A Virtual Power Plant Master-Slave Multi-Chain Resource Interaction Matching Method Based on an Improved Consensus Algorithm

Abstract

This application relates to a virtual power plant master-slave multi-chain resource interaction matching method based on an improved consensus algorithm. The method includes: constructing a virtual power plant interaction architecture model of the target power grid based on data from various aggregators; the virtual power plant interaction architecture model includes a resource aggregation layer and a distributed resource layer; constructing aggregator resource interaction processes for the target power grid in the resource aggregation layer based on data from each aggregator; inputting the data from each aggregator and the aggregator resource interaction processes into a non-cooperative static game model of power resource interaction in the resource aggregation layer to obtain target resource interaction information; inputting the target resource interaction information and the aggregator resource interaction processes into the distributed resource layer to obtain power resource interaction consensus information; and using the power resource interaction consensus information for resource interaction within the target power grid. This method enables peer-to-peer trusted transactions among multiple entities, improves the efficiency of power resource interaction, and maximizes the interests of each party.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a method, apparatus, computer equipment, storage medium, and computer program product for virtual power plant master-slave multi-chain resource interaction matching based on an improved consensus algorithm. Background Technology

[0002] With the development of computer technology, the advancement of intelligent technology, and the high proportion of flexible resources accessed, the common modes of electricity market interaction are mainly divided into: P2P mode and centralized clearing transaction. The former is similar to the electricity interaction platform mode, where the market management end only provides a platform for the interaction of various entities and does not participate in every specific electricity market interaction. The latter is similar to the power pool mode, where the management agency is equivalent to an intermediary that inputs electricity from the upper-level power generation market and sells electricity to the lower-level power output entities or power purchase entities.

[0003] In traditional technologies, within a virtual power plant, interactions between stakeholders rely on two-way communication via a network. However, the output and demand information between stakeholders is vulnerable to malicious attacks and tampering, leading to errors in the virtual power plant's scheduling and operation, and increased costs. Furthermore, the significant increase in frequent power interactions results in more complex inter-stakeholder relationships, lower operational decision-making efficiency, and increased safety risks. Simultaneously, in market interactions, virtual power plants suffer from unclear stakeholder identities, opaque transaction information, and a lack of trust among decision-makers, leading to inefficient power resource interaction. Summary of the Invention

[0004] Based on this, it is necessary to provide a virtual power plant master-slave multi-chain resource interaction matching method, device, computer equipment, computer-readable storage medium, and computer program product that can improve the efficiency of power resource interaction based on an improved consensus algorithm, addressing the aforementioned technical problems.

[0005] Firstly, this application provides a virtual power plant master-slave multi-chain resource interaction matching method based on an improved consensus algorithm. The method includes:

[0006] Based on the data from various aggregators in the target power grid, a virtual power plant interaction architecture model for the target power grid is constructed; the virtual power plant interaction architecture model includes a resource aggregation layer and a distributed resource layer.

[0007] Based on the data of each aggregator, the aggregator resource interaction process of the target power grid is constructed in the resource aggregation layer;

[0008] The data of each aggregator and the resource interaction process of the aggregator are input into the non-cooperative static game model of power resource interaction in the resource aggregation layer to obtain the target resource interaction information.

[0009] The target resource interaction information and the aggregator resource interaction process are input into the distributed resource layer to obtain power resource interaction consensus information; the power resource interaction consensus information is used by the target power grid for resource interaction.

[0010] Secondly, this application also provides a virtual power plant master-slave multi-chain resource interaction matching device based on an improved consensus algorithm. The device includes:

[0011] The model building module is used to construct a virtual power plant interaction architecture model of the target power grid based on the data of each aggregator in the target power grid; the virtual power plant interaction architecture model includes a resource aggregation layer and a distributed resource layer;

[0012] The process construction module is used to construct the aggregator resource interaction process of the target power grid in the resource aggregation layer based on the data of each aggregator;

[0013] The first model calculation module is used to input the data of each aggregator and the resource interaction process of the aggregator into the non-cooperative static game model of power resource interaction of the resource aggregation layer to obtain the target resource interaction information.

[0014] The second model calculation module is used to input the target resource interaction information and the aggregator resource interaction process into the distributed resource layer to obtain power resource interaction consensus information; the power resource interaction consensus information is used by the target power grid for resource interaction.

[0015] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0016] Based on the data from various aggregators in the target power grid, a virtual power plant interaction architecture model for the target power grid is constructed; the virtual power plant interaction architecture model includes a resource aggregation layer and a distributed resource layer.

[0017] Based on the data of each aggregator, the aggregator resource interaction process of the target power grid is constructed in the resource aggregation layer;

[0018] The data of each aggregator and the resource interaction process of the aggregator are input into the non-cooperative static game model of power resource interaction in the resource aggregation layer to obtain the target resource interaction information.

[0019] The target resource interaction information and the aggregator resource interaction process are input into the distributed resource layer to obtain power resource interaction consensus information; the power resource interaction consensus information is used by the target power grid for resource interaction.

[0020] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0021] Based on the data from various aggregators in the target power grid, a virtual power plant interaction architecture model for the target power grid is constructed; the virtual power plant interaction architecture model includes a resource aggregation layer and a distributed resource layer.

[0022] Based on the data of each aggregator, the aggregator resource interaction process of the target power grid is constructed in the resource aggregation layer;

[0023] The data of each aggregator and the resource interaction process of the aggregator are input into the non-cooperative static game model of power resource interaction in the resource aggregation layer to obtain the target resource interaction information.

[0024] The target resource interaction information and the aggregator resource interaction process are input into the distributed resource layer to obtain power resource interaction consensus information; the power resource interaction consensus information is used by the target power grid for resource interaction.

[0025] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0026] Based on the data from various aggregators in the target power grid, a virtual power plant interaction architecture model for the target power grid is constructed; the virtual power plant interaction architecture model includes a resource aggregation layer and a distributed resource layer.

