Green electricity transaction tracing method and system

Abstract

The invention relates to the technical field of electricity markets, in particular to a green electricity transaction tracing method and system, and the method comprises the following steps: collecting original green electricity transaction information generated after the transaction of a green electricity producer is completed, and carrying out the preprocessing of the original green electricity transaction information, and obtaining the standardized green electricity transaction information; verifying the standardized green electricity transaction information by using an intelligent contract, and calculating a decision factor value of each node in the block chain network by using a node decision model after the verification is passed; based on the decision factor value, using a diffusion storage strategy to perform uplink storage on the verified standardized green electricity transaction information; and retrieving each block in the block chain according to the query information provided by the producer, thereby obtaining the corresponding traceability information and feeding back the traceability information to the producer. According to the method, the security of the consensus node is improved by using the node judgment model and the diffusion storage strategy, the transaction processing speed and throughput are improved, and the credibility and speed of transaction tracing are further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power market, and in particular to a method and system for tracking and tracing green electricity transactions. Background Art

[0002] As global climate change and environmental protection become a global consensus, green electricity, as an important component of renewable energy, is becoming increasingly important. With the advancement of technology and the promotion of policies, the green electricity trading market is experiencing unprecedented rapid development. However, the prosperity of this market has also led to a rapid increase in the speed of generation and circulation of green electricity trading data. In order to ensure the credibility of data, it is becoming increasingly important to use data traceability technology to record and save transaction information. However, traditional data traceability systems are mostly centralized, and centralized data traceability information is subject to malicious tampering or accidental loss, which not only affects consumers' willingness to buy and trust, but also restricts the further development of the green electricity market.

[0003] In order to solve the above problems, the industry and academia are actively exploring the application of emerging technologies in the field of green power trading. Among them, blockchain, as a decentralized distributed ledger, can provide a safe and reliable storage environment for data traceability information, ensuring the credibility and integrity of data traceability information. However, there are still some problems in applying blockchain technology to the traceability of green power trading information. Specifically, existing consensus algorithms such as PoW and PoS have the disadvantages of wasting computing power and long transaction time; in the DPoS algorithm, most nodes never participate in voting, there is a phenomenon of malicious nodes bribing voting nodes, and the transaction time is too long; the PBFT algorithm supports a limited number of nodes, and as the number of nodes increases, the communication complexity and delay will also increase; other algorithms such as PoB, dPoW and PoH have problems of asset loss, low flexibility and inability to be used independently. The existence of these problems reduces the processing speed and throughput of green power trading, and thus reduces the credibility and speed of green power trading tracking and tracing.

[0004] In summary, it is necessary to explore a new green electricity trading traceability method to improve the credibility and speed of green electricity trading tracking and tracing, so as to enhance the transparency and credibility of the green electricity market, promote the consumption and utilization of clean energy, and help carbon emission reduction and sustainable development. Summary of the invention

[0005] In view of the defects in the prior art, the present invention provides a method and system for tracking and tracing green electricity transactions.

[0006] In order to achieve the above-mentioned purpose, in the first aspect, the present invention provides a method for tracking and tracing green electricity transactions, the method comprising the following steps: collecting the original green electricity transaction information generated after the green electricity producer and seller completes the transaction, and preprocessing the original green electricity transaction information to obtain standardized green electricity transaction information; using smart contracts to verify the standardized green electricity transaction information, and after the verification is passed, using the node judgment model to calculate the judgment factor value of each node in the blockchain network; based on the judgment factor value, using the diffusion storage strategy to store the verified standardized green electricity transaction information on the chain; according to the query information provided by the producer and seller, each block in the blockchain is retrieved, and then the corresponding traceability information is obtained and fed back to the producer and seller. The present invention uses the node judgment model and the diffusion storage strategy to improve the security of the consensus node, improve the transaction processing speed and throughput, and thus improve the credibility and speed of transaction tracking and tracing.

[0007] Optionally, the operations of preprocessing the original green electricity transaction information include data cleaning, information formatting, data verification, data encryption and data desensitization.

