Blockchain-based main and distribution network flexibility resource transaction method and system

Abstract

The present application belongs to the technical field of blockchain flexible transaction, and discloses a main and distribution network flexibility resource transaction method and system based on blockchain, which comprises the following steps: acquiring TSO system and DSO system internal resource transaction information respectively, constructing TSO flexibility resource transaction model and DSO flexibility resource transaction model, carrying out flexible sharing and obtaining TSO flexible operation cost and DSO-m flexible operation cost, establishing Nash bargaining model based on TSO flexible operation cost and DSO-m flexible operation cost, decomposing Nash bargaining model by using ADMM algorithm and solving to obtain flexibility resource transaction quantity and transaction price between TSO and DSO, and regarding it as final transaction reached by all parties. The main and distribution network flexibility resource transaction method and system based on blockchain are adopted, the resource quantification and pricing problems in the flexibility resource transaction process of main and distribution network are successfully solved, the user privacy in the transaction process is protected, and fair and reliable resource transaction is realized.

Description

Technical Field

[0001] This invention relates to the field of blockchain flexible transaction technology, and in particular to a blockchain-based method and system for flexible resource trading in primary and secondary networks. Background Technology

[0002] With the rapid development of renewable energy in recent years, their installed capacity and power generation have experienced explosive growth. However, renewable energy sources such as wind and solar power are highly volatile and unpredictable. These factors make power supply more unstable and difficult to predict. To maintain grid stability, flexibility resources are essential for rapid response and adjustment of the balance between power generation and load. Flexibility resources refer to various technologies and means that can provide adjustment and dispatch capabilities in the power system to cope with power supply and demand imbalances, load changes, and unexpected events.

[0003] There are a large number of flexible resources in the transmission system operator (TSO) and distribution system operator (DSO). In order to improve the resource utilization efficiency of the entire power system, studying the cross-system trading of flexible resources between them has become an urgent problem to be solved.

[0004] However, existing technologies still have significant shortcomings in establishing flexible resource trading models for primary and distribution networks (i.e., TSOs and DSOs) and protecting user data privacy. First, most existing research focuses on flexible resource trading within each TSO and DSO, with limited research on cross-system resource trading (i.e., determining resource trading volumes and prices). Second, in many studies, to obtain the optimal resource trading scheme, users must disclose some parameters within their power grid, such as local resource price information. This information is often sensitive and involves corporate privacy. Most systems still use traditional encryption methods to protect user transaction data, but these methods typically do not allow calculations without decrypting the data. Furthermore, many existing systems rely on third-party institutions to verify the authenticity and integrity of the data, which not only increases costs and complexity but may also lead to centralized risks, such as the dishonesty or bankruptcy of third-party institutions.

[0005] Therefore, the existing technology has the following drawbacks:

[0006] Lack of a transaction model: In order to attract users, it is necessary to ensure that the transaction is fair, that is, to reasonably determine the transaction volume and transaction price of resources.

[0007] Privacy breach: During the transaction process, users must disclose their energy data, which may lead to the leakage of trade secrets or other private information.

[0008] Reliance on third parties: Many systems rely on third-party institutions to verify the authenticity and integrity of data, which not only increases costs and complexity, but may also lead to risks of centralization and trust issues.

[0009] In conclusion, to ensure the successful completion of flexible resource transactions between TSOs and DSOs while protecting user privacy, we urgently need a blockchain-based method and system for trading flexible resources between primary and secondary networks. Summary of the Invention

[0010] The purpose of this invention is to provide a blockchain-based method and system for trading flexible resources in a primary and secondary distribution network. This method successfully solves the problems of resource quantification and pricing in the trading process, while also protecting user privacy and ensuring fair and reliable resource transactions. The specific details are as follows:

[0011] Blockchain-based methods for trading flexible resources in primary and secondary distribution networks include:

[0012] S1. Obtain resource transaction information from the TSO system and DSO system respectively to construct the TSO flexible resource transaction model and the DSO flexible resource transaction model;

[0013] S2. Flexible sharing of the TSO flexible resource trading model and the DSO flexible resource trading model, and derivation of the flexible operating costs of TSO and DSO-m.