[0027] Based on the data of each aggregator, the aggregator resource interaction process of the target power grid is constructed in the resource aggregation layer;

[0028] The data of each aggregator and the resource interaction process of the aggregator are input into the non-cooperative static game model of power resource interaction in the resource aggregation layer to obtain the target resource interaction information.

[0029] The target resource interaction information and the aggregator resource interaction process are input into the distributed resource layer to obtain power resource interaction consensus information; the power resource interaction consensus information is used by the target power grid for resource interaction.

[0030] The aforementioned method, apparatus, computer equipment, storage medium, and computer program product for virtual power plant master-slave multi-chain resource interaction matching based on an improved consensus algorithm constructs a virtual power plant interaction architecture model for the target power grid based on data from each aggregator. The virtual power plant interaction architecture model includes a resource aggregation layer and a distributed resource layer. Based on the data from each aggregator, the resource interaction process of the target power grid's aggregators is constructed in the resource aggregation layer. The data from each aggregator and the aggregator resource interaction process are input into a non-cooperative static game model of power resource interaction in the resource aggregation layer to obtain target resource interaction information. The target resource interaction information and the aggregator resource interaction process are input into the distributed resource layer to obtain power resource interaction consensus information. This power resource interaction consensus information is used for resource interaction within the target power grid.

[0031] A virtual power plant (VPP) interaction architecture model was constructed using data from various aggregators within the target power grid. At the resource aggregation layer, aggregator resource interaction processes were built based on this data. Next, by inputting the aggregator data and resource interaction processes into a non-cooperative static game model of power resource interaction at the resource aggregation layer, target resource interaction information was obtained. Finally, the target resource interaction information and aggregator resource interaction processes were input into the distributed resource layer to obtain power resource interaction consensus information. This information is used for resource interaction within the target power grid. By building a VPP distributed trading platform and analyzing the CDA matching trading process, multi-party peer-to-peer trusted trading can be achieved, improving power resource interaction efficiency and maximizing the interests of all parties involved. Attached Figure Description

[0032] Figure 1 This is an application environment diagram of a virtual power plant master-slave multi-chain resource interaction matching method based on an improved consensus algorithm in one embodiment;

[0033] Figure 2 This is a flowchart illustrating a virtual power plant master-slave multi-chain resource interaction matching method based on an improved consensus algorithm in one embodiment.

[0034] Figure 3 This is a flowchart illustrating a method for obtaining target resource interaction information in one embodiment;

[0035] Figure 4 This is a flowchart illustrating the method for determining power resource interaction information and power interaction score values ​​in one embodiment.

[0036] Figure 5 This is a flowchart illustrating the method for obtaining the power interaction score value in another embodiment;

[0037] Figure 6 This is a flowchart illustrating the method for obtaining target resource interaction information in another embodiment;

[0038] Figure 7 This is a flowchart illustrating the method for obtaining target resource interaction information in yet another embodiment;

[0039] Figure 8 This is a flowchart illustrating a method for generating power resource interaction security verification information in one embodiment;

[0040] Figure 9 This is a flowchart illustrating the target resource interaction information method in another embodiment;

[0041] Figure 10 This is a schematic diagram of a virtual power plant master-slave interaction architecture in one embodiment;

[0042] Figure 11 This is a schematic diagram of the power resource interaction process among multiple aggregators based on smart contracts in one embodiment;

[0043] Figure 12 This is a schematic diagram of a non-cooperative static game model in one embodiment;

[0044] Figure 13 This is a schematic diagram of the improved consensus algorithm structure in one embodiment;

[0045] Figure 14 This is a schematic diagram of the matching process for one embodiment;

[0046] Figure 15 This is a structural block diagram of a virtual power plant master-slave multi-chain resource interaction matching device based on an improved consensus algorithm in one embodiment;

[0047] Figure 16 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0049] This application provides a virtual power plant master-slave multi-chain resource interaction matching method based on an improved consensus algorithm, which can be applied to, for example... Figure 1In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or placed on a cloud or other network server. Server 104 obtains aggregator data for the target power grid from terminal 102, and further constructs a virtual power plant interaction architecture model for the target power grid based on this data. The virtual power plant interaction architecture model includes a resource aggregation layer and a distributed resource layer. Based on the aggregator data, aggregator resource interaction processes for the target power grid are constructed in the resource aggregation layer. The aggregator data and aggregator resource interaction processes are input into a non-cooperative static game model for power resource interaction in the resource aggregation layer to obtain target resource interaction information. The target resource interaction information and aggregator resource interaction processes are input into the distributed resource layer to obtain power resource interaction consensus information. The power resource interaction consensus information is used for resource interaction within the target power grid. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart vehicle devices, etc. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted devices. Server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0050] In one embodiment, such as Figure 2 As shown, a virtual power plant master-slave multi-chain resource interaction matching method based on an improved consensus algorithm is provided, and this method is applied to... Figure 1 Taking the server in the example, the following steps are included:

[0051] Step 202: Construct a virtual power plant interaction architecture model for the target power grid based on the data from each aggregator in the target power grid.

[0052] The target power grid can be a power grid that requires power resource exchange.

[0053] Among them, the data from aggregators can be of one type, such as data from load aggregators, data from electric vehicle aggregators, data from integrated energy service providers, or data from park microgrids.

[0054] The virtual power plant interaction architecture model can be a computer model used to describe the interaction architecture of a virtual power plant. For example... Figure 10 The diagram shown is a schematic of the master-slave interaction architecture of a virtual power plant.

[0055] Specifically, utilizing the internal resource trading and matching mechanism of the virtual power plant, an interactive architecture based on MAS was designed, namely the virtual power plant interactive architecture model of the target power grid. The VPP is divided into a resource aggregation layer and a distributed resource layer from top to bottom. The resource aggregation layer consists of various aggregator data (Agg), which are generally of one type: load data Agg, electric vehicle data Agg, integrated energy service provider data, and park microgrid data. The distributed resource layer consists of flexible resources (FRs) in the area to which the aggregator data belongs. Flexible resources mainly include one or more of the following: wind turbine (WT), photovoltaic (PV), load users, and distributed energy storage.

