Energy internet data secure transmission and authentication system

Abstract

The invention relates to the technical field of data security protection, in particular to an energy internet data security transmission and authentication system, and provides a scheme that the storage efficiency is improved by adjusting the capacity of a self-adaptive block and dynamically adjusting the size of the block according to the energy data flow. And a credibility rating mechanism is adopted to allocate the data to the main block chain or the auxiliary block chain, so that storage resources are optimized and the data credibility is improved. In a cross-chain interaction process, technologies such as identity verification, zero-knowledge proof and time lock are combined, so that the security and tamper-proof capability of data transmission are improved. Block storage is optimized based on the energy supply and demand balance state, the write-in load is reduced, and efficient storage of data in different load environments is ensured. The method improves the storage flexibility, safety and credibility of energy data, and can be widely applied to the fields of smart power grids, distributed energy transactions, carbon emission monitoring and the like.

Description

Technical Field

[0001] The present invention relates to the field of data security protection technology, and in particular to an energy internet data security transmission and authentication system. Background Art

[0002] In recent years, the rapid development of energy internet technologies has generated massive amounts of energy data in scenarios such as smart grids, distributed energy management, and energy trading markets. This data spans multiple processes, including power generation, transmission, distribution, consumption, and transaction settlement. Its secure storage, transmission, and authentication have become critical challenges that require urgent resolution. Traditional energy data management methods primarily rely on centralized databases or traditional cloud storage. While these methods offer sufficient data storage and computing capabilities, they face numerous technical bottlenecks in areas such as data credibility management, security and anti-tampering, and cross-system interoperability. These limitations make it difficult to meet the data security, efficiency, and decentralized storage requirements of the modern energy internet.

[0003] Blockchain technology is currently being widely used in energy data management and trading due to its decentralized, tamper-proof, and highly traceable properties. Traditional blockchain storage methods use fixed-size blocks for data storage, which presents limitations in the Energy Internet environment. Firstly, energy data traffic fluctuates significantly. For example, during peak periods of renewable energy (such as photovoltaic power generation), data transaction volume surges, while during periods of low load, data volume decreases significantly. Fixed-size blocks can lead to wasted storage resources and data congestion. Secondly, the credibility of energy data varies significantly. For example, smart meter data is generally more reliable, while data submitted by distributed energy users may contain certain deviations or errors. Traditional blockchain storage methods cannot distinguish data credibility, resulting in untrusted data occupying storage resources and even affecting transaction fairness. Furthermore, the need for multi-party data sharing in the Energy Internet exacerbates the problem of cross-chain data interaction between blockchains. Existing technologies lack effective authentication, privacy protection, and data integrity verification mechanisms, which can easily lead to cross-chain data tampering, unidentified transactions, and reduced data consistency, further impacting the normal operation of the energy trading market.

[0004] For example, Chinese patent application CN108564471B discloses a blockchain-based secure intelligent energy internet transaction system and method. The system includes a blockchain energy transaction platform, terminal devices, an energy dispatch system, and a smart contract system. The terminal devices interact with the blockchain energy transaction platform to exchange energy supply and demand information, while the blockchain energy transaction platform interacts with the energy dispatch system to exchange energy supply and demand information and energy transaction plans. The blockchain energy transaction platform interacts with the smart contract system to exchange smart contract information. This invented transaction system combines blockchain technology and smart contracts, eliminating the role of a third-party transaction center in the energy transaction process. All transaction participants are equal, and energy transactions are automatically executed according to pre-set smart contracts.

[0005] The above existing technologies all have the problems raised by this background technology. In order to solve the above problems, this application designs an energy Internet data security transmission and authentication system. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to address the deficiencies of the existing technology and provide an energy internet data security transmission and authentication system. Through adaptive block capacity adjustment, the block size is dynamically adjusted according to the energy data flow to improve storage efficiency. A credibility rating mechanism is adopted to allocate data to the main blockchain or the secondary blockchain to optimize storage resources and improve data credibility. In the cross-chain interaction process, authentication, zero-knowledge proof, time lock and other technologies are combined to improve the security and tamper-proof capability of data transmission. Furthermore, block storage is optimized based on the energy supply and demand balance state, reducing the write load and ensuring efficient storage of data under different load environments. This method improves the storage flexibility, security and credibility of energy data and can be widely used in smart grids, distributed energy trading, carbon emission monitoring and other fields.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] An energy internet data security transmission and authentication system is applied to energy internet data. The data security transmission and authentication system includes a data acquisition module, a data storage module and a data protection module;

[0009] The data acquisition module is used to collect energy data of the energy internet;

[0010] The data storage module is configured with a block configuration strategy, which is used to adjust the size and storage method of the block according to the characteristics and flow changes of the energy data;

[0011] The data protection module is used to provide data encryption and security authentication mechanisms.

[0012] The data storage module includes:

[0013] a storage allocation unit, configured to rate the energy data for credibility and allocate storage areas based on the credibility;

[0014] A capacity adjustment unit, configured to adjust the capacity of a storage area according to flow fluctuations of the energy data;

[0015] The block configuration strategy includes a credibility evaluation logic and a block adjustment logic. The credibility evaluation logic is configured in the storage allocation unit, and the block adjustment logic is configured in the capacity adjustment unit.

[0016] The credibility evaluation logic includes:

[0017] Calculating the credibility weight of each energy transaction data in the energy data;

[0018] Comparing the credibility weight with a preset credibility threshold, and if the credibility weight is greater than or equal to the credibility threshold, allocating the energy transaction data to the main blockchain;

[0019] If it is less than the trust threshold, the energy transaction data will be allocated to the secondary blockchain.

[0020] The block adjustment logic includes:

[0021] Predict data traffic through time series prediction models;

[0022] When an increase in energy data traffic is predicted, the capacity of the storage area is expanded according to the predicted amount;

[0023] When a decrease in energy data flow is predicted, the capacity of the storage area is reduced according to the predicted amount.

[0024] The data storage module further includes:

[0025] A data interaction unit, which is used to provide data interaction logic between the primary blockchain and the secondary blockchain;

[0026] The supply and demand adjustment unit is used to monitor the supply and demand balance of the energy internet and adjust the block capacity in the main blockchain when the supply and demand balance is unbalanced.

[0027] The data interaction logic includes:

[0028] Authenticate the data of the secondary blockchain and call the data of the primary blockchain after passing the authentication;

[0029] Encrypt the data of the main blockchain and the secondary blockchain through zero-knowledge proof;

[0030] Update the credibility weight of the transaction data based on the interaction results to determine whether the data transfer conditions are met;

[0031] If the data transfer conditions are met, secondary verification is performed through a time lock, and data transfer is performed after the verification is passed.

[0032] The authentication of the data on the secondary blockchain includes:

[0033] Generate a physical layer signature based on the power carrier communication characteristics corresponding to the data of the secondary blockchain;

[0034] The main blockchain receives and verifies the physical layer signature.

[0035] Adjusting the block capacity in the main blockchain includes:

[0036] Adjust the trust threshold based on the emergency consensus mechanism to reduce the frequency of data writing to the main blockchain;

[0037] The energy data in the main blockchain is prioritized according to the imbalance direction, and the filtered energy data is stored in the secondary blockchain, where the energy data is filtered according to the size of the priority.

[0038] The energy data in the main blockchain is prioritized according to the imbalance direction, including:

[0039] Adjust the consensus algorithm parameters of the main blockchain based on the direction and severity of the supply and demand imbalance;

[0040] The priority of energy data in the main blockchain is adjusted according to the consensus algorithm parameters.

