Power transfer user green electricity consumption authentication method and system based on trusted privacy calculation

Abstract

The application discloses a green electricity consumption authentication method and system for a transferred power user based on trusted privacy calculation and belongs to the technical field of green electricity consumption authentication. The existing green electricity consumption authentication method for a transferred power user has problems such as difficult trust of electricity data, difficult acquisition of data, easy leakage of data privacy, difficult distribution of green electricity consumption and the like, and cannot realize accurate calculation and trusted authentication of green electricity consumption of the transferred power. The green electricity consumption authentication method for a transferred power user based on trusted privacy calculation of the application acquires user electricity data by using a trusted acquisition algorithm to solve the problem of difficult trust of user data; calculates the green electricity usage of the user by using privacy calculation to solve the problem of electricity data privacy of the transferred power user and avoid leakage of user data; determines the green electricity usage of the user by the green electricity usage of the user to solve the problem of inaccurate calculation of the green electricity usage of the user, and the accurate and trusted green electricity consumption authentication can be provided for the transferred power user.

Description

Technical Field

[0001] This invention relates to a method and system for authenticating green electricity consumption by electricity transfer users based on trusted privacy computing, and belongs to the field of green electricity consumption authentication technology. Background Technology

[0002] Industrial parks equipped with self-generated and self-consumed distributed photovoltaic power generation typically use a power transfer method for their internal enterprise users. Since the power transfer data involves the privacy of the power transfer users, the power grid company has no right to monitor it. In other words, in the power transfer scenario, the park and the power grid company conduct unified electricity billing, and then the electricity is redistributed and billed based on the actual electricity consumption of each enterprise user (power transfer user).

[0003] This means that power grid companies and energy regulatory authorities only have a general understanding of the park's electricity consumption, making it difficult to directly obtain detailed internal data. Consequently, energy regulatory authorities can only rely on the metering data provided by the power grid companies to issue green certificates to photovoltaic investors in the park.

[0004] However, for photovoltaic investors, green certificates do not have direct economic benefits and instead become a kind of "idle resource." For park enterprises that are eager to demonstrate their sustainable development capabilities through green certificates, they cannot prove that they have used green electricity, thus they cannot obtain green electricity consumption certification and cannot use it to offset carbon emissions, which limits the application value of green certificates.

[0005] Therefore, the existing certification of green electricity consumption for electricity resellers faces problems such as difficulty in data trust, difficulty in data acquisition, easy leakage of data privacy, and difficulty in green electricity consumption allocation, making it impossible to achieve accurate calculation and reliable certification of green electricity consumption for electricity resellers.

[0006] The information disclosed in this background section is only for understanding the background of the inventive concept, and therefore may include information that does not constitute prior art. Summary of the Invention

[0007] To address the aforementioned problems, or one of them, the present invention aims to provide a method and system for green electricity consumption authentication for resellers based on trusted privacy computing. This method acquires user electricity consumption data using a trusted acquisition algorithm to solve the problem of difficulty in trusting user data; employs privacy computing to calculate user green electricity usage, resolving the privacy issue of electricity consumption data for resellers and preventing data leakage; and determines user green electricity usage through the correlation of user electricity consumption, thereby solving the problem of inaccurate calculation of user green electricity usage. Therefore, it can provide accurate and reliable green electricity consumption authentication for resellers, providing evidence for them to further conduct green certifications such as product carbon footprint and green factory certifications. This supports resellers in gaining an advantage in bidding, carbon tariffs, green finance, and other related businesses, effectively enhancing the application value of green certificates.

[0008] To address the aforementioned problems, or one of them, the second objective of this invention is to provide a method for authenticating green electricity consumption by resellers based on trusted privacy computation. This method involves constructing a demand acquisition model, a data collection model, a green electricity usage calculation model, and a green electricity authentication processing model. A trusted acquisition algorithm is used to acquire reseller data, thus solving the problem of difficulty in trusting reseller data. Simultaneously, privacy computation is performed on the reseller data to obtain the green electricity usage of resellers. This addresses both the issue of easy privacy leaks for resellers and the challenge of green electricity consumption allocation, enabling accurate calculation of green electricity usage by resellers and resolving the problem of inaccurate green electricity usage calculations. Furthermore, the green electricity usage of resellers is processed to generate green electricity consumption authentication information, achieving accurate calculation and trusted authentication of green electricity consumption in reseller scenarios. The solution is scientific, reasonable, and feasible.

[0009] To achieve one of the above objectives, the first technical solution of the present invention is as follows:

[0010] The green electricity consumption authentication method for electricity resellers based on trusted privacy computing includes the following steps:

[0011] Step 1: Collect information on the demand for green electricity consumption certification from one or more electricity transfer users through a pre-built demand acquisition model;

[0012] Step two: Using a pre-built data acquisition model, based on demand information, and through a reliable acquisition algorithm, obtain the power transfer data;

[0013] Step 3: Using a pre-built green electricity usage calculation model, perform privacy calculations on the electricity transfer data to obtain the green electricity usage of the electricity transfer users;

[0014] Step four involves using a pre-built green electricity authentication processing model to process the green electricity usage of resellers, generating green electricity consumption authentication information for resellers, and completing the green electricity consumption authentication of resellers based on trusted privacy computing.

