

[0097] P2P virtual power plant operators, when certain conditions are met The system composed of producers and consumers achieves Nash equilibrium. These conditions include: for any non-optimal basic service cost... P2P virtual power plant operator At the optimal basic service fee And optimal platform selection strategy Profits ( , Not less than its non-optimal basic service fee And optimal platform selection strategy Profits ( This means that, without changing the prosumer selection strategy, operators cannot increase profits by unilaterally changing service fees. Furthermore, for any non-optimal platform selection strategy... Prosumers at the optimal basic service fee And optimal platform selection strategy The following effect Not less than its optimal basic service fee Non-optimal platform selection strategy The following effect This indicates that, with operator service fees remaining constant, prosumers cannot increase their utility by unilaterally changing their platform selection strategy. Specifically, and Representing any buyer among prosumers and consumers. and the seller The optimal basic service fee, and Representing any buyer among prosumers and consumers. and the seller The optimal platform selection strategy. These conditions together constitute the rigorous definition of Nash equilibrium, ensuring the stability of the game outcome and the optimality of the decisions made by each party.

[0098] In some possible implementations, a method using backward induction to solve the two-stage game is proposed. Specifically, this method uses P2P virtual power plant operators as an example. The process is led by a single entity: first, a basic service fee and a transaction service fee are determined; then, producers and consumers choose to join either Platform 1 or Platform 2 of the P2P virtual power plant operator based on these service fees. This is achieved through the actions of buyers among the producers and consumers. and the seller Maximizing utility leads to the optimal platform selection strategy for P2P virtual power plant operators. Subsequently, the P2P virtual power plant operator... The platform selects a strategy and then maximizes its own profits to obtain the optimal service fee.

[0099] Backward induction is a common method for finding subgame perfect Nash equilibria in dynamic games. Its core idea is to start analyzing from the last stage of the game, determine the optimal strategies of the participants in that stage, and then use these optimal strategies as known conditions to backtrack to the previous stage, and so on, until the beginning of the game. In this method, this means first analyzing the optimal platform selection behavior of prosumers under a given service fee, and then the P2P virtual power plant operator formulates its own optimal service fee strategy based on predictions of prosumer behavior. This method ensures that the obtained equilibrium is stable because each participant makes an optimal response at each stage.

[0100] In the second phase of the game, when P2P virtual power plant operators... k Once the service fee has been determined, each producer and consumer (including the buyer) Seller j) will evaluate the utility of joining different platforms. Prosumers will choose the platform that maximizes their own utility. The utility function comprehensively considers multiple dimensions such as electricity utility, net electricity revenue, carbon sales revenue, transportation costs, perceived service quality utility, and trust utility. By comparing the utility values ​​of joining different platforms, prosumers can make optimal platform selection decisions. In the first stage of the game, P2P virtual power plant operators... When setting service fees, operators will fully consider how prosumers will choose a platform based on these fees in the second phase. The operator's goal is to predict prosumer responses and adjust its service fees accordingly to maximize profits. This requires operators to have accurate modeling and predictive capabilities regarding prosumer behavior patterns.

[0101] Based on the condition that marginal prosumers and consumers have equal utility, the buyer can be obtained. and the seller The equilibrium position. A marginal prosumer is a prosumer whose utility is exactly equal to that of joining either of two competing P2P virtual power plant operators' platforms. By allowing the buyer... Joining Platform 1 and Platform 2 has equal utility, and the seller... By assuming that the utilities of Platform 1 and Platform 2 are equal, we can deduce the positions of these marginal prosumers in the Hotelling model space. and These locations are key points in determining market segmentation, and their calculation formula considers factors such as differences in service fees across different platforms, the value of electricity for prosumers, transportation costs, perceived utility of service quality, and trust utility. Since prosumers are uniformly distributed in the interval [0,1] and satisfy... , The market share of each platform is determined by the position of the marginal prosumer. Therefore, once the marginal prosumer (e.g., the buyer) is identified... ) position All located between 0 and The buyer will choose platform 1, while all those located in Buyers between platform 1 and platform 2 will choose platform 2. Thus, platform 1's market share... It is equal to Platform 2's market share Then it is 1− For the seller market share and The method of determining the buyer is similar to that of the seller.

[0102] When determining the optimal basic service fee, P2P virtual power plant operators The Hessian matrix corresponding to the second derivative of the profit function has all negative diagonal elements and all zero off-diagonal elements; the matrix is ​​negative definite. When the first derivative is zero, the P2P virtual power plant operator... The profit function has a maximum value. This is a standard condition used in mathematical optimization to determine the maximum value of a function. When P2P virtual power plant operators... By taking the first derivative of the profit function with respect to the service fee and setting it to zero, we can find a stationary point of profit. If, at this stationary point, the Hessian matrix of the profit function (composed of second-order partial derivatives) is negative definite, then this stationary point is a local maximum of the profit function. By solving these conditions, we can obtain the profit target for the buyer. and the seller Optimal basic service fee and Considering that in practical applications, P2P virtual power plant operators typically employ tiered pricing strategies rather than customizing service fees for each individual prosumer, after calculating the potential optimal basic service fee for each prosumer, it is necessary to average the optimal basic service fees for prosumers belonging to the same tier based on preset pricing tiers (e.g., tiers 1 and 2 for buyers, and tiers 1 and 2 for sellers). This yields a uniform optimal basic service fee for that tier, simplifying the pricing structure while still reflecting the overall optimization results. For example, for buyers, It is the first tier of buyer's optimal basic service fee, calculated for all buyers belonging to set B1 (i.e., those with expected transaction volume between 0 and 100%). The buyer between the buyers) of The average value is obtained.