[0008] Furthermore, preprocessing the original green electricity transaction information can improve the accuracy of transaction data, thereby improving the credibility of transaction tracking and tracing.

[0009] Optionally, the node decision model satisfies the following relationship: in, is the decision factor value of the i-th node in the blockchain network, is the number of times the i-th node in the blockchain network participates in green electricity transactions, is the registration duration of the i-th node in the blockchain network, N is the number of nodes in the blockchain network, is the number of times the i-th node in the blockchain network participates in the consensus, is the number of times the i-th node in the blockchain network participates in the valid consensus.

[0010] Furthermore, the node judgment model is established based on the number of times the node participates in green electricity transactions, the node registration duration, and the data on participation in consensus. It can reflect the integrity of the node in the entire process of green electricity trading, which provides a basis for improving the credibility of transaction tracking and tracing.

[0011] Optionally, the diffusion storage strategy includes the following steps: Nodes in the blockchain network vote for each other; Construct a node security score data set based on the number of votes of each node in the blockchain network, the value of the decision factor and the basic information of the node; Selecting key nodes using a key node selection scheme according to the node security score data set; The key node packages the verified standardized green electricity transaction information to generate a new block, thereby realizing the on-chain storage of the new block.

[0012] Furthermore, the present invention uses a diffusion storage strategy to store the verified standardized green electricity transaction information on the chain, thereby improving the transaction processing speed and throughput, and thereby improving the credibility and speed of transaction tracking and tracing.

[0013] Optionally, the step of constructing a node security score data set based on the number of votes of each node in the blockchain network, the decision factor value and the basic information of the node comprises the following steps: Calculate the node security score of each node using the node security score calculation model according to the number of votes of each node in the blockchain network, the decision factor value and the basic information of the node; A node safety score dataset is constructed using the node safety scores of the respective nodes.

[0014] Furthermore, the present invention uses a node security score calculation model to calculate the node security score of each node, and then establishes a node security score data set, which provides a data basis for the elimination of abnormal nodes and helps to improve the credibility of transaction tracking and tracing.

[0015] Optionally, the basic information of the node includes the total amount of green electricity transactions, the amount of available funds and the holding period of the available funds; The node security score calculation model satisfies the following relationship: in, is the node security score of the i-th node in the blockchain network, is the total amount of green electricity transactions of the ith node in the blockchain network, is the total amount of green electricity transactions of all nodes in the blockchain network, is the number of votes obtained by the i-th node in the blockchain network, is the amount of available funds held by the i-th node in the blockchain network, is the holding period of available funds of the ith node in the blockchain network, The maximum holding period for the available amount, is the maximum holding period of the available amount of the i-th node in the blockchain network, is the decision factor value of the i-th node in the blockchain network.

[0016] Furthermore, the node security score calculation model integrates the node's green electricity transaction data, node votes, judgment factor values ​​and available amount, which can reflect the security of the node, provide a data basis for eliminating abnormal nodes in the blockchain network, and help improve the credibility of transaction tracking and tracing.

[0017] Optionally, the key node selection scheme includes the following steps: Setting a clustering judgment threshold, and using a clustering judgment model to calculate the clustering value of the security score of each of the nodes; Delete the nodes corresponding to the node security scores whose clustering values ​​are less than the clustering judgment threshold to obtain candidate key nodes; A node decision threshold is set, and the candidate key node whose decision factor value is greater than the node decision threshold is used as the key node.

[0018] Furthermore, the present invention eliminates abnormal nodes in the blockchain network based on the cluster judgment model, and selects nodes with larger judgment factor values ​​from the remaining nodes as key nodes to generate new blocks, thereby improving the credibility and speed of transaction tracking and tracing.

[0019] Optionally, the clustering judgment model satisfies the following relationship: in, is the cluster value of the security score of the i-th node, is the node security score of the i-th node in the blockchain network, is the mean value of the security scores of all nodes in the node security score dataset, is the standard deviation of the node security score in the node security score dataset, S is the node security score dataset, for The maximum value of .