[0056] Step 204: Based on the data from each aggregator, construct the aggregator resource interaction process for the target power grid in the resource aggregation layer.

[0057] Among them, the aggregator resource interaction process can be a process of power resource interaction among multiple aggregators based on smart contracts.

[0058] Specifically, based on the data from each aggregator, a process for the interaction of power resources among multiple aggregators in the target power grid (aggregator resource interaction process) is constructed in the resource aggregation layer, such as... Figure 11 The diagram illustrates the process of power resource interaction among multiple aggregators based on smart contracts. It includes a preparation phase, an interaction and matching phase, a contract signing phase, and a delivery and settlement phase. The functions included in each phase are as follows.

[0059] (1) Preparation phase: Each aggregator's data is registered as either the aggregator data for inputting power resources or the aggregator data for outputting power resources in the interaction, based on the energy forecast results for the next period, and its blockchain resource manager ID is bound to the smart meter ID.

[0060] (2) Interactive matching phase: Aggregators submit bidding applications based on their own bidding strategies, which are then broadcast by the blockchain network in their respective regions, and matching transactions are conducted within the main chain. VPPO executes the internal market matching and matching of virtual power plants by calling the matching function to obtain the initial auction results.

[0061] (3) Contract signing stage: The initial auction results need to undergo security verification calculations. If the interaction does not meet the maximum allowed power flow, the system will be re-matched or the power grid will absorb the compensation. After passing the security verification, the participating entities sign contracts and record the transaction proofs in the blockchain as much as possible.

[0062] (4) Settlement and Delivery Phase: Each Agg executes power supply and consumption according to the final transaction results reached during the contract signing phase, and calculates income and expenditure according to the settlement method signed in the contract based on the execution of energy delivery, and updates the wallet balance of all transaction nodes in the chain. Energy interaction data is recorded and temporarily stored by smart meters deployed on multiple light nodes of the blockchain (including the main chain and all slave chains).

[0063] Step 206: Input the data of each aggregator and the resource interaction process of the aggregator into the non-cooperative static game model of power resource interaction in the resource aggregation layer to obtain the target resource interaction information.

[0064] Among them, the non-cooperative static game model of power resource interaction can be a game model in which there is competition among the participants in the power resource interaction but no direct cooperation. A schematic diagram of the non-cooperative static game model of power resource interaction is shown below. Figure 12 As shown.

[0065] Among them, the target resource interaction information can be the output data of a non-cooperative static game model for power resource interaction, which is used for power resource interaction.

[0066] Specifically, the CDA (Content Delivery Allocation) trading mechanism is adopted for P2P transactions, considering the maximization of interests for all parties. In the interaction, the aggregator data input or output of power resources acts as an independent market entity with unequal interests. To achieve orderly and active interaction among aggregator data, a non-cooperative static game model is constructed, namely the power resource interaction non-cooperative static game model. This model uses VPPO (Power Product Ownership Platform) and the power grid as the main players, and the aggregator data input or output of power resources as secondary players. Based on the model construction, the data of each aggregator and the aggregator resource interaction process are input into the power resource interaction non-cooperative static game model of the resource aggregation layer to obtain the target resource interaction information. In this model, to reflect the advantages of blockchain's decentralization and reduced transaction costs, the non-cooperative static game model needs to consider maximizing the profits of the electricity sales agent (outputting power resource aggregator data in the interaction) and minimizing the costs of the electricity purchase agent (inputting power resource aggregator data in the interaction).

[0067] Step 208: Input the target resource interaction information and the aggregator resource interaction process into the distributed resource layer to obtain the power resource interaction consensus information.

[0068] Among them, the consensus information for power resource interaction can be information used by the target power grid for resource interaction.

[0069] Specifically, the improved DPoA consensus mechanism, based on PBFT, utilizes BD-PSO to optimize the algorithm, improving its usability. The algorithm implements the following specific process for inputting target resource interaction information and aggregator resource interaction procedures into the distributed resource layer to obtain power resource interaction consensus information:

[0070] (1) After inputting the target resource interaction information and the aggregator resource interaction process into the distributed resource layer, when a node needs to generate a new block, it first packages the received broadcast information to generate the Merkel root.

[0071] (2) Verification process: When each node needs to verify whether a block is a valid block, it first replaces the hash calculation that consumes a lot of computing power with the BD-PSO algorithm. If the block is the result of the BD-PSO algorithm optimization calculation, the committee nodes are instructed to verify the results contained in the block (by substituting them into the BD-PSO algorithm). If the information in the block is simple information such as instructions, power generation, or load forecasting, the BD-PSO algorithm calculation result is set to 1 by default, and the next step is directly performed.

[0072] (3) The result of the statistical optimization of the consensus information calculation of power resources interaction is denoted as Z; for the block of the result of the BD-PSO algorithm optimization calculation, if more than 50% of the committee nodes verify that the result is valid, the block is verified by the consensus algorithm and is a valid block; for the block containing simple data content, the validity of the block is judged by a vote. If more than 50% of the nodes vote to agree with the data, the block is verified by the consensus algorithm and is a valid block.

[0073] Z>N / 2

[0074] In summary, the DPoA consensus mechanism ensures that nodes with strong consensus capabilities are more likely to be elected, reducing the possibility of malicious nodes being elected during the committee node election phase, and effectively guaranteeing that participating nodes always have good state or consensus capabilities. Referring to the PBFT algorithm's idea of ​​maintaining identical replica states, it can suppress malicious node behavior. Furthermore, the BD-PSO algorithm can improve decentralization, save computing power, and lay the foundation for the physical security of power transmission. DPoA dynamically selects a subset of qualified nodes as committee nodes in each round, making the consensus mechanism more secure, stable, and efficient. Figure 13 This is a schematic diagram of an improved consensus algorithm structure in one embodiment.

