Green certificate transaction management method and system based on block chain

Abstract

The invention discloses a block chain-based green certificate transaction management method and system, and the method comprises the steps: creating a green certificate equivalent to the power generation amount based on the power generation record data of a seller, and storing the green certificate in a block chain; determining a generating capacity gap of the purchaser, and determining a green certificate equivalent to the generating capacity gap based on the generating capacity gap so as to determine a corresponding candidate seller; determining historical price transaction data of the green certificates of the candidate sellers, and performing prediction based on the historical price transaction data to obtain predicted prices of the green certificates of the candidate sellers; determining an expected price interval of the purchaser, and determining an optimal seller based on the expected price interval and the predicted price of each candidate seller; matching the purchaser with the optimal seller, generating a transaction certificate based on a matching result, and storing the transaction certificate in the block chain; and performing transaction management on the green certificate transaction on the block chain based on the transaction certificate. According to the method, the efficiency, transparency and credibility of green certificate transaction are improved, and market friction and trust cost are remarkably reduced.

Description

Technical Field

[0001] This invention relates to the field of blockchain technology, and in particular to a blockchain-based method and system for managing green certificate transactions. Background Technology

[0002] Against the backdrop of a global effort to address climate change and promote energy structure transformation, developing renewable energy has become a strategic consensus among countries worldwide. To effectively measure and trade the environmental value of green electricity, green certificate trading mechanisms have emerged, becoming a key market tool for incentivizing investment and consumption in renewable energy.

[0003] However, traditional green certificate management systems generally rely on centralized registration, verification, and trading platforms, which have gradually revealed many pain points in practice: insufficient system transparency, lack of public disclosure of certificate issuance, transfer, and cancellation information, and the risk of "double counting" and fraud; high transaction costs, reliance on multi-level intermediaries, cumbersome processes, and low efficiency; limited market liquidity, with regional barriers and standard differences hindering the formation of a unified global market; and complex regulatory audits and difficulties in tracing compliance, posing a huge challenge to compliance verification. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a blockchain-based green certificate transaction management method and system, comprising: Obtain the power generation record data of the seller, create a green certificate equivalent to the amount of power generated based on the power generation record data, and store the green certificate on the blockchain; Identify the power generation gap of the purchaser, and based on the power generation gap, determine the green certificates that correspond to the power generation gap, and identify the sellers corresponding to each green certificate as candidate sellers; Determine the historical price transaction data of the green certificates of the candidate sellers, and make predictions based on the historical price transaction data to obtain the predicted price of the green certificates of each candidate seller. Determine the buyer's expected price range, and select the best seller from the candidate sellers based on the buyer's expected price range and the projected prices of each candidate seller; The system matches buyers with the best sellers, generates a transaction certificate between the buyers and the best sellers based on the matching results, and stores the transaction certificate on the blockchain. Green certificate transactions between buyers and best sellers are managed on the blockchain based on transaction certificates.

[0005] Furthermore, the step of obtaining the seller's power generation record data, creating a green certificate equivalent to the amount of power generated based on the power generation record data, and storing the green certificate on the blockchain includes: Obtain the power generation record data of the seller, verify the power generation record data, and determine the power generation of the seller based on the power generation record data after verification; A green certificate equivalent to the amount of electricity generated by the seller is created and stored on the blockchain.

[0006] Furthermore, the process of determining the power generation gap of the purchaser, identifying green certificates equivalent to the power generation gap based on the gap, and determining the sellers corresponding to each green certificate as candidate sellers includes: Determine the buyer's own electricity consumption and existing green certificates, determine the equivalent existing power generation based on the existing green certificates, and determine the buyer's power generation gap based on its own electricity consumption and existing power generation. Determine the seller's green certificate, determine the equivalent power generation based on the green certificate, and screen green certificates whose power generation is greater than or equal to the power generation gap. Calculate the difference between the power generation equivalent to the selected green certificates and the power generation gap, and determine the sellers corresponding to green certificates with a difference less than a preset threshold as candidate sellers.

[0007] Furthermore, the formula for calculating the power generation gap is as follows: , Where L represents the power generation gap, D represents the electricity consumption, and T represents the existing power generation.

