A method and system for cabin power trading and management based on blockchain technology

Abstract

The present application provides a method and system for cabin electricity trading and management based on blockchain technology. Among them, an intelligent power trading contract is constructed to encrypt the power trading rules, price mechanism and identity authentication process of both parties to the transaction; when the power producer in the cabin generates excess power, the strategy for publishing power sale requests is optimized, a comprehensive analysis of power quantity, quality parameters and expected selling price is conducted, the power price is dynamically adjusted, and the best potential buyer set is selected from all potential buyers; the information of both parties to the transaction is protected through the blockchain platform combined with differential privacy technology, the transaction details are recorded, and a safe and reliable transaction record is generated; the automated settlement process based on the power trading intelligent contract is automatically triggered; the system regularly evaluates power production and consumption and generates an optimized power supply plan. The technical solution provided by this application improves the security, transparency and efficiency of power trading.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of blockchain technology, and in particular to a method and system for cabin electricity trading and management based on blockchain technology. Background Art

[0002] With the widespread adoption of renewable energy, especially in small, distributed power systems like shelters, electricity production and consumption patterns are becoming increasingly diverse. In this context, an efficient, secure, and transparent method is needed to manage electricity trading and ensure the efficient allocation and use of energy.

[0003] Currently, traditional power trading management systems rely primarily on centralized databases and manual operations. These systems typically employ pre-set pricing mechanisms and rely on manual review to complete transaction processes. In some cases, electronic payment systems are used to transfer funds, but the entire process lacks sufficient transparency and real-time performance.

[0004] However, traditional systems are vulnerable to hacker attacks and present a high risk of personal information leakage. Transaction records are often stored within a single institution, making it difficult to ensure that all participants have access to the same information, leading to trust issues. Due to extensive manual intervention, the process from issuing a power sales request to final settlement is time-consuming and error-prone. The existing system is unable to quickly respond to market changes, such as when adjusting prices or handling emergencies. The lack of in-depth analysis of the consumption habits of cabin users makes it difficult to provide personalized energy selection recommendations and services. Summary of the Invention

[0005] The embodiments of the present application provide a method and system for cabin power trading and management based on blockchain technology to solve the problems of low security, low transparency and low efficiency of power trading in the existing technology.

[0006] In a first aspect, an embodiment of the present application provides a method for cabin power trading and management based on blockchain technology, including:

[0007] Build smart contracts for power transactions, encrypt power transaction rules, price mechanisms, and the authentication process of both parties to ensure the security, transparency, and privacy of all transactions;

[0008] According to the electricity trading smart contract, when the electricity producer in the shelter generates excess electricity, the strategy for issuing electricity sales requests is optimized, a comprehensive analysis of electricity quantity, quality parameters, and expected selling price is conducted, and future demand trends are predicted based on historical transaction data. The electricity price is dynamically adjusted to improve the transaction success rate and select the best potential buyer set from all potential buyers.

[0009] Based on the best set of potential buyers, when a buyer responds to the seller's electricity sale request, the blockchain platform combines differential privacy technology to protect the information of both parties, record the transaction details, and use the Byzantine Fault Tolerance consensus algorithm to ensure the consistency and reliability of transaction data, prevent malicious attacks, and generate secure and reliable transaction records.

[0010] Based on the secure and reliable transaction records, the power trading smart contract automatically triggers an automated settlement process based on the power trading smart contract, accurately calculates the transaction amount using real-time exchange rate information obtained by the on-chain oracle, accurately deducts funds from the buyer's account and transfers them to the seller's account based on the transaction records, and simultaneously uses time series analysis to predict future transaction frequencies, provide financial planning advice to the power producer, and generate confirmation information for the completion of the transaction and settlement;

[0011] Using the confirmation information of completed transactions and settlements, the system regularly evaluates electricity production and consumption. When an imbalance between supply and demand is detected, the system automatically adjusts electricity prices to guide the market to a new equilibrium. It analyzes user consumption habits, provides personalized energy selection recommendations to electricity consumers, and generates an optimized electricity supply plan.

[0012] Optionally, based on the set of best potential buyers, when a buyer responds to the seller's electricity sale request, the blockchain platform is combined with differential privacy technology to protect the information of both parties to the transaction, record the transaction details, and use the Byzantine fault-tolerant consensus algorithm to ensure the consistency and reliability of transaction data, prevent malicious attacks, and generate secure and reliable transaction records, including:

[0013] Using the best potential buyer set, monitoring the buyer's response to the seller's power sale request to obtain responding buyer information;

[0014] Based on the buyer's information of the response, the identity information and transaction intentions of both parties to the transaction are anonymized by combining differential privacy technology to obtain anonymized transaction intention information, thereby ensuring personal privacy protection during the transaction process;

[0015] Based on the anonymized transaction intention information, the transaction details are recorded through the blockchain platform to generate a preliminary transaction record;

[0016] The Byzantine fault-tolerant consensus algorithm is used to conduct consensus processing on the preliminary transaction records to ensure the consistency and reliability of transaction data on all participating nodes, prevent malicious attacks, and generate safe and reliable transaction records.

[0017] Optionally, the identity information and transaction intentions of both parties to the transaction are anonymized based on the buyer's information in the response, combined with differential privacy technology, to obtain anonymized transaction intention information to ensure personal privacy protection during the transaction, including:

[0018] Using the buyer's information in the response, differential privacy technology is applied to anonymize the buyer's identity information to generate an irreversible identity identifier;

[0019] Based on the irreversible identity identifier, random noise is added to the buyer's transaction intention data to blur the actual value and obtain the transaction intention data processed with differential privacy;

[0020] The transaction intention data processed with differential privacy is combined with the irreversible identity identifier to generate completely anonymous transaction intention information, ensuring that the true identities and specific transaction intentions of the two parties to the transaction will not be disclosed during the entire transaction process, thereby achieving effective protection of personal privacy.

[0021] Optionally, the use of a Byzantine fault-tolerant consensus algorithm to perform consensus processing on the preliminary transaction records to ensure consistency and reliability of transaction data on all participating nodes, prevent malicious attacks, and generate secure and reliable transaction records includes:

[0022] Using the preliminary transaction record, starting a Byzantine fault-tolerant consensus algorithm, broadcasting the preliminary transaction record to all nodes participating in the transaction, and obtaining a copy of the transaction record received by each node;

[0023] Based on the transaction record copy, each node independently verifies the transaction record according to preset rules and generates its own verification result;

[0024] Based on the verification results, each node votes on the transaction record, and the voting results of all nodes are counted to ensure that more than two-thirds of the nodes vote in favor and reach a consensus;

[0025] By reaching a consensus, the transaction data on all participating nodes is ensured to remain consistent and reliable, malicious attacks are prevented, and secure and reliable transaction records are generated.

[0026] Optionally, based on the secure and reliable transaction records, the power trading smart contract automatically triggers an automated settlement process based on the power trading smart contract, accurately calculates the transaction amount using real-time exchange rate information obtained by an on-chain oracle, accurately deducts funds from the buyer's account and transfers them to the seller's account based on the transaction records, and simultaneously uses time series analysis to predict future transaction frequencies, providing financial planning advice to the power producer, and generating confirmation information on the completion of the transaction and settlement, including:

[0027] By utilizing the secure and reliable transaction records, the power transaction smart contract automatically triggers an automated settlement process based on the power transaction smart contract, thereby obtaining an initiated settlement process;

[0028] According to the initiated settlement process, real-time exchange rate information is obtained through the on-chain oracle, and the transaction amount in the transaction record is accurately calculated to obtain the final payment amount;

[0029] Based on the final payment amount, accurately debit the buyer's account, transfer the funds to the seller's account, and generate payment confirmation information;

[0030] Using the secure and reliable transaction records, using time series analysis technology to predict future transaction frequencies and generate a transaction frequency prediction report;

[0031] Providing financial planning suggestions to the power producer based on the transaction frequency forecast report and generating a financial planning suggestion report;

[0032] Combining the payment confirmation information and the financial planning advice report, confirmation information of completed transactions and settlements is generated to ensure the transparency and traceability of transactions.

[0033] Optionally, according to the power trading smart contract, when the power producer in the shelter generates excess power, the power sale request publishing strategy is optimized, a comprehensive analysis of power quantity, quality parameters and expected selling price is conducted, and future demand trends are predicted based on historical transaction data. The power price is dynamically adjusted to improve the transaction success rate, and the best potential buyer set is screened from all potential buyers, including:

[0034] By using the power trading smart contract, when the power producer in the shelter generates excess power, the excess power amount is detected and confirmed, and confirmed excess power information is obtained;

[0035] Based on the confirmed excess power information and historical transaction data, optimizing the issuance strategy of the power sale request, selecting the best issuance time and channel, improving the visibility and response rate of the request, and generating an optimized power sale request strategy;

[0036] Performing a comprehensive analysis of electricity quantity, quality parameters, and expected selling price based on the optimized electricity sale request strategy to ensure that the information in the electricity sale request is accurate and generate a comprehensive analysis result;

[0037] Using the comprehensive analysis results and historical transaction data, data analysis and machine learning techniques are used to predict future electricity demand trends and generate a future demand trend forecast report;

[0038] Dynamically adjusting the electricity price based on the future demand trend forecast report to generate a dynamically adjusted electricity price;

[0039] From all the potential buyers, the best potential buyers are screened out by comprehensively evaluating the buyers' historical transaction records and credit scores, and generating a set of the best potential buyers.

