Trusted aggregation game transaction method for distributed new energy to participate in electricity market

Abstract

The invention discloses a credible aggregation game transaction method for distributed new energy to participate in a power market, and relates to the technical field of power transaction, the method comprises the following steps: based on a transaction rule, constructing a credible aggregation game transaction architecture comprising a data layer, a supervision layer, an aggregation transaction layer and a contract layer, evaluating the reputation of the generator, the reputation of the aggregator and the reputation of the power consumer, and supervising the whole power transaction process; in the aggregation transaction layer, providing a matching service; in the contract layer, based on an intelligent contract calling method, the data layer is used for storing all power transaction information and contract information; a trusted aggregation game transaction architecture is utilized to construct a transaction process used when distributed new energy aggregation participates in green electricity transaction. According to the credible aggregation game transaction architecture, the credible requirement and the efficient requirement of distributed new energy aggregation participating in green electricity transaction can be met, evaluation and supervision of transaction behaviors of all subjects are achieved, and the electricity transaction efficiency is improved.

Description

Background Art

[0002] Distributed new energy plays an indispensable role in the reform of the power market. It can encourage more renewable energy to enter the market, strive to make the industrial structure develop towards green and low-carbon, and build a clean, low-carbon, safe and efficient energy system. Distributed new energy usually requires distributed project aggregators to aggregate multiple distributed new energy sources and conduct green power transactions externally. However, the aggregation matching between power generators and aggregators and the transaction matching process between aggregators and power users involve a complex negotiation and contract conclusion process among multiple parties, often requiring a large amount of human and time costs. In addition, there may be dishonest behaviors or potential default risks in the process of aggregation and transaction of power generators, aggregators and power users, and it is difficult to establish a trust-based cooperative relationship among the parties involved.

[0003] To address this issue, researchers have made various attempts, among which the application of blockchain smart contract technology has been widely studied. These technologies are considered to be able to improve the security and efficiency of power transactions due to their characteristics of multi-party co-governance, transparency and immutability. In order to improve the credibility and automation level of transactions, although existing research has explored the application of blockchain smart contracts in power transactions, most of the existing research mainly focuses on the macro-framework design and lacks in-depth analysis of specific technical implementations, especially in the whole process of distributed new energy aggregation transactions.

[0004] However, the evaluation and supervision of green power trading behaviors need to be studied through the whole process of the trading process, which includes multiple links such as the credit evaluation of trading subjects, the design of trading matching algorithms, and the automatic execution of smart contracts. Each link has an important impact on the transparency, efficiency and security of transactions. By deeply analyzing and optimizing these links, potential default risks can be effectively identified and prevented, ensuring the fairness and reliability of transactions. Therefore, how to design the process of distributed new energy aggregation participating in green power transactions to ensure that distributed new energy can participate more effectively and credibly is the key to solving green power transactions. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art, and specifically provides the following technical solutions:

[0006] 1) In the first aspect, the present invention provides a credible aggregation game trading method for distributed new energy to participate in the power market. The specific technical solution is as follows:

[0007] Based on trading rules, construct a credible aggregation game trading architecture including a data layer, a supervision layer, an aggregation trading layer and a contract layer;

[0008] Among them, the trading rules include: a multi-agent reputation evaluation model based on a subjective logic framework and a non-cooperative game matching mechanism based on a fireworks algorithm; in the regulatory layer, the multi-agent reputation evaluation model based on the subjective logic framework is used to evaluate the reputation of power generators, aggregators, and electricity users; the regulatory layer is also responsible for reviewing and supervising the entire electricity trading process; in the aggregated trading layer, the non-cooperative game matching mechanism based on the fireworks algorithm is used to provide matching services for aggregators and electricity users; in the contract layer, methods in the regulatory layer and the aggregated trading layer are called based on smart contracts, and the data layer is used to store all electricity trading information and contract information;

[0009] Using the trusted aggregation game trading architecture, a trading process for distributed new energy aggregation to participate in green electricity trading is constructed, enabling power generators, aggregators, and electricity users to conduct transactions using the trading process.

[0010] Based on the above solution, a trusted aggregation game trading method for distributed new energy to participate in the electricity market of the present invention can also be improved as follows.

[0011] Further, using the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of power generators includes:

[0012] Using the update strategy formula corresponding to the power generator to update the positive trading times and negative trading times of the power generator, and substituting the updated positive trading times and negative trading times of the power generator into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the power generator.

[0013] Further, using the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of aggregators includes:

[0014] Using the update strategy formula corresponding to the aggregator to update the positive trading times and negative trading times of the aggregator, and substituting the updated positive trading times and negative trading times of the aggregator into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the aggregator.

[0015] Further, using the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of electricity users includes:

[0016] Using the update strategy formula corresponding to the electricity user to update the positive trading times and negative trading times of the electricity user, and substituting the updated positive trading times and negative trading times of the electricity user into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the electricity user.

[0017] Further, using the non-cooperative game matching mechanism based on the fireworks algorithm to provide matching services for aggregators and electricity users includes:

[0018] Establish the target utility algorithm for the aggregator and the target utility algorithm for the electricity users. The target utility algorithm for the aggregator is used to maximize the aggregator's electricity sales profit, and the target utility algorithm for the electricity users is used to minimize the electricity purchase cost of the electricity users.

[0019] Provide matching services for the aggregator and the electricity users through the target utility algorithm for the aggregator and the target utility algorithm for the electricity users.

[0020] 2) In the second aspect, the present invention also provides a credible aggregation game trading system for distributed new energy participating in the electricity market. The specific technical solution is as follows:

[0021] It includes a trading architecture construction module and a trading process construction module;

[0022] The trading architecture construction module is used to: based on the trading rules, construct a credible aggregation game trading architecture including a data layer, a supervision layer, an aggregation trading layer, and a contract layer;

[0023] Among them, the trading rules include: a multi-agent reputation evaluation model based on the subjective logic framework and a non-cooperative game matching mechanism based on the fireworks algorithm; in the supervision layer, use the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of power generators, aggregators, and electricity users; the supervision layer is also responsible for reviewing and supervising the entire electricity trading process; in the aggregation trading layer, use the non-cooperative game matching mechanism based on the fireworks algorithm to provide matching services for aggregators and electricity users; in the contract layer, based on the smart contract, call the methods in the supervision layer and the aggregation trading layer, and the data layer is used to store all electricity trading information and contract information;

[0024] The trading process construction module is used to: use the credible aggregation game trading architecture to construct the trading process used when distributed new energy aggregates to participate in green electricity trading.