[0075] The aforementioned virtual power plant master-slave multi-chain resource interaction matching method based on an improved consensus algorithm constructs a virtual power plant interaction architecture model for the target power grid based on the data of each aggregator. This model includes a resource aggregation layer and a distributed resource layer. Based on the data of each aggregator, the resource interaction process of the target power grid's aggregators is constructed in the resource aggregation layer. The data of each aggregator and the resource interaction process are input into a non-cooperative static game model of power resource interaction in the resource aggregation layer to obtain target resource interaction information. This target resource interaction information and the aggregator resource interaction process are then input into the distributed resource layer to obtain power resource interaction consensus information. This consensus information is used by the target power grid for resource interaction.

[0076] A virtual power plant (VPP) interaction architecture model was constructed using data from various aggregators within the target power grid. At the resource aggregation layer, aggregator resource interaction processes were built based on this data. Next, by inputting the aggregator data and resource interaction processes into a non-cooperative static game model of power resource interaction at the resource aggregation layer, target resource interaction information was obtained. Finally, the target resource interaction information and aggregator resource interaction processes were input into the distributed resource layer to obtain power resource interaction consensus information. This information is used for resource interaction within the target power grid. By building a VPP distributed trading platform and analyzing the CDA matching trading process, multi-party peer-to-peer trusted trading can be achieved, improving power resource interaction efficiency and maximizing the interests of all parties involved.

[0077] In one embodiment, such as Figure 3 As shown, the data of each aggregator and the resource interaction process of the aggregators are input into the non-cooperative static game model of power resource interaction in the resource aggregation layer to obtain the target resource interaction information, including:

[0078] Step 302: Based on the data from each aggregator and the resource interaction process of each aggregator, determine the power resource interaction information and the power interaction score of each power grid in the target power grid.

[0079] Among them, the electricity resource interaction information can be the electricity price for aggregators to trade electricity resources.

[0080] Among them, the power interaction score can be the transaction reputation value of the aggregator in trading power resources.

[0081] Specifically, data from various aggregators is collected, including information on power resource types, capacity, and availability. The resource interaction processes among aggregators are analyzed, considering interoperability and synergistic effects. Power interaction calculations are performed on each aggregator to obtain corresponding power resource interaction information, namely, the purchase price and sale price of electricity. Finally, an appropriate scoring system is used to evaluate each power interaction, considering factors such as stability, reliability, and efficiency, to determine the interaction score for each power resource. This process ensures that the target power grid achieves optimal operation in terms of resource integration and interaction.

[0082] Step 304: Select target resource interaction information from the power resource interaction information based on the power interaction score.

[0083] Specifically, a weighted system needs to be established to balance various scoring factors, ensuring a comprehensive consideration of stability, reliability, and efficiency. Then, by ranking and comparing the various power resource interaction information, and combining their corresponding power interaction score values, a transaction quality evaluation coefficient is calculated using these scores. Combining the power interaction score values ​​and the transaction quality evaluation coefficient, target resource interaction information is selected from the various power resource interaction information. This process needs to consider the overall operational needs of the power system to ensure that the selected resource interaction information can maximally meet the requirements of stable operation and optimized performance of the power network. Finally, through a rigorous selection process, the selection of target resource interaction information that balances all aspects is achieved.

[0084] In this embodiment, by collecting and comprehensively analyzing the power resource data from various aggregators, the system can gain a comprehensive understanding of the power market landscape, considering factors such as power resource type, capacity, and availability. Through in-depth analysis of the resource interaction processes among aggregators, considering interoperability and synergistic effects, the system achieves interactive calculations of power resources, obtaining key information such as electricity purchase and sales prices. Utilizing the established scoring system, the system comprehensively evaluates power interactions, taking into account factors such as stability, reliability, and efficiency to ensure a balanced scoring. By ranking and comparing the interaction information of various power resources, and combining the power interaction score and transaction quality evaluation coefficient, the system can intelligently select target resource interaction information to maximize the stable operation and optimized performance of the power network. This process achieves the selection of target resource interaction information that balances various aspects, providing a reliable and efficient solution for the overall operation of the power system.

[0085] In one embodiment, such as Figure 4 As shown, based on the data from each aggregator and the resource interaction process of the aggregators, the interaction information of each power resource in the target power grid and the scoring value of each power interaction are determined, including:

[0086] Step 402: Calculate the power interaction score based on the data from each aggregator and the aggregator resource interaction process.

[0087] Specifically, due to the heterogeneity of FRs, the energy regulation capabilities and actual power fluctuations of different resources vary. To ensure the overall power level stability of VPPs and the orderly conduct of their internal transactions, a transaction quality evaluation coefficient is constructed based on transaction completion status to incentivize them to improve transaction completion and gain a greater competitive advantage, as shown in the following formula.

[0088]

[0089] In the formula: a i,t This is a transaction evaluation coefficient. Actual delivery value, P i,t This refers to the contract volume; 2% is the allowable deviation from the contract.

[0090] The interactive score of electricity trading participants is the result of long-term participation in market transactions, calculated on a 24-hour cycle using a transaction evaluation coefficient 'a'. i,t Update the power interaction score:

[0091]

[0092]

[0093] In the formula, R E,i (t): The transaction value in the current trading period; R E,i (t-1): The power interaction score value in the previous cycle; The transaction quality assessment coefficient for the current trading period is higher than the transaction interaction score, reward value, and penalty value of the previous period.

[0094] Step 404: Calculate the initial power interaction information based on the data from each aggregator and the resource interaction process of each aggregator.

[0095] The initial power interaction information can be the calculation result obtained from the first calculation of the electricity purchase price and the electricity sales price.

