Power market information security sharing system, method and device and computer equipment

Abstract

The invention relates to an electric power market information security sharing system, method and device and computer equipment. The system comprises a data preprocessing module used for receiving private data from a plurality of power market subjects and preprocessing the private data to obtain preprocessed private data; the security computing protocol module is used for performing distributed storage on the preprocessed private data based on a secret sharing protocol, calling the preprocessed private data in the distributed storage in response to a computing request, and obtaining a power computing result corresponding to the preprocessed private data based on homomorphic encryption computing; and the information sharing and query module is used for responding to the access request of any power market subject, judging whether the access request of any power market subject has the authority of accessing the power calculation result, and if so, sharing the power calculation result to any power market subject. By adopting the system, the data security of power market information can be improved.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a power market information security sharing system, method, apparatus, computer equipment, computer-readable storage medium, and computer program product. Background Technology

[0002] In the electricity market environment, power generation companies, grid companies, and electricity retailers need to conduct cross-entity calculations and analyses based on their respective power generation plans, load forecasts, and electricity price data to support market operation and transaction decisions. Due to the highly sensitive nature of the data involved, existing information sharing models mostly rely on manual communication or centralized intermediaries for collaboration. Data processing procedures lack unified standards, making it difficult to effectively prevent data leakage during transmission or use, resulting in low efficiency in the use of private data and low security in cross-entity collaborative computing. Summary of the Invention

[0003] Therefore, it is necessary to provide a power market information security sharing system, method, apparatus, computer equipment, computer-readable storage medium, and computer program product that can improve the data security of power market information in response to the above-mentioned technical problems.

[0004] Firstly, this application provides a power market information security sharing system, comprising:

[0005] The data preprocessing module is used to receive private data from multiple electricity market entities and preprocess the private data to obtain preprocessed private data.

[0006] The secure computing protocol module is used to distribute the preprocessed private data based on a secret sharing protocol, and in response to a computing request, call the preprocessed private data in the distributed storage, and obtain the power calculation result corresponding to the preprocessed private data based on homomorphic encryption computing.

[0007] The information sharing and query module is used to respond to any access request from any electricity market entity, determine whether the access request from any electricity market entity has the permission to access the electricity calculation results, and if it has the permission, share the electricity calculation results with the any electricity market entity.

[0008] In one embodiment, the secure computing protocol module is further configured to split the preprocessed private data into multiple data shares based on a secret sharing protocol;

[0009] The data shares are distributed and stored in multiple physically isolated computing nodes.

[0010] In one embodiment, the secure computing protocol module is further configured to encrypt the preprocessed private data based on homomorphic encryption computing to generate encrypted data that can be used for encrypted computing.

[0011] Based on the encrypted data, perform power calculation operations to generate encrypted power calculation results;

[0012] The encrypted power calculation result is subjected to homomorphic decryption to obtain the power calculation result.

[0013] In one embodiment, the system further includes a smart contract and blockchain storage module for performing hash calculation processing on the power calculation information to obtain a new hash digest value of the power calculation; the power calculation information includes the power calculation result, as well as the calculation input information and calculation method identifier corresponding to the power calculation result;

[0014] The new hash digest value of the electricity calculation is written into the blockchain through a smart contract;

[0015] In response to a verification request from any of the electricity market participants, the hash digest value required for the verification request is read from the blockchain, and a hash calculation comparison is performed on the electricity calculation results provided by any of the electricity market participants to verify the integrity and consistency of the electricity calculation results provided by any of the electricity market participants.

[0016] In one embodiment, the system further includes a system interaction and visualization module for generating a graphical interactive interface for configuring data sharing strategies, selecting computing models, and submitting data to be processed in response to computing task requests.

[0017] In response to a result query request, the power calculation results are displayed, and the trend data corresponding to the power calculation results is visualized in the form of charts or curves.

[0018] Secondly, this application provides a method for secure information sharing in the electricity market, including:

[0019] Receive private data from multiple electricity market participants and preprocess the private data to obtain preprocessed private data;

[0020] Based on the secret sharing protocol, the preprocessed private data is distributed and stored. In response to a calculation request, the preprocessed private data in the distributed storage is called, and the power calculation result corresponding to the preprocessed private data is obtained based on homomorphic encryption calculation.

[0021] In response to an access request from any electricity market participant, determine whether the participant has permission to access the electricity calculation results. If permission is granted, share the electricity calculation results with the participant.

[0022] Thirdly, this application also provides a power market information security sharing device, comprising:

[0023] The preprocessing module is used to receive private data from multiple electricity market entities and preprocess the private data to obtain preprocessed private data.

[0024] The power calculation module is used to distribute the preprocessed private data based on a secret sharing protocol, and in response to a calculation request, call the preprocessed private data in the distributed storage, and obtain the power calculation result corresponding to the preprocessed private data based on homomorphic encryption calculation.

[0025] The information sharing module is used to respond to an access request from any electricity market entity, determine whether the access request from any electricity market entity has the permission to access the electricity calculation results, and if it has the permission, share the electricity calculation results with the any electricity market entity.

[0026] Fourthly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0027] Receive private data from multiple electricity market participants and preprocess the private data to obtain preprocessed private data;

[0028] Based on the secret sharing protocol, the preprocessed private data is distributed and stored. In response to a calculation request, the preprocessed private data in the distributed storage is called, and the power calculation result corresponding to the preprocessed private data is obtained based on homomorphic encryption calculation.