[0025] On the basis of the above solution, a credible aggregation game trading system for distributed new energy participating in the electricity market of the present invention can also be improved as follows.

[0026] Further, using the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of power generators includes:

[0027] Use the update strategy formula corresponding to the power generator to update the number of positive transactions and the number of negative transactions of the power generator, and bring the updated number of positive transactions and the number of negative transactions of the power generator into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the power generator.

[0028] Further, the reputation of the aggregator is evaluated using a multi-agent reputation evaluation model based on the subjective logic framework, including:

[0029] Using the update strategy formula corresponding to the aggregator, update the positive transaction times and negative transaction times of the aggregator, and substitute the updated positive transaction times and negative transaction times of the aggregator into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the aggregator.

[0030] Further, the reputation of electricity users is evaluated using a multi-agent reputation evaluation model based on the subjective logic framework, including:

[0031] Using the update strategy formula corresponding to the electricity user, update the positive transaction times and negative transaction times of the electricity user, and substitute the updated positive transaction times and negative transaction times of the electricity user into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the electricity user.

[0032] Further, a non-cooperative game matching mechanism based on the fireworks algorithm is used to provide matching services for aggregators and electricity users, including:

[0033] Establish the target utility algorithm corresponding to the aggregator and the target utility algorithm corresponding to the electricity user. The target utility algorithm corresponding to the aggregator is used to: maximize the electricity sales profit of the aggregator, and the target utility algorithm corresponding to the electricity user is used to: minimize the electricity purchase cost of the electricity user;

[0034] Provide matching services for aggregators and electricity users through the target utility algorithm corresponding to the aggregator and the target utility algorithm corresponding to the electricity user.

[0035] 3) In the third aspect, the present invention also provides an electronic device. The electronic device includes a processor, the processor is coupled with a memory, and at least one computer program is stored in the memory. The at least one computer program is loaded and executed by the processor so that the electronic device implements any one of the above-mentioned trusted aggregation game trading methods for distributed new energy participating in the power market.

[0036] 4) In the fourth aspect, the present invention also provides a computer-readable storage medium. A computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, it implements any one of the above-mentioned trusted aggregation game trading methods for distributed new energy participating in the power market.

[0037] The beneficial effects of the present invention are as follows:

[0038] On the one hand, in response to the trustworthy requirements and efficient needs for distributed new energy aggregation to participate in green power trading, a trustworthy aggregation game trading architecture based on smart contracts is proposed; on the other hand, the evaluation and supervision of the trading behaviors of each subject are realized, and the smart contracts embedded in each level ensure the autonomous and automated operation of power trading, greatly improving the efficiency of power trading. Description of the Drawings

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description in the embodiments of the present invention:

[0040] Figure 1 It is a schematic flow chart of a method for trustworthy aggregation game trading of distributed new energy participating in the power market in an embodiment of the present invention;

[0041] Figure 2 It is a schematic diagram of the trustworthy aggregation game trading architecture;

[0042] Figure 3 It is a schematic diagram of the trading process;

[0043] Figure 4 It is a schematic diagram of the model of the non - cooperative game mechanism;

[0044] Figure 5 It is one of the schematic flow charts of the execution process of the smart contract in the aggregation trading layer;

[0045] Figure 6 It is the second schematic flow chart of the execution process of the smart contract in the aggregation trading layer;

[0046] Figure 7 It is a schematic flow chart of the execution process of the smart contract in the supervision layer;

[0047] Figure 8 It is a schematic structural diagram of a system for trustworthy aggregation game trading of distributed new energy participating in the power market in an embodiment of the present invention;

[0048] Figure 9 It is a schematic structural diagram of an electronic device in an embodiment of the present invention. Detailed Embodiments

[0049] The following describes the principles and features of the present invention. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0050] The following uses specific embodiments to detail the technical solutions of the present invention and how the technical solutions of the present invention solve the above - mentioned technical problems. These several specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The following will describe the embodiments of the present invention in conjunction with the drawings.

[0051] As Figure 1 shown, a method for trustworthy aggregation game trading of distributed new energy participating in the electricity market according to an embodiment of the present invention includes the following steps:

[0052] S1. Based on trading rules, construct a trustworthy aggregation game trading architecture including a data layer, a supervision layer, an aggregation trading layer, and a contract layer. The trustworthy aggregation game trading architecture is as Figure 2 shown.

[0053] Among them, trading rules can be constructed based on the published policies supporting the aggregation of distributed new energy to participate in green power trading. For example, according to the "Implementation Rules for Green Power Trading of Beijing Power Exchange (Revised Draft in 2024)" issued by the Beijing Power Exchange, trading rules are constructed.

[0054] Among them, according to the rules of smart contracts in the blockchain, the constructed trading rules can be converted into data applicable to the blockchain, so that power generators, aggregators, electricity users, and regulatory agencies can use the method of the present invention through the blockchain.

[0055] Among them, the trading rules include: a multi-agent reputation evaluation model based on a subjective logic framework and a non-cooperative game matching mechanism based on a fireworks algorithm; in the supervision layer, the multi-agent reputation evaluation model based on the subjective logic framework is used to evaluate the reputation of power generators, aggregators, and electricity users; the supervision layer is also responsible for reviewing and supervising the entire electricity trading process; in the aggregation trading layer, the non-cooperative game matching mechanism based on the fireworks algorithm is used to provide matching services for aggregators and electricity users; in the contract layer, methods in the supervision layer and the aggregation trading layer are called based on smart contracts, and the data layer is used to store all electricity trading information and contract information.

[0056] S2. Utilize the trustworthy aggregation game trading architecture to construct a trading process for distributed new energy aggregation to participate in green power trading, so that power generators, aggregators, and electricity users can conduct transactions using the trading process.

[0057] Optionally, as Figure 3 shown, the trading process includes 4 stages, specifically as follows:

[0058] 1) In the first stage, power generators, aggregators, and electricity users register and upload their respective registration information to the blockchain and save it to the data layer.

[0059] Among them, the numbers of power generators, aggregators, and electricity users can all be multiple. Denote the first power generator as Power Generator 1, the second power generator as Power Generator 2, and so on, and label each power generator. Denote the first aggregator as Aggregator 1, the second aggregator as Aggregator 2, and so on, and label each aggregator. Denote the first electricity user as Electricity User 1, the second electricity user as Electricity User 2, and so on, and label each electricity user.

[0060] The first stage can be called the "main body information on-chain" stage. In this stage, each power generator, each aggregator, and each electricity user need to complete registration and upload their respective information to the blockchain.