[0014] S3. Establish a Nash bargaining model based on the flexible operating costs of TSO and DSO-m;

[0015] S4. Use the ADMM algorithm to decompose the Nash bargaining model and solve for the flexible resource transaction volume and transaction price between TSO and DSO, which is considered as the parties reaching a final transaction.

[0016] Preferably, the expressions for the flexible operating cost of TSO and the flexible operating cost of DSO-m are as follows:

[0017]

[0018] in, The cost of TSOs when engaging in flexible resource sharing. τ represents the cost of DSO-m when implementing flexible resource sharing. m For the money that TSO pays to DSO-m, π m The money that DSO-m receives from TSO. The set consisting of all DSOs For the set of nodes of TSO, Let n be the set of downlink resource service providers. Let n be the set of uplink resource service providers. and Let k represent the uplink and downlink flexibility resource service provider k for node n in the TSO table. and These represent the corresponding flexible resource transaction volumes.

[0019] The preferred expression for the Nash bargaining model is:

[0020]

[0021] in, The operating cost of a TSO when it operates independently without flexible resource sharing. This refers to the operating cost of DSO-m when it operates independently without flexible resource sharing.

[0022] Preferably, the specific details of using the ADMM algorithm to decompose the Nash bargaining model and simultaneously obtain the flexible resource trading volume and price between TSO and DSO are as follows:

[0023] The Nash bargaining model is transformed into a problem of minimizing social energy costs and a problem of distributing benefits, and constraints are set for each respectively.

[0024] The ADMM algorithm is used to solve the social energy cost minimization problem and the benefit distribution problem respectively, so as to facilitate the parties to reach a final transaction.

[0025] The specific content solved using the ADMM algorithm is as follows:

[0026] Based on the problems of minimizing social energy costs and distributing benefits, augmented Lagrange functions are constructed and Lagrange multipliers are set.

[0027] The DSO-m optimization equation and TSO optimization equation are constructed based on Lagrange multipliers and iterated until the algorithm termination condition is met, which yields the transaction volume of the flexible resource transaction reached by all parties.

[0028] The preferred expression for minimizing social energy costs is:

[0029]

[0030] The constraints are as follows:

[0031]

[0032] in, and Let represent the amount of resources that TSO and DSO-m trade with each other. These two variables are subject to the constraints of their respective internal power grids, and they must be equal when the trade is finalized. Furthermore, this problem omits the remaining internal power grid constraints of TSO and DSO.

[0033] The preferred expression for the benefit distribution problem is:

[0034]

[0035] The constraints are as follows:

[0036] τ m =π m ;

[0037] Among them, I * The meaning is derived from solving the problem of minimizing social energy costs, including The optimal solutions for various variables, including those mentioned above, are substituted as constants into the profit distribution problem to solve for resource prices. The constraint states that the price paid by TSO to DSO-m must be consistent with the price received by DSO-m from TSO.

[0038] The preferred update rule for Lagrange multipliers is:

[0039]

[0040] Where, λ m For Lagrange multipliers, ρ m The penalty coefficient is... This represents the transaction volume of flexibility resources calculated by TSO in round k+1. Let DSO-m be the transaction volume of flexibility resources calculated in round k+1.

[0041] Preferably, during the iteration process, each DSO first calculates based on the results obtained in the previous round. Calculate this round Then DSO will The data is passed to the TSO, which then calculates the current round's... The results are then returned to each DSO, and the Lagrange multipliers are updated globally.

[0042] The process continues iterating until the algorithm's termination condition is met. The termination condition is set as follows: and If the absolute value of the difference between the two is less than the target value, it means that the parties have reached an agreement on the transaction volume of the flexibility resource.

[0043] A blockchain-based primary and secondary network flexibility resource trading system includes:

[0044] Basic model building unit: Obtain resource transaction information from the TSO system and DSO system respectively to build the TSO flexible resource transaction model and the DSO flexible resource transaction model;

[0045] Cost push-down unit: The flexible resource trading model of TSO and the flexible resource trading model of DSO are flexibly shared and pushed down to obtain the flexible operating cost of TSO and the flexible operating cost of DSO-m;

[0046] Main model building unit: Establishing a Nash bargaining model based on the flexible operating costs of TSO and DSO-m;

[0047] Iterative solution unit: The ADMM algorithm is used to decompose the Nash bargaining model and solve for the flexible resource transaction volume and transaction price between TSO and DSO, which is considered as the final transaction reached by all parties.