[0029] In response to an access request from any electricity market participant, determine whether the participant has permission to access the calculation results. If permission is granted, share the electricity calculation results with the participant.

[0030] Fifthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0031] Receive private data from multiple electricity market participants and preprocess the private data to obtain preprocessed private data;

[0032] Based on the secret sharing protocol, the preprocessed private data is distributed and stored. In response to a calculation request, the preprocessed private data in the distributed storage is called, and the power calculation result corresponding to the preprocessed private data is obtained based on homomorphic encryption calculation.

[0033] In response to an access request from any electricity market participant, determine whether the participant has permission to access the calculation results. If permission is granted, share the electricity calculation results with the participant.

[0034] Sixthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0035] Receive private data from multiple electricity market participants and preprocess the private data to obtain preprocessed private data;

[0036] Based on the secret sharing protocol, the preprocessed private data is distributed and stored. In response to a calculation request, the preprocessed private data in the distributed storage is called, and the power calculation result corresponding to the preprocessed private data is obtained based on homomorphic encryption calculation.

[0037] In response to an access request from any electricity market participant, determine whether the participant has permission to access the calculation results. If permission is granted, share the electricity calculation results with the participant.

[0038] The aforementioned power market information security sharing system, method, apparatus, computer equipment, computer-readable storage medium, and computer program products, firstly, involve a data preprocessing module that receives private data from multiple power market participants and preprocesses it to obtain preprocessed private data. By uniformly cleaning, standardizing, and structuring the private data across different power market participants, data quality consistency is improved, and the fusion of data from different sources is enhanced. This provides a unified input format for subsequent collaborative computing, reducing parsing errors and collaboration barriers caused by inconsistent data formats. Then, a secure computing protocol module, based on a secret sharing protocol, distributes the preprocessed private data and, in response to computing requests, calls the preprocessed private data from the distributed storage. Based on homomorphic encrypted computing, it obtains the power calculation results corresponding to the preprocessed private data, ensuring that the data is not leaked. Under the premise of exposing the private data content of all parties, by secretly sharing and homomorphically encrypting the data, and reactively executing joint computing tasks in a distributed environment, sensitive calculations can be completed while the data remains encrypted. This reduces the risk of data leakage and enhances the privacy protection strength and overall credibility of the computing process. Finally, the information sharing and query module responds to any access request from any electricity market entity, determining whether the entity has the authority to access the electricity calculation results. If so, the calculation results are shared with the entity. By performing permission checks when an access request is triggered, only electricity market entities that meet preset conditions are allowed to access the calculation results within their authorized scope. This prevents unauthorized entities from abusing sensitive information, effectively controls the access boundaries of calculation results, minimizes data sharing at the result level, and enhances the controllability and compliance of the result usage process. In the above system, by organically integrating the three functional modules of data preprocessing, secure computing, and result sharing, an end-to-end data processing and computing sharing process is established. The system completes format standardization and security preprocessing before private data leaves the local machine. Then, through encryption and distributed protocols, it supports collaborative computation among stakeholders under conditions where data is not visible. Finally, access to the results is only granted to stakeholders who meet the authorization criteria. This effectively avoids the risk of raw sensitive data being directly exposed during cross-stakeholder interactions, while reducing reliance on third-party intermediaries and improving the privacy and verifiability of the computation process. In summary, this enhances the efficiency of data collaboration and computational reliability among multiple parties in the electricity market, providing support for safe, accurate, and efficient market decision-making. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a block diagram of a power market information security sharing system in one embodiment;

[0041] Figure 2 This is a block diagram of a power market information security sharing system in one embodiment;

[0042] Figure 3 This is a block diagram of a power market information security sharing system in one embodiment;

[0043] Figure 4 This is a flowchart illustrating a method for secure information sharing in the electricity market, as shown in one embodiment.

[0044] Figure 5 Here is a block diagram of the power market information security sharing system in another embodiment;

[0045] Figure 6 This is a structural block diagram of a power market information security sharing device in one embodiment;

[0046] Figure 7 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0048] In one embodiment, such as Figure 1 As shown, a power market information security sharing system is provided. In this embodiment, the system includes:

[0049] The data preprocessing module 101 is used to receive private data from multiple electricity market entities and preprocess the private data to obtain preprocessed private data.

[0050] Private data refers to data generated by electricity market participants during market operation that has business sensitivity and privacy attributes, including but not limited to power generation plans of power generators, electricity load forecasts of grid companies, pricing strategies of electricity sales companies, power equipment operation data, and historical electricity price curves.

[0051] For example, the data preprocessing module 101 may include a data collection unit, a data cleaning unit, and a data standardization unit. The data collection unit accesses data sources from power generators, power grid companies, electricity sales companies, market trading platforms, or smart meters, supporting the collection and aggregation of data in multiple formats. The data cleaning unit removes redundant items, fills in missing fields, and corrects format errors to improve data quality. The data standardization unit performs structural mapping and unit unification on data fields from different sources, enabling subsequent encryption and distributed computing stages to perform logical processing based on a unified structure. After the above processing is completed, the module can perform structural reorganization, label classification, or encrypted pre-packaging of the data to prepare for processing by the secure computing protocol module.

[0052] The secure computing protocol module 102 is used to distribute and store preprocessed private data based on a secret sharing protocol, and in response to a computing request, call the preprocessed private data in the distributed storage, and obtain the power calculation result corresponding to the preprocessed private data based on homomorphic encryption computing.