[0008] Furthermore, the process of determining the historical price transaction data of the green certificates of the candidate sellers and making predictions based on the historical price transaction data to obtain the predicted price of the green certificates of each candidate seller includes: Identify the historical price transaction data of the candidate sellers' green certificates and extract the data characteristics of the historical price transaction data; A dataset is constructed based on historical price transaction data and corresponding data characteristics, and the dataset is input into a preset neural network model to build an initial model for transaction price prediction; The dataset is divided into training and test sets according to a preset ratio, and the training and test sets are then input into the initial model for predicting transaction prices. The initial model for predicting transaction prices is trained and tested until it meets the preset convergence conditions, thus obtaining the transaction price prediction model. Based on the transaction price prediction model, predictions are made to obtain the predicted price.

[0009] Furthermore, determining the buyer's expected price range and selecting the best seller from the candidate sellers based on the buyer's expected price range and the predicted prices of each candidate seller includes: Determine the buyer's expected price range and screen candidate sellers whose predicted prices fall within the expected price range; The predicted price and the equivalent power generation of the green certificate for each candidate seller are determined, and the difference between the predicted price and the lowest price in the expected price range is calculated to obtain the first difference. The difference between the equivalent power generation of the green certificate and the power generation gap is calculated to obtain the second difference. The first difference and the second difference are evaluated and values ​​are obtained respectively to obtain the first evaluation value and the second evaluation value. Based on the first evaluation value and the second evaluation value, the comprehensive evaluation value of each candidate seller is determined. The candidate seller with the highest overall evaluation value among all candidate sellers is selected and determined as the best seller among all candidate sellers.

[0010] Furthermore, the formula for calculating the comprehensive evaluation value of the candidate seller is as follows: , Where L is the comprehensive evaluation value of the candidate seller, α is the first preset weight, X is the first evaluation value, β is the second preset weight, and Y is the second evaluation value.

[0011] Furthermore, the process of matching the buyer and the best seller, generating a transaction certificate between the buyer and the best seller based on the matching result, and storing the transaction certificate on the blockchain includes: Identify the nodes on the blockchain where the buyer and the best seller are located, and match the buyer and the best seller based on their respective nodes; Based on the matching results, a transaction certificate is generated between the buyer and the best seller. The transaction certificate includes the transaction hash, transaction timestamp, buyer ID, seller ID, green certificate ID, and transaction price, and is stored on the blockchain.

[0012] Furthermore, the transaction management of green certificate transactions between the buyer and the best seller on the blockchain based on transaction certificates includes: Based on the transaction certificate, ownership of the green certificate of the best seller is transferred to the buyer on the blockchain node; The green certificate of the best seller on the blockchain node will be revoked, and a new green certificate corresponding to the green certificate of the best seller will be created on the blockchain node of the buyer. All information in the green certificate transaction process is stored on the blockchain.

[0013] This invention also provides a blockchain-based green certificate transaction management system, comprising: The acquisition module is used to acquire the power generation record data of the seller, create a green certificate equivalent to the amount of power generated based on the power generation record data, and store the green certificate on the blockchain; The calculation module is used to determine the power generation gap of the buyer, and based on the power generation gap, determine the green certificates equivalent to the power generation gap, and determine the sellers corresponding to each green certificate as candidate sellers. The prediction module is used to determine the historical price transaction data of the green certificates of the candidate sellers, and make predictions based on the historical price transaction data to obtain the predicted price of the green certificates of each candidate seller. The determination module is used to determine the buyer's expected price range and, based on the buyer's expected price range and the predicted prices of each candidate seller, to determine the best seller from the candidate sellers. The generation module is used to match buyers and best sellers, generate a transaction certificate between buyers and best sellers based on the matching results, and store the transaction certificate on the blockchain. The management module is used to manage green certificate transactions between buyers and best sellers on the blockchain based on transaction certificates.

[0014] Compared with existing technologies, the green certificate transaction management method and system based on blockchain proposed in this invention have the following advantages: This invention utilizes IoT devices to automatically collect power generation data and generate digital green certificates that are 1:1 anchored to the power generation. This achieves automated and tamper-proof mapping from physical energy output to digital assets, eliminating the generation of fake certificates at the source and laying the foundation of trust for the entire system. This invention calculates the buyer quota gap and, based on historical on-chain transaction data, uses a machine learning model to predict the reasonable price of the seller's certificate, thus forming a data-driven dynamic pricing mechanism. This invention intelligently matches the buyer's expected price range with the seller's predicted price, automatically selecting the best trading counterparty, greatly reducing the cost of transaction search and negotiation, and optimizing resource allocation; After a successful match, this invention generates a transaction certificate containing all transaction details, which is permanently stored on the blockchain, thus achieving automated, efficient, and zero-default risk in transaction execution. All transactions in this invention leave an immutable and fully traceable transparent record on the blockchain, providing regulatory agencies with a penetrating and real-time regulatory tool, which greatly improves market compliance. In summary, this invention constructs a decentralized, automated, and intelligent green certificate trading ecosystem, which improves the efficiency, transparency, and credibility of green certificate trading, significantly reduces market friction and trust costs, and provides strong infrastructure support for promoting renewable energy consumption and achieving "dual carbon" goals. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the process structure of the blockchain-based green certificate transaction management method in this embodiment of the invention; Figure 2 This is a schematic diagram of the composition of the blockchain-based green certificate transaction management system in an embodiment of the present invention. Detailed Implementation