[0103] In this embodiment, the principle of backward induction is used to solve the two-stage game model: P2P virtual power plant operator kThe platform primarily determines the basic service fee and transaction service fee, and then producers and consumers choose to join either Platform 1 or Platform 2 of the P2P virtual power plant operator based on the service fee. k The optimal service fee is obtained by selecting a strategy based on the corresponding platform while maximizing one's own profits. Based on the condition of equal marginal prosumer utility, the buyer is obtained. and the seller The equilibrium positions are as follows: (twenty two) (twenty three) Since prosumers are uniformly distributed in the interval [0,1] and satisfy... , Therefore, the market share of each platform is determined by the position of the marginal prosumer, and the equilibrium market share of each P2P virtual power plant operator's platform can be obtained as follows: , (twenty four) , (25) In order to obtain the optimal basic service fee and the optimal transaction service fee, P2P virtual power plant operators k The first-order profit function can be maximized after evaluating the selection of a prosumer platform; P2P virtual power plant operator k The first and second derivatives of the profit function are as follows: (26) (27) , (28) because , , P2P virtual power plant operator The Hessian matrix corresponding to the second derivative of the profit function has all negative diagonal elements and all zero off-diagonal elements; therefore, the matrix is ​​negative definite. When , At that time, P2P virtual power plant operators The profit function has a maximum value. (From...) , The optimal basic service fee can be obtained as follows: (29) (30) in, and For any buyer and the seller The optimal basic service fee; Furthermore, since the basic service fees of P2P virtual power plant operators are divided into two tiers based on the expected transaction volume of both producers and consumers, the average of the potential optimal basic service fees for buyers and sellers within each tier is used to obtain the optimal basic fees for buyers and sellers in each tier, as follows: For the buyer: For the seller: in, and Buyers respectively The optimal basic service fees for Tier 1 and Tier 2, Indicated as a buyer belonging to Tier 1 gather, Indicated as a buyer belonging to Tier 2 gather; and Sellers The optimal basic service fees for Tier 1 and Tier 2, Indicated as a seller belonging to Tier 1 gather, Indicated as a seller belonging to Tier 2 gather.

[0104] Considering the diversity of prosumers in the actual operation of P2P virtual power plants, they can be divided into buyers and sellers based on the volume of electricity transactions. With a fixed basic service fee and transaction service fee, prosumers choose which P2P virtual power plant operator's platform to join to maximize their own utility, thus arriving at the optimal platform selection strategy for prosumers. ; ; in, and Buyers respectively and the seller The optimal platform selection strategy for P2P virtual power plant operators.

[0105] like Figure 2 As shown, this application proposes a pricing device for P2P virtual power plant energy sharing service fees based on a two-stage game theory approach. This pricing device is used to implement the aforementioned pricing method for P2P virtual power plant energy sharing service fees based on a two-stage game theory approach. The device includes a hierarchical collaborative communication architecture establishment module, a nonlinear tiered two-part pricing strategy determination module, a producer-consumer platform selection preference adjustment module, a Nash equilibrium judgment module, and a pricing scheme output module.

[0106] The layered collaborative communication architecture module is responsible for building and managing the information exchange foundation required for the P2P virtual power plant (P2P) electricity sharing service fee pricing method. This module not only defines the communication layers between different entities (such as the main power grid, the P2P P2P virtual power plant operator's platform, and prosumers within the platform), but also clarifies the constraints on information transmission, such as latency requirements. Its role is to provide accurate and real-time input data for subsequent pricing calculations and ensure that pricing results can be effectively communicated and executed. This module can establish data exchange channels between different layers by configuring network communication protocols and data interfaces; utilize distributed databases or message queue services to manage and synchronize information at each layer; and meet information exchange and latency constraints by setting communication priorities and bandwidth allocation strategies.

[0107] The core function of the nonlinear tiered two-part fee strategy determination module is to calculate and determine the base service fee and transaction service fee for each tier for both buyers and sellers based on a preset nonlinear tiered two-part fee strategy. This involves tiering expected and actual transaction volumes and applying corresponding fee rate functions. The module's role is to model complex fee strategies and calculate specific costs, providing clear economic signals for prosumers' decision-making. Its implementation can include: using a built-in or invoked mathematical model library to calculate the base service fee and transaction service fee based on input parameters (such as expected transaction volume, actual transaction volume, tier thresholds, attenuation coefficients, etc.); and using a lookup table method or a piecewise function calculator to determine the fee rates using tiered and piecewise continuous functions.