[0041] The adjustment of the consensus algorithm parameters of the main blockchain includes:

[0042] When energy supply cannot meet demand, increase the stake weight of the proof-of-stake nodes and increase the decision-making power of the reputation nodes in the consensus process;

[0043] When the market transaction volatility is greater than the set volatility threshold, the Byzantine fault tolerance voting cycle is shortened.

[0044] A method for secure transmission and authentication of energy internet data, comprising:

[0045] Collect energy data from the Energy Internet;

[0046] Adjusting the block capacity in the energy blockchain based on the energy data, where each block corresponds to a characteristic of the energy data;

[0047] The energy data is transferred to the corresponding block and stored in shards according to the type of energy data.

[0048] The method further includes encrypting the energy data according to the physical characteristic parameters and storage location of the energy data.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] The present invention can dynamically adjust the block size according to the fluctuation of energy data flow, avoiding waste or congestion of storage resources; adopts a credibility rating mechanism to ensure that high-credibility data is stored in the main blockchain first, and low-credibility data is stored in the secondary blockchain, thereby improving data reliability and storage efficiency; through the supply and demand balance optimization mechanism, it reduces the writing of low-priority data to the main blockchain during the peak period of energy trading, reducing storage pressure; combines identity authentication, zero-knowledge proof, time lock and other technologies to ensure the security of cross-chain data interaction and prevent data tampering and illegal storage. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0052] Figure 1 This is a flow chart of a method for secure transmission and authentication of energy internet data according to embodiment 1 of the present invention;

[0053] Figure 2 This is a module diagram of an energy internet data security transmission and authentication system according to embodiment 2 of the present invention. DETAILED DESCRIPTION

[0054] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0055] Example 1:

[0056] See also Figure 1 The present invention provides an embodiment of a method for secure transmission and authentication of energy internet data. This method addresses key issues such as high volatility in energy internet data traffic, low utilization of data storage resources, and insufficient data security through intelligent data management, dynamic block capacity adjustment, trusted storage tiering, and secure authentication technologies. This method makes the storage, transmission, and authentication of energy data more efficient, secure, and reliable. The specific steps are as follows:

[0057] S1: Collect energy data in the energy internet;

[0058] In this embodiment, energy data is first collected. Within the Energy Internet environment, real-time energy data is acquired using data collection devices such as smart meters, substation monitoring equipment, distributed generation facilities, charging pile terminals, and new energy management systems. The collected energy data includes, but is not limited to, power generation data, distribution data, electricity consumption data, transaction settlement data, and energy consumption analysis data. This data comes from diverse sources, has varying degrees of credibility, and has complex data types. For example, transaction settlement data has a high degree of credibility, while data collected by distributed energy devices may be affected by noise and have a low degree of credibility. Therefore, a standardized data preprocessing process, including data formatting, outlier detection, and data cleaning, is employed to ensure data quality and prepare for subsequent credibility rating and blockchain storage.

[0059] S2: Adjust the block capacity in the energy blockchain based on the energy data, where each block corresponds to the characteristics of the energy data;

[0060] In this embodiment, due to the large fluctuations in energy data traffic, a fixed block capacity could result in excessive data storage pressure during peak periods or resource waste during off-peak periods. Therefore, an adaptive block partitioning strategy is employed to monitor energy data traffic in real time. Combined with a time series prediction algorithm, this strategy predicts energy data trends over a period of time in advance and dynamically adjusts block capacity accordingly. For example, when the frequency of new energy grid-connected transactions increases, the system automatically expands block capacity to improve data throughput and ensure timely writing of high-priority data. When a low-load period (such as a nighttime low-power transaction period) is detected, the block capacity is automatically reduced to avoid inefficient storage space usage and improve blockchain storage efficiency. This approach addresses the problems of energy data load imbalance, storage resource waste, or overflow caused by the rigidly fixed storage capacity of traditional blockchains, improves storage flexibility, and ensures the adaptability of blockchains in different energy trading scenarios.

[0061] S3: Transfer the energy data to the corresponding block and store it in shards according to the type of energy data;

[0062] In this embodiment, energy data is stored using a hierarchical storage strategy combined with a credibility rating mechanism. For the collected energy data, its credibility weight (Trust Score) is first calculated. This weight is quantitatively assessed based on multiple factors, including data source, data integrity, historical transaction records, and smart contract execution. Subsequently, based on the credibility rating results, a primary and secondary blockchain storage model is adopted, namely:

[0063] When the credibility weight is greater than or equal to the preset credibility threshold, the energy data will be directly stored in the main blockchain, which uses the whole network consensus mechanism to ensure the high credibility and non-tamperability of the data.

[0064] When the credibility weight is less than the preset credibility threshold, the energy data will be stored in the secondary blockchain. The secondary blockchain provides a flexible storage method and allows low-credibility data to be transferred to the main blockchain after improving its credibility through secondary verification or data interaction.

[0065] This application not only optimizes the storage resources of the main blockchain and prevents low-credibility data from occupying too much storage space, but also provides a secure and scalable data storage mechanism, so that low-credibility data still has the opportunity to enter the main blockchain through the credibility enhancement mechanism, thereby improving the system compatibility and data integrity.

[0066] S4: Encrypt energy data based on its physical characteristic parameters and storage location;

[0067] In this embodiment, to ensure data security and tamper resistance, a multi-layer encryption mechanism is used to encrypt energy data, specifically including:

[0068] Physical layer encryption: Combines the physical characteristic parameters of energy data (such as power carrier signal characteristics, voltage frequency changes, and current waveform characteristics) to generate a physical layer signature, and appends the signature to the data storage record to prevent data from being tampered with or forged during storage or transmission.

[0069] Zero-knowledge proof (ZKP) encryption: For the blockchain data interaction process, zero-knowledge proof technology is used to verify the legitimacy and integrity of transactions without revealing the specific content of energy transactions, ensuring the security of cross-chain data interaction and preventing man-in-the-middle attacks or illegal data tampering.

[0070] Timelock Mechanism: When data is exchanged between the primary and secondary blockchains, the system dynamically adjusts the timelock strategy based on the credibility rating. For example, data with low credibility must undergo a timelock delay storage mechanism and additional smart contract verification before being migrated to the primary blockchain to ensure data security.

[0071] Although blockchain technology has been widely used in energy data management, existing technical bottlenecks remain, including fixed block storage capacity, insufficient differentiation of data credibility, uneven storage load caused by fluctuations in energy supply and demand, and insufficient security for cross-chain data exchange. Traditional blockchain storage methods typically use fixed block sizes. When the volume of energy transaction data surges, this can easily lead to storage congestion and increased computational load. During periods of lower data volume, fixed block sizes can also waste storage resources. Furthermore, existing blockchain systems typically store all energy data indiscriminately on the main blockchain, failing to distinguish data credibility. This leads to inefficient use of storage resources and can even compromise overall data reliability due to the storage of untrustworthy data. Furthermore, in the Energy Internet, energy supply and demand balances fluctuate. When the grid experiences large-scale new energy integration, peak electricity demand, or sudden load changes, traditional blockchains are unable to dynamically adjust storage strategies, resulting in transaction confirmation delays and even block congestion. Furthermore, existing technologies lack security verification mechanisms for cross-chain data exchange, making data tampering, unidentified cross-chain transactions, and inconsistent transaction information prone to problems. This reduces the credibility of energy data, further impacting the fairness of the power trading market and the accuracy of energy scheduling.