[0016] The specific embodiments of this application will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0017] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the platform or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0018] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0019] like Figure 1As shown in the embodiments of this application, a blockchain-based green certificate transaction management method is provided, including: S100: obtaining the power generation record data of the seller, creating a green certificate equivalent to the power generation based on the power generation record data, and storing the green certificate on the blockchain; S200: determining the power generation gap of the buyer, determining a green certificate equivalent to the power generation gap based on the power generation gap, and identifying the sellers corresponding to each green certificate as candidate sellers; S300: determining the historical price transaction data of the green certificates of the candidate sellers, and making predictions based on the historical price transaction data to obtain the predicted price of the green certificates of each candidate seller; S400: determining the expected price range of the buyer, and determining the best seller from the candidate sellers based on the expected price range of the buyer and the predicted price of each candidate seller; S500: matching the buyer and the best seller, generating a transaction certificate between the buyer and the best seller based on the matching result, and storing the transaction certificate on the blockchain; S600: managing the green certificate transaction between the buyer and the best seller on the blockchain based on the transaction certificate.

[0020] Furthermore, this invention utilizes IoT devices to automatically collect power generation data and generate digital green certificates pegged 1:1 to power generation, achieving automated and tamper-proof mapping from physical energy output to digital assets. This eliminates the generation of fake certificates at the source, laying the foundation of trust for the entire system. This invention calculates the buyer's quota gap and, based on historical on-chain transaction data, uses a machine learning model to predict the reasonable price of the seller's certificate, forming a data-driven dynamic pricing mechanism. This invention intelligently matches the buyer's expected price range with the seller's predicted price, automatically selecting the best trading partner, greatly reducing transaction search and negotiation costs, and optimizing resource allocation. Upon successful matching, the invention generates a transaction certificate containing all transaction details, which is permanently stored on the blockchain, achieving automated, efficient, and zero-default-risk transaction execution. All transaction activities leave an immutable and fully traceable transparent record on the chain, providing regulatory agencies with a transparent and real-time monitoring tool, greatly improving market compliance. In summary, this invention constructs a decentralized, automated, and intelligent green certificate trading ecosystem, improving the efficiency, transparency, and credibility of green certificate trading, significantly reducing market friction and trust costs, and providing strong infrastructure support for promoting renewable energy consumption and achieving "dual-carbon" goals.

[0021] In an embodiment of this application, a blockchain-based green certificate transaction management method is provided. The method includes: obtaining the power generation record data of the seller, creating a green certificate equivalent to the power generation based on the power generation record data, and storing the green certificate on the blockchain.

[0022] Specifically, by integrating Internet of Things (IoT) sensors and smart meters into renewable energy power generation facilities, raw power generation data is collected in real time. The off-chain data is encrypted and transmitted to the blockchain using a blockchain oracle. The signature, data format compliance, and logical rationality of the data source are verified to ensure that the data has not been tampered with or forged, thereby eliminating the risk of "garbage in, garbage out" from the source. After verification, the amount of electricity generated is automatically calculated based on the verified power generation data, and a green certificate equivalent to the power generation of the seller is created. These newly created certificates are permanently recorded and stored on the distributed ledger of the blockchain, with ownership clearly belonging to the blockchain node address of the power generator. This process establishes end-to-end automated trust from the power source to the digital certificate, eliminating the need for manual verification by third-party institutions and significantly reducing trust costs. Based on the immutability of blockchain, each green certificate is unique and unforgeable, completely resolving the persistent problems of duplicate certificate issuance and fraud in traditional systems. The automated data verification, certificate issuance, and registration processes eliminate paperwork and manual intervention, shortening the issuance cycle from days or weeks to near real-time, significantly reducing operating costs. Power generation data verification credentials and certificate creation transactions are permanently recorded on the blockchain, providing regulatory agencies, auditors, and market participants with absolutely credible and fully traceable audit trails, greatly enhancing market transparency and compliance.