[0015] This invention constructs a demand acquisition model, a data collection model, a green electricity usage calculation model, and a green electricity authentication processing model, and utilizes a trusted acquisition algorithm to acquire resold electricity data, thereby addressing the difficulty in trusting resold electricity data. Simultaneously, it performs privacy calculations on the resold electricity data to obtain the green electricity usage of resold electricity users. This addresses both the issue of easily leaked user privacy and the challenge of green electricity consumption allocation, enabling accurate calculation of green electricity usage by resold electricity users and resolving the problem of inaccurate green electricity usage calculations. Furthermore, it processes the green electricity usage of resold electricity users to generate green electricity consumption authentication information, achieving accurate calculation and trusted authentication of green electricity consumption in resold electricity scenarios. The solution is scientific, reasonable, and feasible.

[0016] Furthermore, this invention acquires user electricity consumption data based on a trusted acquisition algorithm to address the difficulty of trusting user data; it employs privacy-preserving computation to calculate user green electricity usage, resolving the privacy issue of electricity data for resellers and preventing data leakage; and it determines user green electricity usage through the correlation of electricity consumption among resellers, thereby solving the problem of inaccurate calculation of user green electricity usage. Therefore, it can provide resellers with accurate and reliable green electricity consumption certification, providing evidence for resellers to further develop green certifications such as product carbon footprint and green factory certifications. This supports resellers in gaining an advantage in bidding, carbon tariffs, green finance, and other related businesses, effectively enhancing the application value of green certificates.

[0017] The users who can transfer electricity can be users in the park, users in the factory area, or users in a certain area.

[0018] As a preferred technical measure:

[0019] Step two involves using a pre-built data acquisition model and, based on demand information, employing a reliable acquisition algorithm to obtain the transferred power supply data. The method is as follows:

[0020] Data transfer data is obtained using a data acquisition terminal; and blockchain technology is used to store the data on the blockchain to ensure the authenticity and completeness of the data; the data transfer data should include at least the name of the user, the amount of electricity consumed, and the time of data collection.

[0021] The trusted computing monitoring unit acquires the hardware and software measurement data of the power supply user and generates a trusted report for on-chain storage, thus obtaining environmental on-chain data to ensure the security and trustworthiness of the computing environment.

[0022] A trusted verification unit is used to verify the on-chain data of electrical energy, and verification data is obtained to verify the transferred power supply data.

[0023] Based on the verification data, the final power supply data is determined.

[0024] As a preferred technical measure:

[0025] The method for obtaining electricity data on the blockchain by using a data acquisition terminal and storing the data on the blockchain using blockchain technology is as follows:

[0026] The power supply data is converted into a data exchange format file and compressed into groups to obtain compressed power data one.

[0027] The encryption algorithm is invoked to perform fingerprint calculation on the compressed electrical energy data 1, resulting in electrical energy fingerprint data 1.

[0028] The electrical fingerprint data is stored on the blockchain to obtain the electrical blockchain data, which serves as electronic evidence. The blockchain storage identifier of the electrical fingerprint data is then fed back to the collection terminal.

[0029] Alternatively / and, by using a trusted computing monitoring unit, the following method is used to obtain hardware and software measurement data of the power supply user and generate a trusted report for on-chain storage, thereby obtaining the on-chain environmental data:

[0030] The initial measurement value of the user's hardware and software information obtained during the power transfer process is set as the baseline value and stored in the trusted chip.

[0031] After that, the measurement frequency is set, and the measurement operation is performed on the software and hardware of the power supply user according to the measurement frequency to obtain the measurement value;

[0032] Compare the measured value with the benchmark value. If the two are completely consistent, it indicates that the computing environment of the power supply user is reliable.

[0033] If the two are inconsistent, it indicates that the computing environment of the power supply user is unreliable;

[0034] Based on the comparison results, a trusted report is generated and stored on the blockchain to obtain environmental data on the blockchain.

[0035] Alternatively / and, a trusted verification unit is used to verify the on-chain data of electrical energy. The method for obtaining the verification data is as follows:

[0036] First, import the power transfer data to be verified, convert the power transfer data into a data exchange format file and compress it into groups to obtain the second compressed power data.

[0037] Then, the encryption algorithm is called to perform fingerprint calculation on the compressed power data to obtain power fingerprint data two;

[0038] Secondly, based on the power transfer data, the blockchain storage identifier is retrieved, and through the blockchain storage identifier, the on-chain stored power fingerprint data is queried.

[0039] Finally, the second power fingerprint data is compared with the first power fingerprint data. If the two are completely consistent, it indicates that the power transfer data has not been tampered with; otherwise, it is determined that the power transfer data has been tampered with, and verification data is generated.

[0040] As a preferred technical measure:

[0041] The method for obtaining power transfer data using a data acquisition terminal is as follows:

[0042] Using the data acquisition terminal, electricity consumption data sequences are collected, including electricity consumption information of transferred power users, charging information and discharging information of energy storage stations;

[0043] Calculate the mean and variance of electricity consumption data series;

[0044] Determine the normal range of electrical energy based on the mean and variance of electrical energy.

[0045] Based on the normal range of electricity consumption, and using the Lagrange interpolation method, the electricity consumption data sequence is interpolated and filled to supplement missing values ​​and remove outliers, so as to obtain a complete data sequence and form the power transfer data.

[0046] As a preferred technical measure:

[0047] Step 3: Using a pre-built green electricity usage calculation model, privacy calculations are performed on the electricity transfer data to obtain the green electricity usage of the transferred electricity users. The method is as follows:

[0048] Step 31: Deploy a privacy computing client for privacy computing at the power transfer user end or the park where the power transfer user is located. This client is used for data signature verification, data encryption, data decryption, initiating computing requests, and transmitting data.