[0048] An electronic device is characterized by comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the content of the blockchain-based main and distribution network flexibility resource trading method when it calls the computer program in the memory.

[0049] A storage medium storing computer-executable instructions, which, when loaded and executed by a processor, implement the content of the blockchain-based main and distribution network flexible resource trading method.

[0050] Therefore, the present invention employs the above-mentioned blockchain-based main and distribution network flexibility resource trading method and system, which has the following advantages compared with existing methods:

[0051] 1. This invention is the first to apply the Nash bargaining model to cross-system flexible resource trading between primary and distribution networks, in order to determine the optimal resource trading volume and price;

[0052] 2. The ADMM algorithm is used to decompose the Nash bargaining model into sub-problems. Each party only needs to calculate the sub-problems locally to obtain the optimal solution through iteration. This means that each party does not need to disclose local information during the transaction process, thus protecting user privacy.

[0053] 3. This invention utilizes blockchain smart contracts to automate the iterative process of the ADMM algorithm, and all transaction data will be securely and immutably stored on the blockchain.

[0054] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0055] Figure 1This is a flowchart illustrating the steps of a blockchain-based primary and secondary network flexibility resource trading method.

[0056] Figure 2 This is a schematic diagram of a blockchain-based main and distribution network flexible resource trading system. Detailed Implementation

[0057] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0058] like Figure 1 As shown, this application mentions a blockchain-based method for trading flexible resources in a primary distribution network. This blockchain-based method for trading flexible resources in a primary distribution network provides a unique solution by combining the Nash bargaining model, the Alternating Direction Method of Multipliers (ADMM), and a blockchain system.

[0059] The Nash bargaining model is used to find the optimal resource trading volume and price while ensuring the fairness and rationality of the transaction. The ADMM algorithm can be used to decompose the centralized Nash bargaining optimization problem into multiple subproblems. The TSO and DSO only need to solve the subproblems locally and share the local solutions to reach a transaction through rounds of iteration without leaking privacy.

[0060] Blockchain-based smart contracts can automate the ADMM algorithm iteration process. The blockchain system ensures independence from third parties, which not only enhances privacy protection but also improves the reliability and efficiency of resource transactions. Specific details include:

[0061] S1. Obtain resource transaction information from the TSO system and DSO system respectively to construct the TSO flexible resource transaction model and the DSO flexible resource transaction model;

[0062] Before studying cross-system resource trading between TSOs and various DSOs, we first establish their respective internal flexible resource trading models. Taking TSOs as an example, the optimization problem is as follows:

[0063]

[0064] Its constraints are as follows:

[0065]

[0066] in, and These represent the quotes from resource service provider k, which indicates the uplink and downlink flexibility of node n in the TSO. and These represent the corresponding flexible resource transaction volumes, where, The cost of TSOs when engaging in flexible resource sharing. τ represents the cost of DSO-m when implementing flexible resource sharing. m For the money that TSO pays to DSO-m, π m The money that DSO-m receives from TSO. The set consisting of all DSOs For the set of nodes of TSO, Let n be the set of downlink resource service providers. Let n be the set of uplink resource service providers. and Let k represent the uplink and downlink flexibility resource service provider k for node n in the TSO table. and These represent the corresponding flexible resource transaction volumes. The power on line ij, Inject the expected power into node n. Let n be the expected power load. For flexible resource trading volume of TSO and DSO-n, For sensitivity factor, Let TSO be the set of all its lines. The optimization problem is to minimize operating costs while ensuring stable grid operation. Similarly, a trading model for the internal flexibility resources of DSO can be established, similar to the model above.

[0067] S2. Flexible sharing of the TSO flexible resource trading model and the DSO flexible resource trading model, and derivation of the flexible operating costs of TSO and DSO-m.

[0068] The operating cost of TSO is:

[0069]

[0070] The operating cost of DSO-m is:

[0071]

[0072] in, The cost function for TSO running independently. The cost function for DSO-m running independently (this is the same as above). no the same, This represents the result of a completed calculation. It is a function that generates additional costs and benefits on top of the above formula when TSO and DSO share flexible resources.