[0053] Among them, the secret sharing protocol refers to a multi-party encrypted computing technology that splits the original data into multiple unidentifiable shares and distributes them to multiple computing nodes. Each node holds a portion of the information independently, and the original data can only be restored when multiple nodes cooperate. It has natural anti-leakage and anti-tampering capabilities.

[0054] Homomorphic encryption computation refers to a processing method that performs mathematical operations (such as addition or multiplication) directly on the ciphertext while the data is kept encrypted. The result of the computation is consistent with the result obtained by performing the operation on the plaintext after decryption.

[0055] For example, the secure computing protocol module 102 may include a secret sharing unit and a homomorphic computing unit. The secret sharing unit performs a linear secret sharing operation on the preprocessed private data, such as splitting each data item into six shares and storing each share in multiple distributed nodes, where different nodes cannot see each other's data. Subsequently, after receiving a computing request, the system schedules each distributed node to transmit the corresponding data share to the computing scheduling component, calls the homomorphic computing unit to load the secret operation algorithm, and performs mathematical processing on the ciphertext data. Taking payment amount as an example, if the ciphertext input is the predicted electricity amount Q and the predicted unit price C, the system performs the multiplication calculation Q×C=P at the ciphertext layer to obtain the ciphertext payment amount P. The final calculation result is output in ciphertext form for subsequent query and sharing processes, without exposing any intermediate plaintext information.

[0056] The information sharing and query module 103 is used to respond to any access request from any electricity market entity, determine whether the access request from any electricity market entity has the permission to access the electricity calculation results, and if it has the permission, share the electricity calculation results with any electricity market entity.

[0057] An access request refers to an interactive behavior initiated by an electricity market participant through a system interface (such as a web interface or an API interface) to obtain electricity calculation results. It includes information parameters such as the visitor's identity, the range of requested data, and the access time.

[0058] Access permissions refer to the data visibility rules set for different electricity market participants, which are used to limit the range of computational results they can access. Access policies are usually set based on roles (such as power generators, grid companies, and government regulatory agencies) to prevent unauthorized access to data.

[0059] For example, the information sharing and query module 103 parses the user identification information attached to the access request to verify whether the requester is legally registered and has a valid identity; based on the system's built-in access control policies (such as Role-Based Access Control, RBAC), it determines whether the requester has authorization to access the requested calculation results. For example, power generation companies can be authorized to access market price forecasts, power grid companies can access the overall supply and demand balance results, while electricity sales companies can only view load forecast information related to their users. If the determination result is that the authorization is approved, the result response unit calls the corresponding power calculation result and pushes it to the subject in the form of an encrypted data packet through the interface; otherwise, the system returns a message indicating that access is denied or an empty result response. The entire sharing process does not expose the original private data, only provides the final calculation results, and can further filter out unnecessary information based on the principle of data minimization.

[0060] In the aforementioned power market information security sharing system, firstly, the data preprocessing module receives private data from multiple power market participants and preprocesses it to obtain preprocessed private data. By uniformly cleaning, standardizing, and structuring the private data on each power market participant's side, data quality consistency can be improved, the fusionability between data from different sources can be enhanced, and a unified input format can be provided for subsequent collaborative computing, reducing parsing errors and collaboration barriers caused by inconsistent data formats. Then, the secure computing protocol module, based on a secret sharing protocol, distributes the preprocessed private data and, in response to computing requests, calls the preprocessed private data in the distributed storage. Based on homomorphic encryption computing, it obtains the power calculation results corresponding to the preprocessed private data, without disclosing the private data content of any party. By secretly sharing and homomorphically encrypting data, and reactively executing joint computation tasks in a distributed environment, sensitive computations can be completed while the data remains encrypted. This reduces the risk of data leakage and enhances the privacy protection strength and overall computational credibility of the computation process. Finally, the information sharing and query module responds to access requests from any electricity market entity, determining whether the entity has permission to access the electricity computation results. If permission is granted, the results are shared with the entity. By performing permission checks at the time of access request triggering, only electricity market entities meeting preset conditions are allowed to access computation results within their authorized scope. This prevents unauthorized entities from abusing sensitive information, effectively controls the access boundaries of computation results, minimizes data sharing at the result level, and enhances the controllability and compliance of result usage. In the above system, by organically integrating the three functional modules of data preprocessing, secure computation, and result sharing, an end-to-end data processing and computation sharing process is established. The system completes format standardization and security preprocessing before private data leaves the local machine. Then, through encryption and distributed protocols, it supports collaborative computation among stakeholders under conditions where data is not visible. Finally, access to the results is only granted to stakeholders who meet the authorization criteria. This effectively avoids the risk of raw sensitive data being directly exposed during cross-stakeholder interactions, while reducing reliance on third-party intermediaries and improving the privacy and verifiability of the computation process. In summary, this enhances the efficiency of data collaboration and computational reliability among multiple parties in the electricity market, providing support for safe, accurate, and efficient market decision-making.

[0061] In an exemplary embodiment, the secure computing protocol module 102 described above is further configured to split the preprocessed private data into multiple data shares based on a secret sharing protocol; and to distribute and store the data shares to multiple physically isolated computing nodes.

[0062] Among them, data shares refer to multiple parts of information calculated from the original data according to the secret sharing algorithm. Each share cannot be used to deduce the original data content when held alone. Only when multiple shares are processed together under specific combination conditions can the original private data be restored. This is used to prevent data exposure caused by single-node leakage.