[0040] Optionally, the system utilizes the confirmation information of completed transactions and settlements to regularly evaluate electricity production and consumption. When an imbalance between supply and demand is detected, the system automatically adjusts electricity prices to guide the market to a new equilibrium. The system also analyzes user consumption habits, provides personalized energy selection recommendations to electricity consumers, and generates an optimized electricity supply plan, including:

[0041] Using the confirmation information of the completed transaction and settlement, the system regularly evaluates the electricity production and consumption in the shelter and generates an evaluation report on the electricity production and consumption;

[0042] Based on the electricity production and consumption assessment report, the system detects whether there is a supply and demand imbalance and obtains a supply and demand imbalance detection result;

[0043] Based on the supply and demand imbalance detection results, the system automatically adjusts the electricity price, generates a dynamically adjusted electricity price, and guides the market to a new equilibrium state;

[0044] Using the confirmation information of the completed transaction and settlement, the system analyzes the user's consumption habits and generates a user consumption habit report;

[0045] Based on the user consumption habit report, the system provides personalized energy selection recommendations to electricity consumers and generates a personalized energy selection recommendation report;

[0046] Combining the evaluation report on electricity production and consumption, the dynamically adjusted electricity price, and the user consumption habit report, the system generates an optimized electricity supply plan to ensure the efficiency and sustainability of electricity supply.

[0047] In a second aspect, the present application provides a modular power trading and management system based on blockchain technology, including:

[0048] A building block for constructing smart contracts for power transactions, encrypting power transaction rules, pricing mechanisms, and the authentication process of both parties to ensure the security, transparency, and privacy of all transaction activities;

[0049] A screening module is used to optimize the issuance strategy of power sale requests when the power producers in the shelter generate excess power according to the power trading smart contract. This module conducts a comprehensive analysis of power quantity, quality parameters, and expected selling price. Furthermore, based on historical transaction data, it predicts future demand trends, dynamically adjusts power prices, improves transaction success rates, and selects the best set of potential buyers from all potential buyers.

[0050] A recording module is used to protect the information of both parties to the transaction through a blockchain platform combined with differential privacy technology, record the transaction details, and use a Byzantine fault-tolerant consensus algorithm to ensure the consistency and reliability of transaction data, prevent malicious attacks, and generate secure and reliable transaction records based on the best set of potential buyers.

[0051] A transaction settlement module, configured to automatically trigger an automated settlement process based on the power trading smart contract based on the secure and reliable transaction records, accurately calculate the transaction amount using real-time exchange rate information obtained by an on-chain oracle, accurately deduct funds from the buyer's account and transfer them to the seller's account based on the transaction records, and simultaneously use time series analysis to predict future transaction frequencies, provide financial planning advice to the power producer, and generate confirmation information for the completion of the transaction and settlement;

[0052] The adjustment suggestion module is used to use the confirmation information of the completed transactions and settlements to regularly evaluate the power production and consumption of the system. When an imbalance between supply and demand is detected, the system automatically adjusts the power price to guide the market to a new equilibrium state, analyzes user consumption habits, provides personalized energy selection suggestions to power consumers, and generates an optimized power supply plan.

[0053] In the embodiment of the present application, an electric power transaction smart contract is constructed, and the electric power transaction rules, price mechanism and identity authentication process of both parties to the transaction are encrypted to ensure the security, transparency and personal privacy protection of all transaction activities; according to the electric power transaction smart contract, when the power producer in the cabin generates excess electricity, the issuance strategy of the power sale request is optimized, and a comprehensive analysis is conducted on the quantity, quality parameters and expected selling price of electricity. At the same time, based on historical transaction data, future demand trends are predicted, the electricity price is dynamically adjusted, the transaction success rate is improved, and the best potential buyer set is screened from all potential buyers; based on the best potential buyer set, when the buyer responds to the seller's power sale request, the information of both parties to the transaction is protected through the blockchain platform combined with differential privacy technology, the transaction details are recorded, and the Byzantine fault-tolerant consensus algorithm is used to ensure the consistency and reliability of the transaction data. Reliability, prevent malicious attacks, and generate safe and reliable transaction records; based on the safe and reliable transaction records, the power trading smart contract automatically triggers the automated settlement process based on the power trading smart contract, uses the real-time exchange rate information obtained by the on-chain oracle to accurately calculate the transaction amount, accurately deducts money from the buyer's account and transfers it to the seller's account based on the transaction record, and uses time series analysis to predict future transaction frequencies, provide financial planning suggestions for the power producer, and generate confirmation information for completed transactions and settlements; using the confirmation information for completed transactions and settlements, the system regularly evaluates power production and consumption. When an imbalance between supply and demand is detected, the power price is automatically adjusted to guide the market to a new equilibrium state, analyzes user consumption habits, provides personalized energy selection suggestions for power consumers, and generates an optimized power supply plan.

[0054] The technical solution of this application has the following beneficial effects:

[0055] The embodiments of the present application improve the security, transparency and personal privacy protection of electricity transactions by constructing an electricity trading smart contract, combining differential privacy technology and Byzantine fault-tolerant consensus algorithm, while optimizing electricity sales strategies and pricing mechanisms, improving transaction success rates, and providing financial planning advice to electricity producers through automated settlement processes and time series analysis, thereby achieving more efficient, secure and personalized electricity trading and management.

[0056] Furthermore, this application ensures personal privacy protection during the transaction process by monitoring the buyer's response behavior and anonymizing the information of both parties to the transaction using differential privacy technology; uses a blockchain platform to record transaction details, and uses a Byzantine fault-tolerant consensus algorithm to ensure data consistency and reliability, prevent malicious attacks, and generate safe and reliable transaction records, thereby enhancing the security and credibility of the transaction.

[0057] Furthermore, this application improves the accuracy and efficiency of settlement by automatically triggering an automated settlement process based on smart contracts, using on-chain oracles to obtain real-time exchange rate information to accurately calculate the transaction amount, and deducting funds from the buyer's account and transferring them to the seller's account; at the same time, it uses time series analysis to predict future transaction frequencies, provides financial planning advice to power producers, and generates confirmation information for completed transactions and settlements, ensuring the transparency and traceability of transactions and improving the overall transaction experience.

[0058] These and other aspects of the present application will become more readily apparent from the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0060] Figure 1 A flowchart of a method for cabin electricity trading and management based on blockchain technology provided in an embodiment of the present application;

[0061] Figure 2 A schematic diagram of the structure of a modular power trading and management system based on blockchain technology provided in an embodiment of the present application;

[0062] Figure 3 A schematic diagram of the structure of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0063] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0064] In some of the processes described in the specification and claims of this application and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this document or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any order of execution. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit "first" and "second" to being different types.

[0065] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0066] Figure 1 The present invention provides a flowchart of a method for electricity trading and management in a shelter based on blockchain technology, as shown in FIG. Figure 1 As shown, the method includes:

[0067] 101. Build smart contracts for power transactions, encrypt power transaction rules, price mechanisms, and the authentication process of both parties to ensure the security, transparency, and privacy of all transactions.

[0068] In this step, the smart contract for electricity transactions is a self-executing contract that contains pre-set rules and conditions. Once these conditions are met, the contract automatically executes. Powered by blockchain technology, smart contracts ensure transaction security, transparency, and personal privacy. Encryption involves encoding data using cryptographic algorithms to protect it from unauthorized access or tampering.

[0069] First, define the electricity trading rules, price mechanism and identity verification process, and write these rules into smart contract code.

[0070] Secondly, encryption technology is used to encrypt sensitive information in smart contracts to ensure that only authorized users can access this information.

[0071] Finally, the smart contract is deployed on the blockchain and rigorously tested to ensure its security and reliability.

[0072] In this application example, we assume a decentralized electricity trading platform based on Ethereum. Smart contracts define the price calculation formula for electricity transactions and the identity verification process for buyers and sellers. All transaction records are stored on the blockchain, ensuring that the data cannot be tampered with. Encryption technology is used to protect user personal information and transaction details, preventing data leakage.

[0073] 102. According to the electricity trading smart contract, when the electricity producer in the shelter generates excess electricity, the strategy for publishing electricity sales requests is optimized, a comprehensive analysis of electricity quantity, quality parameters, and expected selling price is conducted, and future demand trends are predicted based on historical transaction data. The electricity price is dynamically adjusted to improve the transaction success rate and select the best potential buyer set from all potential buyers;

[0074] In this step, optimizing electricity sales requests involves analyzing historical transaction data and current market conditions to determine the optimal time and price for selling electricity, thereby increasing transaction success rates. Dynamically adjusting electricity prices involves adjusting prices in real time based on market demand and supply to attract more buyers and achieve a higher transaction success rate.

[0075] First, collect and analyze historical transaction data to predict future demand trends.