[0049] Step 32: Using a privacy computing platform, generate a public key and a private key for the power supply environment, then store the public key for the power supply environment in the blockchain and make it public;

[0050] Step 33: The electricity transfer user initiates a computing request through the privacy computing client to obtain the public key of the electricity transfer environment. Then, the electricity transfer data is encrypted using the public key of the electricity transfer environment, and the electricity transfer data is signed using the user's private key to obtain the encrypted electricity consumption data of the electricity transfer user. The encrypted electricity consumption data of the electricity transfer user is then sent to the privacy computing platform.

[0051] Step 34: The privacy computing platform uses the corresponding user public key to verify the signature of the encrypted electricity consumption data of the electricity transfer user; and uses the private key of the electricity transfer environment to decrypt the encrypted electricity consumption data of the electricity transfer user to obtain the decrypted electricity transfer data.

[0052] Step 35: Calculate the green electricity consumption of the electricity transfer user based on the decrypted electricity transfer data.

[0053] As a preferred technical measure:

[0054] Step 35: The method for calculating the green electricity consumption of users receiving electricity through power transfer based on the decrypted power transfer data is as follows:

[0055] Step 351: Use the privacy computing client and privacy computing platform to obtain the photovoltaic power generation, grid-connected power, and grid-supplied power provided by the power grid company;

[0056] Step 352: Calculate the user's green electricity consumption using a privacy computing platform based on the decrypted power supply data, photovoltaic power generation, grid-connected power, and grid-connected power.

[0057] Step 353: The privacy computing platform encrypts the user's green electricity usage using the user's public key and signs the user's green electricity usage using the private key of the electricity transfer environment to obtain the encrypted green electricity information, and returns the encrypted green electricity information to the privacy computing client.

[0058] Step 354: The electricity transfer user or the park where the electricity transfer user is located uses a privacy computing client and the public key of the electricity transfer environment for verification and the user's private key to decrypt the encrypted information of green electricity usage, so as to obtain the decrypted information of the electricity transfer user's green electricity usage and determine the final green electricity usage of the electricity transfer user.

[0059] As a preferred technical measure:

[0060] Step four involves using a pre-built green electricity certification processing model to process the green electricity consumption of resellers, obtaining their green electricity consumption certification information as follows:

[0061] Obtain relevant information about the electricity transfer user, including at least the company name, company address, park name, photovoltaic registration party, electricity type, electricity consumption, and consumption cycle;

[0062] The relevant information of the electricity transfer user and the amount of green electricity used are packaged together and a hash value is calculated to obtain a proof of green electricity usage.

[0063] The green electricity usage proof is then stored in a blockchain-based notarization contract to form green electricity consumption certification information;

[0064] The green electricity consumption certification information is then sent to the electricity resellers to prove their green electricity consumption.

[0065] To achieve one of the above objectives, the second technical solution of the present invention is as follows:

[0066] A trusted privacy-preserving computation-based authentication method for green electricity consumption by electricity resellers includes the following:

[0067] Collect information on the green electricity consumption certification needs of one or more electricity resellers;

[0068] Based on demand information, reliable data acquisition algorithms are used to obtain power transfer data;

[0069] Privacy calculations are performed on the electricity transfer data to obtain the green electricity consumption of the electricity transfer users.

[0070] The green electricity usage of resellers is processed to obtain their green electricity consumption certification information.

[0071] Verify the green electricity consumption certification information of users who transfer electricity and generate certification certificates.

[0072] This invention acquires user electricity consumption data based on a trusted acquisition algorithm to address the challenge of trusting user data. It employs privacy-preserving computation to calculate user green electricity usage, resolving data privacy issues for resellers and preventing data leaks. Furthermore, by establishing correlations between resellers' electricity consumption and user usage, it determines their green electricity usage, thus resolving inaccurate calculations. This provides resellers with accurate and reliable green electricity consumption certification, supporting their further development of green certifications such as product carbon footprint and green factory certifications. This gives resellers an advantage in bidding, carbon tariffs, green finance, and other related businesses, effectively enhancing the application value of green certificates.

[0073] As a preferred technical measure:

[0074] The method for verifying the green electricity consumption certification information of electricity resellers and generating certification certificates is as follows:

[0075] Electricity resellers will provide green electricity consumption certification information regarding their green electricity usage to the privacy computing client;

[0076] The privacy computing client packages the green electricity consumption authentication information and calculates its hash value to obtain the hash value to be verified.

[0077] Check whether the hash value to be verified is consistent with the hash value in the corresponding evidence storage contract. If they are consistent, it means that the green electricity consumption certification information has not been tampered with, and the corresponding certification certificate is generated. If they are inconsistent, it means that the green electricity consumption certification information has been tampered with, and the certification certificate is no longer generated.

[0078] To achieve one of the above objectives, the third technical solution of the present invention is as follows:

[0079] A green electricity consumption authentication system for electricity transfer users based on trusted privacy computing includes a demand acquisition module, a data acquisition module, a green electricity usage calculation module, a green electricity authentication processing module, and a green certificate generation module.

