Blockchain-based green electricity identification traceability checking method

Abstract

The application provides a green electricity identification traceability checking method based on a blockchain, comprising the following steps: obtaining green electricity consumption identification basic business data of a user through a green electricity consumption accounting application module, and uploading the data to the blockchain for solidification and evidence storage; the user submits a green power consumption rating application to a green electricity consumption identification management module, the green electricity consumption identification management module receives the application, obtains the green power consumption level grade of the user from the blockchain according to the green electricity consumption identification basic business data, generates a green power consumption grade identification and a traceability two-dimensional code, the user scans the traceability two-dimensional code to send a traceability request to a green electricity identification traceability module, the green electricity identification traceability module queries the corresponding green electricity consumption identification basic business data according to the traceability request, generates a green electricity consumption accounting list according to the green electricity consumption identification basic business data, and feeds back the green electricity consumption accounting list to the user, and the application can realize credible, efficient and transparent application of the green electricity consumption identification.

Description

Blockchain-based Green Electricity Labeling Traceability and Verification Method Technical Field

[0001] This invention relates to the field of green electricity consumption traceability technology, and in particular to a blockchain-based method for green electricity identification and traceability verification. Background Technology

[0002] Green electricity consumption labeling is a key extension of green electricity consumption accounting, helping companies showcase their green development achievements, enhance brand value, and assist in securing policy and financial support, effectively incentivizing the market to actively consume green electricity. With the global energy structure transformation, the demand for green electricity consumption is growing. However, traditional green electricity consumption labeling systems suffer from problems such as opacity, susceptibility to tampering, and difficulty in traceability, leading to irregularities like "greenwashing" and "free-riding" in the green electricity market, severely hindering its healthy development. Therefore, establishing a credible, efficient, and transparent green electricity consumption labeling traceability mechanism is crucial.

[0003] Currently, the traceability of green electricity consumption labels mainly relies on centralized databases and manual review. Data from each participating party is stored independently, lacking an effective data sharing mechanism, resulting in serious information silos and making it difficult to achieve full-process traceability. Furthermore, the centralized storage of green electricity consumption label data in centralized institutions poses a risk of data tampering and forgery, making it difficult to guarantee the authenticity and reliability of the data.

[0004] Blockchain technology, with its decentralized, immutable, and traceable characteristics, provides a new approach to addressing the shortcomings of existing green electricity consumption identification and traceability systems. Summary of the Invention

[0005] The purpose of this invention is to provide a blockchain-based method for tracing and verifying green electricity identification, thereby addressing the shortcomings of existing traceability methods and enabling the reliable, efficient, and transparent application of green electricity consumption identification.

[0006] To achieve the above-mentioned objectives, the present invention provides the following technical solution:

[0007] A blockchain-based method for tracing and verifying green electricity identification, the method comprising:

[0008] The green electricity consumption accounting application module obtains the user's basic business data of green electricity consumption identification and uploads the basic business data of green electricity consumption identification to the blockchain for solidification and storage.

[0009] Users submit green electricity consumption rating applications to the green electricity consumption label management module. After receiving the application, the green electricity consumption label management module obtains the basic business data of green electricity consumption label from the blockchain, verifies the user's green electricity consumption level based on the basic business data of green electricity consumption label, and generates a green electricity consumption level label and a corresponding traceability QR code.

[0010] Users scan the traceability QR code with a scanning device to send a traceability request to the green electricity identification traceability module. The green electricity identification traceability module queries the basic business data of the green electricity consumption level identification on the blockchain according to the traceability request, generates a green electricity consumption accounting list based on the basic business data of the green electricity consumption identification, and feeds the green electricity consumption accounting list back to the user.

[0011] Furthermore, the basic business data for green electricity consumption identification includes green electricity consumption user information, green electricity consumption type, green electricity consumption time, green electricity consumption volume, green electricity source proof, emission reduction effect, and emission reduction calculation method.

[0012] Furthermore, the green electricity consumption accounting application module obtains the user's basic green electricity consumption identification data, and uploads this data to the blockchain for solidification and notarization. Specifically, this includes the following operations:

[0013] The green electricity consumption of users is collected through electricity metering terminals, and the corresponding green electricity consumption user information, green electricity consumption type and green electricity consumption time are recorded to generate green electricity source certificates.