[0063] Physically isolated computing nodes refer to multiple servers or processors deployed in different physical locations, with independent computing resources and limited network communication, used to store and process their respective data shares, thereby improving the anti-attack capability and data security level of the distributed computing system.

[0064] For example, the secure computing protocol module 102 can use an algorithm such as Shamir's secret sharing algorithm to perform data splitting on a standardized power generation plan data D. Specifically, the system can set the total number of shares n=5 and the minimum reconstruction threshold k=3, meaning that selecting any 3 out of any 5 data shares is sufficient to recover the original data, while selecting fewer than 3 shares will not yield any valid information. The module first generates k-1 random numbers a1 and a2, and constructs a pseudo-polynomial f(x) = D + a1x + a2x for secret sharing. 2 And calculate f(1), f(2), ..., f(5) as data shares D1, D2, ..., D5.

[0065] Subsequently, based on a preset node distribution strategy, the module distributes the aforementioned data shares to five physically isolated computing nodes. Each node is deployed on a geographically separated server, establishes a one-way transmission connection with the main system via an encrypted communication protocol, receives and stores an independent data share, and does not have the ability to access other nodes or reconstruct data.

[0066] After data distribution is complete, the system records the mapping relationship between each share and its corresponding node, and generates a share distribution log for subsequent scheduling. When a computation task arrives, this distributed structure automatically sends computation requests to each node through the task scheduling controller. Each node performs homomorphic encryption encapsulation based on its local data share and returns the encryption result to the main control unit. The main unit then uniformly completes subsequent cross-share encrypted computation operations, such as electricity price calculation and supply-demand balance analysis. The entire process requires no node to hold or restore the complete plaintext, effectively preventing single-point leakage and attack propagation.

[0067] In this embodiment, by splitting preprocessed private data into multiple data shares and distributing them to physically isolated computing nodes for storage, and combining this with homomorphic encryption for encrypted computation, cross-entity joint power computation is achieved without exposing the original data content. This significantly improves data security during storage and computation, avoids privacy issues caused by node damage or communication leaks, and reduces reliance on centralized trusted intermediaries, enhancing the system's decentralized collaboration capabilities and attack resistance.

[0068] In an exemplary embodiment, the aforementioned secure computing protocol module 102 is further configured to encrypt preprocessed private data based on homomorphic encryption computing to generate encrypted data that can be used for encrypted computing; perform power calculation operations based on the encrypted data to generate encrypted power calculation results; and perform homomorphic decryption processing on the encrypted power calculation results to obtain the power calculation results.

[0069] Encrypted data refers to ciphertext generated by encrypting original private data using a homomorphic encryption algorithm. This ciphertext, while maintaining its encrypted state, can still support specific mathematical operations, such as addition or multiplication, and is suitable for joint computation of private data.

[0070] Among them, the encrypted power calculation result refers to the calculation result obtained by multiple encrypted data through encrypted calculation logic during the power calculation process. It is still in an encrypted state and cannot be directly obtained without decryption.

[0071] Among them, homomorphic decryption processing refers to the decryption operation performed on the encrypted power calculation result, in order to restore the corresponding plaintext calculation result in the final output stage. This process is usually performed by a trusted entity with key permissions to ensure the correctness and privacy of the result data.

[0072] For example, the secure computation protocol module 102 can use homomorphic encryption schemes such as BFV (Brakerski / Fan-Vercauteren) or CKKS (Cheon-Kim-Kim-Song) to implement encrypted computation. The module first calls an encryption function to generate corresponding ciphertext from preprocessed data such as power generation plans, electricity load forecasts, or market electricity prices. For example, the load represented by Q is encrypted as Enc(Q), and the unit electricity price C is encrypted as Enc(C). Then, the module calls the homomorphic computation engine to perform a multiplication operation on the ciphertext, obtaining Enc(P) = Enc(Q) × Enc(C), representing the total market payment amount in the encrypted state. After the calculation is completed, the system transmits the encrypted result to the result recovery module, which possesses the key, to perform decryption and obtain the plaintext result P. The entire process does not require data decryption at any intermediate step, ensuring data privacy and security during the computation process.

[0073] In this embodiment, by restricting computational operations entirely to encrypted form and decrypting them only at the final output stage by an authorized entity, the risk of leakage of sensitive electricity market data during the computation process is effectively prevented. Compared to the traditional plaintext computation mode, this significantly improves the system's data privacy protection capabilities and result reliability in cross-entity collaborative computing scenarios.

[0074] In one exemplary embodiment, such as Figure 2 As shown, the aforementioned power market information security sharing system also includes a smart contract and blockchain storage module 104, which is used to perform hash calculation processing on power calculation information to obtain a new hash digest value for power calculation; the power calculation information includes the power calculation result, as well as the calculation input information and calculation method identifier corresponding to the power calculation result; the new hash digest value for power calculation is written into the blockchain through a smart contract; in response to a verification request from any power market participant, the system reads the hash digest value required for the verification request from the blockchain, and performs hash calculation comparison on the power calculation result provided by any power market participant to verify the integrity and consistency of the power calculation result provided by any power market participant.

[0075] Among them, power calculation information refers to the calculation-related content generated in the secure calculation module, including but not limited to the final power calculation result, the input data identifier corresponding to the result (such as task ID, calculation round, data digest, etc.), and the calculation method identifier (such as algorithm model version, encryption strategy number, etc.), which are used to uniquely identify the calculation behavior.