[0073] Preferably, the expressions for the flexible operating cost of TSO and the flexible operating cost of DSO-m are as follows:

[0074]

[0075]

[0076] in, The cost of TSOs when engaging in flexible resource sharing. τ represents the cost of DSO-m when implementing flexible resource sharing. m For the money that TSO pays to DSO-m, π m The money that DSO-m receives from TSO. The set consisting of all DSOs For the set of nodes of TSO, Let n be the set of downlink resource service providers. Let n be the set of uplink resource service providers. and Let k represent the uplink and downlink flexibility resource service provider k for node n in the TSO table. and These represent the corresponding flexible resource transaction volumes.

[0077] In other words, the TSO will pay a price based on the flexibility of the resources traded by both parties, while the DSO will generate revenue accordingly.

[0078] S3. Establish a Nash bargaining model based on the flexible operating costs of TSO and DSO-m;

[0079] The preferred expression for the Nash bargaining model is:

[0080]

[0081] In this optimization problem, the goal is to find the resource transaction volume and price that maximizes the interests of all parties. and The point of contention in the Nash bargaining problem represents the cost when the parties only engage in flexible resource transactions internally. Each term in the formula is the cost of internal transactions minus the cost of participating in resource sharing, yielding the reduction in cost, i.e., the benefit. Maximizing the product of the benefits for each party, while adding all necessary constraints, leads to the objective optimization problem of the Nash bargaining model.

[0082] S4. Use the ADMM algorithm to decompose the Nash bargaining model and solve for the flexible resource transaction volume and transaction price between TSO and DSO, which is considered as the parties reaching a final transaction.

[0083] Preferably, the specific details of using the ADMM algorithm to decompose the Nash bargaining model and simultaneously obtain the flexible resource trading volume and price between TSO and DSO are as follows:

[0084] The Nash bargaining model is transformed into a problem of minimizing social energy costs and a problem of distributing benefits, and constraints are set for each respectively.

[0085] By using the ADMM algorithm to solve the social energy cost minimization problem and the benefit distribution problem respectively, it is possible to facilitate a final transaction among all parties while protecting the privacy of information.

[0086] The specific content solved using the ADMM algorithm is as follows:

[0087] Based on the problems of minimizing social energy costs and distributing benefits, augmented Lagrange functions are constructed and Lagrange multipliers are set.

[0088] The DSO-m optimization equation and TSO optimization equation are constructed based on Lagrange multipliers and iterated until the algorithm termination condition is met, which yields the transaction volume of the flexible resource transaction reached by all parties.

[0089] The preferred expression for minimizing social energy costs is:

[0090]

[0091] The constraints are as follows:

[0092]

[0093] in, and Let represent the amount of resources that TSO and DSO-m trade with each other. These two variables are subject to the constraints of their respective internal power grids, and they must be equal when the trade is finalized. Furthermore, this problem omits the remaining internal power grid constraints of TSO and DSO.

[0094] The preferred expression for the benefit distribution problem is:

[0095]

[0096] The constraints are as follows:

[0097] τ m =π m ;

[0098] Among them, I * The meaning is derived from solving the problem of minimizing social energy costs, including The optimal solutions for various variables, including those mentioned above, are substituted as constants into the benefit distribution problem to solve for resource prices. The constraint states that the price paid by TSO to DSO-m must be consistent with the price received by DSO-m from TSO. The social energy cost minimization problem is Problem 1), and the benefit distribution problem is Problem 2).

[0099] The preferred update rule for Lagrange multipliers is:

[0100]

[0101] Preferably, during the iteration process, each DSO first calculates based on the results obtained in the previous round. Calculate this round Then DSO will The data is passed to the TSO, which then calculates the current round's... The results are then returned to each DSO, and the Lagrange multipliers are updated globally.

[0102] The process continues iterating until the algorithm's termination condition is met. The termination condition is set as follows: and If the absolute value of the difference between the two is less than the target value, and the target value is a very small number, it means that the parties have reached an agreement on the transaction volume of the flexibility resource.

[0103] like Figure 2 As shown, this application mentions a blockchain-based main and distribution network flexibility resource trading system, including:

[0104] Basic model building unit: Obtain resource transaction information from the TSO system and DSO system respectively to build the TSO flexible resource transaction model and the DSO flexible resource transaction model;

[0105] Cost push-down unit: The flexible resource trading model of TSO and the flexible resource trading model of DSO are flexibly shared and pushed down to obtain the flexible operating cost of TSO and the flexible operating cost of DSO-m;

[0106] Main model building unit: Establishing a Nash bargaining model based on the flexible operating costs of TSO and DSO-m;

[0107] Iterative solution unit: The ADMM algorithm is used to decompose the Nash bargaining model and solve for the flexible resource transaction volume and transaction price between TSO and DSO, which is considered as the final transaction reached by all parties.