[0096] Specifically, based on the data from each aggregator and the resource interaction process of aggregators, initial power interaction information is calculated. The initial bid is used as the basis for matching aggregator data in the first round of transactions. If the transaction in this round is unsuccessful, a second round of matching will be conducted using the reserve price, and finally, the power grid will absorb and compensate the aggregator for the difference in power volume. The reserve price for the electricity sales agency (Agg) is set based on the relationship between generation cost and generation volume, while the reserve price for the electricity purchase agency (Agg) is determined based on the relationship between the energy efficiency and net load assessed by the purchase agency, according to the unit energy utilization efficiency. The initial bids for the electricity purchase and sales agencies are as follows:

[0097]

[0098]

[0099] In the formula: λ i (t), λ j (t) represents the electricity purchase Agg and the electricity sale Agg, respectively; λ grid λ(t) and λ0(t) represent the electricity sales price and grid connection price of the power grid, respectively; μ∈(0,1) represents the electricity purchasing agent's preference, which is taken as 0.5 in this paper; c j The power generation cost for aggregator j; These represent the predicted output and load of distributed energy resources for aggregator j during time period t.

[0100] Step 406: Adjust the initial power interaction information according to the power interaction score to obtain the power resource interaction information.

[0101] Specifically, an interaction quality evaluation coefficient is established based on each power interaction score. Through comprehensive analysis and weighing of each score, a comprehensive coefficient reflecting the quality of power interaction is derived. Subsequently, the initial power interaction information is adjusted using this evaluation coefficient. This involves adjusting the weights of different scores and correcting relevant parameters to ensure an effective improvement in interaction quality. Finally, the adjusted power resource interaction information represents the final evaluation result for each indicator after considering comprehensive quality factors, providing a reliable basis for optimizing the power interaction system.

[0102] In this embodiment, by comprehensively calculating the data and resource interaction processes of each aggregator, the system successfully generated various power interaction scores, thus providing a basis for the effective assessment of power resources. Based on this data, the system further calculated the initial power interaction information, comprehensively considering key factors such as power resource type, capacity, and interoperability. By utilizing the power interaction scores, the system precisely adjusted the initial power interaction information, ensuring that each resource interaction was optimized while considering comprehensive scoring factors. This process provides beneficial effects for the optimal utilization of power resources, ensuring that the system adjusts and optimizes power resource interaction information in a balanced manner from all aspects, thereby improving the overall operating efficiency and stability of the power system.

[0103] In one embodiment, such as Figure 5 As shown, based on each power interaction score, the initial power interaction information is adjusted to obtain each power interaction score, including:

[0104] Step 502: Construct an interaction quality evaluation coefficient based on each power interaction score.

[0105] Among them, the interaction quality evaluation coefficient can be used to evaluate the quality of the target power grid in the process of power resource interaction.

[0106] Specifically, a transaction quality evaluation coefficient is constructed using the various electricity interaction scores of the electricity purchasing and selling agencies. This coefficient incentivizes each agency to actively participate in VPP intra-transactions and ensures contract fulfillment. The formula is as follows:

[0107]

[0108] Step 504: Adjust each initial power interaction information according to the interaction quality evaluation coefficient to obtain each power interaction score.

[0109] Specifically, in adjusting the initial power interaction information based on the interaction quality evaluation coefficient, firstly, for each evaluation indicator, the weight is adjusted by multiplying it by the corresponding interaction quality evaluation coefficient. This involves accurately considering the relative importance of each indicator to ensure that high-influence factors are more significantly reflected. Secondly, for each score value, appropriate weighting and correction are performed according to its weight in the interaction quality evaluation coefficient. This helps to comprehensively consider the relative importance of each indicator during the adjustment process, so as to more accurately reflect the actual situation of power interaction quality. Finally, through this meticulous adjustment process, a power interaction score value that has been comprehensively considered and weighed is obtained, providing strong support for system performance optimization. The formula is as follows:

[0110]

[0111] In the formula: Transaction price of electricity; ξ i,j (t): Interaction quality evaluation coefficient; Electricity sales Agg power interaction score and electricity purchase Agg power interaction score.

[0112] In this embodiment, by constructing an interaction quality evaluation coefficient based on power interaction scoring values, the system achieves accurate quantification of the quality of power resource interactions. This coefficient considers the weight allocation of various scoring indicators, ensuring a comprehensive evaluation of power interactions. Subsequently, using the obtained interaction quality evaluation coefficient, the system intelligently adjusts the initial power interaction information, ensuring that all indicators are optimized while comprehensively considering interaction quality factors. This process effectively improves the overall performance of the power system, ensures efficient coordination and interoperability of resource interactions, and provides beneficial effects for the reliable operation and optimization of the power system.

[0113] In one embodiment, such as Figure 6 As shown, based on the power interaction score, target resource interaction information is selected from the power resource interaction information, including:

[0114] Step 602: Sort the interaction information of each power resource to obtain the output sorting information and input sorting information of each power resource.

[0115] Among them, the power resource output ranking information can be the electricity sales price of the target power grid.

[0116] Among them, the power resource input sorting information can be the electricity purchase price of the target power grid.

[0117] Specifically, based on predefined ranking indicators and weights, the input and output information of each power resource is quantified. Then, by applying appropriate ranking algorithms, such as multi-factor optimization-based ranking algorithms, the output and input information of the power resources are ranked. For example, each time the blockchain system receives a valid bid, it updates the electricity sales queue and the electricity purchase queue in ascending and descending order of bids, respectively. During the ranking process, considering the importance of each indicator, a corresponding comprehensive ranking value is assigned to each power resource. Furthermore, for output information, ranking is based on indicators such as output power and efficiency; for input information, ranking is based on indicators such as input power and stability. Finally, the input ranking information and the overall ranking information of each power resource are obtained.

[0118] Step 604: Determine the target resource interaction information based on the minimum value of the output sorting information of each power resource and the maximum value of the input sorting information of each power resource.