[0023] In an embodiment of this application, a blockchain-based green certificate transaction management method is provided. The method involves determining the power generation gap of a buyer, identifying green certificates equivalent to the power generation gap based on the gap, and identifying the sellers corresponding to each green certificate as candidate sellers. This includes: determining the buyer's own electricity consumption and existing green certificates; determining the equivalent existing power generation based on the existing green certificates; and determining the buyer's power generation gap based on the buyer's own electricity consumption and existing power generation; determining the seller's green certificates; determining the equivalent power generation based on the green certificates; and screening green certificates whose power generation is greater than or equal to the power generation gap; calculating the difference between the equivalent power generation of the screened green certificates and the power generation gap; and identifying the sellers corresponding to green certificates whose difference is less than a preset threshold as candidate sellers.

[0024] Specifically, all green certificates of sellers in the "for sale" state on the blockchain are scanned and converted into equivalent power generation. Based on the buyer's demand gap, a preliminary screening is conducted, retaining only sellers whose certificates have equivalent power generation greater than or equal to the gap, ensuring that they are capable of independently meeting all the buyer's needs. To further optimize matching accuracy and avoid resource waste, a preset threshold is introduced for a second fine-tuning screening. The difference between the power generation of each candidate certificate and the buyer's gap is calculated, and sellers whose difference is less than the threshold (i.e., whose available power generation is closest to the buyer's demand) are identified as the final candidate sellers. This step automatically queries and calculates on-chain data, transforming vague purchasing needs into precise, quantifiable numerical gaps. This eliminates errors and inefficiencies in manual calculations, making procurement objectives extremely clear. The process is no longer a simple manual search and price comparison, but a two-stage screening algorithm automatically executed by smart contracts. The first stage ensures "capability matching," and the second stage ensures "economic matching," efficiently identifying the most suitable trading partners from a massive market. By controlling the matching accuracy through thresholds, it directly locks in sellers whose supply and demand are most perfectly matched, reducing the complexity of subsequent negotiations and avoiding transaction failures or splitting problems caused by excessive quantity differences, significantly improving market liquidity and transaction efficiency. The logical rules of the entire calculation and screening process are openly and transparently encoded in smart contracts, and all decision-making is based on trusted on-chain data. This not only provides powerful data-driven decision support for both buyers and sellers but also makes the matching results completely transparent and verifiable to regulatory agencies and auditors.

[0025] In an embodiment of this application, a blockchain-based green certificate transaction management method is provided, wherein the formula for calculating the power generation gap is: , Where L represents the power generation gap, D represents the electricity consumption, and T represents the existing power generation.

[0026] Furthermore, the step of determining the historical price transaction data of the candidate sellers' green certificates and making predictions based on the historical price transaction data to obtain the predicted price of each candidate seller's green certificate includes: determining the historical price transaction data of the candidate sellers' green certificates and extracting the data features of the historical price transaction data; constructing a dataset based on the historical price transaction data and corresponding data features, and inputting the dataset into a preset neural network model to construct an initial model for predicting transaction prices; dividing the dataset into a training set and a test set according to a preset ratio, and inputting the training set and the test set into the initial model for predicting transaction prices; training and testing the initial model for predicting transaction prices until the initial model for predicting transaction prices meets a preset convergence condition to obtain a transaction price prediction model, and making predictions based on the transaction price prediction model to obtain the predicted price.

[0027] Specifically, all historical transaction data of candidate sellers' green certificates are reliably obtained from an immutable blockchain distributed ledger. Based on this pure and trustworthy raw data, data feature engineering is further performed to extract key features for prediction, thus transforming the raw data into predictive feature vectors. The labeled historical data and its features are constructed into a high-quality time-series dataset and input into a pre-defined neural network model to build an initial model for transaction price prediction. This dataset is divided into a training set and a test set according to a pre-defined ratio (e.g., 8:2). The training set is used to iteratively train the initial model multiple times, adjusting its internal weight parameters to learn complex nonlinear patterns in historical price fluctuations. The test set is used to independently evaluate the generalization ability and prediction accuracy of the trained model. Model training continues until its loss function value converges to a pre-defined threshold and the prediction accuracy on the test set meets the requirements, ultimately resulting in a reliable transaction price prediction model. Using this model, a forward-looking prediction of the future price of candidate sellers' green certificates can be made, outputting a scientific and objective predicted price. This step abandons the traditional, crude pricing model that relies on human experience or simple historical averages. By using neural network models to mine deep patterns in massive amounts of historical data, it can more accurately reflect the potential market value of certificates, including their own attributes, market supply and demand, and the impact of macroeconomic trends, making pricing more scientific and reasonable. Based on publicly available and tamper-proof historical transaction data, the entire process is algorithmically transparent, providing all market participants with a consistent and reliable price discovery benchmark. This reduces negotiation friction and market manipulation caused by information asymmetry, while also giving both buyers and sellers the ability to predict future price trends.