[0061] 2) In the second stage, the power generator quotes the power supply unit price and determines the supply electricity quantity. The aggregator bids according to the quotes provided by the power generator and determines the supply electricity quantity. The second stage is completed at the aggregation trading layer.

[0062] The second stage can be called the "power generator and aggregator transaction" stage. In this stage, each power generator will first quote the electricity quantity (quote the power supply unit price) and determine the electricity quantity that can be provided (supply electricity quantity). If the transaction is concluded, the power generator will receive the corresponding standby power income. Next, each aggregator bids according to the quotes provided by all power generators and submits the supply electricity quantity.

[0063] 3) In the third stage, the electricity user and the aggregator negotiate the final electricity consumption unit price and the final electricity consumption quantity. If an agreement is finally reached, the electricity transaction is completed. If no agreement is finally reached, the electricity transaction is rejected. The third stage is completed at the aggregation trading layer;

[0064] The third stage can be called the "aggregator and electricity user transaction" stage. In this stage, the aggregator will quote and negotiate the price with the electricity user according to the electricity quantity and price information obtained from the power generator. The electricity user and the aggregator negotiate on the price (final electricity consumption unit price) and the electricity quantity (final electricity consumption quantity), and finally reach an agreement or reject the electricity transaction. If both parties agree to the transaction, they will sign an electricity transaction contract and complete the settlement of the electricity quantity. The electricity user pays the electricity bill (the product of the final electricity consumption unit price and the final electricity consumption quantity) during this process.

[0065] 4) In the fourth stage, after the electricity transaction is completed, the blockchain receives and updates the credibility information of the power generator, the aggregator, and the electricity user, and updates the credibility of the blockchain, the aggregator, and the electricity user. The regulatory agency reviews the information related to the electricity transaction. The fourth stage is completed at the regulatory layer.

[0066] The fourth stage can be called the "subject reputation update" stage. In this stage, after the power transaction is completed, the reputation information of each subject will be updated to the blockchain. The regulatory agency will review the information related to the power transaction (obtained from the signed power transaction contract) to ensure the compliance of the power transaction, update the reputation of each subject, remove the discredited subjects, and store them in the blockchain.

[0067] Among them, the regulatory layer and the aggregated trading layer specifically call corresponding methods through the contract layer to execute tasks in different stages.

[0068] Among them, the trusted aggregated game trading architecture involves four types of subjects, specifically including: distributed new energy power generators (abbreviated as "power generators" in this article), distributed project aggregators (abbreviated as "aggregators" in this article), electricity users, and regulatory agencies. Among them, distributed new energy power generators include: distributed photovoltaic power generators, wind power generators, etc. First, the power generators will collect the generated electricity and give it to the aggregator, and then the aggregator and electricity users will be matched through the non-cooperative game matching mechanism based on the fireworks algorithm in the aggregated trading layer. The electricity users participate in the power transaction on the power trading platform and receive the electricity provided by the aggregator. In the contract layer, methods provided by the contract layer for bidding games (calling the non-cooperative game matching mechanism based on the fireworks algorithm to match the aggregator and electricity users) and reputation updates (calling the multi-subject reputation evaluation model based on the subjective logic framework to evaluate the reputation of power generators, aggregators, and electricity users) are used to perform operations such as bidding games and reputation updates. All power transactions are recorded and managed through blockchain technology to ensure transparency and security. The regulatory layer is responsible for reviewing and supervising the entire power transaction process to ensure the compliance of participants (the four types of subjects) and evaluate the reputation. Finally, all power transaction and contract information is stored in the data layer and managed through the blockchain for subsequent traceability and query.

[0069] Since the method of the present invention is implemented based on the blockchain, the subjects in the present invention are nodes on the blockchain. Therefore, Figure 2 "node removal" in Figure 3 refers to "removing discredited subjects",

[0070] Among them, the expression of the multi-subject reputation evaluation model based on the subjective logic framework established is:

[0071]

[0072] Among them, r s represents: the reputation of subject s, b s represents: the belief of subject s, d s represents: the disbelief of subject s, us Denote: the uncertainty of entity s, b s , d s and u s satisfy: b s +d s +u s = 1,

[0073] p s Denote: the number of positive transactions of entity s, q s Denote: the number of negative transactions of entity s.

[0074] Among them, the regulatory agency can use a multi - entity reputation evaluation model based on the subjective logic framework to evaluate the reputation of power generators, aggregators, and electricity users. Entities with a reputation less than the preset reputation threshold r min are identified as malicious entities, also known as discredited entities, and the discredited entities are removed from the blockchain. Entities with a reputation not less than the preset reputation threshold r min are identified as benign entities.

[0075] Optionally, using a multi - entity reputation evaluation model based on the subjective logic framework to evaluate the reputation of power generators, aggregators, and electricity users, including:

[0076] 1) Using the update strategy formula corresponding to the power generator to update the number of positive transactions and negative transactions of the power generator, and substituting the updated number of positive transactions and negative transactions of the power generator into the multi - entity reputation evaluation model based on the subjective logic framework to evaluate the reputation of the power generator. Specifically:

[0077] When entity s is a power generator, the update strategy formula corresponding to the power generator is:

[0078]

[0079] Among them, p s ′ denotes: the number of positive transactions of the power generator, q s ′ denotes: the number of negative transactions of the power generator, denotes: the updated number of positive transactions of the power generator, denotes: the updated number of negative transactions of the power generator, σ is a positive weighting factor that determines the balance between p s ′ and q s ′, and β s is the output deviation measuring the nature of the transaction, defined as follows:

[0080]

[0081] Among them, Υ s is the actual output of the power generator at time t, and φ s is the predicted output of the power generator at time t. The output deviation reflects the difference between the actual power generation and the predicted power generation. The smaller the value, the more accurate the power generation plan of the power generator, the higher the stability, and the better it can meet the market demand.

[0082] Substitute and into the multi-agent reputation evaluation model based on the subjective logic framework to determine the reputation of the power generator.

[0083] 2) Update the positive and negative transaction times of the aggregator using the corresponding update strategy formula of the aggregator. Substitute the updated positive and negative transaction times of the aggregator into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the aggregator. Specifically:

[0084] When the subject s is the aggregator, the corresponding update strategy formula of the aggregator is:

[0085]

[0086] Among them, δ s represents: the clearing rate that measures the nature of the transaction, μ s represents: the default rate that measures the nature of the transaction, λ represents: the trade-off factor between the clearing rate δ s and the default rate μ s p′ s ′ represents: the positive transaction times of the aggregator, q′ s ′ represents: the negative transaction times of the aggregator, represents: the updated positive transaction times of the aggregator, represents: the updated negative transaction times of the aggregator.