[0072] Specifically, this embodiment employs an adaptive block capacity adjustment strategy based on data traffic, enabling blockchain storage capacity to dynamically expand or shrink as energy data traffic fluctuates. For example, during periods of active new energy trading, such as peak photovoltaic power generation periods or when the electricity trading market experiences significant fluctuations, the system automatically expands block capacity, improving data throughput and ensuring that transaction data is written to the blockchain in a timely manner, avoiding data loss or delays caused by insufficient capacity. During periods of low electricity consumption or low data traffic, block capacity is automatically reduced to minimize storage resource waste and improve overall computing efficiency. Compared to the fixed-capacity storage methods of traditional blockchains, this method significantly improves energy data storage flexibility and blockchain scalability, ensuring efficient operation under varying load conditions.

[0073] Furthermore, this embodiment classifies and stores energy data using a credibility rating mechanism, thereby optimizing the allocation of storage resources. Specifically, the system calculates credibility weights for energy data generated by data sources such as smart meters, photovoltaic inverters, wind power monitoring systems, and distributed energy management platforms. This calculation is based on a variety of factors, including data source reliability, data integrity, transaction records, and smart contract execution. Energy transaction data with a credibility weight greater than a preset threshold is stored on the primary blockchain, which uses a network-wide consensus mechanism to ensure data immutability and authenticity. Energy data with lower credibility is stored on a secondary blockchain, which allows for further verification before transferring it to the primary blockchain or employs a more lightweight storage method to reduce storage costs. For example, in the process of power grid load forecasting, historical electricity consumption data and real-time collected data have different credibility levels. Traditional methods have difficulty distinguishing the storage priority of these data. However, this method intelligently allocates storage locations, ensuring that high-credibility data is stored first while low-credibility data does not occupy the primary blockchain's storage resources, thereby improving the overall storage efficiency and data credibility of the blockchain.

[0074] Furthermore, this embodiment introduces a block optimization strategy based on the balance of energy supply and demand. When there is an imbalance in energy supply and demand (such as a surge in electricity demand or a supply shortage), the system dynamically adjusts the trust threshold, reduces the frequency of data writes to the main blockchain, and adjusts the storage strategy based on the data priority. For example, when large-scale renewable energy power generation is connected to the grid, the system lowers the trust threshold, allowing more renewable energy transaction data to enter the main blockchain to ensure the integrity of market transactions. During normal power load periods, the system raises the trust threshold and only stores the most critical transaction data to reduce storage load. This approach effectively mitigates the impact of supply and demand imbalances on blockchain storage, improves the robustness of the system, and enables it to adapt to dynamic changes in the energy market. Compared to the static storage method of traditional blockchains, this method can better cope with fluctuations in energy supply and demand and ensure the timeliness and reliability of energy data.

[0075] Furthermore, regarding cross-chain data interaction, this embodiment combines security authentication mechanisms such as physical layer signatures, zero-knowledge proofs, and time locks to enhance the security of data interaction. Specifically, a unique physical layer signature is generated using the physical layer characteristics of the power carrier signal, and a matching verification is performed during the data interaction process to ensure the authenticity of the transaction data source. Furthermore, a zero-knowledge proof (ZKP) mechanism is employed to verify data consistency without revealing energy transaction details, preventing data tampering or identity forgery during cross-chain interaction. Furthermore, for data interaction between the primary and secondary blockchains, this method introduces a time lock mechanism to ensure that low-trustworthiness data can only be migrated to the primary blockchain after undergoing a sufficiently long period of security verification, thereby preventing data fraud or illegal tampering. For example, in a new energy trading market, a transaction record may initially be stored on the secondary blockchain due to low data source credibility. However, after a period of time, after confirmation and consensus verification by multiple trading parties, the data's credibility increases, triggering the time lock unlocking mechanism and migrating the data to the primary blockchain, enhancing the data's credibility. This approach not only improves the security of cross-chain data but also effectively reduces the risk of mis-storage and illegal tampering.

[0076] For example, in an electricity trading market, a large number of distributed photovoltaic power generation devices sell surplus electricity to the power grid. Due to the limitations of fixed block capacity, traditional blockchains can lead to data storage congestion during peak trading periods, transaction confirmation delays, and even the occupation of storage resources by low-value data. This embodiment uses adaptive block capacity adjustment to automatically expand block capacity during peak trading periods, improving data throughput. Simultaneously, a credibility rating mechanism is utilized to ensure that high-credibility transaction data is preferentially stored on the primary blockchain, while low-credibility data is only stored on the secondary blockchain, avoiding waste of storage resources. Furthermore, through energy supply and demand balance monitoring, when there is a severe imbalance in electricity supply and demand, the credibility threshold and storage strategy are dynamically adjusted to ensure stable system operation. Finally, physical layer signatures and zero-knowledge proofs are used to ensure the security and integrity of cross-chain transaction data. The combination of these technical approaches enables this application to achieve accurate storage, trusted authentication, and efficient transmission of energy data in high-load, complex energy market environments. Compared to traditional technologies, this application offers higher storage efficiency, stronger security, and improved energy market adaptability.

[0077] The specific steps of S2 are as follows:

[0078] S2.1: Adjusting the capacity of the storage area according to the flow fluctuation of the energy data;

[0079] Specifically, in the Energy Internet, due to the volatility of factors such as energy transactions, electricity load, and renewable energy generation, energy data traffic is not uniform and stable, but rather exhibits distinct temporal and spatial characteristics. For example, during peak electricity demand periods or when large-scale new energy access is implemented, energy data transaction volume surges, while at night or during low-load periods, data traffic is relatively low. Using a fixed-capacity storage area can lead to insufficient storage resources and blockchain network congestion during high traffic periods, while wasting storage space during low traffic periods.

[0080] In this embodiment, when it is predicted that the energy data traffic will increase, the system will automatically expand the capacity of the storage area to provide greater data storage capabilities, while increasing the size and number of write blocks to avoid data backlogs or transaction delays; when it is predicted that the data traffic will decrease, the system will appropriately reduce the capacity of the storage area, reduce unnecessary storage resource usage, improve storage efficiency, and reduce computing resource consumption.

[0081] Furthermore, under high-traffic conditions, the system dynamically adjusts the block packaging frequency, increasing the rate of new block generation for a short period of time to reduce transaction backlogs and improve the speed of energy data writing. Under low-traffic conditions, the frequency of new block generation is reduced to reduce computing costs and storage overhead. This effectively adapts to changes in energy data traffic, ensuring that blockchain storage resources are always optimally configured under varying data traffic conditions, thereby improving storage resource utilization, reducing storage costs, and avoiding storage crashes or computing bottlenecks caused by sudden increases in traffic.

[0082] S2.2: Monitor the supply and demand balance of the Energy Internet;

[0083] Specifically, in the energy Internet environment, supply and demand balance is a key factor determining the stable operation of the power grid. Especially when a high proportion of new energy is connected, supply and demand fluctuations may lead to drastic changes in electricity market prices and frequent fluctuations in energy transactions, which in turn affect the storage and transmission stability of energy data.