[0020] Furthermore, the present invention uses a clustering judgment model to calculate the clustering value of each node security score, and deletes the nodes corresponding to the node security scores whose clustering values ​​are less than the clustering judgment threshold, thereby deleting abnormal nodes, improving the security of key nodes, shortening the block time, and increasing the speed of transaction tracking and tracing.

[0021] Optionally, the key node packages the verified standardized green electricity transaction information to generate a new block, and then implements the on-chain storage of the new block, including the following steps: The key node collects the verified standardized green electricity transaction information to verify its validity, and then packages the verified standardized green electricity transaction information to generate a new block; The key node broadcasts the new block in the blockchain network and other nodes receive it to verify its validity, thereby realizing the on-chain storage of the new block.

[0022] Furthermore, the present invention uses a diffusion storage strategy to store the verified standardized green electricity transaction information on the chain, thereby improving the transaction processing speed and throughput, and thereby improving the credibility and speed of transaction tracking and tracing.

[0023] In the second aspect, the present invention also provides a green electricity transaction tracking and tracing system, the green electricity transaction tracking and tracing system includes: data acquisition equipment, data query equipment, processor and storage, the storage includes a computer-readable storage medium, the computer-readable storage medium stores a computer program, the computer program includes program instructions, and the program instructions, when executed by the processor, enable the processor to implement the green electricity transaction tracking and tracing method described in the present invention. Based on the method provided by the present invention, this system can realize the rapid tracking and tracing of green electricity transactions, and improve the practicality of the method of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0025] Figure 1 A schematic diagram of a flow chart of a green electricity transaction tracking and tracing method according to an embodiment of the present invention; Figure 2 A schematic diagram of the framework of a green electricity transaction tracking and tracing system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are only for illustration and are not intended to limit the present invention. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention. However, it is obvious to those of ordinary skill in the art that these specific details do not need to be adopted to implement the present invention. In other examples, in order to avoid confusing the present invention, known circuits, software or methods are not specifically described.

[0027] Throughout the specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment of the present invention. Therefore, the phrases "in one embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily all refer to the same embodiment or example. In addition, particular features, structures, or characteristics may be combined in one or more embodiments or examples in any suitable combination and / or subcombination. In addition, it should be understood by those of ordinary skill in the art that the figures provided herein are for illustrative purposes and that the figures are not necessarily drawn to scale.

[0028] It should be noted in advance that, in an optional embodiment, except for independent explanations, the same symbols or letters appearing in all formulas have the same meanings and values.

[0029] In an alternative embodiment, see Figure 1 The present invention provides a green electricity transaction tracking and tracing method, the method comprising the following steps: S1. Collecting original green electricity transaction information generated after the green electricity producer and seller completes the transaction, and preprocessing the original green electricity transaction information to obtain standardized green electricity transaction information.

[0030] Specifically, in this embodiment, it is assumed that the green electricity producer and seller has installed a power generation device, an energy storage device and an intelligent collection device, and has completed registration on the blockchain network. Among them, the energy storage device is used to store the electric energy generated by the power generation device, the power generation device and the energy storage device are connected to the intelligent collection device, the intelligent collection device is connected to the distribution network, the power generation device is a photovoltaic power generation system, the energy storage device is a battery pack, and the intelligent collection device is a smart meter. The intelligent collection device can monitor the power generated by the power generation device and the power stored by the energy storage device in real time, and can monitor the transaction power in real time when the producer and seller conducts green electricity transactions.