[0119] Specifically, the output ranking information of each power resource is analyzed to identify the minimum value of each power resource's output ranking information. Simultaneously, the input ranking information of each power resource is analyzed to determine its maximum value. Then, based on the relationship between the minimum value of each power resource's output ranking information and the maximum value of each power resource's input ranking information, power resource interaction security verification information is determined. Further, if the power resource interaction security verification information passes the security verification, target resource interaction information is generated based on the minimum value of each power resource's output ranking information and the maximum value of each power resource's input ranking information. If the power resource interaction security verification information fails the security verification, the matching between the minimum value of each power resource's output ranking information and the maximum value of each power resource's input ranking information is deactivated.

[0120] In this embodiment, by quantifying the input and output information of power resources based on predefined ranking indicators and weights, the system can comprehensively and accurately evaluate the performance of each power resource. Applying a multi-factor optimized ranking algorithm, such as the ascending and descending price ranking in a blockchain system, ensures that the comprehensive ranking of output and input information considers the relative importance of various indicators. By analyzing the output ranking information, the system identifies the minimum value of each power resource's output ranking information and determines the maximum value in the input ranking information, providing an accurate basis for the security verification of power resource interactions. If the security verification passes, the system generates target resource interaction information, considering both security and efficiency factors. If the security verification fails, the system removes the matching of minimum and maximum values ​​between output and input information to ensure that power resource interactions proceed under the premise of meeting security standards. This complex and meticulous process effectively safeguards the reliability and stability of the power system and provides beneficial effects for resource interaction.

[0121] In one embodiment, such as Figure 7 As shown, the target resource interaction information is determined based on the minimum value of the output ranking information of each power resource and the maximum value of the input ranking information of each power resource, including:

[0122] Step 702: When the minimum value of the output sorting information of each power resource is greater than the maximum value of the input sorting information of each power resource, generate power resource interaction security verification information based on the minimum value of the output sorting information of each power resource and the maximum value of the input sorting information of each power resource.

[0123] Among them, the power resource interaction security verification information can be the data information obtained by matching the minimum value of the output sorting information of each power resource with the maximum value of the input sorting information of each power resource.

[0124] Specifically, if the minimum value of the output ranking information for each power resource is greater than the maximum value of the input ranking information for each power resource, then the data from the electricity sales aggregator and the electricity purchase aggregator are matched, and the transaction volume is the minimum of the two. If the minimum value of the output ranking information for each power resource is equal to the maximum value of the input ranking information for each power resource, then the ranking and matching are performed based on the power interaction score, and the matching result is input into the security verification algorithm to obtain the power resource interaction security verification information.

[0125] Step 704: If the power resource interaction security verification information passes the security verification of the target power grid, the target resource interaction information is obtained based on the minimum value of the power resource output sorting information and the maximum value of the power resource input sorting information.

[0126] Specifically, if the power resource interaction security verification information passes the security verification of the target power grid, it means that the two are successfully matched. Then, the target resource interaction information is determined based on the minimum value of the output sorting information of each power resource and the maximum value of the input sorting information of each power resource.

[0127] In this embodiment, the system implements a flexible matching mechanism by comparing the minimum value of the output ranking information and the maximum value of the input ranking information for each power resource. When the minimum value of the output ranking information is greater than the maximum value of the input ranking information, the data of the electricity seller and the electricity purchase aggregator are matched, and the transaction volume is the minimum of the two values, thereby ensuring the effective interaction of power resources. When the minimum value of the output ranking information equals the maximum value of the input ranking information, the system performs ranking matching based on the power interaction score and obtains power resource interaction security verification information through a security check algorithm. Only when the security verification is passed is the matching considered successful, and the target resource interaction information can be determined. This process aims to ensure the security and rationality of power resource interaction, ensuring the robust operation of the system and the high efficiency of resource coordination.

[0128] In one embodiment, such as Figure 8 As shown, power resource interaction security verification information is generated based on the minimum value of the power resource output sorting information and the maximum value of the power resource input sorting information, including:

[0129] Step 802: If the minimum value of the power resource output sorting information and the maximum value of the power resource input sorting information are successfully matched, the minimum value of the power resource output sorting information and the maximum value of the power resource input sorting information are matched to obtain the power resource interaction security verification information.

[0130] Specifically, if the minimum value of the output ranking information of each power resource matches the maximum value of the input ranking information of each power resource, the minimum value of the output ranking information of each power resource and the maximum value of the input ranking information of each power resource are matched to obtain a matching result. An appropriate security verification algorithm, such as rules based on thresholds or security restrictions, is used to obtain security verification information for power resource interactions based on the matching result. This includes comparing, analyzing, and verifying the matched values ​​to ensure the security of the interaction process during power system operation.

[0131] Alternatively, in step 804, if the minimum value of each power resource output sorting information and the maximum value of each power resource input sorting information fail to match, the minimum value of each power resource output sorting information and the maximum value of each power resource input sorting information are removed to obtain the remaining power resource output sorting information and power resource input sorting information.

[0132] Specifically, if the minimum value of each power resource output sorting information and the maximum value of each power resource input sorting information fail to match, then either the minimum value of each power resource output sorting information and the maximum value of each power resource input sorting information, or either the minimum value of each power resource output sorting information or the maximum value of each power resource input sorting information, are deleted. The remaining power resource output sorting information and power resource input sorting information are then called the residual power resource output sorting information and power resource input sorting information. Figure 14 This is a schematic diagram of the matching process for one embodiment.

[0133] Step 806: Obtain power resource interaction security verification information based on the remaining power resource output sorting information and the power resource input sorting information.

[0134] Specifically, based on the remaining power resource output sorting information and the power resource input sorting information, the process returns to the step of "determining the target resource interaction information based on the minimum value of each power resource output sorting information and the maximum value of each power resource input sorting information" to obtain power resource interaction security verification information.

[0135] In this embodiment, when the minimum value of the output sorting information and the maximum value of the input sorting information of each power resource successfully match, the system performs a matching operation and verifies the result using an appropriate security verification algorithm to obtain security verification information for power resource interaction. This process includes comparing, analyzing, and verifying the matching values ​​to ensure the security of the interaction process during power system operation. If the matching fails, the system deletes the minimum value of the output sorting information and the maximum value of the input sorting information of the failed-matching power resource, and the remaining power resource output sorting information and input sorting information are used for the next round of matching operations. This flexible matching and verification mechanism effectively addresses potential mismatches, ensuring the reliability and stability of the system. The iterative operation of the entire process aims to ultimately determine the target resource interaction information through precise matching and security verification, providing beneficial effects for the safe operation of the power system.