[0087] Among them, the clearing rate represents: the degree to which the aggregator successfully completes transactions in the market. The higher the value, the better the performance of the aggregator in market transactions and the more effectively it can complete the buying and selling of electricity. It is defined as follows:

[0088]

[0089] Among them, θ s represents: the actual cleared electricity volume of the aggregator within time t, Θ s represents: the electricity volume to be cleared.

[0090] The default rate reflects the frequency of default of the aggregator in market transactions. The higher the value, the worse the performance of the aggregator in fulfilling its obligations and the possible risks it may bring to the market. It is defined as follows:

[0091]

[0092] Among them, κ represents the number of defaults of the aggregator within the time period Dt.

[0093] Substituting and into the multi-agent reputation evaluation model based on the subjective logic framework can determine the reputation of the aggregator.

[0094] 3) Update the number of positive transactions and negative transactions of the power user using the update strategy formula corresponding to the power user, and substitute the updated number of positive transactions and negative transactions of the power user into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the power user.

[0095] When the subject s is a power user, the update strategy formula corresponding to the power user is:

[0096]

[0097] Among them, ω S represents the payment rate that measures the nature of the transaction, μ S represents the default rate that measures the nature of the transaction, α represents the trade-off factor between the payment rate ω S and the default rate μ S , p′ S ″ represents the number of positive transactions of the power user, q′ S ″ represents the number of negative transactions of the power user, (p s new )″′ represents the updated number of positive transactions of the power user, (q s new )″′ represents the updated number of negative transactions of the power user.

[0098] The payment rate reflects the degree to which the power user pays the fee on time after using the power service. The higher the value, the stronger the ability of the power user to fulfill the contract economically. It is defined as follows:

[0099]

[0100] Among them, ψ s is the fee actually paid by the power user at time t, and Γ s is the fee that needs to be paid.

[0101] Substituting p s =(p s new )″′ and (q s new )″′ into the multi-agent reputation evaluation model based on the subjective logic framework can determine the reputation of the power user.

[0102] In the aggregated trading layer, a non - cooperative game matching mechanism based on the fireworks algorithm is used to provide matching services for aggregators and electricity users. Specifically:

[0103] Establish the target utility algorithm for good aggregators and the target utility algorithm for good electricity users. The target utility algorithm for good aggregators is used to: maximize the electricity selling profit of good aggregators, and the target utility algorithm for good electricity users is used to: minimize the electricity purchase cost of good electricity users; through the target utility algorithm for aggregators and the target utility algorithm for electricity users, matching services are provided for aggregators and electricity users.

[0104] Aggregators compete for more market sales shares through different quotations to obtain greater benefits, and electricity users formulate electricity purchase strategies by predicting the supply - demand relationship within the trading time slot to strive to meet their electricity consumption needs at the lowest cost.

[0105] As Figure 4 shown, the determination process of the target utility algorithm for good aggregators and the target utility algorithm for good electricity users are described, and there are multiple aggregators (good aggregator clusters) and electricity users (good electricity user clusters) participating in the electricity transaction.

[0106] Among them, the acquisition process of the target utility algorithm for good aggregators includes:

[0107] When the entity is an aggregator, the target utility of the aggregator is the target profit, and the target profit comes from the electricity selling profit and subsidies (including government subsidies, etc.), and the costs include operation costs and aggregation costs. The electricity selling profit obtained by the k - th good aggregator at time t is calculated by the following formula

[0108]

[0109] Among them, represents: the electricity quantity sold by the k - th good aggregator to the n - th good electricity user, represents: the quotation per unit electricity quantity of the k - th good aggregator at time t, and the unit electricity quantity can be 1 kwh, and the total number of good electricity users is N.

[0110] Define that for each unit of electricity sold by a good aggregator, the power management department will give a subsidy amount as a green new - energy trading subsidy. The green new - energy trading subsidy obtained by the k - th good aggregator at time t is calculated by the following formula

[0111]

[0112] Among them, G k represents the green new energy trading subsidy given by the power management department to the k-th benign aggregator.

[0113] The operating cost of the k-th benign aggregator at time t is calculated by the following formula

[0114]

[0115] Among them, C k represents the operating cost per unit of electricity of the k-th benign aggregator.

[0116] The aggregation cost of the k-th benign aggregator at time t is calculated by the following formula

[0117]

[0118] Among them, ρ m represents the aggregation fee that the k-th benign aggregator needs to pay to the m-th benign power generator at each moment. x k,m (t) represents the aggregation matching situation between the k-th benign aggregator and the m-th benign power generator at time t. When the aggregation matching situation between the k-th benign aggregator and the m-th benign power generator at time t is a match, x k,m (t)=1. When the aggregation matching situation between the k-th benign aggregator and the m-th benign power generator at time t is a non-match, x k,m (t)=0. f m (t) represents whether the m-th benign power generator is in a normal power supply state at time t. When it is in a normal power supply state, f m (t)=1. When it is not in a normal power supply state, f m (t)=0.

[0119] Then, the objective utility function of the k-th benign aggregator is:

[0120]

[0121] Among them, represents the minimum unit price set by the power management department for the k-th aggregator at time t, represents the maximum unit price set by the power management department for the k-th aggregator at time t, represents the unit price of the k-th benign aggregator at time t; the total sold electricity of the k-th benign aggregator does not exceed the supply electricity of the k-th benign aggregator, represents the target profit of the k-th benign aggregator at time t is maximized.

[0122] Among them, the process of obtaining the target utility function corresponding to a benign electricity user includes:

[0123] When the entity is an electricity user, the target utility corresponding to the electricity user is the target cost, and the target cost includes the expected electricity purchase cost and the transaction deviation penalty.

[0124] The expected electricity purchase cost of the nth benign electricity user at time t is calculated by the following formula

[0125]

[0126] represents the electricity quantity transacted between the kth aggregator and the nth benign electricity user at time t, represents the unit electricity price of the electricity quantity transacted between the kth aggregator and the nth benign electricity user at time t.

[0127] If the benign electricity user does not purchase the full supply electricity quantity, a certain amount of penalty amount is given to the nth benign electricity user for each unit of electricity quantity, which is recorded as the transaction deviation penalty. The transaction deviation penalty of the nth benign electricity user at time t is calculated by the following formula is:

[0128]

[0129] Among them, is the remaining supply electricity quantity of the kth aggregator for the nth benign electricity user, V n represents the transaction deviation penalty.

[0130] The target utility function of the nth benign electricity user is obtained as:

[0131]

[0132] Among them, represents the target cost of the nth benign electricity user at time t is minimized.