[0031] Furthermore, the original green electricity transaction information of the producer and seller includes basic information of both parties to the green electricity transaction, transaction volume, transaction price, transaction time, green electricity project information, green electricity certificate information, transaction method and transaction contract, etc. Among them, the basic information of both parties to the green electricity transaction includes the name, registered address and ID number of the producer and seller. If the producer and seller is not an individual, the basic information of both parties to the green electricity transaction also includes the unified social credit code of the producer and seller; the transaction time includes the transaction start time and the transaction settlement time; the green electricity project information includes the green electricity type and geographical location; the green electricity certificate information includes the green certificate number, green certificate issuing agency and green certificate status. Green electricity certificate information is usually only available to non-individual green electricity producers; the transaction method includes transactions between individual households and purchases from the power grid; the transaction contract is an electronic contract text signed by both parties to the green electricity transaction, which records the transaction terms and liability for breach of contract in detail.

[0032] Furthermore, the original green electricity transaction information is preprocessed to obtain standardized green electricity transaction information. The specific preprocessing operations include data cleaning, information formatting, data verification, data encryption and data desensitization. Preprocessing the original green electricity transaction information can ensure data security, improve the accuracy of transaction data, and thereby improve the credibility of transaction tracking and tracing.

[0033] S2. Use smart contracts to verify the standardized green electricity transaction information, and after the verification is passed, use the node judgment model to calculate the judgment factor value of each node in the blockchain network.

[0034] Specifically, in this embodiment, the source code of the smart contract is written using the high-level programming language Solidity, and the smart contract is deployed to all nodes in the blockchain network to automate some of the regulatory functions for green electricity transaction data. The smart contract should have at least the following functions: assisting producers and sellers to register on the blockchain network; verifying the identity of the equipment and producers and sellers, and then agreeing or rejecting the producers and sellers to query information or upload data; generating transaction orders and transaction contracts, and verifying transaction orders and contracts. Considering that the blockchain technology has already been applied to green electricity transactions in the prior art, the specific functions or design solutions of the smart contract can refer to the prior art, and will not be described in detail in this embodiment.

[0035] Furthermore, after the standardized green electricity transaction information is verified, the node decision model is used to calculate the decision factor value of each node in the blockchain network. The node decision model satisfies the following relationship: in, is the decision factor value of the i-th node in the blockchain network, is the number of times the i-th node in the blockchain network participates in green electricity transactions, is the registration duration of the i-th node in the blockchain network, N is the number of nodes in the blockchain network, is the number of times the i-th node in the blockchain network participates in the consensus, It is the number of times the ith node in the blockchain network participates in effective consensus. The node judgment model is established based on the number of times the node participates in green electricity transactions, the node registration time, and the data of participating in consensus. The larger the value of the node's judgment factor, the more honest the node is in the entire process of green electricity trading. This provides data support for finding accurate and reliable key nodes in the future, and thus provides a basis for improving the credibility of transaction tracking and tracing.

[0036] S3. Based on the value of the decision factor, a diffusion storage strategy is used to store the verified standardized green electricity transaction information on the chain.

[0037] Specifically, in this embodiment, a diffusion storage strategy is used to store the verified standardized green electricity transaction information on the chain, which improves the transaction processing speed and throughput, thereby improving the credibility and speed of transaction tracking and tracing. The diffusion storage strategy includes the following steps: T1. Nodes in the blockchain network vote for each other.

[0038] In this embodiment, all nodes in the blockchain network are eligible to vote, which can improve the enthusiasm of nodes to participate in green electricity transactions to a certain extent, and help find accurate and reliable key nodes, improve the credibility of transaction traceability, and make the traceability results more reliable.

[0039] T2. Construct a node security score dataset based on the number of votes of each node in the blockchain network, the value of the decision factor and the basic information of the node.

[0040] Wherein, step T2 specifically includes the following steps: T21. Calculate the node security score of each node using the node security score calculation model based on the number of votes of each node in the blockchain network, the decision factor value and the basic information of the node.