[0028] In embodiments of this application, a blockchain-based green certificate transaction management method is provided. The method involves determining the buyer's expected price range and, based on the buyer's expected price range and the predicted prices of each candidate seller, determining the best seller from among the candidate sellers. This includes: determining the buyer's expected price range and filtering candidate sellers whose predicted prices fall within the expected price range; determining the predicted price of each candidate seller and the equivalent power generation for the green certificate, and calculating the difference between the predicted price and the lowest price within the expected price range to obtain a first difference, and calculating the difference between the equivalent power generation for the green certificate and the power generation gap to obtain a second difference; evaluating the first difference and the second difference to obtain a first evaluation value and a second evaluation value, and determining a comprehensive evaluation value for each candidate seller based on the first evaluation value and the second evaluation value; and selecting the candidate seller with the highest comprehensive evaluation value from among the candidate sellers as the best seller among all candidate sellers.

[0029] Specifically, the system obtains the buyer's expected price range (e.g., 90-110 yuan / certificate) and initially filters out all candidate sellers whose predicted prices fall within this range, ensuring that their prices are within the buyer's acceptable range. For each selected candidate, two core optimization objectives are extracted: 1. The first difference between its predicted price and the lower limit of the buyer's expected range (price advantage); 2. The second difference between its certificate-equivalent power generation and the buyer's demand gap (power matching degree). These two differences with different dimensions are standardized and evaluated (e.g., the difference is converted into a score between 0 and 1; the smaller the first difference, the higher the price score; the smaller the second difference, the higher the power matching score). The two evaluation values ​​are combined into a comprehensive evaluation value through pre-set weights, and the candidate seller with the highest comprehensive evaluation value is automatically selected as the best seller. This step overcomes the limitations of the single-dimensional "lowest bidder wins" approach in traditional transactions, simultaneously optimizing economics (price) and suitability (electricity matching). It intelligently selects partners whose costs and supply best match the buyer's needs, maximizing overall benefits. By prioritizing sellers whose power generation and demand gaps are closest, it significantly reduces the likelihood of one party needing to re-enter the market for piecemeal transactions (e.g., when the seller's power generation far exceeds demand and needs to be split for sale, or when the buyer needs to purchase from multiple sources). This simplifies the transaction structure, reduces negotiation costs and operational risks, and improves the overall transaction experience for both buyers and sellers. This intelligent matching mechanism facilitates high-quality transactions faster and more accurately, reducing asset mismatch and market friction. It enables green certificates to flow more efficiently to the buyers with the highest valuation and the best matching demand, thereby significantly improving the resource allocation efficiency and asset liquidity of the entire market.

[0030] In an embodiment of this application, a blockchain-based green certificate transaction management method is provided, wherein the formula for calculating the comprehensive evaluation value of the candidate seller is as follows: , Where L is the comprehensive evaluation value of the candidate seller, α is the first preset weight, X is the first evaluation value, β is the second preset weight, and Y is the second evaluation value.

[0031] In embodiments of this application, a blockchain-based green certificate transaction management method is provided. The method involves matching the buyer and the best seller, generating a transaction certificate between the buyer and the best seller based on the matching result, and storing the transaction certificate on the blockchain. The method includes: determining the nodes of the buyer and the best seller on the blockchain, and matching the buyer and the best seller based on their respective nodes; generating a transaction certificate between the buyer and the best seller based on the matching result; the transaction certificate including a transaction hash, a transaction timestamp, a buyer ID, a seller ID, a green certificate ID, and a transaction price; and storing the transaction certificate on the blockchain.