[0076] Secondly, the optimal electricity sales strategy is formulated based on the electricity quantity, quality parameters and expected selling price.

[0077] Then, adjust electricity prices in real time based on market demand and competition.

[0078] Finally, the best potential buyers are selected from all potential buyers to improve the success rate of transactions.

[0079] In this application example, a modular power trading platform used a machine learning algorithm to analyze a year's worth of electricity trading data and discovered that electricity demand peaked between 4:00 PM and 6:00 PM each day. The platform optimized electricity sales hours accordingly and raised prices appropriately during peak periods. The system also screened buyers based on their historical transaction records and credit scores to identify those most likely to complete transactions.

[0080] Optionally, in step 102, according to the power trading smart contract, when the power producer in the shelter generates excess power, the publishing strategy of the power sale request is optimized, the power quantity, quality parameters and expected selling price are comprehensively analyzed, and the future demand trend is predicted based on historical transaction data, the power price is dynamically adjusted, the transaction success rate is improved, and the best potential buyer set is selected from all potential buyers, including: using the power trading smart contract, when the power producer in the shelter generates excess power, the excess power amount is detected and confirmed, and the confirmed excess power information is obtained; based on the confirmed excess power information and historical transaction data, the publishing strategy of the power sale request is optimized, and the best publishing time and channel are selected. Improve the visibility and response rate of requests and generate an optimized electricity sale request strategy; based on the optimized electricity sale request strategy, conduct a comprehensive analysis of electricity quantity, quality parameters and expected selling price to ensure that the information in the electricity sale request is accurate and generate a comprehensive analysis result; use the comprehensive analysis result and historical transaction data to use data analysis and machine learning technology to predict future electricity demand trends and generate a future demand trend forecast report; based on the future demand trend forecast report, dynamically adjust the electricity price and generate a dynamically adjusted electricity price; from all potential buyers, comprehensively evaluate the buyer's historical transaction records and credit score factors, screen out the best potential buyers, and generate a set of best potential buyers.

[0081] In this step, excess power information refers to the amount of electricity remaining after the electricity producers within the shelter meet their own needs. This excess power can be sold through smart contracts to improve energy efficiency and economic benefits. Historical transaction data includes detailed records of electricity transactions over a period of time, such as transaction time, volume, and price. This data is used to analyze market trends, optimize trading strategies, and forecast future demand. The release strategy determines how to choose the optimal time and channel to publish power sale requests to improve visibility and response rates. Comprehensive analysis comprehensively evaluates power sale requests based on factors such as power quantity, quality parameters, and desired selling price to ensure accurate information and increase transaction success rates. The future demand trend forecast report uses data analysis and machine learning techniques to generate a forecast of future power demand trends based on historical transaction data and current market conditions. This report helps dynamically adjust electricity prices to adapt to market demand changes. The optimal potential buyer pool is a comprehensive assessment of buyers' historical transaction records, credit scores, and other factors to identify reputable buyers with the highest likelihood of completing transactions, thereby improving transaction success rates.

[0082] When the electricity producer in the shelter generates excess electricity, the amount of excess electricity is first detected and confirmed through the power trading smart contract, generating confirmed excess power information. Based on this confirmed excess power information and historical transaction data, the power sale request publishing strategy is optimized, selecting the optimal publishing timing and channel to improve request visibility and response rate, and generating an optimized power sale request strategy. Next, based on the optimized power sale request strategy, a comprehensive analysis of power quantity, quality parameters, and expected selling price is conducted to ensure the accuracy of the information in the power sale request, generating a comprehensive analysis result. Then, using this comprehensive analysis result and historical transaction data, data analysis and machine learning techniques are used to predict future power demand trends and generate a future demand trend forecast report. Based on this future demand trend forecast report, the power price is dynamically adjusted to generate a dynamically adjusted power price. Finally, from all potential buyers, the best potential buyers are screened by comprehensively evaluating factors such as their historical transaction records and credit scores, generating a set of optimal potential buyers.

[0083] In this embodiment, assume that a solar power plant in a shelter generates excess electricity on a decentralized electricity trading platform based on blockchain technology. The platform's smart contract automatically detects the excess electricity and records the specific amount of electricity. Based on a year's worth of trading data, the system identifies peak electricity demand between 4:00 PM and 6:00 PM daily. Therefore, the smart contract recommends posting a power sale request during this time period and selects an online trading platform with high user activity as the publishing channel. The system then conducts a comprehensive analysis of the quantity, quality, and expected selling price of the electricity to ensure the accuracy of the sale request information. The system then uses an ARIMA model to predict power demand trends for the coming week and generates a forecast report. Based on this forecast, the smart contract dynamically adjusts the electricity price, appropriately increasing it during peak hours. Finally, the system selects potential buyers with high credit scores and a good trading history from all potential buyers, generating a pool of optimal potential buyers. Upon receiving the power sale request, these buyers actively respond and complete the transaction, improving transaction success rates and market efficiency.

[0084] 103. Based on the best set of potential buyers, when a buyer responds to the seller's request to sell electricity, the blockchain platform is combined with differential privacy technology to protect the information of both parties to the transaction, record the transaction details, and use the Byzantine fault-tolerant consensus algorithm to ensure the consistency and reliability of the transaction data, prevent malicious attacks, and generate secure and reliable transaction records;

[0085] In this step, differential privacy technology is used to protect individual privacy by adding random noise to obfuscate real data, making it impossible for attackers to accurately infer individual information. The Byzantine Fault Tolerant consensus algorithm is an algorithm used to reach consensus in distributed systems. It can tolerate the failure or malicious behavior of some nodes, ensuring system reliability and consistency.

[0086] First, the system starts processing the transaction when the buyer responds to the seller's request to sell electricity.

[0087] Secondly, differential privacy technology is used to anonymize the information of both parties to the transaction.

[0088] Next, the transaction details are recorded through the blockchain platform to ensure the transparency and immutability of the data.

[0089] Finally, the Byzantine Fault Tolerant consensus algorithm is used to ensure the consistency of transaction data on all participating nodes and prevent malicious attacks.

[0090] In this application example, on a Hyperledger Fabric-based electricity trading platform, when a buyer responds to a seller's electricity sale request, the system first anonymizes the buyer and seller's identity information using differential privacy technology. The transaction details are then recorded on the blockchain, and all nodes reach consensus using a Byzantine Fault Tolerant consensus algorithm, ensuring the security and reliability of the transaction record.

[0091] Optionally, in step 103, based on the best potential buyer set, when the buyer responds to the seller's electricity sale request, the information of both parties to the transaction is protected through the blockchain platform in combination with differential privacy technology, the transaction details are recorded, and the Byzantine fault-tolerant consensus algorithm is used to ensure the consistency and reliability of the transaction data, prevent malicious attacks, and generate safe and reliable transaction records, including: using the best potential buyer set to monitor the buyer's response to the seller's electricity sale request to obtain the responding buyer information; based on the responding buyer information, combined with differential privacy technology, the identity information and transaction intentions of both parties to the transaction are anonymized to obtain anonymized transaction intention information to ensure personal privacy protection during the transaction process; based on the anonymized transaction intention information, the transaction details are recorded through the blockchain platform to generate a preliminary transaction record; and the preliminary transaction record is consensus-processed using the Byzantine fault-tolerant consensus algorithm to ensure the consistency and reliability of the transaction data on all participating nodes, prevent malicious attacks, and generate a safe and reliable transaction record.

[0092] Optionally, in step 103, the identity information and transaction intentions of both parties to the transaction are anonymized based on the buyer information of the response and combined with differential privacy technology to obtain anonymous transaction intention information to ensure personal privacy protection during the transaction, including: using the buyer information of the response, applying differential privacy technology to anonymize the buyer's identity information to generate an irreversible identity identifier; based on the irreversible identity identifier, adding random noise to the buyer's transaction intention data to blur the actual value to obtain transaction intention data processed with differential privacy; combining the transaction intention data processed with differential privacy with the irreversible identity identifier to generate completely anonymized transaction intention information, ensuring that the true identity and specific transaction intentions of both parties to the transaction will not be leaked during the entire transaction process, thereby achieving effective protection of personal privacy.

[0093] Optionally, the use of the Byzantine fault-tolerant consensus algorithm in step 103 to perform consensus processing on the preliminary transaction record to ensure consistency and reliability of transaction data on all participating nodes, prevent malicious attacks, and generate secure and reliable transaction records, including: using the preliminary transaction record, starting the Byzantine fault-tolerant consensus algorithm, broadcasting the preliminary transaction record to all nodes participating in the transaction, and obtaining a copy of the transaction record received by each node; based on the transaction record copy, each node independently verifies the transaction record according to preset rules and generates its own verification result; based on the verification result, each node votes on the transaction record, counts the voting results of all nodes, ensures that more than two-thirds of the nodes vote in favor, and reaches a consensus; by reaching a consensus, ensures consistency and reliability of transaction data on all participating nodes, prevents malicious attacks, and generates secure and reliable transaction records.