[0080] The demand acquisition module is used to collect demand information from one or more electricity transfer users regarding green electricity consumption certification;

[0081] The data acquisition module is used to acquire power transfer data based on demand information and through a reliable acquisition algorithm;

[0082] The green electricity usage calculation module is used to perform privacy calculations on the electricity transfer data to obtain the green electricity usage of the electricity transfer users;

[0083] The green electricity certification processing module is used to process the green electricity usage of resold electricity users and obtain the green electricity consumption certification information of the resold electricity users;

[0084] The green certificate generation module is used to verify the green electricity consumption certification information of electricity transfer users and obtain certification certificate data.

[0085] This invention acquires user electricity consumption data based on a trusted acquisition algorithm to address the challenge of trusting user data. It employs privacy-preserving computation to calculate user green electricity usage, resolving data privacy issues for resellers and preventing data leaks. Furthermore, by establishing correlations between resellers' electricity consumption and user usage, it determines their green electricity usage, thus resolving inaccurate calculations. This provides resellers with accurate and reliable green electricity consumption certification, supporting their further development of green certifications such as product carbon footprint and green factory certifications. This gives resellers an advantage in bidding, carbon tariffs, green finance, and other related businesses, effectively enhancing the application value of green certificates.

[0086] Compared with existing technical solutions, the present invention has the following beneficial effects:

[0087] This invention constructs a demand acquisition model, a data collection model, a green electricity usage calculation model, and a green electricity authentication processing model, and utilizes a trusted acquisition algorithm to acquire resold electricity data, thereby addressing the difficulty in trusting resold electricity data. Simultaneously, it performs privacy calculations on the resold electricity data to obtain the green electricity usage of resold electricity users. This addresses both the issue of easily leaked user privacy and the challenge of green electricity consumption allocation, enabling accurate calculation of green electricity usage by resold electricity users and resolving the problem of inaccurate green electricity usage calculations. Furthermore, it processes the green electricity usage of resold electricity users to generate green electricity consumption authentication information, achieving accurate calculation and trusted authentication of green electricity consumption in resold electricity scenarios. The solution is scientific, reasonable, and feasible.

[0088] Furthermore, this invention acquires user electricity consumption data based on a trusted acquisition algorithm to address the difficulty of trusting user data; it employs privacy-preserving computation to calculate user green electricity usage, resolving the privacy issue of electricity data for resellers and preventing data leakage; and it determines user green electricity usage through the correlation of electricity consumption among resellers, thereby solving the problem of inaccurate calculation of user green electricity usage. Therefore, it can provide resellers with accurate and reliable green electricity consumption certification, providing evidence for resellers to further develop green certifications such as product carbon footprint and green factory certifications. This supports resellers in gaining an advantage in bidding, carbon tariffs, green finance, and other related businesses, effectively enhancing the application value of green certificates. Attached Figure Description

[0089] Figure 1 This is a schematic diagram of a privacy-based computing-based green certificate distribution method according to the present invention.

[0090] Figure 2 This is a schematic diagram of a trusted computing monitoring process according to the present invention;

[0091] Figure 3 A schematic diagram of a joint calculation process for this invention;

[0092] Figure 4 A schematic diagram illustrating a process for obtaining an authentication certificate using this invention;

[0093] Figure 5 A schematic diagram illustrating a process for calculating green electricity usage using this invention;

[0094] Figure 6 A schematic diagram of a process for distributing authentication certificates using this invention. Detailed Implementation

[0095] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0096] Conversely, this invention encompasses any substitutions, modifications, equivalent methods, and solutions made within the spirit and scope of the invention as defined in the claims. Furthermore, to provide a better understanding of the invention, certain specific details are described in detail below. However, those skilled in the art will fully understand the invention even without these detailed descriptions.

[0097] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. The term "or / and" as used herein includes any and all combinations of one or more of the associated listed items.

[0098] like Figure 1 As shown, this is the first specific embodiment of the privacy-based green certificate distribution method of the present invention:

[0099] The green electricity consumption authentication method for electricity resellers based on trusted privacy computing includes the following steps:

[0100] Step 1: Collect information on the demand for green electricity consumption certification from one or more electricity transfer users through a pre-built demand acquisition model;

[0101] Step two: Using a pre-built data acquisition model, based on demand information, and through a reliable acquisition algorithm, obtain the power transfer data;

[0102] Step 3: Using a pre-built green electricity usage calculation model, perform privacy calculations on the electricity transfer data to obtain the green electricity usage of the electricity transfer users;

[0103] Step four involves using a pre-built green electricity certification processing model to process the green electricity usage of resellers and generate green electricity consumption certification information for them.

[0104] A second specific embodiment of the privacy-based green certificate distribution method of the present invention:

[0105] A trusted privacy-preserving computation-based authentication method for green electricity consumption by electricity resellers includes the following:

[0106] S1 calculates the actual photovoltaic power consumption of each electricity transfer user within the park, including the following:

[0107] Current calculation methods allocate electricity based on monthly electricity consumption. Even if they are allocated based on daily electricity consumption, they cannot accurately reflect the actual photovoltaic electricity consumption of each electricity transfer user in the park.

[0108] For example, there are only two electricity transfer users in the park: User A and User B. User A uses electricity only during the day and not at night, while User B uses electricity only at night and not during the day. All the self-consumed photovoltaic power generation in the park is generated by User A, and User B's photovoltaic power consumption is zero. If the electricity consumption is allocated based on daily or monthly consumption, it will obviously differ significantly from the actual photovoltaic power consumption. Therefore, using daily or monthly allocation cannot reflect the true photovoltaic power consumption.