[0014] Calculate the emission reduction effect based on green electricity consumption and record the corresponding calculation method;

[0015] The amount of green electricity consumed, the type of green electricity consumed, the time of green electricity consumption, proof of the source of green electricity, emission reduction effect, and calculation method are written into the blockchain for storage.

[0016] Furthermore, the generation of green electricity source proof specifically includes the following operations:

[0017] Determine the pseudo-random function, electricity metering terminal identification information, green electricity consumption user information, maximum number of iterations, and length of green electricity source proof;

[0018] In the first iteration of the pseudo-random function, the electricity metering terminal identification information is used as the key, and the green electricity consumption user information is concatenated with t+1 to obtain the first concatenation result. t represents the iteration round number. The first concatenation result is used as the salt value. The key and salt value are input into the pseudo-random function to obtain the output p[0] of the pseudo-random function in this iteration.

[0019] In subsequent iterations of the pseudo-random function, the electricity metering terminal identification information is used as the key, and the output of the previous round of the pseudo-random function is used as the input to obtain the output result p[1,...,T-1] of the pseudo-random function, where T represents the maximum number of iteration rounds;

[0020] In each subsequent iteration of the pseudo-random function, all outputs of the pseudo-random function up to the current iteration are XORed to obtain e[t] for that iteration, where t∈[0,t]. lv], t lv The calculation formula is as follows:

[0021] t lv =COS length / OV length

[0022] In the above formula, COS length Indicates the length of the green electricity source proof, OV length Indicates the length of the pseudo-random function output value;

[0023] The e[t] of each iteration is concatenated to obtain the second concatenation result. The length control operation is performed on the second concatenation result to make the result of the length control operation meet the length limit of the green electricity source proof. The result of the length control operation is used as the green electricity source proof.

[0024] Furthermore, after receiving a green electricity consumption rating application, the green electricity consumption identification module generates a green electricity consumption level identification and a corresponding traceability QR code, specifically including the following operations:

[0025] Analyze green electricity consumption rating applications to obtain information on green electricity consumers and the approval time range;

[0026] The smart contract is invoked to query and obtain the corresponding green electricity consumption identifier basic business data on the blockchain based on green electricity consumption user information and approved time range information.

[0027] The green electricity consumption ratio is calculated based on the amount of green electricity consumed: Green electricity consumption ratio = 100% × (Green electricity consumption / Total electricity consumption) × Correction factor;

[0028] The user's green electricity consumption level is determined based on the user's green electricity consumption volume and green electricity consumption ratio;

[0029] Based on green electricity consumption user information and green electricity consumption level, generate corresponding green electricity consumption level identifiers; and based on green electricity consumption user information, verification time range information, and green electricity consumption level, generate corresponding traceability QR codes.

[0030] Green electricity consumption level labels and traceability QR codes will be issued to users.

[0031] Furthermore, the determination of the correction factor includes the following operations:

[0032] Acquire users’ historical behavior data, determine users’ historical behavior score based on the historical behavior data, wherein the historical behavior data consists of user behavior data that has been recorded in the blockchain in real time in the past.

[0033] The system acquires electricity metering terminal commissioning information, inputs this information into a neural network model for processing, and obtains data acquisition accuracy information. The electricity metering terminal commissioning information includes the electricity metering terminal model information, the electricity metering terminal commissioning duration information, and the electricity metering terminal deployment environment information.

[0034] Verify the green electricity source proof in the basic business data of green electricity consumption identification, and obtain the verification results;

[0035] The historical behavior scores, data collection accuracy information, and verification results were normalized.

[0036] The correction factor is calculated based on the normalized historical behavior scores, data collection accuracy information, and verification results, as shown in the following formula:

[0037]

[0038] In the above formula, θ represents the correction factor, α represents the weight of the historical behavior score, hs represents the historical behavior score, β represents the weight of the collection accuracy information, acc represents the collection accuracy information, γ represents the weight of the verification result, and vr represents the verification result.

[0039] Furthermore, the basic business data for green electricity consumption identification is uploaded to the blockchain for solidification and notarization, specifically including the following operations:

[0040] Once the basic business data for green electricity consumption identification is successfully uploaded to the blockchain, a smart contract is triggered to authenticate the authenticity of the basic business data for green electricity consumption identification and obtain a data authenticity authentication report.

[0041] The on-chain information for generating basic business data for green electricity consumption identification includes the blockchain information to which the basic business data for green electricity consumption identification belongs, the information of the block to which it is written, and the on-chain time information.