[0108] The prosumer platform selection preference adjustment module, based on the extended Hotelling model, dynamically adjusts prosumers' platform selection preferences for P2P virtual power plant operators. This module introduces factors such as perceived service quality utility and trust utility to more comprehensively characterize the multidimensional heterogeneous preferences of prosumers. Its role is to simulate prosumers' selection behavior across different platforms, providing crucial feedback information for solving the game theory model. This module can implement the mathematical calculation logic of the Hotelling model, calculating the utility value of joining different platforms based on parameters such as the prosumer's location, the service quality provided by the platform, the trust coefficient, and various service fees; or, through machine learning algorithms, dynamically adjust the perceived service quality factor and trust factor based on historical data and real-time feedback to more accurately reflect changes in prosumers' preferences.

[0109] The Nash equilibrium judgment module is responsible for determining whether the two-stage game system composed of P2P virtual power plant operators and prosumers has reached a Nash equilibrium state. If not, it triggers an iterative optimization process. This module ensures the stability and optimality of the pricing scheme, preventing the system from operating in a non-equilibrium state. Its implementation may include: embedding mathematical conditions for Nash equilibrium, such as verifying whether the conditions for maximizing operator profits and maximizing prosumer utility are simultaneously satisfied; determining equilibrium by comparing the convergence of continuous iteration results, for example, considering equilibrium reached when the change in pricing scheme or platform selection strategy between two iterations is less than a preset threshold; if equilibrium has not been reached, sending an instruction to the nonlinear tiered two-part pricing strategy determination module to initiate a new round of pricing calculation.

[0110] The pricing scheme output module outputs the final pricing scheme determined by Nash equilibrium. This module presents the calculated optimal pricing result to users or downstream systems for practical application. Its implementation can include: outputting the optimal basic service fee, optimal transaction service fee, and the optimal platform selection strategy for prosumers in a structured data format; displaying the pricing result through a user interface; storing the result in a database for subsequent analysis or decision-making; or providing the pricing scheme to other systems for execution via an API interface.

[0111] This application proposes a specific structure for establishing a hierarchical collaborative communication architecture module, which includes a large power grid-platform layer communication unit, an inter-platform layer communication unit, and an internal platform layer communication unit.

[0112] The large power grid-platform layer communication unit aims to facilitate information exchange between the large power grid and the P2P virtual power plant operator's platform. This communication unit can be implemented using various technologies, such as deploying communication interfaces and protocol converters compliant with power industry communication standards (e.g., IEC 61850, Modbus TCP / IP), ensuring seamless integration between the P2P virtual power plant operator's platform and the large power grid's dispatching and market trading systems. Specifically, it can receive real-time electricity prices, load forecast data, grid operating status information, and dispatching instructions from the large power grid, while simultaneously uploading aggregated power generation, load response capabilities, and transaction settlement data from the P2P virtual power plant to the large power grid. This bidirectional information flow provides the necessary data support for P2P virtual power plant operators when conducting electricity transactions with the large power grid.

[0113] The inter-platform communication unit is used to facilitate information exchange between competing P2P virtual power plant operators' platforms. Considering the competitive relationship between platforms, the implementation of this communication unit needs to balance the necessity of information sharing with the protection of trade secrets. One approach is to establish an interconnection mechanism based on secure API interfaces or encrypted communication protocols, allowing platforms to exchange partial market information under preset rules, such as aggregated available capacity, approximate pricing strategy ranges, or market share data. Alternatively, it is possible to explore using distributed ledger technology (such as blockchain) to build a decentralized information-sharing platform. This would promote limited information transparency between platforms while ensuring data immutability and traceability, thereby supporting platform-level strategy formulation and equilibrium analysis in two-stage game theory.

[0114] The platform's internal communication unit facilitates information exchange between the P2P virtual power plant operator's platform and the prosumers within the platform. This unit is a crucial link connecting the virtual power plant operator's platform with end users. Implementation can include deploying smart meters, smart home gateways, or energy management systems on the prosumer side and transmitting data with the P2P virtual power plant operator's platform via Internet of Things (IoT) communication technologies (such as Wi-Fi, Zigbee, NB-IoT, and LoRa). This unit is responsible for real-time collection of detailed data from prosumers, including electricity consumption, power generation, energy storage status, load type, and the prosumer's expected transaction volume. , and actual transaction volume , At the same time, it is also responsible for accurately and timely pushing information such as service fees, transaction matching results, demand response instructions, and carbon emission reduction benefits set by the P2P virtual power plant operator's platform to prosumers, so as to guide the behavior of prosumers and serve as an important input for prosumer utility calculation.

[0115] In some possible embodiments, a nonlinear tiered two-part fee strategy determination module is proposed, comprising: a buyer's basic service fee determination unit, a buyer's transaction service fee determination unit, a seller's basic service fee determination unit, and a seller's transaction service fee determination unit.