[0041] In this embodiment, the basic information of the node includes the total amount of green electricity transactions, the amount of available funds, and the number of years of holding the available funds, and the node security score calculation model satisfies the following relationship: in, is the node security score of the i-th node in the blockchain network, is the total amount of green electricity transactions of the ith node in the blockchain network, is the total amount of green electricity transactions of all nodes in the blockchain network, is the number of votes obtained by the i-th node in the blockchain network, is the amount of available funds held by the i-th node in the blockchain network, is the holding period of available funds of the ith node in the blockchain network, The maximum holding period for the available amount, is the maximum holding period of the available amount of the i-th node in the blockchain network, is the decision factor value of the i-th node in the blockchain network. The node security score calculation model integrates the node's green power transaction data, node votes, decision factor value and available amount, and can reflect the node's security. Generally speaking, the larger the node security score, the higher the node security. This embodiment provides a data basis for eliminating abnormal nodes in the blockchain network by calculating the node security score, which helps to improve the credibility of transaction tracking and tracing.

[0042] Furthermore, producers and sellers use available funds to trade green electricity in the blockchain network. If a producer and seller has held a certain amount of available funds for 1 year, then the available funds holding period for this part of available funds is 1 year. Obviously, the available funds of producers and sellers will be divided into different parts as the number of transactions changes. Assuming that the available funds of a producer and seller are divided into 6 parts, each part of the available funds has a different available funds holding period. The maximum value of these 6 different available amount holding periods. As for the available amount holding period of each node, it is calculated by the available amount holding period of different parts of the available amount of the node. The specific calculation method can refer to the PoS consensus mechanism.

[0043] T22. Construct a node security score dataset using the node security score of each node.

[0044] In this embodiment, the node security score dataset can be expressed as , S represents the node security score dataset.

[0045] T3. Select key nodes using a key node selection scheme based on the node security score data set.

[0046] Among them, the key node selection scheme includes the following steps: H1. Set a clustering judgment threshold, and use a clustering judgment model to calculate the clustering value of the security score of each node.

[0047] In this embodiment, the clustering judgment threshold is 0.4, and the clustering judgment model satisfies the following relationship: in, is the cluster value of the security score of the i-th node, is the node security score of the i-th node in the blockchain network, is the mean of all node security scores in the node security score dataset, is the standard deviation of the node security score in the node security score dataset, S is the node security score dataset, for The maximum value of .

[0048] In general, the greater the node security score, the higher the node security. However, if there are malicious nodes that collude with each other to conduct malicious voting, it will have a greater impact on the node security score. Usually, the votes of malicious nodes are significantly higher than those of other nodes, which makes their node security score significantly higher than the node security scores of other nodes. If malicious nodes are used as key nodes to verify green power transaction information and generate new blocks for chain storage, abnormal data may be generated, thereby reducing the accuracy of information. Subsequent producers and sellers may not be able to obtain accurate traceability information when tracking and tracing green power transactions. Therefore, on the basis of obtaining the node security scores of each node, it is necessary to delete malicious nodes so that the remaining normal nodes can reach consensus faster, ensure the security and stability of the blockchain network, improve the credibility of green power transaction tracking and tracing, make the traceability results more reliable, and shorten the node block time to meet the increasing green power transaction volume.

[0049] H2. Delete the nodes corresponding to the node security scores whose clustering values ​​are less than the clustering judgment threshold to obtain candidate key nodes.

[0050] H3. Set a node decision threshold, and use the candidate key node whose decision factor value is greater than the node decision threshold as the key node.

[0051] In this embodiment, since the value of the node decision factor can reflect the integrity of the node in the entire process of green electricity trading, after deleting the malicious node, this embodiment selects the most honest and reliable node from the candidate key nodes by setting the node decision threshold, so as to further improve the security of the selected node, and further improve the credibility of green electricity trading tracking and tracing.

[0052] Furthermore, in this embodiment, the node decision threshold is set to the median of the decision factor values ​​of all nodes in the blockchain network. In other optional embodiments, the node decision threshold can also be set to other values.

[0053] T4. The key node packages the verified standardized green electricity transaction information to generate a new block, and then realizes the on-chain storage of the new block.

[0054] Wherein, step T4 specifically includes the following steps: T41. The key node collects the verified standardized green electricity transaction information for validity verification, and then packages the verified standardized green electricity transaction information to generate a new block.