[0109] Power grid companies typically measure photovoltaic (PV) power generation and surplus grid-connected power every 15 minutes. Therefore, by shortening the calculation frequency from daily to 15 minutes, and using data collected every 15 minutes on grid-connected power, grid power supply, PV power generation, and electricity consumption by resellers, the PV power consumption of each reseller can be accurately calculated, avoiding the inaccuracies of daily or monthly calculations. The specific calculation method is as follows:

[0110] When the time period to be statistically analyzed is (Taking 24 hours as an example) when, Divided into short time interval Specifically, taking a 15-minute interval as an example, the 24 hours are divided into 96 intervals, and the expression is as follows:

[0111]

[0112] Furthermore, based on time intervals, reliable data collection is performed on electricity consumption within the park. When a total of One electricity transfer user, When a single energy storage station is used, Within the interval, the data collected by the meter includes photovoltaic power generation. Electricity resellers Electricity consumption Internet power consumption Power supply from the power grid Energy storage station Charging capacity Discharge quantity .

[0113] Based on the collected power consumption data, in Within the interval, calculate the energy storage station Storage power The calculation formula is as follows:

[0114]

[0115] Based on the collected power consumption data, in Within the interval, calculate the energy storage station photovoltaic power generation ratio The calculation formula is as follows:

[0116]

[0117] in, For energy storage stations Initial stored power, For energy storage stations Initial photovoltaic power generation ratio For energy storage stations Initial charge amount, For energy storage stations Initial discharge amount, This represents the initial photovoltaic power generation. This is the initial battery level for internet access. This represents the initial power supply.

[0118] Finally, calculate the electricity transfer users. During the period to be statistically analyzed The photovoltaic power used in the area The calculation formula is as follows:

[0119] .

[0120] In this embodiment, the method for reliably collecting electricity consumption data within the park is as follows:

[0121] The electricity transfer data is collected by the park itself rather than by official or trusted third parties. This data presents trust issues, primarily the risk of data tampering within the database. To address this, a trusted data collection device is deployed in the park, consisting of three parts: a data collection terminal, a trusted computing monitoring unit, and a trusted verification unit.

[0122] The data acquisition terminal obtains electricity transfer data before it is stored in the warehouse and uses blockchain technology to store it on the blockchain, ensuring the data's authenticity and integrity. The trusted computing monitoring unit obtains hardware and software measurement data, monitors the operation of the park's energy management system in real time, and generates a trusted report, which is then stored on the blockchain to ensure the computing environment's security and trustworthiness. The trusted verification unit performs automated verification based on the electricity fingerprint data stored on the blockchain to verify the electricity consumption data. In addition, the trusted acquisition device records the storage identifier returned by the blockchain each time it is stored on the blockchain and can correct the collected park electricity consumption data.

[0123] In this embodiment, the data acquisition terminal is constructed based on a trusted data acquisition algorithm, and its data acquisition method is as follows:

[0124] If there are N electricity transfer users in the park, and only M of them require green certificates, then data only needs to be collected from these M users, making it highly adaptable. Before parsing and storing the electricity transfer data, it is first converted into a JSON data exchange format file and compressed into groups. Then, the SHA256 encryption algorithm is used to calculate the fingerprint, and the fingerprint is stored on the blockchain as electronic evidence.

[0125] In this embodiment, please refer to Figure 2 The method for monitoring trusted computing using a trusted computing monitoring unit is as follows:

[0126] The initial measurement values ​​of the park's energy management system's hardware and software information are set as baseline values ​​and stored in a trusted chip. Subsequently, a measurement operation is performed every 15 minutes by default to obtain data fingerprints, which are then stored in the database. The measurement frequency can be adjusted according to actual needs. By comparing the baseline values ​​with the data fingerprints collected each time, it is verified whether the data has been tampered with.

[0127] In this embodiment, the trusted verification unit performs trusted verification as follows:

[0128] First, import the power transfer data to be verified and calculate the data fingerprint according to the trusted data collection algorithm. Second, retrieve the blockchain storage identifier based on the imported data information (power transfer user name, electricity consumption, collection time, etc.), and query the on-chain stored data fingerprint using the identifier. Finally, use the storage identifier to obtain the on-chain stored data fingerprint and compare it with the fingerprint of the data to be verified. If the two are completely identical, the data has not been tampered with; otherwise, the data is determined to have been tampered with.

[0129] In this embodiment, the method for uploading data to the blockchain is as follows:

[0130] Given security and compliance requirements, a domestic consortium blockchain platform, such as the Blockchain-based Service Network (BSN), was selected. 00:15:00 was set as the daily data processing and on-chain time point, where the previous day's power transfer data was aggregated and uploaded to the blockchain. To address on-chain failures due to network congestion or large data volumes, an automatic retry mechanism was designed. The default threshold for repeated on-chain attempts is 5 times. If the attempt still fails after exceeding this threshold, manual intervention is initiated to ensure complete data upload to the blockchain.

[0131] In this embodiment, the method for correcting the collected electricity consumption data of the park is as follows:

[0132] Step 1: Due to missing and abnormal data collected by the meters, it is necessary to correct the collected electricity consumption data, which includes the following:

[0133] Power generation meters and grid-connected meters are installed and maintained by the power grid company; missing and outlier values ​​are handled by the power grid company. Meters for users transferring power within the park are installed and maintained by the park itself; missing and outlier values ​​must be handled by the park itself, with specific solutions as follows. The collected data sequence is denoted as... Since electricity consumption data is cumulative, it is normally a non-decreasing sequence.