[0133] Among them, the specific calculation process for both the target utility algorithm corresponding to the benign aggregator and the target utility algorithm corresponding to the benign electricity user to reach the Nash equilibrium point is as follows:

[0134] Initialization: Randomly generate a certain number of fireworks in the solution space of the problem, and each firework represents an initial solution. Initialize the maximum number of iterations L and the precision ε;

[0135] Evaluation: Calculate the fitness value of each firework according to the fitness function to evaluate its quality. If the fitness is less than or equal to ε or the maximum number of iterations is reached, the iteration terminates, and the solution at this time is the optimal Nash equilibrium solution;

[0136] Explosion: Simulate the explosion process of fireworks according to the fitness value of the fireworks to generate a certain number of sparks. The better the fitness value of the firework, the more sparks it generates, and vice versa;

[0137] Mutation: To maintain the diversity of the population, if the random number is greater than the set value, perform Gaussian mutation on some fireworks;

[0138] Selection: According to the roulette wheel selection strategy, select a part from the fireworks, sparks, and Gaussian mutation sparks as the fireworks for the next generation and continue the iteration.

[0139] Finally, construct a trusted aggregation game transaction architecture based on blockchain smart contracts.

[0140] 1) Smart contract design for the aggregation transaction layer:

[0141] a. Aggregation execution function: This function resets the aggregation relationship topology map and updates the power of the benign aggregator according to the aggregation matching results submitted by the benign power generator and the benign aggregator. Finally, increment the transaction times of the benign power generator and the benign aggregator by 1.

[0142] b. Bidding game function: This function is called by the benign aggregators and benign electricity users who need to purchase and sell electricity at the current moment, and solves the Nash equilibrium point according to the game algorithm.

[0143] c. Transaction confirmation function: This function is called by both parties who reach the Nash equilibrium, mainly for the feedback of the transaction matching results. When the Nash equilibrium point is reached, the transaction contract at this time is the optimal result. This function needs to ensure that both the buyer and the seller agree to this transaction and conduct the transaction at the agreed price and electricity quantity.

[0144] d. Transaction settlement function: This function is called by both parties who confirm the transaction, mainly for the transfer of funds and electricity according to the confirmed contract. This function needs to ensure that the transaction has been confirmed and not yet settled, calculate the amount that the benign electricity user needs to pay according to the electricity quantity and price of the transaction, transfer funds from the account of the benign electricity user to the account of the benign aggregator, and at the same time handle relevant fund flows such as fees and subsidies, record the payment and clearing situations. If the payment is complete or the clearing is completed, it is necessary to mark the transaction as settled to prevent repeated settlement.

[0145] 3) Smart contract design for the supervision layer:

[0146] a. Reputation update function: This function is called by the regulatory agency after a transaction is completed. Its main role is to update the reputation scores of the participants according to the execution status of the transaction. This function needs to ensure that the transaction exists and has been completed, and update the reputation values of the participating entities according to the multi - entity reputation evaluation mechanism.

[0147] b. Dishonest entity exclusion function: This function is called by the regulatory agency after reputation update. Its main role is to identify and exclude the participants who show malicious behavior in the system, so as to maintain the fairness and security of the trading system. For nodes with a reputation less than r min , mark them as untrusted nodes, freeze their accounts, and exclude them from the system. Record the exclusion event and notify all nodes.

[0148] Provide matching services for the benign aggregators and benign electricity users through the target utility algorithms corresponding to the benign aggregators and the target utility algorithms corresponding to the benign electricity users. Specifically:

[0149] Under the trading requirements of the non - cooperative game matching mechanism, provide matching services for the benign aggregators and benign electricity users through the target utility algorithms corresponding to the benign aggregators and the target utility algorithms corresponding to the benign electricity users.

[0150] The trading requirements in the non - cooperative game matching mechanism are:

[0151] Regard the process in which the trading entities adjust their quotes according to the market information until the equilibrium state during the transaction process as a non - cooperative game. Its participants are all the benign electricity users in the benign aggregator market or all the benign aggregators in the benign electricity user market. Their strategy is to adjust their quotes when the market information is announced on the trading platform. In terms of utility, the benign electricity users hope to save more funds to purchase electricity in the benign aggregator market, while the benign aggregators hope to obtain a higher selling price in the benign electricity user market. During the whole process of participating in distributed energy trading, the goal of the traders is to maximize their own utility. In the aggregated trading layer, the benign aggregators compete for more market share through different quotes to obtain greater benefits, and the benign electricity users formulate power purchase strategies by predicting the supply - demand relationship within the trading moment to strive to meet their electricity consumption needs at the minimum cost.

[0152] When the nth benign electricity user and the kth benign aggregator are mutually matched, the nth benign electricity user will try its best to meet its electricity demand from the kth benign aggregator, unless the electricity of the kth benign aggregator is insufficient to supply. It will not occur that the nth benign electricity user only purchases part of the electricity when the electricity of the kth benign aggregator is sufficient. All game players participate in the transaction with only one identity, either as a power purchaser or as a power seller. When the bid of the nth benign electricity user is not less than the offer of the kth benign aggregator, the two parties conduct the transaction, and the transaction price is the offer of the kth benign aggregator.

[0153] The smart contract design of the aggregation trading layer is as Figure 5 and Figure 6 shown. Specifically:

[0154] As Figure 5 shown, the aggregation execution function resets the aggregation relationship topology graph and updates the electricity of the benign aggregator according to the aggregation matching results submitted by the benign power generator and the benign aggregator. Finally, the transaction times of the benign power generator and the benign aggregator are incremented by 1. As Figure 6 shown, the bidding game function is called by the benign aggregators and benign electricity users that need to purchase and sell electricity at the current moment, and the Nash equilibrium point is solved according to the game algorithm.

[0155] The transaction confirmation function is called by both parties that reach the Nash equilibrium, mainly for the feedback of the transaction matching results. When the Nash equilibrium point is reached, the transaction contract at this time is the optimal result. This function needs to ensure that both the buyer and the seller agree to this transaction and conduct the transaction at the agreed price and electricity quantity.

[0156] The transaction settlement function is called by both parties that confirm the transaction, mainly for the transfer of funds and electricity according to the confirmed contract. This function needs to ensure that the transaction has been confirmed and not yet settled, calculate the amount that the benign electricity user needs to pay according to the electricity quantity and price of the transaction, transfer funds from the account of the benign electricity user to the accounts of the benign aggregator and the benign power generator, and at the same time handle relevant fund flows such as fees and subsidies, and record the payment and clearing situations. If the payment is fully made or cleared, it is necessary to mark the transaction as settled to prevent repeated settlement.