[0094] In this step, the irreversible identity is a unique identifier generated using differential privacy technology. It is unrelated to the user's real identity and cannot be reverse-derived. Preliminary transaction records refer to transaction details recorded after the two parties reach a preliminary agreement, including the identities of both parties, transaction quantity, price, and other information. These records require further processing to ensure their security and reliability.

[0095] When a buyer responds to a seller's electricity sale request, the system first monitors the buyer's response and collects the buyer's information. Then, using differential privacy technology, the identity information and transaction intentions of both parties are anonymized to generate irreversible identifiers. Random noise is added to the transaction intention data to produce completely anonymized transaction intention information. Based on this anonymized transaction intention information, the transaction details are recorded on the blockchain platform to generate a preliminary transaction record. This preliminary transaction record is then processed using a Byzantine Fault Tolerant consensus algorithm and broadcast to all participating nodes. Each node independently verifies the transaction record according to pre-set rules and generates its own verification result. Based on the verification results, each node votes on the transaction record, and the votes of all nodes are tallied to ensure that more than two-thirds of the nodes vote in favor, thus reaching consensus. This consensus ensures the consistency and reliability of transaction data on all participating nodes, preventing malicious attacks and generating a secure and reliable transaction record.

[0096] In an embodiment of the present application, it is assumed that in a decentralized electricity trading platform based on Hyperledger Fabric, a seller issues a request to sell electricity, and multiple potential buyers respond to the request. The system first monitors the information of the responding buyers and collects the basic information and transaction intentions of the buyers. Next, the system applies differential privacy technology to anonymize the buyer's identity information and generate an irreversible identity identifier. For example, the identity information of buyer A is converted into a unique hash value "1234567890". Then, the system adds random noise to buyer A's transaction intention data (such as the desired amount of electricity and price to be purchased), blurs the actual value, and obtains transaction intention data processed with differential privacy. For example, buyer A wants to purchase 100 kWh of electricity. After the system adds random noise, it displays a value between 95 and 105 kWh.

[0097] Based on the anonymized transaction intention information, the system records the transaction details through the Hyperledger Fabric platform and generates a preliminary transaction record. The preliminary transaction record includes the irreversible identity of buyer A, the obfuscated transaction intention data, and the seller's information.

[0098] The system then activates the Byzantine Fault Tolerance consensus algorithm, broadcasting the preliminary transaction record to all participating nodes. Each node independently verifies the transaction record according to pre-set rules and generates its own verification result. For example, Node 1 verifies the buyer's identity and transaction data in the transaction record, confirms that they are correct, and generates a verification result. After all nodes complete verification, they vote on the transaction record. Suppose there are 10 nodes, and 8 of them vote in favor, exceeding two-thirds of the nodes, thus reaching consensus.

[0099] By reaching consensus, transaction data on all participating nodes remains consistent and reliable, preventing malicious attacks and ultimately generating secure and reliable transaction records. These records are stored on the blockchain, ensuring the transparency and immutability of transactions.

[0100] In distributed systems, especially blockchain networks, the Byzantine Fault Tolerant consensus algorithm is used to ensure consistency and reliability of transaction data across all participating nodes, preventing malicious attacks. To improve the robustness and security of the consensus process, a weighted consensus mechanism was introduced. This mechanism calculates the consensus conditions by considering the trust weights of the nodes and the confidence level of the voting results.

[0101] Optionally, the use of a Byzantine fault-tolerant consensus algorithm in step 103 to perform consensus processing on the preliminary transaction records to ensure consistency and reliability of transaction data on all participating nodes, prevent malicious attacks, and generate secure and reliable transaction records includes:

[0102] The weighted consensus condition C is calculated using the following formula: w :

[0103]

[0104] Calculate the node trust weight w using the following formula: i :

[0105] w i =α·c i +(1-α)·h i

[0106] The confidence v of the voting result is calculated by the following formula i :

[0107]

[0108] Among them, C w Indicates the weighted consensus condition; N total Refers to the total number of nodes participating in the transaction; w i is the trust weight of the i-th node; v i is the confidence of the voting result of the i-th node on the transaction record; c i is the credit score of the i-th node, ranging between [0, 1]; h i is the historical transaction success rate of the i-th node, ranging between [0, 1]; α is the weight balance factor between the credit score and the historical transaction success rate, ranging between [0, 1]; s i is the score of the transaction record by the i-th node, ranging from [0, 1]; β is the slope parameter of the confidence function, which is used to adjust the steepness of the confidence curve; θ is the threshold parameter of the confidence function, which is used to adjust the center point of the confidence curve.

[0109] Weighted consensus reaching condition C w The consensus conditions are calculated by weighted average, ensuring that more than two-thirds of the weighted voting results support a transaction record, thus reaching a consensus. i It is to dynamically adjust the weight of each node to reflect its credibility by combining the node's credit score and historical transaction success rate. i The Sigmoid function is used to calculate each node's score for the transaction record, generating a confidence value between 0 and 1, which reflects the node's degree of recognition of the transaction record.

[0110] The following is a brief introduction to the design reasons of each sub-item of the formula:

[0111] In the weighted consensus reaching condition formula C w In the molecule It is the sum of the trust weights of all nodes and the product of their confidence in the voting results of transaction records, reflecting the weighted voting results. It is the sum of the trust weights of all nodes and is used to standardize the weighted voting results.

[0112] The following is a brief introduction to the design reasons of each sub-item of the formula:

[0113] In the node trust weight formula w i In the i Indicates credit score c i Reflects the reputation of the node and adjusts its importance through the weight balance factor α. (1-α)·h i Indicates the historical transaction success rate h i It reflects the success rate of the node's past transactions and adjusts its importance by 1-α. This ensures that even nodes with low credit scores but good historical performance can still receive a certain weight.

[0114] The following is a brief introduction to the design reasons of each sub-item of the formula:

[0115] In the confidence formula of the voting results v i middle, The Sigmoid function converts the node's score of the transaction record into i Mapped to between 0 and 1. The parameter β controls the steepness of the curve, and θ controls the center point of the curve. i >θ, the confidence v i Close to 1: When s i When <θ, the confidence v i Close to 0.

[0116] The following is a brief introduction to how to obtain the parameters of this formula:

[0117] Among them, the credit score c i It can be derived based on a comprehensive evaluation of the node's historical behavior, transaction records, user reviews, etc. For example, a scoring mechanism such as a machine learning model or expert system can be used. i The weight balancing factor α can be adjusted based on the actual needs of the system, such as whether to prioritize credit score or historical transaction success rate. i : This can be based on the node's verification of transaction records and its own judgment. For example, a node can assign a score based on factors such as transaction validity and completeness. The slope parameter β can be set through experimentation or experience to control the steepness of the confidence curve. The threshold parameter θ can also be set through experimentation or experience to control the center point of the confidence curve.

[0118] Assume that there are five participating nodes in a power trading platform based on Hyperledger Fabric. The relevant information of each node is as follows:

[0119] Node 1:

[0120] Credit score c1 = 0.8

[0121] Historical transaction success rate h1 = 0.9

[0122] Score of transaction record s1 = 0.7

[0123] Node 2:

[0124] Credit score c2 = 0.7

[0125] Historical transaction success rate h2 = 0.8

[0126] Score of transaction record s2 = 0.6

[0127] Node 3:

[0128] Credit score c3 = 0.9

[0129] Historical transaction success rate h3 = 0.7

[0130] Score of transaction record s3 = 0.8

[0131] Node 4:

[0132] Credit score c4 = 0.6

[0133] Historical transaction success rate h4 = 0.6

[0134] Score of transaction record s4 = 0.5

[0135] Node 5:

[0136] Credit score c5 = 0.8

[0137] Historical transaction success rate h5 = 0.8

[0138] Score of transaction record s5 = 0.7

[0139] Other parameter settings:

[0140] Weight balancing factor α = 0.6

[0141] Slope parameter β = 5

[0142] Threshold parameter θ = 0.6

[0143] Calculate the node trust weight w i :

[0144] W1=0.6·0.8+(1-0.6)·0.9=0.48+0.36=0.84

[0145] W2=0.6·0.7+(1-0.6)·0.8=0.42+0.32=0.74

[0146] w3=0.6·0.9+(1-0.6)·0.7=0.54+0.28=0.82

[0147] W4=0.6·0.6+(1-0.6)·0.6=0.36+0.24=0.60

[0148] W5=0.6·0.8+(1-0.6)·0.8=0.48+0.32=0.80

[0149] Calculate the confidence v of the voting result i :

[0150]

[0151]

[0152]

[0153]

[0154]

[0155] Calculate the weighted consensus condition C w

[0156]

[0157] The calculation results show that C w ≈0.5835, not reaching greater than Therefore, in this example, consensus was not reached. This indicates that under the current node trust weight and voting result confidence, there is insufficient support to confirm the validity of the transaction record.