[0055] In this embodiment, the key nodes will verify the validity of the collected and verified standardized green electricity transaction information, including checking the qualifications of the transaction parties, the integrity of the transaction data, whether the transaction complies with the relevant laws and policies of green electricity transactions, etc. Only when the standardized green electricity transaction information passes the validity verification of at least 2 / 3 of the key nodes will it be regarded as valid standardized green electricity transaction information, and then the key nodes will package the valid standardized green electricity transaction information to generate a new block.

[0056] T42. The key node broadcasts the new block in the blockchain network and other nodes receive it to verify its validity, thereby realizing the on-chain storage of the new block.

[0057] S4. Retrieve each block in the blockchain based on the query information provided by the producer and seller, and then obtain the corresponding traceability information and feed it back to the producer and seller.

[0058] Specifically, in this embodiment, the query information provided by the producer and seller can be one or more combinations of the basic information of the two parties to the green electricity transaction, transaction volume, transaction price, transaction time, green electricity project information, green electricity certificate information and transaction method. Then, based on the query information provided by the producer and seller, each block in the blockchain is retrieved to obtain the corresponding traceability information and feed it back to the producer and seller.

[0059] It should be noted that, in some cases, the actions described in the specification can be performed in a different order and still achieve the desired results. In this embodiment, the order of steps given is only to make the embodiment appear clearer and easier to explain, rather than to limit it.

[0060] In an alternative embodiment, see Figure 2 The present invention provides a green electricity transaction tracking and tracing system, which includes: a data acquisition device A1, a data query device A2, a processor A3 and a storage A4, the storage A4 includes a computer-readable storage medium, the computer-readable storage medium stores a computer program, the computer program includes program instructions, and when the program instructions are executed by the processor A3, the processor A3 executes the contents of steps S1 to S4.

[0061] Specifically, in this embodiment, when the computer program run by processor A3 implements the contents described in steps S1-S4, the data acquisition device A1 is used to collect original green electricity transaction information and pre-process the original green electricity transaction information to obtain standardized green electricity transaction information. Producers and sellers can use data query device A2 to input query information, and traceability information will be displayed to producers and sellers on data query device A2.

[0062] Based on the method provided by the present invention, the system can realize the rapid tracking and tracing of green electricity transactions, thereby improving the practicality of the method of the present invention.

[0063] In summary, this method uses a diffusion storage strategy to store the standardized green electricity transaction information that has been verified on the chain, which improves the transaction processing speed and throughput, and thus improves the credibility and speed of transaction tracking and tracing. Among them, the use of the node judgment model to calculate the judgment factor value of each node can reflect the integrity of the node in the entire process of green electricity trading, which provides a basis for improving the credibility of transaction tracking and tracing; the node security score calculation model is used to calculate the node security score of each node and establish a node security score data set, and then the cluster judgment model is used to calculate the cluster value of each node security score, and the node corresponding to the node security score whose cluster value is less than the cluster judgment threshold is deleted as an abnormal node, and the abnormal data carried by the malicious node is eliminated at the same time, so that the key nodes obtained have higher security, and can shorten the block time, and improve the credibility and speed of transaction tracking and tracing. In addition, the system provided by the present invention is a system compatible with the method provided by the present invention, which can realize the rapid tracking and tracing of green electricity transactions, and improve the practicality of the method of the present invention.

[0064] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A green electricity trading tracking method, characterized in that: The steps include: Collecting original green electricity transaction information generated after the green electricity producer and seller completes the transaction, and preprocessing the original green electricity transaction information to obtain standardized green electricity transaction information; Using smart contracts to verify the standardized green electricity transaction information, and after the verification is passed, using a node judgment model to calculate the judgment factor value of each node in the blockchain network; Based on the decision factor value, a diffusion storage strategy is used to store the verified standardized green electricity transaction information on the chain; According to the query information provided by the producer and seller, each block in the blockchain is retrieved, and then the corresponding traceability information is obtained and fed back to the producer and seller.