[0157] The smart contract design of the supervision layer is as Figure 7 shown. The reputation update function is called by the regulatory agency after the transaction is completed, and its main function is to update the reputation scores of the participating parties according to the execution situation of the transaction. This function needs to ensure that the transaction exists and has been completed, and update the reputation values of the participating entities according to the multi-agent reputation evaluation mechanism.

[0158] Next, the beneficial effects of the present invention are further verified and illustrated through simulation experiments.

[0159] Assume that the trading unit is 1 hour, and the trading time slot is divided into 24 moments, i.e., t ∈ [1, 24]. On this basis, calculate the predicted output and actual output of the power generator at each moment. The actual output of the benign power generator 1 is not less than the predicted output from moment 1 to moment 6, and at this time, the reputation slowly grows. When the actual output is less than the predicted output from moment 7 to moment 8, the reputation shows a downward trend. The evaluation situations from moment 9 to moment 11, from moment 13 to moment 14, from moment 16 to moment 17, and from moment 19 to moment 24 are the same as those from 1 to 6, and the evaluation situations at moment 12, moment 15, and moment 18 are the same as those from 7 to 8. The number of moments when the actual output of the benign power generator 2 is less than the predicted output is relatively large, and the output deviation is large. The output deviation of the power generator 2 is within the normal range from moment 1 to moment 2. The difference between the predicted output and the actual output at moment 3 is nearly 4 KWh. At this time, the reputation is lower than the benchmark reputation and shows an overall downward trend thereafter. For the entity with a reputation less than the basic reputation, the smart contract automatically removes the entity from the trading system.

[0160] The window size for the aggregator 1 to calculate the default rate is set to 3. The actual cleared volume at moment 13 is lower than the demand cleared volume, and at this time, the updated reputation shows a downward trend. A default situation occurs at moment 14, and at this time, the updated reputation shows a downward trend. After 3 moments without the next default, the updated reputation shows an upward trend. The aggregator 2 clears 100% at moment 1, and the updated reputation shows an upward trend. The actual cleared volume is about 5 KWh less than the demand cleared volume at moment 2, and the updated reputation shows a downward trend and is approximately equal to the basic reputation. It clears 100% at moment 3 without default, and the reputation shows an upward trend. A default situation occurs at moment 4, and at this time, the updated reputation is less than the benchmark reputation. The overall reputation shows a downward trend in subsequent moments and is less than the benchmark reputation. The scheme proposed in this description calls the defaulting entity removal function of the smart contract to remove the aggregator 2 from the trading system when the reputation is updated at moment 4.

[0161] The actual payment amount of the electricity user 1 at moment 7 is less than the due payment amount, and the updated reputation shows a downward trend and is approximately equal to the benchmark reputation. The payment is normal from moment 8 to moment 9, and the reputation shows an upward trend. The payment is incomplete at moment 10, and the updated reputation is less than the benchmark reputation, and it is removed from the electricity market. The electricity user 2 makes normal payments from moment 1 to moment 3, and the updated reputation shows an upward trend. A default situation occurs at moment 4, and the updated reputation shows a downward trend. A default situation occurs again at moment 6, and the updated reputation is lower than the reputation benchmark and is removed from the electricity market.

[0162] It can be seen from the comparison of the trading volumes of the aggregator and the electricity users that the present invention has completed a higher trading volume compared with the bilateral trading scheme, promoting the consumption of market electricity. It can be seen from the comparison of the trading revenues of the aggregator and the electricity users shown that the method proposed in the present invention also demonstrates better performance in terms of the revenues of all parties, greatly improving the market efficiency.

[0163] Moreover, as the number of power generators increases, the system trading time is continuously increasing, and the algorithm proposed by the present invention has a lower time delay. As the number of power generators increases, the normalized throughput of the system first increases and then decreases, and the present invention has always demonstrated better performance. When the number of power generators is 100, the normalized throughput is small, less than 0.5. When the number of power generators is 5000, the normalized throughput reaches the peak, which is the optimal node for trading at this time.

[0164] The above experimental results show that the method provided by the present invention achieves the purpose of efficient and trustworthy transactions.

[0165] The beneficial effects of the present invention are as follows:

[0166] 1) On the one hand, aiming at the trustworthy and efficient requirements for distributed new energy aggregation to participate in green power trading, a trustworthy aggregation game trading architecture is proposed; on the other hand, a multi-agent reputation evaluation mechanism, a non-cooperative game trading matching algorithm, and a smart contract integrating the whole process of green power trading are designed, which can effectively meet the trustworthy and efficient requirements for distributed new energy aggregation to participate in green power trading, realize the evaluation and trustworthy supervision of the trading behaviors of each subject, can effectively detect malicious nodes, and the smart contracts embedded in each layer ensure the autonomous and automated operation of the power trading system, greatly improving the trading efficiency.

[0167] 2) The present invention constructs a trustworthy aggregation game trading architecture to ensure the protection of the rights and interests of all parties in the transaction. The simulation results show that the method of the present invention shows superiority in terms of trading volume, revenue, system time delay, etc., significantly improving the trading efficiency of the market and the revenue of participants.

[0168] 3) The present invention not only provides an efficient trading platform for distributed new energy, but also provides technical support for promoting the market application of renewable energy and green and low-carbon development.

[0169] In the above embodiments, although the steps are numbered S1, S2, etc., these are only specific embodiments given by the present invention. Those skilled in the art can adjust the execution order of S1, S2, etc. according to the actual situation, which is also within the protection scope of the present invention. It can be understood that in some embodiments, it may include some or all of the above embodiments.

[0170] As Figure 8 shown, a trustworthy aggregation game trading system 200 for distributed new energy to participate in the power market according to an embodiment of the present invention includes a trading architecture construction module 201 and a trading process construction module 202;

[0171] The trading architecture construction module 201 is used to: construct a trustworthy aggregation game trading architecture including a data layer, a supervision layer, an aggregation trading layer, and a contract layer based on trading rules;

[0172] Among them, the trading rules include: a multi-agent reputation evaluation model based on a subjective logic framework and a non-cooperative game matching mechanism based on a fireworks algorithm; in the regulatory layer, the multi-agent reputation evaluation model based on the subjective logic framework is used to evaluate the reputation of power generators, aggregators, and electricity users; the regulatory layer is also responsible for reviewing and supervising the entire electricity trading process; in the aggregated trading layer, the non-cooperative game matching mechanism based on the fireworks algorithm is used to provide matching services for aggregators and electricity users; in the contract layer, methods in the regulatory layer and the aggregated trading layer are invoked based on smart contracts, and the data layer is used to store all electricity trading information and contract information.