[0158] 104. Based on the secure and reliable transaction records, the power trading smart contract automatically triggers an automated settlement process based on the power trading smart contract, accurately calculates the transaction amount using real-time exchange rate information obtained by the on-chain oracle, accurately deducts funds from the buyer's account and transfers them to the seller's account based on the transaction records, and simultaneously uses time series analysis to predict future transaction frequencies, provide financial planning advice to the power producer, and generate confirmation information for the completion of the transaction and settlement;

[0159] In this step, on-chain oracles are services that connect blockchains to external data sources, providing real-time data to smart contracts to support their automatic execution. Time series analysis is a statistical method used to analyze data that changes over time and predict future trends.

[0160] First, the smart contract automatically triggers the settlement process based on transaction records.

[0161] Secondly, real-time exchange rate information is obtained through the on-chain oracle to accurately calculate the transaction amount.

[0162] Then, the buyer's account is accurately deducted and the funds are transferred to the seller's account.

[0163] Finally, time series analysis is used to predict future transaction frequencies and provide financial planning advice for power producers.

[0164] In this application example, consider an Ethereum-based electricity trading platform. Once a transaction is confirmed, a smart contract automatically triggers the settlement process. Using Chainlink oracles, the system obtains real-time exchange rate information to accurately calculate the transaction amount. The system debits the buyer's account and transfers the funds to the seller's account. Furthermore, the system uses an ARIMA model to predict future transaction frequencies, providing financial planning advice to power producers and helping them better manage their cash flow.

[0165] Optionally, in step 104, according to the secure and reliable transaction records, the power transaction smart contract automatically triggers the automated settlement process based on the power transaction smart contract, accurately calculates the transaction amount using the real-time exchange rate information obtained by the on-chain oracle, accurately deducts money from the buyer's account and transfers it to the seller's account based on the transaction records, and uses time series analysis to predict future transaction frequencies, provide financial planning advice for the power producer, and generate confirmation information for completing the transaction and settlement, including: using the secure and reliable transaction records, the power transaction smart contract automatically triggers the automated settlement process based on the power transaction smart contract, and obtains the started settlement process; according to the The initiated settlement process obtains real-time exchange rate information through the on-chain oracle, accurately calculates the transaction amount in the transaction record, and obtains the final payment amount; based on the final payment amount, accurately deducts money from the buyer's account, transfers the money to the seller's account, and generates payment confirmation information; utilizes the secure and reliable transaction records, adopts time series analysis technology to predict future transaction frequency, and generates a transaction frequency prediction report; based on the transaction frequency prediction report, provides financial planning advice to the power producer, and generates a financial planning advice report; combines the payment confirmation information and the financial planning advice report to generate confirmation information of the completed transaction and settlement, ensuring the transparency and traceability of the transaction.

[0166] In this step, the automated settlement process refers to the process of automatically handling transaction settlement through smart contracts, including deducting funds from the buyer's account and transferring them to the seller's account, generating payment confirmation information, etc. This process ensures the efficiency and accuracy of transactions.

[0167] Once secure and reliable transaction records are confirmed, the power trading smart contract automatically triggers an automated settlement process based on smart contracts. Based on the initiated settlement process, the system obtains real-time exchange rate information through an on-chain oracle, accurately calculates the transaction amount in the transaction record, and determines the final payment amount. Based on the final payment amount, the system accurately debits the buyer's account, transfers the funds to the seller's account, and generates a payment confirmation. Simultaneously, leveraging secure and reliable transaction records, time series analysis techniques are used to predict future transaction frequencies and generate a transaction frequency forecast report. Based on this forecast report, financial planning recommendations are provided to power producers and a financial planning recommendation report is generated. Finally, the payment confirmation information and the financial planning recommendation report are combined to generate confirmation of the transaction and settlement, ensuring transparency and traceability throughout the entire transaction process.

[0168] In this embodiment of the present application, assume that after a power transaction is completed on an Ethereum-based decentralized power trading platform, the system generates a secure and reliable transaction record. Upon detecting this transaction record, the smart contract automatically triggers the automated settlement process. First, the smart contract obtains real-time exchange rate information from the Chainlink oracle. Assume that the current exchange rate is 1.20 USD / ETH. Based on the transaction amount in the transaction record (for example, 100 ETH), the smart contract calculates the final payment amount as 120 USD (100 ETH * 1.20 USD / ETH).

[0169] The system then deducts $120 from the buyer's account and transfers the amount to the seller's account. The system generates a payment confirmation message, confirming that the transaction amount has been successfully transferred.

[0170] The system also conducts time series analysis using historical transaction records and uses the ARIMA model to predict transaction frequency over the next three months. Assuming the forecast indicates a 15% increase in the average monthly number of transactions over the next three months, the system provides financial planning advice to power producers, recommending increased investment in power production to address the expected increase in demand.

[0171] Finally, the system combines payment confirmation information with a financial planning advice report to generate complete transaction and settlement confirmation. This information includes not only the transaction amount and payment status, but also a forecast of future transaction frequency and corresponding financial planning advice. All of this information is stored on the blockchain, ensuring transaction transparency and traceability.

[0172] In this way, the power trading platform not only achieves efficient automated settlement, but also provides valuable financial planning advice to power producers, thereby improving the efficiency and reliability of the entire market.

[0173] In electricity trading, smart contracts can automatically process transaction settlements and utilize on-chain oracles to obtain real-time exchange rate information to accurately calculate transaction amounts. Furthermore, time series analysis can be used to predict future transaction frequencies and provide financial planning advice to electricity producers. These formulas are designed to ensure transaction accuracy, enhance the scientific nature of financial planning, and dynamically adjust parameters to adapt to market changes.

[0174] Optionally, in step 104, based on the secure and reliable transaction records, the power trading smart contract automatically triggers an automated settlement process based on the power trading smart contract, accurately calculates the transaction amount using real-time exchange rate information obtained by the on-chain oracle, accurately deducts the amount from the buyer's account and transfers it to the seller's account based on the transaction records, and simultaneously uses time series analysis to predict future transaction frequencies, provides financial planning advice to the power producer, and generates confirmation information on the completion of the transaction and settlement, including:

[0175] The final payment amount P is calculated using the following formula: f :

[0176] P f =A·R·(1+γ·V)

[0177] Calculate the transaction frequency prediction value F using the following formula: t :

[0178]

[0179] Calculate the financial planning recommendation value S using the following formula: p :

[0180]

[0181] The weight coefficient w in time series analysis is calculated by the following formula i :

[0182]

[0183] Among them, P f represents the final payment amount; A represents the transaction amount in the transaction record; H represents the real-time exchange rate information obtained through the on-chain oracle; γ is the volatility coefficient, which is used to adjust the changes in the transaction amount due to market fluctuations; V represents the market volatility, which reflects the degree of market fluctuations; F t Indicates the predicted value of future transaction frequency; represents the future transaction frequency predicted by time series analysis; y t Indicates the transaction frequency of the current time unit; Indicates the predicted transaction frequency of the previous time unit; represents the predicted transaction frequency of the previous two time units; α is a smoothing parameter ranging from [0, 1], which is used to adjust the weight of the current value and the historical forecast value; S p represents the financial planning recommendation value; T represents the time unit, which is used to convert the payment amount and transaction frequency into the financial planning recommendation value; δ is the logarithmic adjustment coefficient, which is used to adjust the impact of the financial planning recommendation value caused by the logarithmic change of the transaction frequency; w i Represents the weight coefficient in time series analysis; λ is the decay parameter, which is used to adjust the decay rate of the weight over time; η is the seasonal adjustment coefficient, which is used to adjust the seasonal change of the weight; P is the cycle length, which represents the cycle of seasonal change; β is the quadratic smoothing parameter, which ranges from [0, 1] and is used to adjust the weight of the predicted value of the previous time unit and the previous two time units; i usually represents the time index or time unit in the time series.

[0184] Final payment amount P f The formula takes into account the transaction amount, real-time exchange rate and the impact of market fluctuations on the transaction amount to ensure the accuracy and rationality of the payment amount. t Double exponential smoothing is used to predict future transaction frequencies, combining current and historical data to improve the accuracy of the forecast. p The formula combines the payment amount with the transaction frequency and considers the impact of changes in transaction frequency on financial planning, providing specific financial planning suggestions for power producers. i Through the decay function and seasonal adjustment terms, the weights of data at different time points are dynamically adjusted to better reflect the importance of recent data and take into account seasonal changes.

[0185] The following is a brief introduction to the design reasons of each sub-item of the formula:

[0186] The final payment amount P f In the formula, A·R is the transaction amount multiplied by the real-time exchange rate, which gives the base payment amount. (1+γ·V) accounts for the impact of market fluctuations on the payment amount, where γ is the volatility coefficient and V is the market volatility.

[0187] The following is a brief introduction to how to obtain the parameters of this formula:

[0188] Among them, the transaction amount A is obtained directly from the transaction record; the real-time exchange rate R is obtained through the on-chain oracle; the volatility coefficient γ and market volatility V can be obtained through historical market data analysis.

[0189] The following is a brief introduction to the design reasons of each sub-item of the formula:

[0190] In the transaction frequency prediction formula F t In the t is the actual transaction frequency in the current time unit, weighted by the smoothing parameter α. It is a weighted average of historical forecast values, adjusted by a quadratic smoothing parameter β.