[0084] In this embodiment, by accessing data sources such as power dispatch centers, smart meters, and load forecasting systems, it monitors energy supply and demand trends in real time and calculates the current grid supply and demand status, including indicators such as grid load level, generator output power, user electricity demand, renewable energy output forecast, and market trading activity. This system then builds a supply and demand balance analysis model based on information such as blockchain storage load, transaction data volume, and historical supply and demand status. When supply and demand fluctuations are detected, the system analyzes their potential impact on data flow and storage requirements. For example, when renewable energy output is high, renewable energy transaction data may increase. The system predicts blockchain storage pressure in advance and prepares adaptive storage expansion plans. When electricity demand decreases and trading market activity decreases, the system reduces the generation of new blocks and optimizes storage strategies to reduce the storage burden of low-priority data. Simultaneously, the system feeds the monitored supply and demand status back to the blockchain smart contract, achieving deep collaborative optimization of blockchain storage and grid operation. For example, in the event of significant fluctuations in renewable energy, the smart contract can automatically adjust the blockchain data storage strategy, prioritizing the storage of highly reliable renewable energy transaction data and delaying the writing of low-priority market data to ensure the security and stability of power transaction information. In this way, this application can grasp the changing trends of energy supply and demand in real time, and combine with the storage needs of blockchain to ensure that the data flow and storage resources in the energy Internet environment are in a dynamic balance, thereby improving the reliability and stability of data storage.

[0085] S2.3: When the supply-demand balance becomes unbalanced, adjust the block capacity in the main blockchain;

[0086] Specifically, when supply and demand imbalances occur, they can lead to dramatic fluctuations in electricity market transactions, impacting energy data storage requirements. For example, when grid load suddenly surges and power supply capacity is insufficient, a large amount of dispatch transactions and market adjustment transaction data will surge. If blockchain storage capacity is fixed, this can lead to a backlog of transaction data storage, blockchain network congestion, impacting transaction confirmation time, and even causing data storage failure.

[0087] In this embodiment, the severity of the imbalance is first analyzed, including factors such as the magnitude, duration, and transaction activity of the supply-demand mismatch, and the block capacity of the main blockchain is adjusted accordingly. For example, when electricity demand rises significantly and market transactions increase, the system automatically increases the block capacity of the main blockchain, increasing data packaging and writing rates to quickly respond to market transaction needs and ensure the integrity of power dispatch and transaction records. Once supply and demand gradually return to equilibrium, the system gradually reduces the block capacity to reduce unnecessary data storage and computing resource consumption.

[0088] Furthermore, the present application also combines a data credibility rating mechanism to prioritize data during periods of supply and demand imbalance. For example, during power shortages, the system prioritizes the storage of high-value transaction data and real-time scheduling instructions, while low-priority data such as low-value market forecast data and historical electricity consumption records can be temporarily stored in the secondary blockchain, or a distributed storage solution can be used to reduce the storage burden of the main blockchain. Furthermore, the present technology combines a time lock mechanism. For transaction data stored during periods of supply and demand imbalance, a delayed confirmation mechanism can be used to perform secondary verification on the stored data after the supply and demand balance is restored, to ensure the accuracy of data written under abnormal conditions and to prevent data errors or tampering risks caused by market fluctuations. Through this strategy, blockchain storage resources can be optimized under conditions of supply and demand imbalance, ensuring efficient storage and scheduling of energy data, while avoiding transaction data backlogs, increasing transaction confirmation speed, and enhancing the stability and reliability of the blockchain system.

[0089] The specific steps of S2.1 are as follows:

[0090] S2.1.1: Predict data traffic using a time series prediction model;

[0091] In this embodiment, to improve the blockchain's ability to rationally allocate energy data storage resources, a time series prediction model is used to predict energy data flow. This allows the system to adjust storage area capacity in advance to avoid storage congestion caused by sudden increases in flow or waste of storage resources due to decreases in flow. This embodiment uses a long short-term memory (LSTM) network, an ARIMA (autoregressive integrated moving average) model, and an exponentially weighted moving average (EWMA) model to predict data flow. LSTM can effectively capture the long-term dependencies of energy data flow and is suitable for processing cyclically fluctuating power trading data, while the ARIMA model is suitable for load forecasting of short-term fluctuations. The EWMA is used to smooth energy data flow in real time to reduce the impact of sudden changes. During the data flow prediction process, the system first collects historical transaction records and real-time power data from multiple data sources such as energy trading platforms, smart meters, and distribution network dispatch centers. It then uses feature extraction methods to extract key parameters that influence flow fluctuations, such as transaction time, equipment load, market electricity prices, weather conditions, and user electricity usage habits. The system then uses a sliding window approach to construct time series input data and feeds it into an LSTM model for training. The trained model automatically captures cyclical changes in energy data flow, load trends, and the impact of sudden trading events, ultimately deriving a forecast for future data flow. To ensure the reliability of the forecast results, the system further integrates ARIMA and EWMA models on top of LSTM forecasting to enhance the robustness and adaptability of the forecast, ensuring that the forecast reflects both long-term trends and can quickly respond to short-term changes.

[0092] S2.1.2: When an increase in energy data traffic is predicted, expand the capacity of the storage area based on the predicted amount;

[0093] In this embodiment, when the system predicts a future increase in energy data traffic using a time-series prediction model, it automatically implements a storage area expansion strategy to ensure sufficient storage resources during high-traffic periods, preventing transaction delays or storage failures due to insufficient blockchain capacity. Expanding the storage area's capacity primarily involves dynamically adjusting block size, increasing block generation frequency, and introducing a temporary cache storage mechanism. First, the system calculates the current utilization of the storage area and dynamically adjusts the block capacity based on the predicted traffic growth rate. For example, if energy transaction volume is expected to increase by more than 50% over the next 10 block periods, the system automatically increases the block capacity to store more energy transaction data per block. Furthermore, the system dynamically adjusts the block generation frequency to accelerate the generation of new blocks, mitigating transaction delays caused by single-block storage overflow. During high-traffic conditions, the system temporarily activates a cache storage mechanism to store some low-priority data (such as historical transaction logs and device operating data) off-chain. Once the system load returns to normal, the cached data is written to the blockchain in batches to balance storage pressure on the main blockchain. Through the above technical means, the system can ensure that data storage can still be carried out stably even during the peak period of large-scale energy trading, avoid transaction delays and block overflow problems, and improve the throughput capacity and storage elasticity of the blockchain.

[0094] S2.1.3: When a decrease in energy data flow is predicted, reduce the capacity of the storage area based on the predicted amount;

[0095] In this embodiment, when the system predicts that energy data traffic will decrease over the next period of time, it will implement a storage area reduction strategy to avoid wasting storage resources and optimize storage efficiency. Technical means for reducing storage area include reducing block capacity, reducing block generation frequency, compressing low-priority data, and merging storage areas. In the event of a traffic decrease, the system will first dynamically reduce the capacity of new blocks, enabling the blockchain to record energy data at a lower storage cost. For example, if transaction volume is predicted to drop by 70% over the next 30 block periods, the system will automatically reduce block capacity to 50% of its original capacity to reduce unnecessary storage space. Simultaneously, the blockchain's block generation frequency will also be reduced to reduce computing resource consumption and improve the system's overall energy efficiency. Furthermore, the system will compress and consolidate low-priority data (such as expired transaction records and duplicated log data), merging multiple small blocks into larger blocks to reduce blockchain storage fragmentation. For historical data that has not been accessed for a long time, the system can also enable a tiered storage mechanism, migrating it to secondary blockchains or off-chain storage to further free up storage space on the main blockchain. Through the above strategies, the system can reasonably allocate storage resources under low load conditions, improve storage utilization, and ensure the system's adaptability and storage efficiency under different load scenarios.