[0136] In one embodiment, such as Figure 9 As shown, the method also includes:

[0137] Step 902: If the minimum value of the output sorting information of each power resource is less than the maximum value of the input sorting information of each power resource, read the matching time between the output sorting information of each power resource and the input sorting information of each power resource.

[0138] The matching time is the time required to match the power resource output sorting information with the power resource input sorting information.

[0139] Specifically, if the minimum value of the output sorting information of each power resource is less than the maximum value of the input sorting information of each power resource, the server 104 reads the matching time required to match the output sorting information of each power resource with the input sorting information of each power resource, and uses this time to determine whether the matching time has expired or whether two rounds of matching have been completed.

[0140] Step 904: If the matching time exceeds the preset time, determine the target resource interaction information based on the resource absorption information of the target power grid, the output sorting information of each power resource, and the input sorting information of each power resource.

[0141] Among them, the resource absorption information can be the absorption compensation of the target power grid.

[0142] Specifically, if the matching time exceeds the preset time, it indicates that the matching was unsuccessful. A comprehensive evaluation is then performed based on the target grid's resource absorption information, the output ranking information of each power resource, and the input ranking information. This evaluation considers factors such as load demand, output power, and efficiency of the power resources. Subsequently, appropriate optimization algorithms or decision models, such as optimization-based or artificial intelligence methods, are used to determine the target resource interaction information. This process requires comprehensive consideration of factors such as the grid's absorption capacity, the supply and demand relationship of power resources, and system stability to ensure that the determined resource interaction information still meets the safety and efficiency requirements of the power system even in the event of a timeout.

[0143] In this embodiment, when the matching timeout occurs, the system can quickly perform a comprehensive evaluation, considering factors such as load demand, output power, and efficiency of power resources, and intelligently determine the target resource interaction information through optimization algorithms or decision models. The system comprehensively considers key factors such as the grid's resource absorption capacity, the power resource supply and demand relationship, and system stability to ensure that the safety and efficiency requirements of the power system are still met even in the event of a timeout. This intelligent decision-making mechanism improves the robustness of the power system, ensuring the rationality of resource interaction and the stability of the system.

[0144] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0145] Based on the same inventive concept, this application also provides a virtual power plant master-slave multi-chain resource interaction matching device based on an improved consensus algorithm for implementing the aforementioned virtual power plant master-slave multi-chain resource interaction matching method based on an improved consensus algorithm. The solution provided by this device is similar to the implementation scheme described in the above method. Therefore, the specific limitations of one or more embodiments of the virtual power plant master-slave multi-chain resource interaction matching device based on an improved consensus algorithm provided below can be found in the limitations of the virtual power plant master-slave multi-chain resource interaction matching method based on an improved consensus algorithm described above, and will not be repeated here.

[0146] In one embodiment, such as Figure 15 As shown, a virtual power plant master-slave multi-chain resource interaction matching device based on an improved consensus algorithm is provided, including: a model building module 1502, a process building module 1504, a first model calculation module 1506, and a second model calculation module 1508, wherein:

[0147] The model building module 1502 is used to build a virtual power plant interaction architecture model of the target power grid based on the data of each aggregator of the target power grid; the virtual power plant interaction architecture model includes a resource aggregation layer and a distributed resource layer;

[0148] The process construction module 1504 is used to construct the aggregator resource interaction process of the target power grid in the resource aggregation layer based on the data of each aggregator.

[0149] The first model calculation module 1506 is used to input the data of each aggregator and the resource interaction process of the aggregator into the non-cooperative static game model of power resource interaction in the resource aggregation layer to obtain the target resource interaction information.

[0150] The second model calculation module 1508 is used to input the target resource interaction information and the aggregator resource interaction process into the distributed resource layer to obtain power resource interaction consensus information; the power resource interaction consensus information is used by the target power grid to carry out resource interaction.

[0151] In one embodiment, the first model calculation module 1506 is further configured to determine the power resource interaction information and power interaction score of the target power grid based on the data of each aggregator and the resource interaction process of the aggregator; and select the target resource interaction information from the power resource interaction information based on the power interaction score.

[0152] In one embodiment, the first model calculation module 1506 is further configured to calculate each power interaction score based on the data of each aggregator and the resource interaction process of each aggregator; calculate each initial power interaction information based on the data of each aggregator and the resource interaction process of each aggregator; and adjust each initial power interaction information based on each power interaction score to obtain each power resource interaction information.

[0153] In one embodiment, the first model calculation module 1506 is further configured to construct an interaction quality evaluation coefficient based on each power interaction score value; and adjust each initial power interaction information based on the interaction quality evaluation coefficient to obtain each power interaction score value.

[0154] In one embodiment, the first model calculation module 1506 is further configured to sort the interaction information of each power resource to obtain the output sorting information and the input sorting information of each power resource; and to determine the target resource interaction information based on the minimum value of the output sorting information and the maximum value of the input sorting information of each power resource.

[0155] In one embodiment, the first model calculation module 1506 is further configured to generate power resource interaction security verification information based on the minimum value of each power resource output ranking information and the maximum value of each power resource input ranking information when the minimum value of each power resource output ranking information is greater than the maximum value of each power resource input ranking information; and to obtain target resource interaction information based on the minimum value of each power resource output ranking information and the maximum value of each power resource input ranking information when the power resource interaction security verification information passes the security verification of the target power grid.