2. A green electricity transaction tracing method according to claim 1, characterized in that: The operations of preprocessing the original green electricity transaction information include data cleaning, information formatting, data verification, data encryption and data desensitization.

3. A green electricity transaction tracing method according to claim 1, characterized in that: The node decision model satisfies the following relationship: in, is the decision factor value of the i-th node in the blockchain network, is the number of times the i-th node in the blockchain network participates in green electricity transactions, is the registration duration of the i-th node in the blockchain network, N is the number of nodes in the blockchain network, is the number of times the i-th node in the blockchain network participates in the consensus, is the number of times the i-th node in the blockchain network participates in the valid consensus.

4. A green electricity transaction tracing method according to claim 1, characterized in that: The diffusion storage strategy includes the following steps: Nodes in the blockchain network vote for each other; Construct a node security score data set based on the number of votes of each node in the blockchain network, the value of the decision factor and the basic information of the node; Selecting key nodes using a key node selection scheme according to the node security score data set; The key node packages the verified standardized green electricity transaction information to generate a new block, thereby realizing the on-chain storage of the new block.

5. A green electricity transaction tracing method according to claim 4, characterized in that: The step of constructing a node security score data set based on the number of votes of each node in the blockchain network, the decision factor value and the basic information of the node includes the following steps: Calculate the node security score of each node using the node security score calculation model according to the number of votes of each node in the blockchain network, the decision factor value and the basic information of the node; A node safety score dataset is constructed using the node safety scores of the respective nodes.

6. A green electricity transaction tracing method according to claim 5, characterized in that: The basic information of the node includes the total amount of green electricity transactions, the amount of available funds and the number of years the available funds are held; The node security score calculation model satisfies the following relationship: in, is the node security score of the i-th node in the blockchain network, is the total amount of green electricity transactions of the ith node in the blockchain network, is the total amount of green electricity transactions of all nodes in the blockchain network, is the number of votes obtained by the i-th node in the blockchain network, is the amount of available funds held by the i-th node in the blockchain network, is the holding period of available funds of the ith node in the blockchain network, The maximum holding period for the available amount, is the maximum holding period of the available amount of the i-th node in the blockchain network, is the decision factor value of the i-th node in the blockchain network.

7. A green electricity transaction tracing method according to claim 4, characterized in that: The key node selection scheme includes the following steps: Setting a clustering judgment threshold, and using a clustering judgment model to calculate the clustering value of the security score of each of the nodes; Delete the nodes corresponding to the node security scores whose clustering values ​​are less than the clustering judgment threshold to obtain candidate key nodes; A node decision threshold is set, and the candidate key node whose decision factor value is greater than the node decision threshold is used as the key node.

8. A green electricity transaction tracing method according to claim 7, characterized in that: The clustering judgment model satisfies the following relationship: in, is the cluster value of the security score of the i-th node, is the node security score of the i-th node in the blockchain network, is the mean value of the security scores of all nodes in the node security score dataset, is the standard deviation of the node security score in the node security score dataset, S is the node security score dataset, for The maximum value of .

9. A green electricity transaction tracing method according to claim 4, characterized in that: The key node packages the verified standardized green electricity transaction information to generate a new block, and then implements the on-chain storage of the new block, including the following steps: The key node collects the verified standardized green electricity transaction information to verify its validity, and then packages the verified standardized green electricity transaction information to generate a new block; The key node broadcasts the new block in the blockchain network and other nodes receive it to verify its validity, thereby realizing the on-chain storage of the new block.

10. A green electricity trading tracking and tracing system, characterized in that: The green electricity transaction tracking and tracing system comprises: a data acquisition device, a data query device, a processor and a storage device, wherein the storage device comprises a computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and wherein the computer program comprises program instructions, and when the program instructions are executed by the processor, the processor implements the green electricity transaction tracking and tracing method as described in any one of claims 1 to 9.

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