[0116] The Buyer Basic Service Fee Determination Unit is used to determine the Tier 1 and Tier 2 basic service fees in a tiered function format based on the buyer's expected transaction volume. This unit is responsible for determining the basic service fee payable by the buyer in the form of a tiered function, according to the buyer's expected transaction volume. Specifically, this unit divides the buyer's expected transaction volume into different tiers, such as Tier 1 and Tier 2, and sets a different basic service fee rate for each tier. This tiered mechanism reflects the potential scale of buyers' demand for platform services, enabling differentiated management for buyers of different sizes.

[0117] The buyer transaction service fee determination unit is used to determine the first and second tier transaction service fees in the form of a piecewise continuous function based on the buyer's actual transaction volume. This unit determines the single transaction fee based on the buyer's actual transaction volume, using a piecewise continuous function. For example, this unit can set the transaction service fee rates for the first and second tiers and introduce a decay coefficient and a minimum transaction fee, so that the transaction fee changes non-linearly with the increase in actual transaction volume. This design aims to encourage buyers to conduct larger-scale transactions while ensuring the reasonableness of platform revenue.

[0118] The seller's basic service fee determination unit is used to determine the first and second tiers of basic service fees in a tiered function form based on the seller's expected transaction volume. This unit is similar to the buyer's basic service fee determination unit, but is specifically designed for sellers. It determines the basic service fee payable by the seller, such as the first and second tiers, in a tiered function form based on the seller's expected transaction volume. This measure aims to incentivize sellers to actively participate in electricity sharing by tiering fees based on their potential supply capacity for platform services.

[0119] The seller's transaction service fee determination unit is used to determine the first, second, and third tiers of transaction service fees in the form of a piecewise continuous function based on the seller's actual transaction volume. This unit determines the single transaction fee for the seller based on their actual transaction volume, using a piecewise continuous function. Unlike the buyer's unit, this unit can set more tiers, such as tier 1, tier 2, and tier 3, and introduce corresponding attenuation coefficients and minimum transaction fees. This more granular tiering and non-linear charging mechanism can better adapt to the diverse electricity supply behaviors and scales of sellers, providing a more flexible charging scheme.

[0120] In some possible embodiments, a prosumer platform selection preference adjustment module is proposed, comprising: a buyer utility calculation unit, used to calculate the buyer's utility in joining Platform 1 and Platform 2 of the P2P virtual power plant operator based on an extended Hotelling model, the utility including electricity utility, net electricity revenue, carbon sales revenue, transportation costs, perceived service quality utility, and trust utility; a seller utility calculation unit, used to calculate the seller's utility in joining Platform 1 and Platform 2 of the P2P virtual power plant operator based on an extended Hotelling model, the utility including net electricity revenue, carbon sales revenue, transportation costs, perceived service quality utility, and trust utility; and a platform selection decision unit, used to determine the optimal platform selection strategy for prosumers based on buyer utility and seller utility.

[0121] Specifically, the buyer utility calculation unit is used to calculate the buyer's utility in joining Platform 1 and Platform 2 of the P2P virtual power plant operator, based on the extended Hotelling model. This unit receives data from the buyer. Electricity efficiency function ,buyer On the platform of P2P virtual power plant operators Net electricity revenue obtained from ,buyer Revenue from selling carbon ,buyer The transportation costs of Platform 1 and Platform 2, respectively, are added to the P2P virtual power plant operator. and ,buyer For P2P virtual power plant operators' platforms Service quality perceived utility and the buyer For P2P virtual power plant operators' platforms Trust utility Parameters such as these.

[0122] This unit is based on a preset utility function, for example: These utility components are then comprehensively calculated to arrive at the buyer's conclusion. The total utility values ​​of Platform 1 and Platform 2, which are joined by P2P virtual power plant operators.

[0123] The seller utility calculation unit is used to calculate the seller's utility in joining Platform 1 and Platform 2 of the P2P virtual power plant operator, based on the extended Hotelling model. This unit receives data from the seller. On the platform of P2P virtual power plant operators Net electricity revenue obtained from Seller Revenue from selling carbon Seller The transportation costs of Platform 1 and Platform 2, respectively, are added to the P2P virtual power plant operator. and Seller For P2P virtual power plant operators' platforms Service quality perceived utility and the seller For P2P virtual power plant operators' platforms Trust utility Parameters such as these.

[0124] This unit is based on a preset utility function, for example: These utility components are then comprehensively calculated to arrive at the seller's... The total utility values ​​of Platform 1 and Platform 2, which are joined by P2P virtual power plant operators.

[0125] The platform selection decision unit is used to determine the optimal platform selection strategy for prosumers based on the buyer and seller utilities calculated by the buyer utility calculation unit and the seller utility calculation unit. Specifically, for each buyer... The unit compares its total utility value on Platform 1 and Platform 2 of the P2P virtual power plant operator. and Choose the platform with greater utility value as the buyer. The optimal choice. Similarly, for each seller... The unit compares its total utility value on Platform 1 and Platform 2 of the P2P virtual power plant operator. and Choose a platform with greater utility value as the seller. The optimal choice is determined. This unit outputs the determined optimal platform selection strategy as its value for subsequent Nash equilibrium determination and iterative optimization.