[0108] An electronic device is characterized by comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the content of the blockchain-based main and distribution network flexibility resource trading method when it calls the computer program in the memory.

[0109] A storage medium storing computer-executable instructions, which, when loaded and executed by a processor, implement the content of the blockchain-based main and distribution network flexible resource trading method.

[0110] Example 1

[0111] The solution process for the problem of minimizing social energy costs is as follows:

[0112] First, construct the augmented Lagrange function:

[0113]

[0114] Where, λ m As Lagrange multipliers, the optimization problems within TSO and DSO-m in each iteration are defined below, i.e., the subproblems after decomposition:

[0115] The (k+1)th round optimization of DSO-m is:

[0116]

[0117] The (k+1)th round optimization of TSO is:

[0118]

[0119] The update rule for Lagrange multipliers is:

[0120]

[0121] In each round, each DSO first calculates based on the results of the previous round. Calculate this round Then DSO will The data is passed to the TSO, which then calculates the current round's... The results are then returned to each DSO, and the Lagrange multipliers are updated globally.

[0122] The process continues iterating until the algorithm's termination condition is met. The termination condition is set as follows: and If the absolute value of the difference is less than a very small number, it indicates that the parties have reached an agreement on the transaction volume of the flexibility resources. In the above process, the calculations for the TSO and each DSO are performed locally, effectively protecting the information privacy of all parties. Using the same calculation method, the profit distribution problem can be solved to obtain the transaction price of the flexibility resources. When both the transaction volume and transaction price of the flexibility resources between the TSO and each DSO are obtained, it is considered that the parties have reached a final agreement.

[0123] Smart contracts can automate flexible resource transactions as follows: First, each node (TSO or DSO) calculates its local optimization problem based on parameters obtained from the blockchain (from the previous round of calculation) and stores the result in the blockchain. Next, a smart contract is executed on the blockchain based on the calculation results of each node to update the Lagrange multipliers, and the result is also stored in the blockchain. Simultaneously, the smart contract determines whether the termination condition of the ADMM algorithm has been met in this round; if so, an event is triggered to notify all nodes that the transaction is complete.

[0124] Example 2

[0125] Considering the diversity of designs, this invention primarily focuses on a blockchain-based primary-secondary network flexible resource trading system. Its core objective is to find a fair and reasonable resource trading scheme and protect user privacy to incentivize greater user participation. Theoretically, the following potential alternative strategies can be explored:

[0126] Proxy re-encryption technology: Users can use proxy re-encryption to entrust their encrypted energy data to a third party for processing and verification, eliminating the need for data decryption.

[0127] Homomorphic encryption can be used to perform calculations on energy data from all parties without decryption, thereby verifying the authenticity and integrity of the data and ensuring its security.

[0128] Data obfuscation strategy: By using data obfuscation technology, energy data from multiple users can be merged together and processed and verified as a whole, thus protecting the data privacy of each user.

[0129] Multi-party secure computation method: Employing multi-party computation allows multiple users to collaboratively compute the output of a function without disclosing their respective inputs, thus protecting the privacy of seller data.

[0130] After a smart contract executes an operation, it triggers an event. The Oracle listens for these events and transmits the relevant data to the off-chain system.

[0131] Acquiring event data: The Oracle listens for smart contract events (such as DSOResultSubmitted or AllDSOResultsReceived) by connecting to the blockchain node. Once an event is detected, the Oracle reads the event data and initiates off-chain operations.

[0132] Data processing: The Oracle transmits on-chain data to off-chain systems (such as optimized algorithms written in Python, Go, Java, etc.). The off-chain system performs calculations based on the received parameters, such as the DSO or TSO subproblems in the ADMM algorithm.

[0133] Return Results: After the off-chain system completes the calculation, it writes the result back to the blockchain smart contract via an Oracle. The Oracle then calls a function in the smart contract (such as submitDSOResult() or submitTSOResult()) to submit the off-chain calculation result to the blockchain.