[0134] Assuming the missing value is Calculate the mean of electricity consumption data that does not include these missing values. ,variance Then calculate the standard score for each non-missing value. Values ​​marked outside the threshold range are considered outliers and are denoted as _____. The expression for the threshold interval is as follows:

[0135] .

[0136] For missing values and outliers The Lagrange interpolation method is used to interpolate and fill in the data, resulting in the processed data sequence. The Lagrange interpolation method described is an open-source algorithm that can be directly applied in this embodiment.

[0137] Step 2, check the decreasing interval of the new sequence, and denote the first decreasing subsequence as... .

[0138] Let the starting point of the corrected sequence be... Correcting the end of the sequence , corrected subsequence The value is used to obtain the corrected value through linear interpolation (an open-source algorithm applied within the interval from s to t). .

[0139] Step 3: Repeat step 2 for the sequence until the sequence no longer contains a decreasing interval.

[0140] S2, considering the privacy of electricity consumption data in the park, jointly calculates the green electricity usage of different electricity transfer users, which includes the following:

[0141] Calculating the proportion of photovoltaic power consumption for different electricity resellers within the industrial park requires joint calculation using power grid company and park power consumption data. However, the power grid company only possesses data on photovoltaic power generation, grid-connected power, and grid-supplied power; the park itself holds the power consumption data. Therefore, see [link to relevant documentation]. Figure 3 The construction of a joint computing method that considers protecting the privacy of electricity consumption data in the park mainly includes the following steps:

[0142] The first step is to build a privacy computing platform on the side of the power grid company or a trusted third party. This privacy computing platform consists of a Trusted Execution Environment (TEE) and the aforementioned electricity consumption calculation algorithm is deployed on the platform.

[0143] The second step involves deploying privacy-preserving computing clients on both the park side and the power grid company side. These clients are equipped with functions such as signature verification, data encryption and decryption, initiating computation requests, and data transmission. The data in this scenario includes photovoltaic power generation (timestamp, identification code, power generation), grid-connected electricity (timestamp, identification code, grid-connected electricity), grid-supplied electricity (timestamp, identification code, supplied electricity), electricity consumption by transferred users (timestamp, identification code, electricity consumption), energy storage station charging and discharging (timestamp, identification code, charging, discharging), and platform calculation results (time period, identification code, percentage of allocated green certificates).

[0144] Third, as described above, the privacy computing platform generates a TEE public-private key pair and stores the TEE public key on the blockchain for public access; the privacy computing client generates a public-private key pair for the power user, stores the user's public key on the blockchain, and makes it public.

[0145] The fourth step involves the park initiating a computing request through the privacy computing client to obtain the TEE public key, which serves as the encryption key for the electricity consumption of the transferred power users and the charging and discharging amounts of the energy storage station. As mentioned earlier, the TEE public key is used for encryption, and the user's private key is used for signing before the key is sent to the privacy computing platform.

[0146] Fifth, the privacy computing platform verifies the signature using the corresponding user's public key and decrypts the data using the TEE private key. It then uses the same method to obtain the photovoltaic power generation, grid-connected power, and grid-supplied power provided by the power grid company, calculates the green electricity consumption allocation results for users transferring electricity in the park, stores the results on the blockchain, and returns the results to the privacy computing client after encrypting them with the user's public key and signing them with the TEE private key, as described above.

[0147] The sixth step involves the park using the privacy computing client, as described above, to verify the signature using the TEE public key and the user's private key, decrypt the data, and obtain the green electricity consumption allocation result, i.e., proof of green electricity usage.

[0148] S3, based on blockchain, manages proof of green electricity usage and includes the following:

[0149] Users reselling electricity in the park apply for relevant certification from third-party organizations based on their time-related green electricity usage certificates and park green certificates. During the verification process, the third-party organizations need to verify the accuracy of the green electricity usage certificates. Therefore, a management method for green electricity usage certificates is proposed, including the following:

[0150] Step 1: The green electricity usage (consumption ratio) calculated by the privacy computing platform is packaged together with the company name, company address, park name, photovoltaic filing party (photovoltaic investor), electricity type, consumed electricity (total power generation), and consumption period (one month), and a hash value is calculated. The result is then stored in a notarization contract deployed on the blockchain. The green electricity usage proof is only valid after it is notarized on the blockchain.

[0151] Step 2: The privacy computing platform sends the green electricity usage certificate of the park to the park's electricity resellers. The electricity resellers can then apply for certification from a third-party organization based on the certificate.

[0152] Step 3: After the users transferring electricity in the park provide their green electricity usage certificates to a third-party organization, the third-party organization uses the original data (company, address, consumption ratio, etc.) on the green electricity usage certificates to package the original data, calculate the hash value, and then calls the query function of the blockchain's notarization contract to check whether the hash value to be verified and the notarized hash value are consistent. If they are consistent, it means that the green electricity consumption certification information has not been tampered with, and a corresponding certification certificate is generated; if they are inconsistent, it means that the green electricity consumption certification information has been tampered with, and no certification certificate is generated.