[0126] In the pricing method for P2P virtual power plant energy sharing services based on two-stage game theory, determining whether the two-stage game system composed of P2P virtual power plant operators and prosumers has reached Nash equilibrium is crucial to ensuring the effectiveness and stability of the pricing scheme. However, in practical applications, the lack of comprehensive verification of the constraints of the game system and a precise mechanism for judging the equilibrium state may lead to the system failing to converge to the optimal solution during the iteration process, or even resulting in unstable pricing outcomes, thereby affecting the normal operation of P2P virtual power plants and the participation enthusiasm of prosumers.

[0127] To address this, this application proposes a Nash equilibrium judgment module for performing equilibrium judgment and iterative optimization control on the aforementioned two-stage game system. This module specifically includes: First, a participation constraint verification unit is set up, whose function is to verify whether the buyer's participation constraint and the seller's participation constraint are satisfied. Specifically, this unit evaluates the buyer's participation constraint. Participation constraints and the seller Participation constraints These constraints ensure that prosumers have sufficient incentive to participate in P2P virtual power plant energy-sharing services after considering the benefits they receive from the platform and the service fees they pay. Validating these constraints helps avoid generating unrealistic or unattractive pricing schemes for prosumers.

[0128] Secondly, this module also includes a transportation cost constraint verification unit, used to verify whether the transportation cost constraints are met. This unit checks... This condition, in the extended Hotelling model, means that transportation cost is an abstract concept that measures the "inconvenience" or "cost" incurred by prosumers when choosing different platforms. Verifying this constraint helps ensure the rationality of the model parameters, prevents extreme or unrealistic platform selection behaviors, and thus guarantees the effectiveness of the game theory model.

[0129] Furthermore, the equilibrium condition judgment unit is configured to determine whether the equilibrium conditions for P2P virtual power plant operators to maximize profits and for prosumers to maximize utility are met. This unit checks, according to the definition of Nash equilibrium, whether any P2P virtual power plant operators exist. or producers and consumers (Buyers or sellers) can gain higher profits or utility by unilaterally changing their strategies (such as operators changing service fees, or prosumers changing their platform choices). Specifically, it verifies... : and These two conditions apply. A system is considered to have reached Nash equilibrium only when all participants are unable to improve their situation by unilaterally changing their strategies.

[0130] Finally, the iterative optimization control unit is used to control the nonlinear tiered two-part pricing strategy determination module for iterative optimization when equilibrium has not been reached. When the equilibrium condition judgment unit finds that the system has not yet reached Nash equilibrium, the control unit issues an instruction to prompt the P2P virtual power plant operator to readjust its base service fees and transaction service fees for buyers and sellers. This iterative process continues until the game system satisfies all equilibrium conditions, thereby ensuring that the final output pricing scheme is stable and optimal.

[0131] In some possible embodiments, an electronic device is proposed, comprising one or more processors and a memory. The memory stores one or more programs that, when executed by one or more processors, cause the processors to implement the aforementioned pricing method for P2P virtual power plant energy sharing services based on a two-phase game.

[0132] Specifically, one or more processors are the core computing units of an electronic device, responsible for executing instructions and processing data. They can be central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), or other dedicated processing units. Processors perform various computational tasks and logical control by executing program instructions stored in memory. In implementing a pricing method, the processor is responsible for executing various steps within the method, including establishing a hierarchical collaborative communication architecture, determining the optimization objective function and constraints, determining a nonlinear tiered two-part pricing strategy, adjusting prosumers' platform preferences for P2P virtual power plant operators, determining whether the two-stage game system has reached Nash equilibrium, and outputting the final pricing scheme. It can be a single-core or multi-core processor to meet different computational complexity and real-time requirements. For example, large-scale P2P virtual power plants may require multi-core or distributed processors to accelerate the solution of complex game models.

[0133] Memory is a component in electronic devices used to store data and instructions. It can be random access memory (RAM), read-only memory (ROM), flash memory, hard disk drive (HDD), solid-state drive (SSD), etc. Memory stores the operating system, application programs (i.e., one or more programs), and temporary data and results generated during program execution. In implementing a pricing method, memory stores the algorithm code for the pricing method, the operating data of the P2P virtual power plant, transaction information of prosumers, game model parameters, and the final pricing scheme. The program can be compiled executable code or an interpreted script.

[0134] When one or more programs are executed by one or more processors, the aforementioned pricing method for P2P virtual power plant energy sharing services based on a two-stage game is implemented. This process ensures that complex pricing methods can be executed practically and automatically. The processor reads the program instructions for the pricing method from memory and performs calculations and control according to the instruction sequence. For example, the processor first executes the steps of establishing a hierarchical collaborative communication architecture and determining the objective function; then it executes the steps of determining the initial service fee and adjusting the preferences of prosumers and consumers; then it enters the iterative process of Nash equilibrium judgment until equilibrium is reached; finally, it executes the step of outputting the final pricing scheme. The entire process is controlled by the program, with the processor providing computing power and the memory providing storage space for data and instructions. This combination of hardware and software enables the efficient solution and iterative optimization of complex game models.