[0042] Provide users with data authenticity verification reports and on-chain information.

[0043] Furthermore, the authentication of the authenticity of the basic business data for green electricity consumption identification specifically includes the following operations:

[0044] The emission reduction calculation method is determined based on the basic business data of green electricity consumption identification. The emission reduction effect is calculated based on the emission reduction calculation method, green electricity consumption type, and green electricity consumption amount. The calculation result is compared with the emission reduction effect in the basic business data of green electricity consumption identification to obtain the first comparison result.

[0045] Verification information is generated based on the identification information of the electricity metering terminal that collects green electricity consumption and the user information that generates green electricity consumption. The verification information is then compared with the green electricity source certificate to obtain a second comparison result.

[0046] The authenticity of the basic business data for green electricity consumption identification is determined based on the first and second comparison results, and a data authenticity certification report is generated.

[0047] Furthermore, the green electricity labeling and traceability module provides users with a green electricity consumption accounting list, which specifically includes:

[0048] Trusted evidence verification: The data authenticity verification report is displayed on the green electricity consumption accounting list display page;

[0049] Hash verification involves performing hash calculations on the green electricity consumption accounting list, comparing the hash calculation result with the corresponding hash value pre-stored on the blockchain, and issuing an early warning for potentially tampered data and generating an audit report if the comparison is inconsistent.

[0050] Any abnormal verification results are recorded on the blockchain.

[0051] Compared with the prior art, the beneficial effects of the present invention are:

[0052] This invention provides a blockchain-based method for tracing and verifying green electricity labels. Basic business data for green electricity consumption labels is uploaded to the blockchain for solidification and notarization, improving the quality of source data. Upon receiving a user application, the green electricity consumption label management module retrieves the basic business data from the blockchain and verifies the user's green electricity consumption level, generating a green electricity consumption level label and a corresponding traceability QR code. This invention, on the one hand, helps market participants clearly understand the source and consumption of green electricity, enhancing their trust in green electricity; on the other hand, based on blockchain and smart contract technology, it tracks and records every step of the green electricity consumption label process from generation to use, ensuring that all relevant data is secure, accurate, and tamper-proof. This achieves a trustworthy, efficient, and transparent application of green electricity consumption labels, promoting the healthy development of the green electricity market and providing strong support for achieving the "dual carbon" goal. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only preferred embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 is a schematic diagram of the overall process of a blockchain-based green electricity identification traceability and verification method provided by an embodiment of the present invention. Detailed Implementation

[0055] The principles and features of the present invention are described below with reference to the accompanying drawings. The listed embodiments are only used to explain the present invention and are not intended to limit the scope of the present invention.

[0056] Referring to Figure 1, this embodiment provides a blockchain-based method for tracing and verifying green electricity labels, the method comprising:

[0057] S101. Obtain the user's green electricity consumption identification basic business data through the green electricity consumption accounting application module, and upload the green electricity consumption identification basic business data to the blockchain for solidification and storage.

[0058] In this embodiment, the basic business data for green electricity consumption identification includes:

[0059] Green electricity consumer information is used to identify the identity of users who consume green electricity;

[0060] Green electricity consumption types are used to characterize the types of green electricity consumed by users, such as wind power, solar power, and wave power.

[0061] Green electricity consumption time is used to characterize the time period during which a user consumes green electricity;

[0062] Green electricity consumption is used to record the total amount of green electricity consumed by users, and can be measured in kilowatt-hours (kWh).

[0063] Green electricity source verification, used to provide proof of the source of green electricity consumption data;

[0064] Emission reduction effect, used to record the amount of greenhouse gas emissions such as carbon dioxide reduced by consuming green electricity, can be expressed in tons of carbon dioxide equivalent (tCO2e);

[0065] Emission reduction calculation method is used to record the standards or calculation methods on which the emission reduction effect is calculated.

[0066] S102. The user submits a green electricity consumption rating application to the green electricity consumption label management module. After receiving the application, the green electricity consumption label management module obtains the basic business data of green electricity consumption label from the blockchain, verifies the user's green electricity consumption level based on the basic business data of green electricity consumption label, and generates a green electricity consumption level label and a corresponding traceability QR code.