[0096] The specific steps of S2.3 are as follows:

[0097] S2.3.1: Adjust the trust threshold according to the emergency consensus mechanism to reduce the frequency of data writing to the main blockchain;

[0098] Specifically, when the Energy Internet system detects an imbalance in energy supply and demand, such as the integration of large-scale renewable energy, a sudden increase in grid load, or a demand-side response event, the system monitors energy data fluctuations in real time through its built-in supply and demand status monitoring module. This data is then compared with historical load data to identify imbalance trends. To prevent blockchain write congestion, storage resource overload, and transaction confirmation delays caused by the surge in data during this period, the system triggers an emergency consensus mechanism to automatically adjust the trust threshold. This involves raising the trustworthiness requirements of the primary blockchain to reduce the frequency of data writes to the primary blockchain. Specifically, the system dynamically adjusts the minimum trustworthiness weight threshold of the primary blockchain, for example, from 70 to 85. This ensures that only high-trustworthiness data is stored on the primary blockchain, while medium- and low-trustworthiness data is temporarily stored on secondary blockchains pending further verification or delayed storage. To ensure the rationality of the trust threshold adjustment, the system combines real-time energy market transaction data, historical load fluctuation models, and short-term forecasting algorithms (such as those based on LSTM or random forests) to predict future energy data trends. This determines the threshold adjustment range and applicable period. For example, when renewable energy generation surges and the power grid becomes overloaded, the system not only raises the trusted threshold but also simultaneously reduces the block write frequency, extending the data packaging time from 5 seconds to 15 seconds to reduce storage pressure. It also prioritizes the storage of critical energy data, such as transaction settlement data and dispatch instruction data, while temporarily postponing the writing of low-value data (such as equipment operation logs and redundant sensor data). Furthermore, the emergency consensus mechanism can be combined with a voting mechanism, allowing the main blockchain nodes to quickly vote on threshold adjustments to reach a consensus, ensuring that the policy can take effect quickly in an emergency, safeguarding the stability of the main blockchain, and preventing slow system response or even crashes due to block write overload.

[0099] S2.3.2: Prioritize the energy data in the primary blockchain based on the direction of the imbalance, and store the selected energy data in the secondary blockchain, where the energy data is selected based on the priority level;

[0100] Specifically, when the system detects an imbalance in energy supply and demand, it first determines the specific direction of the imbalance—whether it's an oversupply (energy surplus) or an oversupply (energy shortage)—so it can implement appropriate data storage strategies. In situations of oversupply, due to the high volume of electricity trading in the market, the system prioritizes storing high-frequency trading data and real-time electricity market settlement data. Lower-priority data, such as electricity usage logs during low-load periods, general energy consumption monitoring data, and some predictive data, is automatically filtered and stored on the secondary blockchain through a data tiered storage mechanism. This filtering mechanism uses an energy data classification algorithm, incorporating factors such as historical transaction importance assessment, data access frequency analysis, and data integrity requirements, to ensure that data stored on the secondary blockchain does not impact core decision-making data on the primary blockchain. For example, distributed renewable energy transaction data with low transaction volume can be temporarily stored on the secondary blockchain, while high-value transaction data related to market pricing is stored on the primary blockchain to ensure fair and timely market transactions. On the other hand, when electricity demand outstrips supply, to ensure the smooth operation of the energy trading market, the system prioritizes the storage of large-scale user power transactions, dispatch control instructions, and energy management system (EMS) data. Transaction data and predictive data from smaller, distributed users are transferred to secondary blockchains, reducing storage pressure on the primary blockchain. Furthermore, to ensure the integrity and traceability of secondary blockchain data, the system employs data hash indexing technology. When data is stored on the secondary blockchain, its hash fingerprint is simultaneously recorded on the primary blockchain, ensuring rapid verification of data integrity and consistency when data needs to be backdated. To further enhance the efficiency of data interaction between the primary and secondary blockchains, the system employs a smart contract-based automatic triggering mechanism. When data on the secondary blockchain reaches a certain level of credibility or when the market requires a data recall, the data on the secondary blockchain is automatically resubmitted to the primary blockchain and its authenticity verified through zero-knowledge proofs. This dynamic data storage optimization solution, based on the balance of energy supply and demand, ensures that the primary blockchain maintains efficient storage and rapid access to critical data, while the secondary blockchains also take on temporary storage and backup tasks for lower-priority data. This improves overall storage flexibility, ensuring energy data reliability and system stability.

[0101] The energy data in the main blockchain is prioritized according to the imbalance direction, including:

[0102] Adjust the consensus algorithm parameters of the main blockchain based on the direction and severity of the supply and demand imbalance;

[0103] The priority of energy data in the main blockchain is adjusted according to the consensus algorithm parameters.

[0104] The adjustment of the consensus algorithm parameters of the main blockchain includes:

[0105] When energy supply is insufficient, the stake weight of the proof-of-stake nodes is increased, thereby strengthening the decision-making power of the credit nodes in the consensus process.

[0106] When market transactions fluctuate violently, the Byzantine fault-tolerant voting cycle is optimized to speed up transaction confirmation.

[0107] In this embodiment, to ensure that the main blockchain can adapt to energy market volatility and achieve reasonable priority classification and storage management of energy data in the event of an imbalance between energy supply and demand, the system dynamically adjusts consensus algorithm parameters to enable the blockchain to adapt to varying supply and demand conditions, improving transaction confirmation efficiency and data storage reliability. In the energy market, changes in supply and demand directly affect the write speed of blockchain data, consensus efficiency, and data storage strategies. Therefore, this method achieves intelligent allocation of data priorities by adjusting the core parameters of the consensus algorithm, ensuring that the system can maintain efficient and stable operation even in situations of insufficient energy supply or severe transaction fluctuations.

[0108] In times of energy shortage, the stake weight of Proof-of-Stake (PoS) nodes is increased, strengthening the decision-making power of high-reputation nodes in the consensus process. Since energy shortages are often accompanied by a decrease in transaction volume but an increase in transaction importance, the standard PoS weight calculation method could cause the votes of low-reputation nodes to influence consensus results, increasing the risk of malicious attacks and data tampering. Therefore, in times of energy shortage, the system dynamically adjusts the parameters of the PoS consensus algorithm, increasing the voting weight of nodes with larger stakes and a good historical transaction record, giving high-reputation nodes greater voting power. Specifically, the system comprehensively evaluates metrics such as a node's historical consensus success rate, data storage integrity, number of transactions processed, and the amount of staked assets. Nodes ranked in the top 10%-20% by reputation are given higher consensus weights to ensure data authenticity and immutability. Furthermore, the system embeds automatic adjustment logic in the smart contract. When the system detects energy shortages (such as a drop in power load exceeding a certain threshold or power generation falling below a safe operating level), the PoS consensus mechanism automatically increases the voting weight of high-reputation nodes to reduce the influence of low-reputation nodes. This method can effectively improve the reliability of energy trading data, prevent malicious nodes from manipulating energy trading results through low-cost attacks during periods of energy shortage, and at the same time ensure that the data stored in the main blockchain is more accurate and reliable, providing accurate decision-making basis for subsequent market regulation.