[0135] Implementing the aforementioned pricing method for P2P virtual power plant energy sharing services based on a two-stage game involves complex mathematical models, multi-stage iterative optimization, and extensive data processing. Relying entirely on manual calculations and decisions is not only inefficient and prone to errors, but also difficult to adapt to dynamic changes in grid operation and the market environment, thus affecting the real-time performance, accuracy, and effectiveness of the pricing scheme.

[0136] In response, this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned pricing method for P2P virtual power plant energy sharing services based on a two-phase game.

[0137] Specifically, a computer-readable storage medium is a non-transitory medium capable of storing data and computer programs, serving as a persistent storage medium for the P2P virtual power plant energy sharing service fee pricing method based on a two-stage game. This medium can be, but is not limited to, flash memory, hard disk drives, solid-state drives, optical discs (such as CD-ROMs and DVD-ROMs), magnetic tape, or any other non-volatile storage device capable of storing digital information. By storing the logic and instructions of the pricing method on such a medium, it can be ensured that the pricing method can be reliably read and executed by a processor when needed. A computer program is a collection of instructions written to implement a specific function. In this application, the computer program contains instructions for executing all steps of the aforementioned P2P virtual power plant energy sharing service fee pricing method based on a two-stage game. These instructions cover the entire process from establishing a hierarchical collaborative communication architecture, determining cost-benefit factors, constructing an optimization objective function, determining the basic service fee and transaction service fee based on a nonlinear tiered two-part charging strategy, adjusting the prosumer platform selection preferences based on an extended Hotelling model, determining the Nash equilibrium and performing iterative optimization, until outputting the final pricing scheme. The processor is the core computing unit of an electronic device, responsible for interpreting and executing instructions in a computer program. When a computer program is executed by one or more processors, the processor processes the input data according to the preset logical sequence in the program, performing various calculations, judgments, and control operations, thereby automatically completing each step of the pricing method described above. This enables complex pricing models to operate with high efficiency and precision, without human intervention, and can be dynamically adjusted based on real-time data.

[0138] By storing the aforementioned P2P virtual power plant (PVP) electricity sharing service fee pricing method based on a two-stage game theory on a computer-readable storage medium and executing it via a processor, the pricing method can be automated, efficient, and accurate. This implementation overcomes the inefficiency and error-proneness of manual operation, as well as the lack of flexibility and maintenance difficulties of pure hardware solutions. Specifically, the processor can quickly process large amounts of market data, producer-consumer behavior data, and grid operation data, performing complex game model calculations and iterative optimizations in real time, thereby deriving the optimal electricity sharing service fee pricing scheme and producer-consumer platform selection strategy in a short period of time. Furthermore, when market conditions, policies and regulations, or model parameters change, only the computer program needs to be updated to achieve rapid adjustment and optimization of the pricing strategy, greatly improving the adaptability and maintainability of the pricing method. This ensures that P2P PPV operators can continuously obtain maximum profits while maximizing the utility of producer-consumers, promoting the healthy development of the P2P PPV electricity sharing market.

[0139] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A pricing method for P2P virtual power plant energy sharing service fees based on two-stage game theory, characterized in that, The method includes: S1. Based on a nonlinear tiered two-part pricing strategy, an optimization objective function for P2P virtual power plant operators is constructed; the optimization objective function includes a first-order profit function based on the cost and revenue factors of P2P virtual power plant operators, and a second-order profit function based on profit changes. S2. Based on the first-order profit function and the second-order profit function, obtain the basic service fees and transaction service fees for each level for the buyer and the seller. S3. Based on the extended Hotelling model, adjust the preferences of producers and consumers for P2P virtual power plant operators according to the basic service fees of each level, the transaction service fees of each level, the expected transaction volume of producers and consumers, and the actual transaction volume. S4. Determine whether the two-stage game between the P2P virtual power plant operator and the producer-consumer has reached Nash equilibrium. If equilibrium has not been reached, return to step S2 to obtain the basic service fees and transaction service fees for the buyer and seller. If equilibrium has been reached, proceed to step S5. S5. Output the final pricing scheme; the final pricing scheme includes the optimal basic service fee and optimal transaction service fee for the buyer, the optimal basic service fee and optimal transaction service fee for each tier for the seller, and the optimal platform selection strategy for prosumers.