[0076] The hash digest value refers to a fixed-length data digest obtained by performing a hash operation on the above-mentioned power calculation information using a one-way hash function. This digest is collision resistant and can be used to identify whether the data has been tampered with or forged.

[0077] Among them, smart contracts refer to automatically executed logic scripts deployed in a blockchain system, which can automatically complete the on-chain operation of hash values ​​or receive verification requests and retrieve on-chain information for logical judgment after meeting specific trigger conditions.

[0078] For example, the smart contract and blockchain storage module 104 can call a secure hash function such as SHA-256 or SM3 after each electricity calculation to perform hash processing on the structured object composed of the calculation result, the electricity demand input data digest, and the version number of the homomorphic algorithm used, and generate a hash digest value H. result The system then writes the hash value into the corresponding transaction block in the consortium blockchain via a pre-deployed smart contract, and adds a timestamp and computation task ID tag.

[0079] When any electricity market participant submits a verification request, the system will invoke the smart contract to recalculate the hash value H based on the calculation results provided by that participant and the input content. input And retrieve the H corresponding to the task ID from the blockchain. result The system will compare the results. If they match, the system will confirm that the result provided by the market entity was generated by the system's original calculation and has not been tampered with; if they do not match, the system will refuse verification and issue an alarm.

[0080] In this embodiment, by solidifying the power calculation results and their related context into the blockchain in the form of a hash digest, and by automating the writing and verification logic through smart contracts, the verifiability and immutability of the calculation process and results are achieved. This effectively enhances the system's ability to automatically identify the authenticity of the results, increases the trust of all parties in the power market in the shared results, and provides technical support for subsequent auditing, supervision, and dispute arbitration.

[0081] In one exemplary embodiment, such as Figure 3 As shown, the aforementioned power market information security sharing system also includes a system interaction and visualization module 105, which is used to generate a graphical interactive interface for configuring data sharing strategies, selecting calculation models, and submitting data to be processed in response to calculation task requests; and to display power calculation results in response to result query requests, and to visualize the trend data corresponding to the power calculation results in the form of charts or curves.

[0082] Among them, a computing task request refers to a system interaction operation initiated by an electricity market entity to perform a specific electricity computing task. It includes information such as the selected computing model, data source selection, and execution condition settings, and is used to trigger the system scheduling computing process.

[0083] Among them, the result query request refers to the operation request issued by the electricity market entity to obtain the electricity calculation results within its authority. It usually includes parameters such as query target identifier, time period selection, and data dimension preference.

[0084] Trend data refers to data items in power calculation results that can change over time or region, such as time series, supply and demand dynamics, and electricity price fluctuations. This type of data can be displayed through curves, bar charts, heat maps, and other methods to show its changing trends.

[0085] For example, the system interaction and visualization module 105 can build a dynamic interface based on a web front-end framework, allowing users to log in and enter the "Task Management" page, configure data sharing strategies as needed (such as authorized data range, accessible party roles, etc.), select power calculation models (such as prediction models, supply and demand balance models), and upload or select data files to be processed. The system generates a task summary and submits it to the backend processing queue through interactive controls.

[0086] Once the calculations are complete, the system receives query requests and retrieves the corresponding results, displaying key output indicators such as predicted electricity prices, regional load, and payment amounts. Simultaneously, the system can utilize visualization components to generate supply and demand curves, electricity price time-based graphs, market share pie charts, and other charts. Users can customize the view by selecting the time range, granularity, and graphical format, improving the understandability of the results and the efficiency of analysis. The graphical interface also supports data export, allowing structured downloads in CSV and JSON formats.

[0087] In this embodiment, by constructing a graphical interactive interface and visualization display function, the threshold for users to understand the underlying computing logic is significantly reduced, the human-computer interaction friendliness and the intuitiveness of result interpretation of the system are improved, and various market entities can obtain useful information in a non-professional way, thereby enhancing the applicability and promotion capability of the system.

[0088] In one exemplary embodiment, such as Figure 4 As shown, this application provides a method for secure information sharing in the electricity market, comprising the following steps:

[0089] Step S401: Receive private data from multiple electricity market participants and preprocess the private data to obtain preprocessed private data;

[0090] Step S402: Based on the secret sharing protocol, the preprocessed private data is distributed and stored. In response to the calculation request, the preprocessed private data in the distributed storage is called. Based on homomorphic encryption calculation, the power calculation result corresponding to the preprocessed private data is obtained.

[0091] Step S403: In response to an access request from any electricity market entity, determine whether the access request from any electricity market entity has the permission to access the electricity calculation results. If it has the permission, share the electricity calculation results with any electricity market entity.

[0092] Private data refers to data types that are business-sensitive or have compliance and privacy requirements and are held by electricity market entities (such as power generation companies, grid companies, and electricity sales organizations), including but not limited to power generation plans, electricity price forecasts, electricity load, market trading strategies, and equipment operating status.

[0093] Preprocessing refers to performing operations such as cleaning, denoising, and standardizing format conversion on the raw data. The purpose is to improve data quality and unify its structure so that the subsequent secure computing module can identify and process it.

[0094] The secret sharing protocol refers to splitting the original data into multiple irreversible shares and distributing them to multiple distributed nodes for independent storage, ensuring that no single node can reconstruct the original data, thereby achieving data storage resistance to leakage and decentralization.