[0173] The trading process construction module 202 is used to: utilize the trusted aggregated game trading architecture to construct the trading process used when distributed new energy aggregates participate in green electricity trading.

[0174] Optionally, in the above technical solution, using the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of power generators includes:

[0175] Using the update strategy formula corresponding to the power generator to update the positive trading times and negative trading times of the power generator, and substituting the updated positive trading times and negative trading times of the power generator into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the power generator.

[0176] Optionally, in the above technical solution, using the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of aggregators includes:

[0177] Using the update strategy formula corresponding to the aggregator to update the positive trading times and negative trading times of the aggregator, and substituting the updated positive trading times and negative trading times of the aggregator into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the aggregator.

[0178] Optionally, in the above technical solution, using the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of electricity users includes:

[0179] Using the update strategy formula corresponding to the electricity user to update the positive trading times and negative trading times of the electricity user, and substituting the updated positive trading times and negative trading times of the electricity user into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the electricity user.

[0180] Optionally, in the above technical solution, using the non-cooperative game matching mechanism based on the fireworks algorithm to provide matching services for aggregators and electricity users includes:

[0181] Establish a target utility algorithm for the aggregator and a target utility algorithm for the electricity users. The target utility algorithm for the aggregator is used to maximize the aggregator's electricity sales profit, and the target utility algorithm for the electricity users is used to minimize the electricity purchase cost of the electricity users;

[0182] Provide matching services for the aggregator and the electricity users through the target utility algorithm for the aggregator and the target utility algorithm for the electricity users.

[0183] A trustworthy aggregation game trading system 200 for distributed new energy participating in the electricity market according to the present invention can be implemented based on blockchain. That is to say, a trustworthy aggregation game trading system for distributed new energy participating in the electricity market according to the present invention can be a blockchain-based system.

[0184] It should be noted that the beneficial effects of the trustworthy aggregation game trading system 200 for distributed new energy participating in the electricity market provided in the above embodiments are the same as those of the above-mentioned method for trustworthy aggregation game trading of distributed new energy participating in the electricity market, and will not be elaborated here. In addition, when the system provided in the above embodiments implements its functions, only the division of the above-mentioned functional modules is used as an example for illustration. In actual applications, the above functions can be allocated to different functional modules according to needs, that is, the system can be divided into different functional modules according to the actual situation to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be seen in the method embodiments and will not be elaborated here.

[0185] Among them, the trustworthy aggregation game trading system for distributed new energy participating in the electricity market according to the present invention can be a computer program (including program code) running in a computer device. For example, the trustworthy aggregation game trading system for distributed new energy participating in the electricity market according to the present invention is an application software and can be used to execute the corresponding steps in the method for trustworthy aggregation game trading of distributed new energy participating in the electricity market according to the present invention.

[0186] In some embodiments, the trustworthy aggregation game trading system for distributed new energy to participate in the power market of the present invention can be implemented in a combination of software and hardware. As an example, the trustworthy aggregation game trading system for distributed new energy to participate in the power market of the present invention can be a processor in the form of a hardware decoding processor, which is programmed to execute the method for distributed new energy to participate in the trustworthy aggregation game trading in the power market of the present invention. For example, the processor in the form of a hardware decoding processor can employ one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic components.

[0187] Among them, the modules involved in the embodiments of the present invention can be implemented in software or in hardware. Among them, the name of the module does not constitute a limitation on the module itself in some cases.

[0188] An electronic device according to an embodiment of the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned method for distributed new energy to participate in the trustworthy aggregation game trading in the power market is implemented. That is to say, an electronic device according to an embodiment of the present invention may include, but is not limited to: a processor and a memory; the memory is used to store the computer program; the processor is used to execute the method for distributed new energy to participate in the trustworthy aggregation game trading shown in any embodiment of the present invention by calling the computer program.

[0189] In an alternative embodiment, an electronic device is provided, as Figure 9 shown. Figure 9 As shown, the electronic device 4000 includes: a processor 4001 and a memory 4003. Among them, the processor 4001 and the memory 4003 are connected, such as through a bus 4002. Optionally, the electronic device 4000 may further include a transceiver 4004, and the transceiver 4004 can be used for data interaction between this electronic device and other electronic devices, such as data sending and / or data receiving, etc. It should be noted that in practical applications, the transceiver 4004 is not limited to one, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present invention.

[0190] The processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logical blocks, modules, and circuits described in connection with the disclosure of the present invention. The processor 4001 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0191] The bus 4002 may include a path for transmitting information between the above components. The bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus 4002 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 9 only a thick line is used to represent the bus 4002 in the figure, but it does not mean that there is only one bus or one type of bus.

[0192] The memory 4003 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, or it may also be an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic storage media, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0193] The memory 4003 is used to store the application program code (computer program) for implementing the solution of the present invention, and is controlled by the processor 4001 for execution. The processor 4001 is used to execute the application program code stored in the memory 4003 to implement the content shown in the foregoing method embodiments.

[0194] Among them, the electronic device may also be a terminal device, and the terminal device may be any device on which an application can be installed, including at least one of a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, a smart TV, and a smart vehicle-mounted device.

[0195] It should be noted that Figure 9 the illustrated electronic device is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present invention.

[0196] A computer-readable storage medium according to an embodiment of the present invention has a computer program stored thereon, and when the computer program is executed by a processor, it implements any one of the above-mentioned credible aggregation game trading methods for distributed new energy participating in the power market.

[0197] Optionally, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0198] In an exemplary embodiment, there is also provided a computer program product or a computer program. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device executes any one of the above-mentioned credible aggregation game trading methods for distributed new energy participating in the power market.

[0199] Computer program code for performing the operations of the present invention may be written in one or more programming languages or combinations thereof. The above-mentioned programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0200] It should be understood that the flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system for performing the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0201] The computer-readable storage medium provided by the embodiments of the present invention may be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0202] The above computer-readable storage medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to execute the method shown in the above embodiments.

[0203] The above description is only a preferred embodiment of the present invention and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of disclosure involved in the present invention is not limited to the technical solutions formed by the specific combination of the above technical features, but also covers other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosure concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) having similar functions disclosed in the present invention.

[0204] It should be noted that the terms "first", "second", etc. in the description and claims of this application are used to distinguish similar objects, and represent a limitation on a specific order or sequence. In appropriate cases, the order of use of similar objects can be interchanged so that the embodiments of the present application described here can be implemented in an order other than the illustrated or described order.