2. The pricing method for P2P virtual power plant energy sharing service fees based on two-stage game theory as described in claim 1, characterized in that, The first-order profit function is: (1) in, k =1, 2 represent two competing P2P virtual power plant operators; P2P virtual power plant operator k During the period t Profits; P2P virtual power plant operator k Revenue from electricity trading between producers and consumers, The price of electricity traded within the platform of a P2P virtual power plant operator. P2P virtual power plant k Electricity traded with producers and consumers within the platform; P2P virtual power plant operator k Revenue from selling electricity to the grid, For grid connection electricity price, P2P Virtual Power Plant k Electricity sold to the power grid; P2P virtual power plant operator k The cost of purchasing electricity from the grid, The purchase price of electricity from the grid. P2P virtual power plant operator k Purchase electricity from the power grid; P2P virtual power plant operator k Revenue from selling carbon, For carbon emission prices, P2P virtual power plant operator k Carbon emission reductions; P2P virtual power plant operator k The power generation and operation and maintenance costs, The cost of operation and maintenance per unit of electricity generated. P2P virtual power plant operator k During the period t The amount of electricity generated; P2P virtual power plant operator k The total cost of providing services to the buyer, Cost of service for the buyer To join the P2P virtual power plant operator platform k The number of buyers; P2P virtual power plant operator k The total cost of providing services to the seller Service cost for the seller To join the P2P virtual power plant operator platform k The number of sellers.

3. The pricing method for P2P virtual power plant energy sharing service fees based on two-stage game theory as described in claim 2, characterized in that, The second-order profit function is expressed as: (2) in, Indicates buyer During the period t The two-part payment fee, P2P virtual power plant operator k During the period t To the buyer The basic service fee charged; The basic service fee corresponding to the buyer is based on the buyer's expected transaction volume. The tiering is set as a step function, specifically in the following form: in, P2P virtual power plant operator k For the buyer Tier 1 basic service fee, P2P virtual power plant operator k For the buyer Tier 2 basic service fee, For P2P virtual power plant operators to buyers The threshold for the basic service fee tiers; and Indicates buyer During the period t Transaction service fee, For the buyer During the period t Number of transactions P2P virtual power plant operator k During the period t To the buyer The fee charged per transaction; The corresponding single transaction fee for the buyer is based on the actual transaction volume of the buyer. Set as a piecewise continuous function, specifically in the form of: in, P2P virtual power plant operator k For the buyer The first tier of the benchmark rate function, P2P virtual power plant operator k For the buyer The second tier of the benchmark rate function, and These are the attenuation coefficients for level 1 and level 2, respectively. and P2P virtual power plant operators k For the buyer The minimum transaction fees for Tier 1 and Tier 2, Platform for P2P virtual power plant operators k For the buyer The threshold values ​​for the first and second tiers of transaction service fees; Indicates the seller During the period t The two-part payment fee, P2P virtual power plant operator During the period t To the seller The basic service fee charged; The basic service fee corresponding to the seller is based on the seller's expected transaction volume. The tiering is set as a step function, specifically in the following form: in, P2P virtual power plant operator k For the seller Tier 1 basic service fee, P2P virtual power plant operator k For the seller Tier 2 basic service fee, For P2P virtual power plant operators to sellers The threshold for the basic service fee tiers; and Indicates the seller Transaction service fees during the time period, For the seller During the period t Number of transactions P2P virtual power plant operator k During the period t To the seller The fee charged per transaction.

4. The pricing method for P2P virtual power plant energy sharing service fees based on two-stage game theory as described in claim 3, characterized in that, The buyer's single transaction fee is based on the seller's actual transaction volume. Set as a piecewise continuous function (seller level 3), specifically in the following form: in, P2P virtual power plant operator k For the seller The first tier of the benchmark rate function, P2P virtual power plant operator k For the seller The second tier of the benchmark rate function, P2P virtual power plant operator k For the seller The third tier of the benchmark rate function, 、 and These are the attenuation coefficients for levels 1, 2, and 3, respectively. 、 and These are the minimum transaction fees for tier 1, tier 2, and tier 3, respectively. and These are platforms for P2P virtual power plant operators. k For the seller The threshold values ​​for transaction service fees at the first and second tiers, and the second and third tiers.

5. The pricing method for P2P virtual power plant energy sharing service fees based on two-stage game theory according to claim 4, characterized in that, buyer i During the period t The number of transactions is determined by the number of platforms that join the P2P virtual power plant operator. k The number of sellers, the actual electricity transaction volume, and the marginal transaction frequency coefficient are all factors that determine this, specifically as follows: (7) in, This is the marginal transaction frequency coefficient. To join the P2P virtual power plant operator platform k The number of sellers, For the buyer Actual electricity trading volume; The seller During the period t The number of transactions is determined by the number of platforms that join the P2P virtual power plant operator. k Number of buyers, number of sellers The cost difference and the marginal transaction frequency coefficient are jointly determined, specifically expressed as follows: (8) in, To join the P2P virtual power plant operator platform k Number of buyers For the seller The actual volume of electricity traded.