[0134] Data acquisition (collecting power balance data, line transmission data, and flexibility resource provision and demand data within TSO and DSO)

[0135] Establish a market model for flexible resource trading based on the interaction between TSOs and DSOs; (resource scheduling volume and bid price of TSOs and DSOs) (determine the parameters and variables in the model, such as the net actual power inflow of nodes, expected basic power inflow and load, bid price and resource scheduling volume of service providers, etc.)

[0136] The final resource transaction volume and resource price are obtained based on the market model;

[0137] By recording the final resource transaction volume and price on the blockchain as a reference for the next round of calculations, the model parameters and constraints are updated as needed to reflect changes in the power system.

[0138] TSO calculation and optimization:

[0139] TSO performs preliminary calculations based on its independent operation model to obtain preliminary resource scheduling quantities and costs under various constraints.

[0140] These results will be recorded on the blockchain for use by the DSO in subsequent steps.

[0141] DSO obtains the calculation results of TSO:

[0142] Each DSO retrieves the computation results of the previous round of TSO from the blockchain and uses them as parameters for the current round of problems.

[0143] This ensures that each DSO can use the latest TSO data for local optimization.

[0144] Local computation and optimization of DSO:

[0145] DSO nodes perform off-chain calculations based on their local sub-problems (which may include load forecasting, local generation status, availability of flexibility resources, etc.) and the results obtained from TSO.

[0146] Calculate the resource demand and price under the condition of satisfying local constraints.

[0147] Determine resource trading volume and price:

[0148] By using a mechanism in the market model (such as auctions or bidding), combined with the resource allocation volume and bid price of TSO and DSO, the final resource transaction volume and resource price are determined.

[0149] This process may require multiple iterations until the market clearing point is reached or other termination conditions are met.

[0150] Records and updates:

[0151] The final resource transaction volume and price will be recorded on the blockchain as a reference for the next round of calculations.

[0152] The model parameters and constraints are updated as needed to reflect changes in the power system.

[0153] At the end of the first phase, each DSO node generates a temporary plan based on its own situation, and in the second phase, TSO nodes use these plans to generate a new global resource allocation or scheduling plan.

[0154] Phase 1: Calculation of DSO Nodes

[0155] Retrieve the calculation results of the previous round of TSO from the chain: Each DSO retrieves the calculation results of the previous round of TSO from the chain and uses them as parameters for the current round of problems.

[0156] Perform local computation: The DSO node performs off-chain computation based on its local subproblem and the results of the TSO to obtain the temporary result for this round.

[0157] Write the results to the blockchain: The DSO node writes the calculated results to the blockchain via an oracle.

[0158] Triggering event: The smart contract records the result of each DSO and triggers the DSOResultSubmitted event.

[0159] Wait for all DSOs to complete commit: Once all DSOs have been committed, an AllDSOResultSubmitted event is triggered, indicating that the TSO can begin computation.

[0160] Phase Two: Computation of TSO Nodes

[0161] Listen for events and collect data: TSO listens for the AllDSOResultSubmitted event and collects the provisional results of all DSOs (as parameters for its own optimization problem).

[0162] Perform off-chain computation: After receiving the results of all DSOs, the TSO node begins off-chain computation to obtain new temporary TSO results.

[0163] Update blockchain data: TSO updates the calculation results to the smart contract via Oracle and triggers the TSOResultSubmitted event.

[0164] Repeat the above steps: DSO listens for the TSOResultSubmitted event, retrieves the latest TSO result from the chain, and then repeats the steps of the first phase.

[0165] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A blockchain-based method for trading flexible resources in a primary and secondary distribution network, characterized by: include: S1. Obtain resource transaction information from the TSO system and DSO system respectively to construct the TSO flexible resource transaction model and the DSO flexible resource transaction model; S2. Flexible sharing of the TSO flexible resource trading model and the DSO flexible resource trading model, and derivation of the flexible operating costs of TSO and DSO-m. The expressions for the flexible operating costs of TSO and DSO-m are as follows: ； ； in, The cost of TSOs when engaging in flexible resource sharing. The cost of DSO-m when implementing flexible resource sharing. The money that TSO pays to DSO-m The money that DSO-m receives from TSO. The set consisting of all DSOs For the set of nodes of TSO, Let n be the set of downlink resource service providers. Let n be the set of uplink resource service providers. and Let k represent the uplink and downlink flexibility resource service provider k for node n in the TSO table. and These represent the corresponding flexible resource transaction volumes; S3. Establish a Nash bargaining model based on the flexible operating costs of TSO and DSO-m; The expression for the Nash bargaining model is: ； in, The operating cost of a TSO when it operates independently without flexible resource sharing. The operating cost of DSO-m when it operates independently without flexible resource sharing; S4. Use the ADMM algorithm to decompose the Nash bargaining model and solve for the flexible resource transaction volume and transaction price between TSO and DSO, which is considered as the parties reaching a final transaction.