[0153] like Figure 4 , Figure 5 , Figure 6 As shown, a specific embodiment of the present invention is applied:

[0154] Using this invention, industrial parks can apply for green certificates free of charge through the green certificate issuance and trading system or the green certificate issuance system; park electricity resellers or park users, combined with green electricity consumption and allocation certificates, can apply for corresponding certification certificates from third-party certification bodies with "carbon footprint certification" qualifications, thereby participating in green bidding. The specific data processing process is as follows:

[0155] Step 1: As the photovoltaic (PV) registration entity, the park applies for green certificates free of charge through the green certificate issuance and trading system. After the park registers its PV equipment information in the system, the system obtains PV power generation data from the power grid company, and after verification, obtains the corresponding number of green certificates. Simultaneously, the park records the information of the obtained green certificates, including the number of green certificates and the issuance date.

[0156] Step 2: Enterprises reselling electricity within the park determine their need for green certificates based on their own requirements. For example, some enterprises, due to product export needs, require carbon label certification or participation in green bidding, thus having a significant need for green certificates; while other enterprises may not currently have this need. Enterprises reselling electricity with such needs should inform the park of their requirements and provide relevant business application instructions, such as information on carbon verification projects they are participating in, green bidding plans, etc.

[0157] Step 3: For users who need green certificates, the power transfer data is obtained using a trusted data collection device. The data is then combined with the photovoltaic power generation, grid-connected power, and grid power provided by the power grid company to perform privacy calculations through a privacy computing platform. This process calculates the green electricity usage of the users in the park and generates certificates based on the blockchain.

[0158] Step 4: The electricity reseller uses the park's green electricity usage certificate and the park's green certificate to apply for the corresponding certification from a qualified third-party certification body. The third-party certification body conducts a comprehensive evaluation based on the materials provided by the electricity reseller. If the certification conditions are met, a certification certificate is issued to the electricity reseller, such as a carbon footprint certification certificate or a green bidding qualification certificate.

[0159] Step 5: With the obtained certification, electricity resellers can participate in business applications such as carbon labeling, carbon footprint verification, and carbon auditing, or showcase their green energy usage in green bidding to enhance their competitiveness. The industrial park and third-party certification bodies can track and supervise the use of green certificates by electricity resellers to ensure the reasonable use of green certificates and the effectiveness of certification.

[0160] An embodiment of a device applying the method of the present invention:

[0161] An electronic device comprising:

[0162] One or more processors;

[0163] Storage device for storing one or more programs;

[0164] When the one or more programs are executed by the one or more processors, the one or more processors implement the above-described green certificate distribution method based on trusted privacy computing.

[0165] An embodiment of a computer medium applying the method of the present invention:

[0166] A computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the aforementioned method for distributing green certificates based on trusted privacy computation.

[0167] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, optical storage, etc.) containing computer-usable program code.

[0168] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0169] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0170] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0171] The model in this application is an object that uses physical or virtual representation to objectively describe the form and structure. The object is not the same as a physical object, and is not limited to physical or virtual. It can be a data processing function, software program, processing mode, usage method, operation mode, workflow, application process, electronic hardware, circuit module, processing system, system imitation or simulation object.

[0172] 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 it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can still modify or make equivalent substitutions to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for authenticating green electricity consumption by electricity transfer users based on trusted privacy computing, characterized in that: Includes the following steps: Step 1: Collect information on the demand for green electricity consumption certification from one or more electricity transfer users through a pre-built demand acquisition model; Step two: Using a pre-built data acquisition model, based on demand information, and through a reliable acquisition algorithm, obtain the power transfer data; The method is as follows: use a data acquisition terminal to obtain electricity transfer data; and use blockchain technology to store the data on the blockchain to obtain electricity data on the blockchain; the electricity transfer data should at least include the name of the electricity transfer user, the amount of electricity consumed, and the time of data collection. The trusted computing monitoring unit acquires the hardware and software measurement data of the power supply user and generates a trusted report for on-chain storage, thus obtaining environmental on-chain data to ensure the security and trustworthiness of the computing environment. The trusted verification unit is used to verify the on-chain data of electrical energy to obtain verification data; The method is as follows: First, import the power transfer data to be verified, convert the power transfer data into a data exchange format file and compress it into groups to obtain the second compressed power data. Then, the encryption algorithm is called to perform fingerprint calculation on the compressed power data to obtain power fingerprint data two; Secondly, based on the power transfer data, the blockchain storage identifier is retrieved, and through the blockchain storage identifier, the on-chain stored power fingerprint data is queried. Finally, the second power fingerprint data is compared with the first power fingerprint data. If the two are completely consistent, it indicates that the power transfer data has not been tampered with; otherwise, it is determined that the power transfer data has been tampered with, and verification data is generated. Based on the verification data, determine the final power supply data; Step 3: Using a pre-built green electricity usage calculation model, perform privacy calculations on the electricity transfer data to obtain the green electricity usage of the electricity transfer users; The method is as follows: Step 31: Deploy a privacy computing client for privacy computing at the power transfer user end or the park where the power transfer user is located. This client is used for data signature verification, data encryption, data decryption, initiating computing requests, and transmitting data. Step 32: Using a privacy computing platform, generate a public key and a private key for the power supply environment, then store the public key for the power supply environment in the blockchain and make it public; Step 33: The electricity transfer user initiates a computing request through the privacy computing client to obtain the public key of the electricity transfer environment. Then, the electricity transfer data is encrypted using the public key of the electricity transfer environment, and the electricity transfer data is signed using the user's private key to obtain the encrypted electricity consumption data of the electricity transfer user. The encrypted electricity consumption data of the electricity transfer user is then sent to the privacy computing platform. Step 34: The privacy computing platform uses the corresponding user's public key to verify the signature of the encrypted electricity consumption data of the electricity transfer user; Then, using the private key of the power supply environment, the encrypted power consumption data of the power supply user is decrypted to obtain the decrypted power supply data; Step 35: Calculate the green electricity consumption of the electricity transfer user based on the decrypted electricity transfer data; It includes the following: The electricity transfer user or the park where the electricity transfer user is located can use a privacy computing client and the public key of the electricity transfer environment for verification and the user's private key to decrypt the encrypted information of green electricity consumption, so as to obtain the decrypted information of the electricity transfer user's green electricity consumption and determine the final green electricity consumption of the electricity transfer user. Step four involves using a pre-built green electricity certification processing model to process the green electricity consumption of resellers and generate green electricity consumption certification information for them. The method is as follows: Obtain relevant information about the electricity transfer user, including at least the company name, company address, park name, photovoltaic registration party, electricity type, electricity consumption, and consumption cycle; The relevant information of the electricity transfer user and the amount of green electricity used are packaged together and a hash value is calculated to obtain a proof of green electricity usage. The green electricity usage proof is then stored in a blockchain-based notarization contract to form green electricity consumption certification information; The green electricity consumption certification information is then sent to the electricity resellers to prove their green electricity consumption.