[0095] Among them, homomorphic encryption computation refers to performing power-related joint operations such as addition and multiplication on the ciphertext while keeping the data in an encrypted state, generating encrypted power calculation results, which are then decrypted and restored by the authorized party in the final stage.

[0096] Among them, an access request refers to a request initiated by an electricity market entity to the system through an API interface or web platform to obtain calculation results based on its business needs. It includes parameters such as entity identity information, query task identifier, and time period.

[0097] For example, the system first accesses load forecasts, electricity pricing schemes, and historical transaction data from multiple market participants, and the data preprocessing module uniformly performs format cleaning, anomaly removal, field alignment, and encryption encapsulation operations. The processed data is split into several shares through a secret sharing protocol, such as dividing each record into 6 parts, and distributed to multiple trusted computing nodes for storage.

[0098] Upon receiving a computation task trigger request, the system schedules computational resources, retrieves encrypted shares from each node, and invokes the homomorphic computation engine to perform encrypted calculations on tasks such as "market payment amount = electricity price × settlement amount." During this process, nodes cannot access the original data or intermediate results. After the calculation is completed, the system generates the power calculation result. The access control module determines the identity of the access party. If the access rules are met (e.g., power generators can view market price forecasts, and power grid companies can view the overall supply and demand curve), the calculation result is pushed to the designated access subject.

[0099] In this embodiment, by organically combining data collection, preprocessing, distributed encrypted computation, and result sharing based on access control, joint computation and controlled sharing among multiple parties in the electricity market are achieved while ensuring the privacy of private data. This method can effectively reduce the risk of data leakage, improve the efficiency of multi-party collaboration, and has good scalability and platform adaptability, making it suitable for various electricity market trading and analysis scenarios.

[0100] In another exemplary embodiment, such as Figure 5 As shown, this application provides a multi-party secure computation-based electricity market information sharing system, including:

[0101] The data preprocessing module 501 is responsible for collecting and processing the private data of various market participants, including power generation plans, supply and demand forecasts, and electricity price information; it uses data encryption to preprocess the data to make it suitable for multi-party secure computation.

[0102] The data preprocessing module 501 includes a data collection unit, a data cleaning unit, and a data standardization unit. The data collection unit processes data including power generation forecasts provided by power generators, electricity demand forecasts from grid companies and electricity retailers, electricity price information, market clearing prices, historical price trends, equipment operation data, power load curves, and equipment health status. Data sources include the grid company's database of power generators, the internal systems of electricity retailers, market trading platforms, and smart meters. The data processing unit cleans the data, removing outliers, filling in missing data, and deduplicating. The data standardization unit converts data from different formats into a unified format.

[0103] The secure computing protocol module 502 employs secret sharing and homomorphic encryption to achieve secure multi-party collaborative computing, ensuring that data is not leaked during the computing process and only outputting computing results to participants without exposing any intermediate data.

[0104] The secure computing protocol module 502 includes secret sharing, homomorphic encryption, and obfuscation circuitry. Secret sharing divides each market participant's data into multiple shares, which are stored on different servers. The original data can only be recovered when multiple holders collaborate. Homomorphic encryption allows direct addition, multiplication, and other operations on encrypted data without decryption, making it suitable for electricity price calculations and supply-demand balance analysis. Obfuscation circuitry is suitable for scenarios requiring protection of algorithmic logic, such as bidding strategy optimization. By obfuscating the computational logic, even if an attacker obtains the computation process, they cannot recover the original data.

[0105] Secret sharing includes linear secret sharing and multiplicative secret sharing.

[0106] Addition Secret Sharing: Let x be the private data to be shared, and select n-1 random numbers. ,

[0107] Calculate the nth secret share ,

[0108] Each calculation method Only holding No single party can recover x, but the sum of all shares can recover it:

[0109] .

[0110] Multiplication secret sharing: Let x and y be secretly shared as ( )and( ).

[0111] Calculate the local product of each party: ;

[0112] The final summation is calculated using a secure summation protocol. value:

[0113] .

[0114] Synchronous encryption supports addition and multiplication calculations. Let Enc(x) and Enc(y) be the encrypted data of x and y, respectively, then Enc(x) × Enc(y) = Enc(x × y). This can be used for electricity price calculation: Enc(P) = Enc(Q) × Enc(C), where Q is the market clearing volume and C is the price per unit of electricity, directly calculating the total payment amount P in the encrypted state.

[0115] The information sharing and query module 503 allows all participants in the electricity market to query and obtain relevant calculation results while ensuring data privacy. It adopts an access control policy to ensure that different roles can only access data within their authorized scope.

[0116] The information sharing and query module 503 includes a data sharing strategy, role-based access control, allowing power generators to query electricity price forecasts and market supply and demand, electricity retailers to query user load forecasts and electricity price information, power grid companies to query overall market transaction data, and government regulatory agencies to query all market data to ensure fair competition. It also adheres to the principle of data minimization, providing only calculation results without exposing raw data, and includes query interfaces, an API interface (supporting RESTful APIs for system integration by market participants), a web query (providing a visual interface and supporting custom queries), and data subscription (allowing market participants to subscribe to specific data, such as daily electricity price forecasts).

[0117] The smart contract and blockchain storage module 504 combines blockchain technology to record the calculation process and share the results through smart contracts, ensuring data traceability and immutability.

[0118] The smart contract and blockchain storage module 504 includes the following functions:

[0119] Transaction record storage: Smart contracts are used to record market transaction data to ensure the authenticity and immutability of the data; the execution of computation tasks is recorded, including the input, method, and hash of the result, for subsequent auditing and traceability; the transaction data is stored in a Merkle tree structure to optimize storage space and speed up query efficiency.