[0067] S103. The user scans the traceability QR code with a scanning device to send a traceability request to the green electricity identification traceability module. The green electricity identification traceability module queries the basic business data of the green electricity consumption level identification on the blockchain according to the traceability request, generates a green electricity consumption accounting list based on the basic business data of the green electricity consumption identification, and feeds back the green electricity consumption accounting list to the user.

[0068] The method provided in this embodiment uploads the user's basic green electricity consumption identification data to the blockchain for solidification and notarization. Based on blockchain and smart contract technology, it tracks and records every step of the green electricity consumption identification from generation to use, ensuring that all relevant data is secure, accurate and tamper-proof, improving market transparency, enabling market participants to clearly understand the source and consumption of green electricity, and enhancing their trust in green electricity.

[0069] As one possible implementation, the user's basic green electricity consumption identification data is obtained through the green electricity consumption accounting application module, and then uploaded to the blockchain for solidification and notarization. Specifically, this includes the following operations:

[0070] S201. Collect users' green electricity consumption through electricity metering terminals, record the corresponding green electricity consumption user information, green electricity consumption type and green electricity consumption time, and generate green electricity source certificate.

[0071] S202. Calculate the emission reduction effect based on green electricity consumption and record the corresponding calculation method.

[0072] S203. The amount of green electricity consumed, the type of green electricity consumed, the time of green electricity consumption, proof of the source of green electricity, the emission reduction effect, and the calculation method are written into the blockchain for storage.

[0073] Based on this, as a further possible implementation, the generation of green electricity source proof specifically includes the following operations:

[0074] S301. Determine the pseudo-random function, electricity metering terminal identification information, green electricity consumption user information, maximum number of iterations, and length of green electricity source proof.

[0075] The pseudo-random function can be a hash function-based type, such as HMAC (Hash-based Message Authentication Code), or a block cipher-based type, such as CMAC (Cipher-based Message Authentication Code), or other types. This implementation does not specifically limit the types used.

[0076] In this implementation, the electricity metering terminal identification information is used to uniquely identify the electricity metering terminal that collects green electricity consumption data. The green electricity consumption user information is used to uniquely identify users who consume green electricity. The maximum number of iterations is used to limit the number of iterations of the pseudo-random function. The green electricity source proof length is used to limit the length of the final output green electricity source proof.

[0077] S302. In the first iteration of the pseudo-random function, the electricity metering terminal identification information is used as the key, and the green electricity consumption user information is concatenated with t+1 to obtain the first concatenation result. t represents the iteration round number. The first concatenation result is used as the salt value. The key and salt value are input into the pseudo-random function to obtain the output p[0] of the pseudo-random function in this iteration.

[0078] S303. In subsequent iterations of the pseudo-random function, the electricity metering terminal identification information is used as the key, and the output of the previous round of the pseudo-random function is used as the input to obtain the output result p[1,...,T-1] of the pseudo-random function, where T represents the maximum number of iteration rounds.

[0079] S304. In each subsequent iteration of the pseudo-random function, perform an XOR operation on all output results of the pseudo-random function up to the current iteration to obtain e[t] for that iteration, t∈[0,t]. lv ], t lv The calculation formula is as follows:

[0080] t lv =COS length / OV length

[0081] In the above formula, COS length Indicates the length of the green electricity source proof, OV length This indicates the length of the output value of the pseudo-random function.

[0082] S305. Concatenate e[t] from each iteration to obtain a second concatenation result. Perform a length control operation on the second concatenation result to ensure that the result of the length control operation meets the length limit of the green electricity source proof. Use the result of the length control operation as the green electricity source proof.

[0083] This implementation method, based on electricity metering terminal identification information and green electricity consumption user information, generates green electricity source proof through multiple rounds of pseudo-random function iteration, thereby increasing the difficulty of forging green electricity source proof, ensuring the quality of source data, and reducing the possibility of forgery.

[0084] As another possible implementation, the green electricity consumption identification module generates a green electricity consumption level identification and a corresponding traceability QR code after receiving a green electricity consumption rating application, specifically including the following operations:

[0085] S401. Analyze green electricity consumption rating applications to obtain information on green electricity consumption users and the approved time range.

[0086] In this implementation, the green electricity consumption rating application submitted by the user includes at least green electricity consumption user information and approved time range information. The approved time range is used to determine the time period for which the green electricity consumption rating is applied.

[0087] S402. Call the smart contract. The smart contract queries and obtains the corresponding green electricity consumption identifier basic business data on the blockchain based on the green electricity consumption user information and the approved time range information.