[0109] During periods of significant market volatility, the Byzantine Fault Tolerance (PBFT) voting cycle is optimized to speed up transaction confirmation. Transaction volume in the energy market is often extremely volatile. For example, during peak periods of renewable energy generation or sudden market adjustments, transaction volume can surge rapidly in a short period of time, while during periods of low electricity demand or market stability, transaction volume can plummet. Traditional PBFT consensus mechanisms, with fixed voting cycles, can make it difficult for transaction confirmation efficiency to dynamically adapt to market demand, thereby impacting data storage efficiency and the real-time nature of energy scheduling. To address this, in this embodiment, the system uses a transaction fluctuation monitoring mechanism to analyze market transaction volume trends in real time and adjust the PBFT consensus voting cycle based on transaction load. When transaction volume increases rapidly, the system automatically shortens the PBFT voting cycle, accelerating the consensus process and enabling transaction data to be written to the blockchain more quickly, reducing the risk of transaction backlogs. Furthermore, the system dynamically increases the parallel processing capacity of voting nodes. Specifically, when transaction load exceeds a certain threshold (e.g., a 50% increase in transactions per unit time), the system automatically increases the load balancing mechanism of voting nodes, enabling multiple nodes to perform transaction verification simultaneously, thereby improving overall transaction throughput. When transaction volume decreases, the system automatically extends the voting cycle, reducing unnecessary computing resource consumption and optimizing blockchain storage efficiency, thereby avoiding excessive computing resource consumption even when the energy trading market is under low load. This optimization method not only improves the real-time nature of energy transactions but also reduces the storage burden caused by transaction backlogs, ensuring that the blockchain maintains efficient and stable operation in both peak and trough scenarios.

[0110] Furthermore, when trading fluctuates significantly, the system introduces a dynamic voting weight adjustment mechanism, adjusting the voting weights of different nodes in real time based on changes in trading volume. For example, when trading volume is high, the system prioritizes increasing the voting weights of nodes with greater computing power to increase transaction processing speed. However, when trading volume is low, the system prioritizes nodes with greater data storage capabilities to lead the consensus process, ensuring the integrity and long-term storage reliability of transaction data. This approach ensures that the system consistently maintains the optimal consensus strategy in varying market environments, improving overall storage and transaction efficiency.

[0111] The specific steps for S3 are as follows:

[0112] S3.1: Rating the credibility of the energy data and allocating storage areas based on the credibility;

[0113] Specifically, in the Energy Internet environment, energy data comes from a variety of sources, including but not limited to smart meters, charging stations, power trading platforms, distributed energy systems, and wind-solar hybrid microgrids. Data from different sources has different levels of credibility. Therefore, in this method, an energy data credibility model is first constructed. This model comprehensively considers multiple factors, including the reliability of the data source, historical transaction records, data integrity, calibration of the collection equipment, data consistency, network communication quality, and smart contract execution, and assigns a credibility weight to each piece of energy data. Credibility calculation methods include but are not limited to statistical models based on historical records, scoring mechanisms based on transaction behavior analysis, and artificial intelligence-based machine learning models (such as decision trees, random forests, and deep neural networks). Multi-dimensional data analysis methods are used to improve the accuracy of credibility assessments. After the credibility weights are determined, the system stores the energy data in different storage areas. Highly credible data is directly stored in the main blockchain to ensure data immutability, security, and efficient traceability, while less credible data is stored in the secondary blockchain. The secondary blockchain allows data to be further validated by the smart contract before deciding whether to migrate to the main blockchain, or adopts a more flexible storage solution to reduce the storage burden. The benefit of adopting a credibility rating storage strategy is that it prevents low-credibility data from directly occupying the main blockchain's storage resources, preventing contamination of the main blockchain's data and improving the blockchain's overall credibility. It also provides an upgradeable storage mechanism that allows data credibility to be dynamically adjusted over time or as the verification process progresses. For example, in the distributed photovoltaic trading market, the data credibility of some small power generation companies may be lower than that of large power grid operators. Therefore, when storing data, a credibility rating mechanism can be used to categorize and store different types of data, thereby improving the credibility of transaction data and optimizing blockchain storage efficiency.

[0114] S3.2: When data interaction occurs between the primary blockchain and the secondary blockchain, interaction processing is performed;

[0115] Specifically, to ensure data consistency and security during the interaction between the primary and secondary blockchains, this method employs a multi-layered security authentication mechanism, including but not limited to identity verification, data integrity checks, zero-knowledge proofs (ZKPs), physical-layer signatures, and time-lock verification. First, before data interaction, data on the secondary blockchain must undergo an identity authentication mechanism to verify whether the data originates from a legitimate and trusted node. This authentication is also performed through a smart contract. For example, in a blockchain consensus network, only data submitted by authorized smart meters or power trading platforms is allowed to participate in primary and secondary blockchain interactions. Second, for data submitted from the secondary blockchain to the primary blockchain, this method employs zero-knowledge proof technology to verify the authenticity and consistency of the data without revealing transaction details, thereby preventing tampering or falsification. Furthermore, to further enhance data security, this method incorporates physical-layer signatures, utilizing the frequency, phase, and waveform characteristics of the power carrier signal as a unique identifier to ensure the authenticity of the data source and guarantee data immutability even during cross-chain transmission. During the interaction process, the system uses a time lock mechanism. That is, for data with low credibility, it must undergo a certain period of secure storage before entering the main blockchain. During this period, it must undergo review by more verification nodes or be executed by smart contracts. Only after its credibility reaches a set threshold can it be officially migrated to the main blockchain. This method can effectively prevent malicious data from quickly entering the main blockchain and avoid data contamination. In addition, to improve the efficiency of interaction, this method adopts an asynchronous cross-chain interaction mechanism. That is, when data is exchanged between the main and secondary blockchains, the system will prioritize high-priority energy trading data, such as real-time electricity transactions and key market settlement data. For low-priority data (such as equipment log data and historical load curves), delayed storage is used for batch synchronization, thereby optimizing the efficiency of storage resources. For example, in a new energy trading market, the transaction data initially submitted by a distributed photovoltaic power generator may be stored on a secondary blockchain due to a lack of transaction records. However, as subsequent transactions are successfully completed, the generator's credibility gradually increases. Once the system detects that its credibility has exceeded the storage threshold of the primary blockchain, it automatically triggers a smart contract to migrate the trader's data to the primary blockchain, ensuring the complete storage of trusted data while reducing the system's initial storage pressure on low-trustworthiness data. Compared to the single storage mechanism of traditional blockchains, this approach significantly improves data security, storage flexibility, and transaction credibility, providing more reliable protection for the trusted storage and transaction security of energy data.

[0116] The specific steps of S3.1 are as follows:

[0117] S3.1.1: Calculate the credibility weight of each energy transaction data in the energy data;

[0118] Specifically, a credibility weight calculation model is established for different types of energy transaction data within the Energy Internet to quantitatively assess its credibility before data is stored. The credibility weight calculation comprehensively considers multiple factors, including but not limited to the credibility of the data source, the reputation of the transacting parties, historical transaction records, data integrity, data anomalies, transaction frequency, and data encryption level. For example, the credibility of data from devices such as smart meters, photovoltaic inverters, wind power monitoring systems, and charging stations can be affected by factors such as the device's operating status, data transmission path, and whether it passes through an authenticated gateway. Therefore, a weighted calculation can be performed based on the device's historical stability and data integrity. Furthermore, if transaction data is derived from consensus authentication by multiple nodes, such as transactions from multiple power trading platforms or verified by multiple third-party certification agencies, its credibility will be relatively high and will be assigned a higher weight. Conversely, if transaction data contains anomalies, such as uncompleted transactions in the transacting parties' historical records, frequent order cancellations, or transaction amounts that significantly mismatch historical patterns, its credibility weight will be reduced. Credibility score calculation can be completed through a weighted scoring model to ensure the scientificity and rationality of the credibility assessment, thereby supporting subsequent tiered storage decisions.

[0119] S3.1.2: Compare the credibility weight with a preset credibility threshold. If the credibility weight is greater than or equal to the credibility threshold, assign the energy transaction data to the main blockchain.