[0120] Hash storage of computation results: The hash value of the computation results is stored in the blockchain through a smart contract to ensure the integrity and verifiability of the computation results; the hash storage of computation results supports a timestamp mechanism to ensure the time consistency of the data and prevent tampering; it allows market participants to verify the authenticity of the computation results through the blockchain without accessing the original data.

[0121] Distributed ledger recording: Adopting a consortium blockchain architecture, it ensures that only authorized market participants can access and write relevant data; the ledger stores electricity market supply and demand data, electricity price history, market clearing information, etc., ensuring data traceability; a hierarchical storage strategy is adopted, with high-frequency access data stored on the chain and low-frequency access data stored off the chain, and consistency is ensured through hash verification.

[0122] Smart contract automatic execution mechanism: Set trigger conditions, such as automatically executing preset calculation tasks when market supply and demand reach a specific threshold, and storing the results; allow market participants to set personalized rules, such as automatic data sharing and transaction settlement under specific conditions; adopt an automatic settlement mechanism based on time or event triggers, such as automatically executing settlement payment logic after the calculation result is confirmed.

[0123] Data privacy and access control: Combining zero-knowledge proof technology to achieve data sharing and verification while protecting privacy; adopting role-based access control to ensure that different market participants can only access data within their authorized scope; allowing market participants to define personalized data access policies through smart contracts, such as allowing the querying of specific data only during specific time periods.

[0124] The system interaction and visualization interface 505 provides a web-based visualization interface for market entities to input data, manage calculation tasks, query results, and analyze data.

[0125] The system interaction and visualization interface 505 includes data management (uploading private data and configuring data sharing permissions); calculation task management (submitting calculation requests and viewing task execution status); result visualization (supply and demand curves, electricity price forecast trend charts, market bidding analysis, and optimization suggestions); and an interaction module (real-time notifications, automatically sending notifications upon completion of calculations, data export, supporting CSV and JSON format export, mobile adaptation and compatibility with PCs, mobile phones, and tablets, and remote access support).

[0126] For example, the data preprocessing module 501 preprocesses the collected data, then transmits the data to the secure computing protocol module 502. After the data is encrypted, it enters the secure computing protocol module 502 for secure computing. The processed data is then transmitted to the information sharing and query module 503 for sharing of the computing results. The data processed by the secure computing protocol module 502 and the information sharing and query module 503 is stored through the smart contract and blockchain storage module 504. Finally, the data is queried and visualized through the system interaction and visualization interface 505.

[0127] In a specific example, the parameters required for electricity price forecasting based on homomorphic encryption are shown in Table 1. The specific steps are as follows: the data preprocessing module 501 collects load forecast data provided by the power grid company and the electricity sales company; the data is encrypted using homomorphic encryption, and electricity price forecast calculation is performed in the encrypted state; joint calculation is performed based on secret sharing and homomorphic encryption through the secure calculation protocol module 502; the calculation results are accessed through the information sharing and query module 503, and power generators and electricity sales companies query the electricity price forecast according to their permissions; the blockchain stores the hash value of the calculation results to ensure data integrity.

[0128] Table 1. Parameters required for electricity price forecasting based on homomorphic encryption.

[0129]

[0130] In another specific example, the market supply and demand balance analysis based on secret sharing requires parameters as shown in Table 2. The specific steps are as follows: the data preprocessing module 501 cleans and standardizes the power generation plan and electricity demand data; the data is linearly and secretly shared, split into multiple shares, and stored in a distributed manner; the supply and demand balance is jointly calculated using the secure computing protocol module 502; the power grid company and regulatory agencies query the balance results through the information sharing and query module 503; and the blockchain stores the hash value of the supply and demand balance to prevent data tampering.

[0131] Table 2. Parameters Required for Market Supply and Demand Balance Analysis Based on Secret Sharing

[0132]

[0133] In this embodiment, compared to existing data preprocessing technologies, which suffer from heterogeneous data sources, inconsistent formats, and poor data quality affecting subsequent calculation results, this embodiment adopts a unified data preprocessing process to support the fusion of multi-source heterogeneous data from smart meters and market platforms. Traditional privacy-preserving computations, mostly based on trusted third parties or anonymization, pose a risk of leakage. This embodiment achieves joint computation without leakage or trusted intermediaries through a combination of secret sharing, homomorphic encryption, and obfuscation circuits. Traditional information sharing and access control have coarse-grained authorization management with unclear user role separation. This embodiment introduces role-based access control and the principle of data minimization to achieve on-demand access and strict permission allocation. Existing blockchain integration technologies are generally only used for evidence storage and are not deeply integrated with computation. This embodiment uses blockchain to fully participate in data storage, hash record calculation, and result verification, using a Merkle tree structure, consortium blockchain, and zero-knowledge proofs to enhance traceability and efficiency. Traditional user interfaces are mostly command-line or API integrations, which are not user-friendly. This embodiment introduces a web visual interface, mobile adaptation, real-time notifications, and custom subscriptions to improve user experience and ease of use. In summary, this embodiment introduces secret sharing technology, where each party retains only a share of the data, preventing leakage during the process; homomorphic encryption enables "electricity price calculation / supply and demand analysis to be completed in an encrypted state," ensuring the data is never decrypted; obfuscated circuits protect the bidding logic algorithm itself, preventing reverse reasoning; the verifiability and transparency of the system are enhanced, with all calculation process hashes and transaction records stored on the blockchain, making them tamper-proof; it supports result timestamp and hash value verification, allowing any party to independently verify the correctness of the result; it enables traceable auditing of the entire market transaction / bidding analysis process; and it strengthens the flexibility and control of data sharing by adopting role-based access control + zero-knowledge proofs, allowing power generators, electricity retailers, grid companies, and regulatory agencies to obtain visible data within their respective permissions; users can customize access policies, such as time period control and query frequency limits; it supports efficient automated management of market behavior, automatically triggering calculation tasks and transaction settlements after setting conditions; it saves manual operation costs and reduces human error rates, constructing an adaptive power trading platform through autonomous logic driven by smart contracts.