[0088] S403. Calculate the green electricity consumption ratio based on the green electricity consumption amount. Green electricity consumption ratio = 100% × (green electricity consumption amount / total electricity consumption) × correction factor.

[0089] S404. Determine the user's green electricity consumption level based on the user's green electricity consumption amount and green electricity consumption ratio.

[0090] For example, the higher a user's green electricity consumption and the higher the proportion of green electricity consumption, the higher the corresponding level of green electricity consumption.

[0091] S405. Generate corresponding green electricity consumption level identifiers based on green electricity consumption user information and green electricity consumption level, and generate corresponding traceability QR codes based on green electricity consumption user information, approved time range information, and green electricity consumption level.

[0092] S406. Issue green electricity consumption level labels and traceability QR codes to users.

[0093] In this implementation, both the user and other users can trace the green electricity consumption level label by scanning the traceability QR code. On the one hand, this provides users with a flexible query method, improving the convenience of user query and use; on the other hand, market participants can clearly understand the source and consumption of green electricity, which helps to enhance market participants' trust in the green electricity consumption level label.

[0094] Based on this, as a further possible implementation, the determination of the correction factor includes the following operations:

[0095] S501. Obtain the user's historical behavior data and determine the user's historical behavior score based on the historical behavior data. The historical behavior data consists of user behavior data that has been recorded in the blockchain in real time in the past.

[0096] In this implementation, when users upload green electricity consumption data or apply for verification of their green electricity consumption levels, the system records their actions. Different types of actions correspond to different behavior scores; good behaviors as defined by the system can earn points, while bad behaviors can deduct points. The user's historical behavior score reflects the system's evaluation of the user's credit from the perspective of user behavior.

[0097] S502. Obtain the power metering terminal commissioning information, input the power metering terminal commissioning information into the neural network model for processing, and obtain the collection accuracy information. The power metering terminal commissioning information includes the power metering terminal model information, the power metering terminal commissioning duration information, and the power metering terminal deployment environment information.

[0098] In this step, the neural network model is pre-trained using the commissioning information of labeled sample electricity metering terminals. It is mainly used to analyze whether the data collected by the electricity metering terminal is accurate enough based on the terminal's model, commissioning duration, and the environmental information in which it is deployed.

[0099] S503. Verify the green electricity source proof in the basic business data of green electricity consumption identification and obtain the verification results.

[0100] For example, the verification result includes two cases: verification passed and verification failed. For those without proof of green electricity source, the verification is also considered failed.

[0101] S504. Normalize the historical behavior scores, collection accuracy information, and verification results.

[0102] S505. Calculate the correction factor based on the normalized historical behavior scores, data collection accuracy information, and verification results. The calculation formula is as follows:

[0103]

[0104] In the above formula, θ represents the correction factor, α represents the weight of the historical behavior score, hs represents the historical behavior score, β represents the weight of the collection accuracy information, acc represents the collection accuracy information, γ represents the weight of the verification result, and vr represents the verification result.

[0105] This implementation measures user credit based on historical user behavior, analyzes the accuracy of data collected by electricity metering terminals based on their operational information, and verifies the source of green electricity to determine whether the basic business data for green electricity consumption identification has a credible source. Then, based on user credit, the accuracy of electricity metering terminals, and the verification results of green electricity source proof, a correction factor is determined to calculate the green electricity consumption ratio, so that the calculation results are more consistent with the actual situation.

[0106] As another possible implementation method, the basic business data of green electricity consumption identification is uploaded to the blockchain for solidification and notarization, specifically including the following operations:

[0107] S601. After the basic business data of green electricity consumption identification is successfully uploaded to the blockchain, the smart contract is triggered to authenticate the authenticity of the basic business data of green electricity consumption identification and obtain a data authenticity authentication report.

[0108] S602. Generate on-chain information for the basic business data of green electricity consumption identification, wherein the on-chain information includes the blockchain information to which the basic business data of green electricity consumption identification belongs, the information of the block written, and the on-chain time information.

[0109] S603, Provide users with data authenticity verification reports and on-chain information.

[0110] For example, authenticating the authenticity of basic business data for green electricity consumption identification specifically includes the following operations:

[0111] S701. Determine the emission reduction calculation method based on the basic business data of green electricity consumption identification, calculate the emission reduction effect based on the emission reduction calculation method, green electricity consumption type, and green electricity consumption amount, and compare the calculation result with the emission reduction effect in the basic business data of green electricity consumption identification to obtain the first comparison result.