[0191] The following is a brief introduction to how to obtain the parameters of this formula:

[0192] Among them, the transaction frequency y of the current time unit t Obtained from historical transaction data; historically predicted transaction frequency and Derived from the previous forecast model; the smoothing parameter α and the quadratic smoothing parameter β are set through experiments or experience.

[0193] The following is a brief introduction to the design reasons of each sub-item of the formula:

[0194] Suggested Value Formulas in Financial Planning p middle, It converts the payment amount and transaction frequency into the financial planning recommendation value within the time unit; (1+δ·log(F t )) is a logarithmic adjustment item that takes into account the impact of logarithmic changes in transaction frequency on the financial planning recommendation value.

[0195] The following is a brief introduction to how to obtain the parameters of this formula:

[0196] The time unit T is set according to actual conditions, such as hours, days, etc.; the logarithmic adjustment coefficient δ is set through experiments or experience.

[0197] The following is a brief introduction to the design reasons of each sub-item of the formula:

[0198] In the weight coefficient formula w i In, e -λi is an exponential decay function that reduces the weight over time; (1+η·sin(2πi / P)) is a seasonal adjustment term that takes into account cyclical changes.

[0199] The following is a brief introduction to how to obtain the parameters of this formula:

[0200] The decay parameter λ and the seasonal adjustment coefficient η are set through experiments or experience; the cycle length P is set according to the actual business cycle, such as weekly, monthly, etc.

[0201] Assume that in a power trading platform based on blockchain technology, the specific data of a power transaction is as follows:

[0202] Transaction amount A = 1000 USD; real-time exchange rate R = 0.85 USD / ETH; volatility coefficient γ = 0.05; market volatility V = 0.02; transaction frequency y in the current time unit t = 150 times / day; the predicted transaction frequency of the previous time unit times / day; predicted transaction frequency of the first two time units times / day; smoothing parameter α = 0.6; quadratic smoothing parameter β = 0.3; time unit T = 1 day; logarithmic adjustment coefficient δ = 0.01; decay parameter λ = 0.1; seasonal adjustment coefficient η = 0.2; cycle length P = 7 days;

[0203] Calculate the final payment amount P f :

[0204] P f =1000·0.85·(1+0.05·0.02)=850.85USD

[0205] Calculate the transaction frequency prediction value F t :

[0206] F t =0.6·150+(1-0.6)·(0.3·140+(1-0.3)·130)=143.2 times / day

[0207] Calculate the financial planning recommendation value S p :

[0208]

[0209] Calculate the weight coefficient w i (Take i=1 as an example):

[0210]

[0211] Final payment amount P f = 850.85 USD, the payment amount adjusted based on the real-time exchange rate and market fluctuations. Transaction frequency prediction value F t = 143.2 times / day, the predicted transaction frequency for the next day is slightly higher than the current actual frequency. Financial planning recommendation value S p = 124,517.57 USD / day. This, combined with the financial planning recommendations for payment amount and transaction frequency, reflects the expected daily income. The weight coefficient w1 ≈ 0.982 indicates that the most recent day's data has a higher weight in the time series analysis, but with a slight attenuation.

[0212] Through these calculations, the system can provide detailed financial planning advice to power producers, helping them better manage cash flows and optimize future production and sales strategies. Furthermore, these calculations provide accurate data support for the system's automated settlement process, ensuring transaction transparency and traceability.

[0213] 105. Using the confirmation information of completed transactions and settlements, the system regularly evaluates electricity production and consumption. When an imbalance between supply and demand is detected, the system automatically adjusts electricity prices to guide the market to a new equilibrium. The system analyzes user consumption habits, provides personalized energy selection recommendations to electricity consumers, and generates an optimized electricity supply plan.

[0214] In this step, supply and demand balance is ensured by monitoring electricity production and consumption to ensure the balance of supply and demand in the electricity market.

[0215] Personalized energy selection recommendations are provided based on users' consumption habits and preferences to optimize electricity supply plans.

[0216] First, the system regularly assesses electricity production and consumption.

[0217] Secondly, when a supply-demand imbalance is detected, electricity prices are automatically adjusted to guide the market to a new equilibrium.

[0218] Next, it analyzes the user's consumption habits and provides personalized energy selection recommendations.

[0219] Finally, an optimized power supply plan is generated based on the evaluation results and user needs.

[0220] In this application example, a city's smart grid system regularly assesses electricity production and consumption daily. When it detects an imbalance between supply and demand during the peak summer electricity consumption period, the system automatically adjusts electricity prices to encourage users to use electricity during off-peak hours. Furthermore, by analyzing user electricity usage data, the system discovers that some users prefer renewable energy. Therefore, the system offers these users preferential solar and wind power packages, optimizing electricity supply plans and improving user satisfaction.

[0221] Optionally, the system uses the confirmation information of the completed transaction and settlement in step 105 to regularly evaluate the power production and consumption. When an imbalance between supply and demand is detected, the system automatically adjusts the power price to guide the market to a new equilibrium state, analyzes user consumption habits, provides personalized energy selection suggestions for power consumers, and generates an optimized power supply plan, including: using the confirmation information of the completed transaction and settlement, the system regularly evaluates the power production and consumption in the cabin and generates an evaluation report on power production and consumption; based on the evaluation report on power production and consumption, the system detects whether there is a supply and demand imbalance and obtains a supply and demand imbalance. The system automatically adjusts the electricity price based on the supply and demand imbalance detection result, generates a dynamically adjusted electricity price, and guides the market to a new equilibrium state; using the confirmation information of the completed transaction and settlement, the system analyzes the user's consumption habits and generates a user consumption habit report; based on the user consumption habit report, the system provides personalized energy selection recommendations for electricity consumers and generates a personalized energy selection recommendation report; combining the electricity production and consumption evaluation report, the dynamically adjusted electricity price, and the user consumption habit report, the system generates an optimized electricity supply plan to ensure the efficiency and sustainability of electricity supply.

[0222] In this step, the electricity production and consumption assessment report is generated based on completed transactions and settlement confirmation information. It analyzes electricity production and consumption within the shelter. This report includes data such as actual electricity production, electricity consumption, and remaining electricity, and is used to monitor the supply and demand balance. The system detects supply and demand imbalances by comparing electricity production and consumption data. If an imbalance is detected, the system generates corresponding detection results, providing a basis for subsequent price adjustments. Dynamically adjusted electricity prices automatically adjust prices when a supply and demand imbalance is detected to guide the market to a new equilibrium. For example, prices may be lowered to stimulate demand when there is an oversupply, or raised to suppress demand when there is a shortage. The system generates a user consumption habit report based on user electricity consumption data. This report includes information such as peak usage times, fluctuations in electricity consumption, and preferred energy types, providing personalized energy selection recommendations. Based on user consumption habit reports, the system provides personalized energy selection recommendations to electricity consumers, such as recommendations for renewable energy and optimized electricity usage times, helping them use electricity more efficiently. The optimized power supply plan is generated by combining power production and consumption assessment reports, dynamically adjusted power prices, and user consumption habit reports to ensure efficient and sustainable power supply.

[0223] The system uses confirmation information from completed transactions and settlements to regularly assess electricity production and consumption within the shelter and generate a production and consumption assessment report. Based on this report, the system detects whether there is a supply and demand imbalance and generates a supply and demand imbalance detection result. Based on this supply and demand imbalance detection result, the system automatically adjusts electricity prices, generating dynamically adjusted electricity prices to guide the market to a new equilibrium. Furthermore, the system uses confirmation information from completed transactions and settlements to analyze user consumption habits and generate a user consumption habit report. Based on this user consumption habit report, the system provides electricity consumers with personalized energy selection recommendations and generates a personalized energy selection recommendation report. Finally, combining the production and consumption assessment report, the dynamically adjusted electricity price, and the user consumption habit report, the system generates an optimized power supply plan to ensure efficient and sustainable power supply.

[0224] In an embodiment of the present application, it is assumed that in a smart grid system based on blockchain technology, the electricity production and consumption in a certain cabin are recorded in real time by smart meters and stored and managed through the blockchain platform. The system collects this data regularly every day and generates an assessment report on electricity production and consumption. Suppose that on a hot day in summer, the system detects that the electricity consumption on that day is significantly higher than the average, while the electricity production is relatively stable, resulting in a tight electricity supply. Based on the supply and demand imbalance detection results, the system automatically increases the electricity price from 0.12 yuan per kilowatt-hour to 0.15 yuan to curb some unnecessary electricity consumption.

[0225] The system also analyzes user consumption habits, finding that most users consume the most electricity between 4:00 PM and 7:00 PM, and that most prefer renewable energy sources like solar power. Based on this finding, the system provides personalized energy recommendations, suggesting users use electricity during off-peak hours and recommending the installation of solar panels to reduce reliance on external power.

[0226] Finally, the system combines electricity production and consumption assessments, dynamically adjusted electricity prices, and reports on user consumption habits to generate an optimized electricity supply plan. This plan includes increasing the output of solar power plants, encouraging users to charge their electric vehicles at night, and promoting smart home devices for more efficient energy management. Through these measures, the system not only alleviates the current power supply shortage but also improves the efficiency and sustainability of the entire system.