[0205] Those skilled in the art know that the present invention can be implemented as a system, method or computer program product. Therefore, the present invention can be specifically implemented in the following forms: it can be completely hardware, can also be completely software (including firmware, resident software, microcode, etc.), and can also be a combination of hardware and software, generally referred to as "circuit", "module" or "system" in this article. In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, which contains computer-readable program code.

[0206] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A trusted aggregation game trading method for distributed renewable energy to participate in the power market, characterized in that: include: Based on the trading rules, a trusted aggregated game trading architecture is constructed, which includes the data layer, the regulatory layer, the aggregated trading layer and the contract layer; Among them, the trading rules include: a multi-agent reputation evaluation model based on a subjective logic framework and a non-cooperative game matching mechanism based on a fireworks algorithm; in the regulatory layer, the multi-agent reputation evaluation model based on a subjective logic framework is used to evaluate the reputation of power generators, aggregators and power users; the regulatory layer is also responsible for reviewing and supervising the entire power trading process; in the aggregated trading layer, a non-cooperative game matching mechanism based on a fireworks algorithm is used to provide matching services for the aggregators and the power users; in the contract layer, the methods in the regulatory layer and the aggregated trading layer are called based on smart contracts, and the data layer is used to store all power trading information and contract information; The trusted aggregation game transaction architecture is used to construct a transaction process used when distributed new energy aggregation participates in green electricity transactions.

2. According to claim 1, a trusted aggregation game trading method for distributed new energy to participate in the power market is characterized in that: The credibility of the power generator is evaluated by using the multi-agent credibility evaluation model based on the subjective logic framework, including: The positive transaction times and negative transaction times of the power generator are updated using the update strategy formula corresponding to the power generator, and the updated positive transaction times and negative transaction times of the power generator are brought into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the power generator.

3. According to claim 1, a trusted aggregation game trading method for distributed new energy to participate in the power market is characterized in that: The reputation of the aggregator is evaluated using the multi-agent reputation evaluation model based on the subjective logic framework, including: The positive transaction times and negative transaction times of the aggregator are updated using the update strategy formula corresponding to the aggregator, and the updated positive transaction times and negative transaction times of the aggregator are brought into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the aggregator.

4. According to claim 1, a trusted aggregation game trading method for distributed new energy to participate in the power market is characterized in that: The credibility of the power user is evaluated by using the multi-agent credibility evaluation model based on the subjective logic framework, including: The positive transaction times and negative transaction times of the power user are updated by using the update strategy formula corresponding to the power user, and the updated positive transaction times and negative transaction times of the power user are brought into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the power user.

5. A trusted aggregation game trading method for distributed new energy participating in the power market according to any one of claims 1 to 4, characterized in that: A non-cooperative game matching mechanism based on a fireworks algorithm is used to provide matching services for the aggregator and the power user, including: Establishing a target utility algorithm corresponding to an aggregator and a target utility algorithm corresponding to an electricity user, wherein the target utility algorithm corresponding to the aggregator is used to maximize the electricity sales profit of the aggregator, and the target utility algorithm corresponding to the electricity user is used to minimize the electricity purchase cost of the electricity user; Matching services are provided for the aggregator and the power user through the target utility algorithm corresponding to the aggregator and the target utility algorithm corresponding to the power user.

6. A trusted aggregation game trading system for distributed new energy to participate in the power market, characterized in that: Includes transaction architecture building modules and transaction process building modules; The transaction architecture building module is used to: build a trusted aggregated game transaction architecture including a data layer, a regulatory layer, an aggregated transaction layer and a contract layer based on transaction rules; Among them, the trading rules include: a multi-agent reputation evaluation model based on a subjective logic framework and a non-cooperative game matching mechanism based on a fireworks algorithm; in the regulatory layer, the multi-agent reputation evaluation model based on a subjective logic framework is used to evaluate the reputation of power generators, aggregators and power users; the regulatory layer is also responsible for reviewing and supervising the entire power trading process; in the aggregated trading layer, a non-cooperative game matching mechanism based on a fireworks algorithm is used to provide matching services for the aggregators and the power users; in the contract layer, the methods in the regulatory layer and the aggregated trading layer are called based on smart contracts, and the data layer is used to store all power trading information and contract information; The transaction process building module is used to: use the trusted aggregation game transaction architecture to build a transaction process used when distributed new energy aggregation participates in green electricity transactions.

7. A trusted aggregation game trading system for distributed new energy participating in the power market according to claim 6, characterized in that: The credibility of the power generator is evaluated by using the multi-agent credibility evaluation model based on the subjective logic framework, including: The positive transaction times and negative transaction times of the power generator are updated using the update strategy formula corresponding to the power generator, and the updated positive transaction times and negative transaction times of the power generator are brought into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the power generator.

8. A trusted aggregation game trading system for distributed new energy participating in the power market according to claim 6, characterized in that: The reputation of the aggregator is evaluated using the multi-agent reputation evaluation model based on the subjective logic framework, including: The positive transaction times and negative transaction times of the aggregator are updated using the update strategy formula corresponding to the aggregator, and the updated positive transaction times and negative transaction times of the aggregator are brought into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the aggregator.

9. A trusted aggregation game trading system for distributed new energy participating in the power market according to claim 6, characterized in that: The credibility of the power user is evaluated by using the multi-agent credibility evaluation model based on the subjective logic framework, including: The positive transaction times and negative transaction times of the power user are updated by using the update strategy formula corresponding to the power user, and the updated positive transaction times and negative transaction times of the power user are brought into the multi-agent reputation evaluation model based on the subjective logic framework to evaluate the reputation of the power user.

10. A trusted aggregation game trading system for distributed new energy participating in the power market according to any one of claims 6 to 9, characterized in that: A non-cooperative game matching mechanism based on a fireworks algorithm is used to provide matching services for the aggregator and the power user, including: Establishing a target utility algorithm corresponding to an aggregator and a target utility algorithm corresponding to an electricity user, wherein the target utility algorithm corresponding to the aggregator is used to maximize the electricity sales profit of the aggregator, and the target utility algorithm corresponding to the electricity user is used to minimize the electricity purchase cost of the electricity user; Matching services are provided for the aggregator and the power user through the target utility algorithm corresponding to the aggregator and the target utility algorithm corresponding to the power user.

11. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, a trusted aggregation game trading method for distributed new energy sources to participate in the electricity market as described in any one of claims 1 to 5 is implemented.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, it implements the trusted aggregation game trading method for distributed new energy participating in the electricity market as described in any one of claims 1 to 5.

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