[0120] Specifically, based on the calculated credibility weight of energy transaction data, the system compares this weight with a preset credibility threshold to determine the data storage path. This credibility threshold is pre-set by the system and can be dynamically adjusted based on historical data. Typically, the credibility threshold is determined by a combination of industry regulatory standards, transaction history stability analysis, and data statistical patterns. For example, for large-scale power grid transactions, the credibility threshold may be higher to ensure that only well-verified, high-value transaction data is stored on the main blockchain. However, for scenarios with potentially volatile data, such as distributed photovoltaic transactions, the credibility threshold can be relaxed to increase data storage flexibility. When the credibility weight of a particular energy transaction data is greater than or equal to the credibility threshold, the system directly stores the data on the main blockchain, which utilizes a more stringent consensus mechanism (such as PBFT or PoS) to ensure data immutability and high security. This process not only ensures that the data stored on the main blockchain is highly credible and reduces resource consumption caused by storing unnecessary data, but also improves the overall operational efficiency of the blockchain, enabling high-value transactions to be quickly confirmed through consensus, thereby enhancing transaction transparency and stability. For example, in the settlement process of the electricity spot market, the high-value transactions involved must ensure the authenticity and integrity of the data. Therefore, the credibility of these transactions is usually high, and the system will prioritize storing them on the main blockchain to ensure the fairness and credibility of energy settlement.

[0121] S3.1.3: If the value is less than the trust threshold, the energy transaction data is assigned to the secondary blockchain;

[0122] Specifically, if the credibility of energy transaction data falls below a trust threshold, the system stores the data on a secondary blockchain for subsequent processing and verification. Secondary blockchains typically employ lighter-weight storage and consensus mechanisms, such as DAG (directed acyclic graph) structures or sidechain storage, enabling faster storage of large amounts of data while reducing computing resource usage and improving overall blockchain system throughput. Data stored on secondary blockchains does not immediately enter the primary blockchain but instead undergoes additional verification steps, including time-lock verification, historical data matching, multi-party consensus signatures, and AI-powered anomaly detection. For example, if the credibility of a piece of new energy transaction data falls below the trust threshold but its data matches historical patterns well, the system may automatically increase its credibility after a certain period of stable verification and ultimately migrate it to the primary blockchain for storage. Conversely, if the data exhibits anomalies during subsequent monitoring (e.g., repeated submissions from multiple transaction nodes without a completed transaction), an anomaly alert may be triggered and manual review may be required. This tiered storage mechanism effectively reduces the burden on the primary blockchain while ensuring data integrity and security, making it particularly suitable for large-scale data transactions and storage in energy internet scenarios. For example, in the distributed energy trading market, since the trading behavior of small photovoltaic users may have greater uncertainty, the storage method of the secondary blockchain can provide a flexible verification mechanism for this data, ensuring that high-credibility data can eventually enter the main blockchain, and low-credibility or abnormal transactions can be effectively screened, thereby improving the security and stability of the overall system.

[0123] The specific steps of S3.2 are as follows:

[0124] S3.2.1: Authenticate the data on the secondary blockchain and call the data on the primary blockchain after authentication.

[0125] In this embodiment, in order to ensure the legitimacy and traceability of the data in the secondary blockchain during the interaction process, an identity authentication mechanism based on digital signature and physical layer feature binding is adopted.

[0126] Specifically, the system will first extract key attributes such as the transaction hash value, signature information, and data source ID of the data to be interacted with in the secondary blockchain, and verify the signature of the data using a public key infrastructure (PKI) or a distributed identity authentication mechanism (DID). If the signature is valid, it means that the data source is credible, otherwise the data interaction request will be rejected. In addition, the system will also combine the physical layer signature of the power carrier signal to verify whether the data actually comes from a specific physical device by comparing the physical layer signal characteristics (such as phase offset, modulation mode, voltage and current waveforms) to prevent man-in-the-middle attacks or forged data sources. Only when the identity authentication is passed will the system allow the data to call the relevant data in the main blockchain and perform the next step. The advantage of this authentication mechanism is that it can not only ensure the authenticity of the data source from the encryption level, but also further enhance security from the perspective of physical characteristics, ensuring that only legitimate data can enter the cross-chain interaction process and prevent malicious data from contaminating blockchain storage.

[0127] S3.2.2: Encrypt data on the primary blockchain and secondary blockchain using zero-knowledge proof;

[0128] Specifically, the system first hashes the data to be exchanged between the primary and secondary blockchains to generate a unique hash fingerprint. It then constructs a data verification scheme based on zk-SNARKs (Succinct Non-Interactive Zero-Knowledge Arguments) or zk-STARKs (Scalable Transparent Zero-Knowledge Arguments). This scheme allows verification nodes between the primary and secondary blockchains to prove data consistency across both chains without exposing the data's specific content. For example, in a scenario involving energy transaction data migration, the data provider on the secondary blockchain can use a zero-knowledge proof algorithm to calculate the transaction hash and send it to the verification node on the primary blockchain. The verification node then uses the same algorithm to calculate the corresponding transaction hash on the primary blockchain. If the two match, the data is proven to be consistent, thus completing verification without directly exposing the transaction content. This technology offers the advantage of avoiding the privacy risks associated with plaintext data transmission in traditional cross-chain blockchain interactions, while also effectively preventing data tampering and improving the security of data exchange. Furthermore, zero-knowledge proofs can be used to protect identity privacy, ensuring that even if the same transaction is stored differently on different chains, the validity of the data can still be verified, significantly enhancing the security and privacy of data sharing.

[0129] S3.2.3: Update the credibility weight of the transaction data based on the interaction results to determine whether the data transfer conditions are met;

[0130] Specifically, the trust score is calculated based on multiple factors, including but not limited to the historical reputation of the data source, the success rate of smart contract execution, data integrity verification, and the identity authentication of the transaction parties. In this embodiment, the system uses a trust calculation method based on the Bayesian update model. That is, when the data of a transaction successfully passes the cross-chain interaction and no anomalies (such as data conflicts or invalid signatures) occur during the verification process on the main blockchain, the trust score of the data will be increased. If an anomaly is detected in the data during the interaction (such as zero-knowledge proof mismatch, identity verification failure, transaction hash conflict, etc.), the trust score will be reduced and the security review mechanism will be triggered. In addition, to ensure the rationality of the trust score, the system will also use machine learning-based anomaly detection models (such as LSTM or random forest) to analyze historical transaction data to identify whether there is data fraud or malicious tampering. For example, in a new energy transaction scenario, if the data of a distributed photovoltaic power station has been rejected from being stored on the main blockchain multiple times due to anomalies, the trust score of its future submitted transaction data may be reduced. The system will prioritize retaining this data on the secondary blockchain and require it to provide additional verification proof. This dynamic credibility adjustment mechanism ensures that only stable and reliable data is ultimately stored in the main blockchain, thereby optimizing storage resources and improving the overall security and data reliability of the system.

[0131] S3.2.4: If the data transfer conditions are met, a secondary verification is performed using a time lock, and the data transfer is performed after the verification is passed;

[0132] Specifically, timelocks can be implemented using either block-height-based or smart-contract-based timelocks, ensuring that even after data migration conditions are met, a buffer period remains before it can be written to the main blockchain. For example, in the electricity trading market, if a renewable energy generation transaction record meets the credibility migration threshold on a secondary blockchain, the system will enforce a timelock mechanism before migrating it to the main blockchain. This mechanism sets a minimum time window (e.g., 50 block confirmations or one hour) during which other validators can submit challenges. If the transaction remains unchallenged within the timelock, the system will execute the final storage operation. Furthermore, to prevent malicious manipulation of the timelock, the system also incorporates a multi-signature mechanism, requiring the final decision on data migration to be approved by consensus from multiple trusted nodes. The advantage of this timelock mechanism is that it effectively prevents short-term data tampering. Even if low-confidence data ultimately passes the credibility assessment, it still undergoes a certain observation period to ensure its authenticity, thereby improving the storage quality and security of the main blockchain.