2. The green electricity consumption authentication method for electricity transfer users based on trusted privacy computing as described in claim 1, characterized in that: The method for obtaining electricity data on the blockchain by using a data acquisition terminal and storing the data on the blockchain using blockchain technology is as follows: The power supply data is converted into a data exchange format file and compressed into groups to obtain compressed power data one. The encryption algorithm is called to perform fingerprint calculation on the compressed electrical energy data 1, resulting in electrical energy fingerprint data 1. The first power fingerprint data is stored on the blockchain to obtain the power blockchain data, which serves as electronic evidence. The blockchain storage identifier of the first power fingerprint data is then fed back to the collection terminal. Alternatively / and, by using a trusted computing monitoring unit, the following method is used to obtain hardware and software measurement data of the power supply user and generate a trusted report for on-chain storage, thereby obtaining on-chain environmental data: The initial measurement value of the user's hardware and software information obtained during the power transfer process is set as the baseline value and stored in the trusted chip. After that, the measurement frequency is set, and the measurement operation is performed on the software and hardware of the power supply user according to the measurement frequency to obtain the measurement value; Compare the measured value with the benchmark value. If the two are completely consistent, it indicates that the computing environment of the power supply user is reliable. If the two are inconsistent, it indicates that the computing environment of the power supply user is unreliable; Based on the comparison results, a trusted report is generated and stored on the blockchain to obtain environmental data on the blockchain.

3. The green electricity consumption authentication method for electricity transfer users based on trusted privacy computing as described in claim 2, characterized in that: The method for obtaining power transfer data using a data acquisition terminal is as follows: Using the data acquisition terminal, electricity consumption data sequences are collected, including electricity consumption information of transferred power users, charging information and discharging information of energy storage stations; Calculate the mean and variance of electricity consumption data series; Determine the normal range of electrical energy based on the mean and variance of electrical energy. Based on the normal range of electricity consumption, and using the Lagrange interpolation method, the electricity consumption data sequence is interpolated and filled to supplement missing values ​​and remove outliers, so as to obtain a complete data sequence and form the power transfer data.

4. The green electricity consumption authentication method for electricity transfer users based on trusted privacy computing as described in claim 1, characterized in that: Step 35: The method for calculating the green electricity consumption of users receiving electricity through power transfer based on the decrypted power transfer data is as follows: Step 351: Use the privacy computing client and privacy computing platform to obtain the photovoltaic power generation, grid-connected power, and grid-supplied power provided by the power grid company; Step 352: Calculate the user's green electricity consumption using a privacy computing platform based on the decrypted power supply data, photovoltaic power generation, grid-connected power, and grid-connected power. Step 353: The privacy computing platform encrypts the user's green electricity usage using the user's public key and signs the user's green electricity usage using the private key of the electricity transfer environment to obtain the encrypted green electricity information, and returns the encrypted green electricity information to the privacy computing client. Step 354: The electricity transfer user or the park where the electricity transfer user is located uses a privacy computing client and the public key of the electricity transfer environment for verification and the user's private key to decrypt the encrypted information of green electricity usage, so as to obtain the decrypted information of the electricity transfer user's green electricity usage and determine the final green electricity usage of the electricity transfer user.

5. A green electricity consumption authentication system for electricity transfer users based on trusted privacy computing, characterized in that: The method for authenticating green electricity consumption by electricity transfer users based on trusted privacy computing as described in any one of claims 1-4 includes a demand acquisition module, a data acquisition module, a green electricity usage calculation module, a green electricity authentication processing module, and a green certificate generation module. The demand acquisition module is used to collect demand information from one or more electricity transfer users regarding green electricity consumption certification; The data acquisition module is used to acquire power transfer data based on demand information and through a reliable acquisition algorithm; The green electricity usage calculation module is used to perform privacy calculations on the electricity transfer data to obtain the green electricity usage of the electricity transfer users; The green electricity certification processing module is used to process the green electricity usage of resold electricity users and obtain the green electricity consumption certification information of the resold electricity users; The green certificate generation module is used to verify the green electricity consumption certification information of electricity transfer users and obtain certification certificate data.

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