2. The blockchain-based primary and secondary network flexibility resource trading method according to claim 1, characterized in that, The ADMM algorithm is used to decompose the Nash bargaining model and solve for the specific details of the flexible resource trading volume and price between TSO and DSO: The Nash bargaining model is transformed into a problem of minimizing social energy costs and a problem of distributing benefits, and constraints are set for each respectively. The ADMM algorithm is used to solve the social energy cost minimization problem and the benefit distribution problem respectively, so as to facilitate the parties to reach a final transaction. The specific content solved using the ADMM algorithm is as follows: Based on the problems of minimizing social energy costs and distributing benefits, augmented Lagrange functions are constructed and Lagrange multipliers are set. The DSO-m optimization equation and TSO optimization equation are constructed based on Lagrange multipliers and iterated until the algorithm termination condition is met, which yields the transaction volume of the flexible resource transaction reached by all parties.

3. The blockchain-based primary and secondary network flexibility resource trading method according to claim 1, characterized in that, The expression for the social energy cost minimization problem is: ； The constraints are as follows: ； in, and This represents the amount of resources that TSO and DSO-m trade with each other. These two variables are respectively subject to the constraints of their respective internal power grids, and they must be equal when the transaction is finally completed. The expression for the problem of profit distribution is: ； The constraints are as follows: ； in, The meaning is derived from solving the problem of minimizing social energy costs, including The optimal solution for various variables, including the resource price, is substituted as a constant into the problem of benefit distribution. The constraint indicates that the price paid by TSO to DSO-m must be consistent with the price received by DSO-m from TSO.

4. The blockchain-based primary and secondary network flexibility resource trading method according to claim 1, characterized in that, The update rule for Lagrange multipliers is: ； in, For Lagrange multipliers, The penalty coefficient is... This represents the transaction volume of flexibility resources calculated by TSO in round k+1. Let DSO-m be the transaction volume of flexibility resources calculated in round k+1.

5. The blockchain-based primary and secondary network flexibility resource trading method according to claim 1, characterized in that, During the iteration process, each DSO first calculates based on the results of the previous round. Calculate the current round Then the DSO will The data is passed to the TSO, which then calculates the current round's... The results are then returned to each DSO, and the Lagrange multipliers are updated globally. The process continues iterating until the algorithm's termination condition is met. The termination condition is set as follows: and If the absolute value of the difference between the two is less than the target value, it means that the parties have reached an agreement on the transaction volume of the flexibility resource.

6. A blockchain-based primary and secondary network flexibility resource trading system, characterized in that: To perform the method of claim 1, comprising: Basic model building unit: Obtain resource transaction information from the TSO system and DSO system respectively to build the TSO flexible resource transaction model and the DSO flexible resource transaction model; Cost push-down unit: The flexible resource trading model of TSO and the flexible resource trading model of DSO are flexibly shared and pushed down to obtain the flexible operating cost of TSO and the flexible operating cost of DSO-m; Main model building unit: Establishing a Nash bargaining model based on the flexible operating costs of TSO and DSO-m; Iterative solution unit: The ADMM algorithm is used to decompose the Nash bargaining model and solve for the flexible resource transaction volume and transaction price between TSO and DSO, which is considered as the final transaction reached by all parties.

7. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and the processor, when calling the computer program in the memory, implements the content of the blockchain-based main and distribution network flexibility resource trading method as described in any one of claims 1 to 5.

8. A storage medium, characterized in that, The storage medium stores computer-executable instructions, which, when loaded and executed by a processor, implement the content of the blockchain-based main and distribution network flexibility resource trading method as described in any one of claims 1 to 5.

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