6. The pricing method for P2P virtual power plant energy sharing service fees based on two-stage game theory as described in claim 5, characterized in that, Step S3 includes: Based on the extended Hotelling model, this paper introduces a service quality perception factor and a dynamic trust factor, assuming two P2P virtual power plant operators' platforms. Located at opposite ends of the interval [0,1], producers and consumers are evenly distributed across the interval; for those located at position... For any buyer, the utility of joining Platform 1 and Platform 2 of different P2P virtual power plant operators is expressed as follows: (9) (10) in, Indicates producer-consumer The power efficiency function, For producers and consumers During the period t The value coefficient of electrical energy, As a preset constant, For producers and consumers During the period t The actual electricity consumption; Indicates buyer On the platform of P2P virtual power plant operators k Net electricity revenue obtained from the source Platform for P2P virtual power plant operators k For the buyer The operational efficiency coefficient; Indicates buyer Revenue from selling carbon, For the buyer Carbon emission reductions; and Indicates buyer The transportation costs of Platform 1 and Platform 2, both P2P virtual power plant operators, are added separately. For the buyer The unit transportation cost; Indicates buyer For P2P virtual power plant operators' platforms k The perceived utility of service quality The sensitivity coefficient of producers and consumers to electricity trading service fees; Indicates buyer For P2P virtual power plant operators' platforms k Trust utility For the buyer For P2P virtual power plant operators' platforms k Trust coefficient.

7. The pricing method for P2P virtual power plant energy sharing service fees based on two-stage game theory as described in claim 6, characterized in that, For the location Any seller j The utility of joining Platform 1 and Platform 2 of the P2P virtual power plant operator is expressed as follows: (11) (12) in, Indicates the seller On the platform of P2P virtual power plant operators k Net electricity revenue obtained from the source Platform for P2P virtual power plant operators k For the seller The operational efficiency coefficient; Indicates the seller Revenue from selling carbon, For the seller Carbon emission reductions; and Indicates the seller The transportation costs of Platform 1 and Platform 2, both P2P virtual power plant operators, are added separately. For the seller The unit transportation cost; Indicates the seller For P2P virtual power plant operators' platforms The perceived utility of service quality; Indicates the seller For P2P virtual power plant operators' platforms k Trust utility For the seller For P2P virtual power plant operators' platforms Trust coefficient; For any buyer The utility of joining Platform 1 and Platform 2 of different P2P virtual power plant operators is expressed as follows: (13) (14) in, Indicates buyer On the platform of P2P virtual power plant operators k Platform not considered k For the buyer Net electricity revenue obtained from the operating efficiency coefficient; Platforms representing P2P virtual power plant operators k For the buyer The operational efficiency coefficient, This serves as a benchmark coefficient for the platform operation efficiency of P2P virtual power plant operators. For any seller j, the utility of joining Platform 1 and Platform 2 of different P2P virtual power plant operators is expressed as follows: (15) (16) in, Indicates the seller On the platform of P2P virtual power plant operators k Platform not considered k For the seller Net electricity revenue obtained from the operating efficiency coefficient; Platforms representing P2P virtual power plant operators For the seller The operational efficiency coefficient; The platform selection behavior of the buyer and seller is subject to the following constraints: buyer Participation constraints: (17) Seller Participation constraints: (18) Transportation cost constraints: (19)。 8. The pricing method for P2P virtual power plant energy sharing service fees based on two-stage game theory as described in claim 7, characterized in that, The two-stage game is solved using backward induction: The method for solving the Nash equilibrium described in step S4 is as follows: A two-stage game model is used to study P2P virtual power plant operators. k Describe the two-way interaction between producers and consumers; definition , , P2P virtual power plant operators are eligible to operate under the following conditions. k Prosumers and consumers will achieve Nash equilibrium: : (20) (21) Among them, any buyer among prosumers and the seller Optimal basic service fee Any buyer among prosumers and the seller Optimal platform selection strategy , , .

9. A pricing device for P2P virtual power plant energy sharing service fees based on two-stage game theory, characterized in that, The pricing device is used to implement the P2P virtual power plant power sharing service fee pricing method based on two-stage game theory as described in any one of claims 1 to 8, and the pricing device includes: The hierarchical collaborative communication architecture establishment module is used to establish a hierarchical collaborative communication architecture including the large power grid-platform layer, the inter-platform layer, and the internal platform layer. It determines information interaction and latency constraints, analyzes the cost and benefit factors of P2P virtual power plant operators and prosumers, and determines the optimization objective function and corresponding constraints that take into account the platform's multidimensional heterogeneous selection preferences and nonlinear tiered two-part charging changes. The non-linear tiered two-part fee strategy determination module is used to determine the basic service fees and transaction service fees for each tier for both the buyer and the seller. The producer-consumer platform selection preference adjustment module is used to adjust the producer-consumer's platform selection preference for P2P virtual power plant operators based on the extended Hotelling model, according to the basic service fees and transaction service fees of each level, the producer-consumer's expected transaction volume and actual transaction volume, and introduces service quality perceived utility and trust utility to characterize multidimensional heterogeneous preferences. The Nash equilibrium judgment module is used to determine whether the two-stage game system composed of P2P virtual power plant operators and prosumers has reached Nash equilibrium; if it has not reached equilibrium, it returns to the nonlinear tiered two-part charging strategy determination module for iterative optimization. The pricing scheme output module is used to output the final pricing scheme, including the optimal basic service fee and optimal transaction service fee for the buyer, the optimal basic service fee and optimal transaction service fee for each tier for the seller, and the optimal platform selection strategy for prosumers.

10. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the pricing method for P2P virtual power plant energy sharing service fees based on two-stage game theory as described in any one of claims 1 to 8.

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