[0133] The authentication of the data on the secondary blockchain includes:

[0134] Generate a physical layer signature based on the power carrier communication characteristics corresponding to the data of the secondary blockchain;

[0135] The main blockchain receives and verifies the physical layer signature.

[0136] Example 2:

[0137] See also Figure 2 , the present invention provides an embodiment: an energy internet data security transmission and authentication system, the data security transmission and authentication system includes a data acquisition module, a data storage module and a data protection module;

[0138] The data acquisition module is used to collect energy data of the energy internet;

[0139] The data storage module is configured with a block configuration strategy, which is used to adjust the size and storage method of the block according to the characteristics and flow changes of the energy data;

[0140] The data protection module is used to provide data encryption and security authentication mechanisms.

[0141] The data storage module includes:

[0142] a storage allocation unit, configured to rate the energy data for credibility and allocate storage areas based on the credibility;

[0143] A capacity adjustment unit, configured to adjust the capacity of a storage area according to flow fluctuations of the energy data;

[0144] The block configuration strategy includes a credibility evaluation logic and a block adjustment logic. The credibility evaluation logic is configured in the storage allocation unit, and the block adjustment logic is configured in the capacity adjustment unit.

[0145] The credibility evaluation logic includes:

[0146] Calculating the credibility weight of each energy transaction data in the energy data;

[0147] Comparing the credibility weight with a preset credibility threshold, and if the credibility weight is greater than or equal to the credibility threshold, allocating the energy transaction data to the main blockchain;

[0148] If it is less than the trust threshold, the energy transaction data will be allocated to the secondary blockchain.

[0149] The block adjustment logic includes:

[0150] Predict data traffic through time series prediction models;

[0151] When an increase in energy data traffic is predicted, the capacity of the storage area is expanded according to the predicted amount;

[0152] When a decrease in energy data flow is predicted, the capacity of the storage area is reduced according to the predicted amount.

[0153] The data storage module further includes:

[0154] A data interaction unit, which is used to provide data interaction logic between the primary blockchain and the secondary blockchain;

[0155] The supply and demand adjustment unit is used to monitor the supply and demand balance of the energy internet and adjust the block capacity in the main blockchain when the supply and demand balance is unbalanced.

[0156] The data interaction logic includes:

[0157] Authenticate the data of the secondary blockchain and call the data of the primary blockchain after passing the authentication;

[0158] Encrypt the data of the main blockchain and the secondary blockchain through zero-knowledge proof;

[0159] Update the credibility weight of the transaction data based on the interaction results to determine whether the data transfer conditions are met;

[0160] If the data transfer conditions are met, secondary verification is performed through a time lock, and data transfer is performed after the verification is passed.

[0161] The authentication of the data on the secondary blockchain includes:

[0162] Generate a physical layer signature based on the power carrier communication characteristics corresponding to the data of the secondary blockchain;

[0163] The main blockchain receives and verifies the physical layer signature.

[0164] Adjusting the block capacity in the main blockchain includes:

[0165] Adjust the trust threshold based on the emergency consensus mechanism to reduce the frequency of data writing to the main blockchain;

[0166] The energy data in the main blockchain is prioritized according to the imbalance direction, and the filtered low-priority energy data is stored in the secondary blockchain.

[0167] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and are not to be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. An energy internet data security transmission and authentication system, applied to energy internet data, characterized by: The secure transmission and authentication system includes a data acquisition module, a data storage module, and a data protection module, wherein: The data acquisition module is used to collect energy data of the energy internet; The data storage module is configured with a block configuration strategy, which is used to adjust the size and storage method of the block according to the characteristics and flow changes of the energy data; The data protection module is used to provide data encryption and security authentication mechanisms.

2. The energy internet data security transmission and authentication system according to claim 1 is characterized in that: The data storage module includes: a storage allocation unit, configured to rate the energy data for credibility and allocate storage areas based on the credibility; A capacity adjustment unit, configured to adjust the capacity of a storage area according to flow fluctuations of the energy data; The block configuration strategy includes a credibility evaluation logic and a block adjustment logic. The credibility evaluation logic is configured in the storage allocation unit, and the block adjustment logic is configured in the capacity adjustment unit.

3. The energy internet data security transmission and authentication system according to claim 2 is characterized in that: The credibility evaluation logic includes: Calculating the credibility weight of each energy transaction data in the energy data; Comparing the credibility weight with a preset credibility threshold, and if the credibility weight is greater than or equal to the credibility threshold, allocating the energy transaction data to the main blockchain; If it is less than the trust threshold, the energy transaction data will be allocated to the secondary blockchain.

4. The energy internet data security transmission and authentication system according to claim 2 is characterized in that: The block adjustment logic includes: Predict data traffic through time series prediction models; When an increase in energy data traffic is predicted, the capacity of the storage area is expanded according to the predicted amount; When a decrease in energy data flow is predicted, the capacity of the storage area is reduced according to the predicted amount.

5. The energy internet data security transmission and authentication system according to claim 3 is characterized in that: The data storage module further includes: A data interaction unit, which is used to provide data interaction logic between the primary blockchain and the secondary blockchain; The supply and demand adjustment unit is used to monitor the supply and demand balance of the energy internet and adjust the block capacity in the main blockchain when the supply and demand balance is unbalanced.

6. The energy internet data security transmission and authentication system according to claim 5 is characterized in that: The data interaction logic includes: Authenticate the data of the secondary blockchain and call the data of the primary blockchain after passing the authentication; Encrypt the data of the main blockchain and the secondary blockchain through zero-knowledge proof; Update the credibility weight of the transaction data based on the interaction results to determine whether the data transfer conditions are met; If the data transfer conditions are met, secondary verification is performed through a time lock, and data transfer is performed after the verification is passed.

7. The energy internet data security transmission and authentication system according to claim 6 is characterized in that: The authentication of the data on the secondary blockchain includes: Generate a physical layer signature based on the power carrier communication characteristics corresponding to the data of the secondary blockchain; The main blockchain receives and verifies the physical layer signature.

8. The energy internet data security transmission and authentication system according to claim 5, characterized in that: Adjusting the block capacity in the main blockchain includes: Adjust the trust threshold based on the emergency consensus mechanism to reduce the frequency of data writing to the main blockchain; The energy data in the main blockchain is prioritized according to the imbalance direction, and the filtered energy data is stored in the secondary blockchain, where the energy data is filtered according to the size of the priority.

9. The energy internet data security transmission and authentication system according to claim 8, characterized in that: The energy data in the main blockchain is prioritized according to the imbalance direction, including: Adjust the consensus algorithm parameters of the main blockchain based on the direction and severity of the supply and demand imbalance; The priority of energy data in the main blockchain is adjusted according to the consensus algorithm parameters.

10. The energy internet data security transmission and authentication system according to claim 9, characterized in that: The adjustment of the consensus algorithm parameters of the main blockchain includes: When energy supply cannot meet demand, increase the stake weight of the proof-of-stake nodes and increase the decision-making power of the reputation nodes in the consensus process; When the market transaction volatility is greater than the set volatility threshold, the Byzantine fault tolerance voting cycle is shortened.

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