[0227] Figure 2 The present invention provides a schematic diagram of a block chain-based electricity trading and management system. Figure 2 As shown, the system includes:

[0228] Construction module 21 is used to build a smart contract for power transactions, encrypting power transaction rules, price mechanisms, and the authentication process of both parties to the transaction to ensure the security, transparency, and privacy of all transaction activities;

[0229] The screening module 22 is used to optimize the issuance strategy of power sale requests when the power producers in the shelter generate excess power according to the power trading smart contract, conduct a comprehensive analysis of power quantity, quality parameters, and expected selling price, and predict future demand trends based on historical transaction data, dynamically adjust power prices, improve transaction success rates, and screen the best set of potential buyers from all potential buyers;

[0230] Recording module 23 is used to protect the information of both parties to the transaction through the blockchain platform combined with differential privacy technology, record the transaction details, and use the Byzantine Fault Tolerance consensus algorithm to ensure the consistency and reliability of transaction data, prevent malicious attacks, and generate secure and reliable transaction records based on the best potential buyer set.

[0231] The transaction settlement module 24 is configured to automatically trigger an automated settlement process based on the power trading smart contract based on the secure and reliable transaction records, accurately calculate the transaction amount using real-time exchange rate information obtained by the on-chain oracle, accurately deduct funds from the buyer's account and transfer them to the seller's account based on the transaction records, and simultaneously use time series analysis to predict future transaction frequencies, provide financial planning advice to the power producer, and generate confirmation information for the completion of the transaction and settlement;

[0232] The adjustment suggestion module 25 is used to use the confirmation information of the completed transaction and settlement to regularly evaluate the power production and consumption situation of the system. When an imbalance between supply and demand is detected, the power price is automatically adjusted to guide the market to a new equilibrium state. The user's consumption habits are analyzed to provide personalized energy selection suggestions to power consumers and generate an optimized power supply plan.

[0233] Figure 2 The above-mentioned block chain-based cabin power transaction and management system can execute Figure 1 The implementation principles and technical effects of the blockchain-based shelter power trading and management method described in the illustrated embodiment are not further elaborated. The specific manner in which each module and unit performs operations in the blockchain-based shelter power trading and management system described in the aforementioned embodiment has been described in detail in the relevant embodiments of the method and will not be further elaborated here.

[0234] In one possible design, Figure 2The block chain technology-based cabin power transaction and management system of the embodiment shown can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32;

[0235] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0236] The processing component 32 is used to: construct an electricity trading smart contract, encrypt the electricity trading rules, price mechanism and the identity authentication process of both parties to the transaction to ensure the security, transparency and personal privacy protection of all transaction activities; according to the electricity trading smart contract, when the electricity producer in the cabin generates excess electricity, optimize the issuance strategy of the electricity sale request, conduct a comprehensive analysis of the electricity quantity, quality parameters and expected selling price, and predict future demand trends based on historical transaction data, dynamically adjust the electricity price, improve the transaction success rate, and screen out the best potential buyer set from all potential buyers; based on the best potential buyer set, when the buyer responds to the seller's electricity sale request, the blockchain platform is combined with differential privacy technology to protect the information of both parties to the transaction, record the transaction details, and use the Byzantine fault-tolerant consensus algorithm to ensure the consistency and Reliability, prevent malicious attacks, and generate safe and reliable transaction records; based on the safe and reliable transaction records, the power trading smart contract automatically triggers the automated settlement process based on the power trading smart contract, uses the real-time exchange rate information obtained by the on-chain oracle to accurately calculate the transaction amount, accurately deducts money from the buyer's account based on the transaction record and transfers it to the seller's account, and uses time series analysis to predict future transaction frequencies, provide financial planning suggestions for the power producer, and generate confirmation information for completed transactions and settlements; using the confirmation information for completed transactions and settlements, the system regularly evaluates power production and consumption, and when an imbalance between supply and demand is detected, automatically adjusts the power price to guide the market to a new equilibrium state, analyzes user consumption habits, provides personalized energy selection suggestions for power consumers, and generates an optimized power supply plan.

[0237] The processing component 32 may include one or more processors to execute computer instructions to perform all or part of the steps in the above method. Of course, the processing component may also be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above method.

[0238] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0239] Of course, a computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0240] The input / output interface provides an interface between the processing component and the peripheral interface module, which can be an output device, an input device, etc.

[0241] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0242] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0243] The present application also provides a computer storage medium storing a computer program, wherein the computer program can achieve the above-mentioned Figure 1 The illustrated embodiment shows a method for cabin electricity trading and management based on blockchain technology.

[0244] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0245] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0246] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0247] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for cabin power trading and management based on blockchain technology, characterized in that: include: Build smart contracts for power transactions, encrypt power transaction rules, price mechanisms, and the authentication process of both parties to ensure the security, transparency, and privacy of all transactions; According to the electricity trading smart contract, when the electricity producer in the shelter generates excess electricity, the strategy for issuing electricity sales requests is optimized, a comprehensive analysis of electricity quantity, quality parameters, and expected selling price is conducted, and future demand trends are predicted based on historical transaction data. The electricity price is dynamically adjusted to improve the transaction success rate and select the best potential buyer set from all potential buyers. Based on the best set of potential buyers, when a buyer responds to the seller's electricity sale request, the blockchain platform combines differential privacy technology to protect the information of both parties, record the transaction details, and use the Byzantine Fault Tolerance consensus algorithm to ensure the consistency and reliability of transaction data, prevent malicious attacks, and generate secure and reliable transaction records. Based on the secure and reliable transaction records, the power trading smart contract automatically triggers an automated settlement process based on the power trading smart contract, accurately calculates the transaction amount using real-time exchange rate information obtained by the on-chain oracle, accurately deducts funds from the buyer's account and transfers them to the seller's account based on the transaction records, and simultaneously uses time series analysis to predict future transaction frequencies, provide financial planning advice to the power producer, and generate confirmation information for the completion of the transaction and settlement; Using the confirmation information of completed transactions and settlements, the system regularly evaluates electricity production and consumption. When an imbalance between supply and demand is detected, the system automatically adjusts electricity prices to guide the market to a new equilibrium. It analyzes user consumption habits, provides personalized energy selection recommendations to electricity consumers, and generates an optimized electricity supply plan.

2. The method for cabin power trading and management based on blockchain technology according to claim 1 is characterized in that: Based on the best set of potential buyers, when a buyer responds to the seller's electricity sale request, the blockchain platform is combined with differential privacy technology to protect the information of both parties to the transaction, record the transaction details, and use the Byzantine fault-tolerant consensus algorithm to ensure the consistency and reliability of transaction data, prevent malicious attacks, and generate secure and reliable transaction records, including: Using the best potential buyer set, monitoring the buyer's response to the seller's power sale request to obtain responding buyer information; Based on the buyer's information of the response, the identity information and transaction intentions of both parties to the transaction are anonymized by combining differential privacy technology to obtain anonymized transaction intention information, thereby ensuring personal privacy protection during the transaction process; Based on the anonymized transaction intention information, the transaction details are recorded through the blockchain platform to generate a preliminary transaction record; The Byzantine fault-tolerant consensus algorithm is used to conduct consensus processing on the preliminary transaction records to ensure the consistency and reliability of transaction data on all participating nodes, prevent malicious attacks, and generate safe and reliable transaction records.

3. The method for cabin power trading and management based on blockchain technology according to claim 2 is characterized in that: The identity information and transaction intentions of both parties to the transaction are anonymized based on the buyer's information in the response, combined with differential privacy technology, to obtain anonymized transaction intention information, thereby ensuring personal privacy protection during the transaction, including: Using the buyer's information in the response, differential privacy technology is applied to anonymize the buyer's identity information to generate an irreversible identity identifier; Based on the irreversible identity identifier, random noise is added to the buyer's transaction intention data to blur the actual value and obtain transaction intention data processed with differential privacy. The transaction intention data processed with differential privacy is combined with the irreversible identity identifier to generate completely anonymous transaction intention information, ensuring that the true identities and specific transaction intentions of the two parties to the transaction will not be disclosed during the entire transaction process, thereby achieving effective protection of personal privacy.

4. The method for cabin power trading and management based on blockchain technology according to claim 2 is characterized in that: The use of the Byzantine Fault Tolerant consensus algorithm to process the preliminary transaction records in a consensus manner ensures that the transaction data on all participating nodes remains consistent and reliable, prevents malicious attacks, and generates secure and reliable transaction records, including: Using the preliminary transaction record, starting a Byzantine fault-tolerant consensus algorithm, broadcasting the preliminary transaction record to all nodes participating in the transaction, and obtaining a copy of the transaction record received by each node; Based on the transaction record copy, each node independently verifies the transaction record according to preset rules and generates its own verification result; Based on the verification results, each node votes on the transaction record, and the voting results of all nodes are counted to ensure that more than two-thirds of the nodes vote in favor and reach a consensus; By reaching a consensus, the transaction data on all participating nodes is ensured to remain consistent and reliable, malicious attacks are prevented, and secure and reliable transaction records are generated.