[0134] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0135] Based on the same inventive concept, this application also provides a power market information security sharing device for implementing the power market information security sharing method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more power market information security sharing device embodiments provided below can be found in the limitations of the power market information security sharing method described above, and will not be repeated here.

[0136] In one exemplary embodiment, such as Figure 6 As shown, a power market information security sharing device is provided, comprising: a preprocessing module 601, a power calculation module 602, and an information sharing module 603, wherein:

[0137] The preprocessing module 601 is used to receive private data from multiple electricity market entities and preprocess the private data to obtain preprocessed private data.

[0138] The power calculation module 602 is used to distribute and store preprocessed private data based on a secret sharing protocol, and in response to a calculation request, call the preprocessed private data in the distributed storage, and obtain the power calculation result corresponding to the preprocessed private data based on homomorphic encryption calculation.

[0139] The information sharing module 603 is used to respond to any access request from any electricity market entity, determine whether the access request from any electricity market entity has the permission to access the electricity calculation results, and if it has the permission, share the electricity calculation results with any electricity market entity.

[0140] Each module in the aforementioned power market information security sharing device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0141] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 7 As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a method for secure sharing of electricity market information. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0142] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0143] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0144] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0145] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0146] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0147] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0148] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0149] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A power market information security sharing system, characterized in that, The system includes: The data preprocessing module is used to receive private data from multiple electricity market entities and preprocess the private data to obtain preprocessed private data. The secure computing protocol module is used to distribute the preprocessed private data based on a secret sharing protocol, and in response to a computing request, call the preprocessed private data in the distributed storage, and obtain the power calculation result corresponding to the preprocessed private data based on homomorphic encryption computing. The information sharing and query module is used to respond to any access request from any electricity market entity, determine whether the access request from any electricity market entity has the permission to access the electricity calculation results, and if it has the permission, share the electricity calculation results with the any electricity market entity.

2. The system according to claim 1, characterized in that, The secure computing protocol module is also used to split the preprocessed private data into multiple data shares based on a secret sharing protocol. The data shares are distributed and stored in multiple physically isolated computing nodes.

3. The system according to claim 1, characterized in that, The secure computing protocol module is also used to encrypt the preprocessed private data based on homomorphic encryption computing to generate encrypted data that can be used for encrypted computing. Based on the encrypted data, perform power calculation operations to generate encrypted power calculation results; The encrypted power calculation result is subjected to homomorphic decryption to obtain the power calculation result.

4. The system according to claim 1, characterized in that, The system also includes a smart contract and blockchain storage module, used to perform hash calculation processing on the power calculation information to obtain a new hash digest value for the power calculation. The power calculation information includes the power calculation result, as well as the calculation input information and calculation method identifier corresponding to the power calculation result; The new hash digest value of the electricity calculation is written into the blockchain through a smart contract; In response to a verification request from any of the electricity market participants, the hash digest value required for the verification request is read from the blockchain, and a hash calculation comparison is performed on the electricity calculation results provided by any of the electricity market participants to verify the integrity and consistency of the electricity calculation results provided by any of the electricity market participants.

5. The system according to any one of claims 1 to 4, characterized in that, The system also includes a system interaction and visualization module, which is used to generate a graphical interactive interface for configuring data sharing strategies, selecting computing models, and submitting data to be processed in response to computing task requests. In response to a result query request, the power calculation results are displayed, and the trend data corresponding to the power calculation results is visualized in the form of charts or curves.

6. A method for secure information sharing in the electricity market, characterized in that, The method includes: Receive private data from multiple electricity market participants and preprocess the private data to obtain preprocessed private data; Based on the secret sharing protocol, the preprocessed private data is distributed and stored. In response to a calculation request, the preprocessed private data in the distributed storage is called, and the power calculation result corresponding to the preprocessed private data is obtained based on homomorphic encryption calculation. In response to an access request from any electricity market participant, determine whether the participant has permission to access the electricity calculation results. If permission is granted, share the electricity calculation results with the participant.

7. A power market information security sharing device, characterized in that, The device includes: The preprocessing module is used to receive private data from multiple electricity market entities and preprocess the private data to obtain preprocessed private data. The power calculation module is used to distribute the preprocessed private data based on a secret sharing protocol, and in response to a calculation request, call the preprocessed private data in the distributed storage, and obtain the power calculation result corresponding to the preprocessed private data based on homomorphic encryption calculation. The information sharing module is used to respond to an access request from any electricity market entity, determine whether the access request from any electricity market entity has the permission to access the electricity calculation results, and if it has the permission, share the electricity calculation results with the any electricity market entity.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method described in claim 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method described in claim 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method described in claim 6.

Images