[0156] In one embodiment, the first model calculation module 1506 is further configured to, when the minimum value of each power resource output sorting information and the maximum value of each power resource input sorting information are successfully matched, match the minimum value of the power resource output sorting information and the maximum value of each power resource input sorting information to obtain power resource interaction security verification information; or, when the minimum value of each power resource output sorting information and the maximum value of each power resource input sorting information fail to match, remove the minimum value of each power resource output sorting information and the maximum value of each power resource input sorting information to obtain the remaining power resource output sorting information and power resource input sorting information; and obtain power resource interaction security verification information based on the remaining power resource output sorting information and power resource input sorting information.

[0157] In one embodiment, the first model calculation module 1506 is further configured to: read the matching time between the power resource output ranking information and the power resource input ranking information when the minimum value of the power resource output ranking information is less than the maximum value of the power resource input ranking information; and determine the target resource interaction information based on the resource absorption information of the target power grid, the power resource output ranking information, and the power resource input ranking information when the matching time exceeds a preset time.

[0158] The modules in the aforementioned virtual power plant master-slave multi-chain resource interaction matching device based on an improved consensus algorithm can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0159] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 16 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores server data. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a virtual power plant master-slave multi-chain resource interaction matching method based on an improved consensus algorithm.

[0160] Those skilled in the art will understand that Figure 16The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0161] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0162] In one embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0163] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and executes the computer instructions, causing the computer device to perform the steps in the above method embodiments.

[0164] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0165] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0166] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0167] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A virtual power plant master-slave multi-chain resource interaction matching method based on an improved consensus algorithm, characterized in that, The method includes: Based on the data from various aggregators in the target power grid, a virtual power plant interaction architecture model for the target power grid is constructed; the virtual power plant interaction architecture model includes a resource aggregation layer and a distributed resource layer. Based on the data of each aggregator, the aggregator resource interaction process of the target power grid is constructed in the resource aggregation layer; The aggregator data and resource interaction processes are input into the non-cooperative static game model of power resource interaction in the resource aggregation layer to obtain target resource interaction information. This includes: determining the power resource interaction information and power interaction score of the target power grid based on the aggregator data and resource interaction processes; sorting the power resource interaction information to obtain power resource output sorting information and power resource input sorting information; if the minimum value of the power resource output sorting information is greater than the maximum value of the power resource input sorting information, and if the minimum value of the power resource output sorting information and the maximum value of the power resource input sorting information fail to match, removing the minimum value of the power resource output sorting information and the maximum value of the power resource input sorting information to obtain remaining power resource output sorting information and remaining power resource input sorting information; obtaining power resource interaction security verification information based on the remaining power resource output sorting information and remaining power resource input sorting information; and obtaining the target resource interaction information based on the minimum value of the power resource output sorting information and the maximum value of the power resource input sorting information if the power resource interaction security verification information passes the security verification of the target power grid. The target resource interaction information and the aggregator resource interaction process are input into the distributed resource layer to obtain power resource interaction consensus information; the power resource interaction consensus information is used by the target power grid for resource interaction.

2. The method according to claim 1, characterized in that, The step of determining the power resource interaction information and power interaction score of the target power grid based on the data of each aggregator and the resource interaction process of the aggregator includes: Calculate the power interaction score based on the data from each aggregator and the resource interaction process of each aggregator. Based on the data from each aggregator and the resource interaction process of the aggregator, calculate each initial power interaction information; Based on the power interaction score, the initial power interaction information is adjusted to obtain the power resource interaction information.

3. The method according to claim 2, characterized in that, The step of adjusting the initial power interaction information according to the power interaction score to obtain the power resource interaction score includes: Based on the power interaction score values, an interaction quality evaluation coefficient is constructed. Based on the interaction quality evaluation coefficient, the initial power interaction information is adjusted to obtain the power resource interaction score value.

4. The method according to claim 1, characterized in that, The method further includes: If the minimum value of each power resource output sorting information and the maximum value of each power resource input sorting information are successfully matched, the minimum value of the power resource output sorting information and the maximum value of the power resource input sorting information are combined to obtain the power resource interaction security verification information.

5. The method according to claim 1, characterized in that, The method further includes: When the minimum value of each power resource output sorting information is less than the maximum value of each power resource input sorting information, the matching time between each power resource output sorting information and each power resource input sorting information is read. If the matching time exceeds a preset time, the target resource interaction information is determined based on the resource absorption information of the target power grid, the power resource output sorting information, and the power resource input sorting information.

6. A virtual power plant master-slave multi-chain resource interaction matching device based on an improved consensus algorithm, characterized in that, The device includes: The model building module is used to construct a virtual power plant interaction architecture model of the target power grid based on the data of each aggregator in the target power grid; the virtual power plant interaction architecture model includes a resource aggregation layer and a distributed resource layer; The process construction module is used to construct the aggregator resource interaction process of the target power grid in the resource aggregation layer based on the data of each aggregator; The first model calculation module is used to input the data of each aggregator and the resource interaction process of the aggregator into the non-cooperative static game model of power resource interaction in the resource aggregation layer to obtain target resource interaction information, including: determining the power resource interaction information and the power interaction score of the target power grid according to the data of each aggregator and the resource interaction process of the aggregator; sorting the power resource interaction information to obtain the power resource output sorting information and the power resource input sorting information; and, if the minimum value of the power resource output sorting information is greater than the maximum value of the power resource input sorting information, further sorting the power resource output sorting information according to the power resource input sorting information. If the minimum value of the power resource output sorting information and the maximum value of the power resource input sorting information fail to match, the minimum value of the power resource output sorting information and the maximum value of the power resource input sorting information are removed to obtain the remaining power resource output sorting information and the remaining power resource input sorting information. Based on the remaining power resource output sorting information and the remaining power resource input sorting information, power resource interaction security verification information is obtained. If the power resource interaction security verification information passes the security verification of the target power grid, the target resource interaction information is obtained based on the minimum value of the power resource output sorting information and the maximum value of the power resource input sorting information. The second model calculation module is used to input the target resource interaction information and the aggregator resource interaction process into the distributed resource layer to obtain power resource interaction consensus information; the power resource interaction consensus information is used by the target power grid for resource interaction.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

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