[0112] S702. Based on the identification information of the electricity metering terminal that collects green electricity consumption and the user information that generates green electricity consumption, verification information is generated. The verification information is compared with the green electricity source certificate to obtain the second comparison result.

[0113] S703. Based on the first comparison result and the second comparison result, determine the authenticity of the basic business data of green electricity consumption identification, and generate a data authenticity certification report.

[0114] In this implementation, the basic business data of green electricity consumption identification is considered to be authentic only when both the first comparison result and the second comparison result pass the comparison; if one of them fails the comparison but the other passes the comparison, the authenticity of the corresponding basic business data of green electricity consumption identification is questionable; if both of them fail the comparison, the corresponding basic business data of green electricity consumption identification is considered not authentic.

[0115] As another possible implementation method, the green electricity identification and traceability module provides users with a green electricity consumption accounting list, which includes two parts: trusted evidence verification and hash verification.

[0116] The trusted evidence verification involves displaying a data authenticity verification report on the green electricity consumption accounting list display page.

[0117] Hash verification involves performing hash calculations on the contents of the green electricity consumption accounting list, comparing the hash calculation result with the corresponding hash value pre-stored on the blockchain, and issuing an alert for potentially tampered data and generating an audit report if the comparison is inconsistent.

[0118] In this implementation, the results of anomaly checks are recorded on the blockchain.

[0119] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A blockchain-based method for tracing and verifying green electricity identification, characterized in that, The method includes: obtaining basic business data of a user's green electricity consumption identifier through a green electricity consumption accounting application module, and uploading the basic business data of the green electricity consumption identifier to a blockchain for solidification and notarization; the user submits a green electricity consumption rating application to the green electricity consumption identifier management module, and after receiving the application, the green electricity consumption identifier management module obtains the basic business data of the green electricity consumption identifier from the blockchain, determines the user's green electricity consumption level based on the basic business data of the green electricity consumption identifier, and generates a green electricity consumption level identifier and a corresponding traceability QR code; the user scans the traceability QR code with a scanning device to send a traceability request to the green electricity identifier traceability module, and the green electricity identifier traceability module checks the traceability request. The system queries the basic business data of green electricity consumption rating on the blockchain, generates a green electricity consumption accounting list based on the basic business data, and provides the green electricity consumption accounting list to the user. The green electricity consumption rating module receives a green electricity consumption rating application and generates a green electricity consumption rating label and a corresponding traceability QR code. Specifically, this includes the following operations: parsing the green electricity consumption rating application to obtain green electricity consumption user information and approval time range information; calling a smart contract to query and obtain the corresponding basic business data of green electricity consumption on the blockchain based on the green electricity consumption user information and approval time range information; and calculating the green electricity consumption ratio based on the green electricity consumption amount. The green electricity consumption ratio is calculated as follows: 100% × (green electricity consumption / total electricity consumption) × correction factor. The user's green electricity consumption level is determined based on their green electricity consumption and green electricity consumption ratio. A corresponding green electricity consumption level identifier is generated based on the user's green electricity consumption information and green electricity consumption level. A corresponding traceability QR code is also generated based on the user's green electricity consumption information, the determined time range, and the green electricity consumption level. The green electricity consumption level identifier and traceability QR code are then issued to the user. The determination of the correction factor includes the following operations: obtaining the user's historical behavior data, determining the user's historical behavior score based on the historical behavior data, wherein the historical behavior data is generated by... The data consists of user behavior data recorded in real time in the blockchain; electricity metering terminal commissioning information is obtained and input into a neural network model for processing to obtain collection accuracy information. The electricity metering terminal commissioning information includes electricity metering terminal model information, electricity metering terminal commissioning duration information, and electricity metering terminal deployment environment information; the green electricity source proof in the green electricity consumption identification basic business data is verified to obtain verification results; the historical behavior score, collection accuracy information, and verification results are normalized; and a correction factor is calculated based on the normalized historical behavior score, collection accuracy information, and verification results, as shown in the following formula: In the above formula, Indicates the correction factor. The weights representing the historical behavior scores, Represents the score of historical behavior. The weights represent the accuracy of the collected information. This indicates the accuracy of the collected information. The weights of the validation results are represented. This indicates the verification result.