5. The method for cabin power trading and management based on blockchain technology according to claim 4 is characterized in that: The use of the Byzantine Fault Tolerant consensus algorithm to process the preliminary transaction records in a consensus manner ensures that the transaction data on all participating nodes remains consistent and reliable, prevents malicious attacks, and generates secure and reliable transaction records, including: The weighted consensus condition C is calculated using the following formula: w : Calculate the node trust weight w using the following formula: i : w i =α·c i +(1-a)·h i The confidence v of the voting result is calculated by the following formula i : Among them, C w Indicates the weighted consensus condition; N total Refers to the total number of nodes participating in the transaction; w i is the trust weight of the i-th node; v i is the confidence of the voting result of the i-th node on the transaction record; c i is the credit score of the i-th node, ranging between [0, 1]; h i is the historical transaction success rate of the i-th node, ranging between [0, 1]; α is the weight balance factor between the credit score and the historical transaction success rate, ranging between [0, 1]; s i is the score of the transaction record by the i-th node, ranging from [0, 1]; β is the slope parameter of the confidence function, which is used to adjust the steepness of the confidence curve; θ is the threshold parameter of the confidence function, which is used to adjust the center point of the confidence curve.

6. The method for cabin power trading and management based on blockchain technology according to claim 1 is characterized in that: Based on the secure and reliable transaction records, the power trading smart contract automatically triggers an automated settlement process based on the power trading smart contract, accurately calculates the transaction amount using real-time exchange rate information obtained by the on-chain oracle, accurately deducts funds from the buyer's account and transfers them to the seller's account based on the transaction records, and simultaneously uses time series analysis to predict future transaction frequencies, providing financial planning advice to the power producer and generating confirmation information for the completion of the transaction and settlement, including: By utilizing the secure and reliable transaction records, the power transaction smart contract automatically triggers an automated settlement process based on the power transaction smart contract, thereby obtaining an initiated settlement process; According to the initiated settlement process, real-time exchange rate information is obtained through the on-chain oracle, and the transaction amount in the transaction record is accurately calculated to obtain the final payment amount; Based on the final payment amount, accurately debit the buyer's account, transfer the funds to the seller's account, and generate payment confirmation information; Using the secure and reliable transaction records, using time series analysis technology to predict future transaction frequencies and generate a transaction frequency prediction report; Providing financial planning suggestions to the power producer based on the transaction frequency forecast report and generating a financial planning suggestion report; Combining the payment confirmation information and the financial planning advice report, confirmation information of completed transactions and settlements is generated to ensure the transparency and traceability of transactions.

7. The method for cabin power trading and management based on blockchain technology according to claim 6 is characterized in that: Based on the secure and reliable transaction records, the power trading smart contract automatically triggers an automated settlement process based on the power trading smart contract, accurately calculates the transaction amount using real-time exchange rate information obtained by the on-chain oracle, accurately deducts funds from the buyer's account and transfers them to the seller's account based on the transaction records, and simultaneously uses time series analysis to predict future transaction frequencies, providing financial planning advice to the power producer and generating confirmation information for the completion of the transaction and settlement, including: The final payment amount P is calculated using the following formula: f : P f =A·R·(1+γ·V) Calculate the transaction frequency prediction value F using the following formula: t : Calculate the financial planning recommendation value S using the following formula: p : The weight coefficient w in time series analysis is calculated by the following formula i : Among them, P f represents the final payment amount; A represents the transaction amount in the transaction record; R represents the real-time exchange rate information obtained through the on-chain oracle; γ is the volatility coefficient, which is used to adjust the changes in the transaction amount due to market fluctuations; V represents the market volatility, which reflects the degree of market fluctuations; F t Indicates the predicted value of future transaction frequency; represents the future transaction frequency predicted by time series analysis; y t Indicates the transaction frequency of the current time unit; Indicates the predicted transaction frequency of the previous time unit; represents the predicted transaction frequency of the previous two time units; α is a smoothing parameter ranging from [0, 1], which is used to adjust the weight of the current value and the historical forecast value; S p represents the financial planning recommendation value; T represents the time unit, which is used to convert the payment amount and transaction frequency into the financial planning recommendation value; δ is the logarithmic adjustment coefficient, which is used to adjust the impact of the financial planning recommendation value caused by the logarithmic change of the transaction frequency; w i Represents the weight coefficient in time series analysis; λ is the decay parameter, which is used to adjust the decay rate of the weight over time; η is the seasonal adjustment coefficient, which is used to adjust the seasonal change of the weight; P is the cycle length, which represents the cycle of seasonal change; β is the quadratic smoothing parameter, which ranges from [0, 1] and is used to adjust the weight of the predicted value of the previous time unit and the previous two time units; i usually represents the time index or time unit in the time series.

8. The method for cabin power trading and management based on blockchain technology according to claim 1 is characterized in that: According to the power trading smart contract, when the power producer in the shelter generates excess power, the power sale request publishing strategy is optimized, and a comprehensive analysis of power quantity, quality parameters and expected selling price is conducted. At the same time, based on historical transaction data, future demand trends are predicted, and power prices are dynamically adjusted to improve transaction success rates. The best potential buyers are selected from all potential buyers, including: By using the power trading smart contract, when the power producer in the shelter generates excess power, the excess power amount is detected and confirmed, and confirmed excess power information is obtained; Based on the confirmed excess power information and historical transaction data, optimizing the issuance strategy of the power sale request, selecting the best issuance time and channel, improving the visibility and response rate of the request, and generating an optimized power sale request strategy; Performing a comprehensive analysis of electricity quantity, quality parameters, and expected selling price based on the optimized electricity sale request strategy to ensure that the information in the electricity sale request is accurate and generate a comprehensive analysis result; Using the comprehensive analysis results and historical transaction data, data analysis and machine learning techniques are used to predict future electricity demand trends and generate a future demand trend forecast report; Dynamically adjusting the electricity price based on the future demand trend forecast report to generate a dynamically adjusted electricity price; From all the potential buyers, the best potential buyers are screened out by comprehensively evaluating the buyers' historical transaction records and credit scores, and generating a set of the best potential buyers.

9. The method for cabin power trading and management based on blockchain technology according to claim 1 is characterized in that: The system utilizes the confirmation information of completed transactions and settlements to regularly evaluate electricity production and consumption. When an imbalance between supply and demand is detected, it automatically adjusts electricity prices to guide the market to a new equilibrium. It also analyzes user consumption habits, provides personalized energy selection recommendations to electricity consumers, and generates optimized electricity supply plans, including: Using the confirmation information of the completed transaction and settlement, the system regularly evaluates the electricity production and consumption in the shelter and generates an evaluation report on the electricity production and consumption; Based on the electricity production and consumption assessment report, the system detects whether there is a supply and demand imbalance and obtains a supply and demand imbalance detection result; Based on the supply and demand imbalance detection results, the system automatically adjusts the electricity price, generates a dynamically adjusted electricity price, and guides the market to a new equilibrium state; Using the confirmation information of the completed transaction and settlement, the system analyzes the user's consumption habits and generates a user consumption habit report; Based on the user consumption habit report, the system provides personalized energy selection recommendations to electricity consumers and generates a personalized energy selection recommendation report; Combining the evaluation report on electricity production and consumption, the dynamically adjusted electricity price, and the user consumption habit report, the system generates an optimized electricity supply plan to ensure the efficiency and sustainability of electricity supply.

10. A modular power trading and management system based on blockchain technology, characterized in that: include: A building block for constructing smart contracts for power transactions, encrypting power transaction rules, pricing mechanisms, and the authentication process of both parties to ensure the security, transparency, and privacy of all transaction activities; A screening module is used to optimize the issuance strategy of power sale requests when the power producers in the shelter generate excess power according to the power trading smart contract. This module conducts a comprehensive analysis of power quantity, quality parameters, and expected selling price. Furthermore, based on historical transaction data, it predicts future demand trends, dynamically adjusts power prices, improves transaction success rates, and selects the best set of potential buyers from all potential buyers. A recording module is used to protect the information of both parties to the transaction through a blockchain platform combined with differential privacy technology, record the transaction details, and use a Byzantine fault-tolerant consensus algorithm to ensure the consistency and reliability of transaction data, prevent malicious attacks, and generate secure and reliable transaction records based on the best set of potential buyers. A transaction settlement module, configured to automatically trigger an automated settlement process based on the power trading smart contract based on the secure and reliable transaction records, accurately calculate the transaction amount using real-time exchange rate information obtained by an on-chain oracle, accurately deduct funds from the buyer's account and transfer them to the seller's account based on the transaction records, and simultaneously use time series analysis to predict future transaction frequencies, provide financial planning advice to the power producer, and generate confirmation information for the completion of the transaction and settlement; The adjustment suggestion module is used to use the confirmation information of the completed transactions and settlements to regularly evaluate the power production and consumption of the system. When an imbalance between supply and demand is detected, the system automatically adjusts the power price to guide the market to a new equilibrium state. The system also analyzes user consumption habits, provides personalized energy selection suggestions to power consumers, and generates an optimized power supply plan.

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