2. The method for tracing and verifying green electricity identification based on blockchain according to claim 1, characterized in that, The basic business data for green electricity consumption identification includes green electricity consumption user information, green electricity consumption type, green electricity consumption time, green electricity consumption amount, green electricity source proof, emission reduction effect, and emission reduction calculation method.

3. The method for tracing and verifying green electricity identification based on blockchain according to claim 2, characterized in that, The green electricity consumption accounting application module acquires basic business data on users' green electricity consumption identification and uploads this data to the blockchain for solidification and notarization. Specifically, this includes the following operations: collecting users' green electricity consumption through electricity metering terminals and recording corresponding green electricity consumption user information, green electricity consumption type, and green electricity consumption time, generating green electricity source proof; calculating emission reduction effects based on green electricity consumption and recording the corresponding calculation method; and writing green electricity consumption amount, green electricity consumption type, green electricity consumption time, green electricity source proof, emission reduction effect, and calculation method into the blockchain for storage.

4. The method for tracing and verifying green electricity identification based on blockchain according to claim 3, characterized in that, The generation of green electricity source proof specifically includes the following operations: determining the pseudo-random function, electricity metering terminal identification information, green electricity consumer information, maximum iteration count, and green electricity source proof length; in the first iteration of the pseudo-random function, the electricity metering terminal identification information is used as the key, and the green electricity consumer information is concatenated with t+1 to obtain the first concatenation result, where t represents the iteration round number. The first concatenation result is used as the salt value, and the key and salt value are input into the pseudo-random function to obtain the output p[0] of the pseudo-random function in this iteration; in subsequent iterations of the pseudo-random function, the electricity metering terminal identification information is used as the key, and the output of the previous pseudo-random function is used as the input to obtain the output result p[1,...,T-1] of the pseudo-random function, where T represents the maximum iteration round number; in each subsequent iteration of the pseudo-random function, all output results of the pseudo-random function up to this round are XORed to obtain e[t] of this iteration, where t∈[0,t lv ], t lv The formula for calculating t is as follows: lv =COS length / OV length In the above formula, COS length Indicates the length of the green electricity source proof, OV length The length of the pseudo-random function output value is represented; the e[t] of each iteration is concatenated to obtain the second concatenation result, and the length control operation is performed on the second concatenation result so that the result of the length control operation meets the length limit of the green electricity source proof, and the result of the length control operation is used as the green electricity source proof.

5. A method for tracing and verifying green electricity identification based on blockchain according to claim 2, characterized in that, The basic business data for green electricity consumption identification is uploaded to the blockchain for solidification and notarization. Specifically, this includes the following operations: After the basic business data for green electricity consumption identification is successfully uploaded to the blockchain, a smart contract is triggered to authenticate the authenticity of the data and obtain a data authenticity authentication report; on-chain information for the basic business data for green electricity consumption identification is generated, including the blockchain information to which the data belongs, the block information written to, and the on-chain time information; the data authenticity authentication report and on-chain information are then fed back to the user.

6. The method for tracing and verifying green electricity identification based on blockchain according to claim 5, characterized in that, The authentication of the authenticity of the basic business data for green electricity consumption identification specifically includes the following operations: determining the emission reduction calculation method based on the basic business data for green electricity consumption identification; calculating the emission reduction effect based on the emission reduction calculation method, green electricity consumption type, and green electricity consumption amount; comparing the calculation result with the emission reduction effect in the basic business data for green electricity consumption identification to obtain a first comparison result; generating verification information based on the identification information of the electricity metering terminal that collects green electricity consumption and the user information that generates green electricity consumption; comparing the verification information with the green electricity source certificate to obtain a second comparison result; determining the authenticity of the basic business data for green electricity consumption identification based on the first comparison result and the second comparison result, and generating a data authenticity authentication report.

7. A method for tracing and verifying green electricity identification based on blockchain according to claim 6, characterized in that, The green electricity identification and traceability module provides users with a green electricity consumption accounting list, which includes: trusted evidence verification, displaying a data authenticity certification report on the green electricity consumption accounting list display page; hash verification, performing a hash operation on the green electricity consumption accounting list content, comparing the hash operation result with the corresponding hash value pre-stored on the blockchain, and if the comparison is inconsistent, issuing an alert for potentially tampered data and generating an audit report; and recording abnormal verification results on the blockchain.

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