[0032] Specifically, by querying the blockchain network, the unique blockchain nodes corresponding to the buyer and the best seller are accurately located. Based on this node information, the two parties are directly matched and connected via a peer-to-peer (P2P) network communication protocol, establishing a secure and direct transaction channel. After a successful match, the transaction is automatically executed. The contract atomically swaps the buyer's payment with the seller's green certificate, ensuring that both are transferred simultaneously and eliminating the risk of default by either party. After the transaction is confirmed by the blockchain network, a detailed transaction certificate is automatically generated. This certificate is essentially an immutable digital credential. Key fields include: transaction hash (the unique fingerprint of the transaction), timestamp (the exact time the transaction occurred), buyer and seller IDs (their blockchain addresses), green certificate ID (the unique number of the traded asset), and transaction price. This transaction certificate is broadcast to the entire network and, after being verified by the consensus mechanism, is permanently stored on the blockchain's distributed ledger, becoming a newly added and undeletable transaction record. This step achieves "transaction as settlement," with the transfer of ownership of funds and assets completed instantly and automatically, without any third-party guarantees. This completely solves the credit risk caused by the asynchronous "cash on delivery" in traditional transactions and immediately completes the final confirmation of asset ownership on the blockchain. The generated transaction certificate contains all core elements and uses its transaction hash as a unique index, linking it with the certificate generation records of previous steps and subsequent cancellation records to form a complete and verifiable full-lifecycle audit trail, providing an absolutely reliable data foundation for regulatory, compliance verification, and ESG reporting. The entire execution and evidence storage process is code-driven, requiring no human intervention, reducing transaction confirmation and settlement time from several days in traditional markets to minutes or even seconds. The transaction certificate is completely transparent to authorized nodes, greatly enhancing market credibility. Transaction data is not stored in a centralized server database but is encrypted and distributed across numerous nodes globally, making it extremely difficult to tamper with or destroy, effectively resisting network attacks and data leakage risks, and ensuring the permanence and reliability of transaction history.

[0033] In the embodiments of this application, a blockchain-based green certificate transaction management method is provided. The method manages the green certificate transaction between the buyer and the best seller on the blockchain based on the transaction certificate, including: transferring the ownership of the best seller's green certificate to the buyer's node on the blockchain based on the transaction certificate; canceling the best seller's green certificate on the blockchain node, and creating a new green certificate corresponding to the best seller's green certificate on the buyer's blockchain node; and storing all information in the green certificate transaction process on the blockchain.

[0034] Specifically, based on the previously generated, blockchain-confirmed transaction certificate as the sole legal authorization credential, the ownership change clause in the smart contract is triggered. The ownership field of the green certificate, originally belonging to the best seller's node and recorded on the blockchain, is officially updated to the buyer's blockchain node address, completing the on-chain transfer of ownership in a legal sense. To ensure the uniqueness of environmental rights, the seller's original certificate is cancelled, not by deleting the data, but by marking its status as "used" through the smart contract, permanently removing it from market circulation. At the same time, to clearly record the flow of assets and reflect it in the buyer's account, a corresponding new ownership record is created on the buyer's blockchain node. This new certificate is completely consistent with the core attributes of the original certificate (such as power generation, energy type, and time), except for the owner field, thus clearly demonstrating that the buyer now owns the environmental rights to this portion of green electricity. From the initiation and execution of the ownership change to the creation of the new certificate, all operational information in the entire process is treated as new transaction data. After being verified by the consensus mechanism, it is completely and sequentially recorded on the blockchain's distributed ledger, forming an immutable final credential. This step, based on transaction certificates, fully automates the ownership transfer process, eliminating human intervention and errors. Once confirmed by the blockchain network, the transfer is irrevocable and permanently valid, providing absolute legal certainty for both parties. The "one-cancel-create" mechanism is key to ensuring the uniqueness of environmental rights. Canceling the original certificate ensures that the environmental value generated by a unit of green electricity can only be declared and sold once, technically eliminating the possibility of the same unit of green electricity being repeatedly used for emission reduction commitments or environmental claims, thus maintaining the integrity of the market. The on-chain information throughout the entire process makes the entire lifecycle of green electricity—from its generation, certification, multiple transactions to its final cancellation—completely transparent and traceable. Any regulatory agency or auditor can easily verify the final ownership and historical flow of any green certificate, greatly reducing compliance and audit costs. The clear, reliable, and efficient ownership transfer mechanism is the foundation of high-risk liquidity, making green certificates a highly trustworthy and easily tradable digital asset, providing a solid technical guarantee for developing innovative green finance products such as pledging and securitization.

[0035] like Figure 2As shown in the embodiments of this application, a blockchain-based green certificate transaction management system is provided, comprising: an acquisition module, used to acquire the power generation record data of the seller, create a green certificate equivalent to the power generation based on the power generation record data, and store the green certificate on the blockchain; a calculation module, used to determine the power generation gap of the buyer, and determine a green certificate equivalent to the power generation gap based on the power generation gap, and determine the sellers corresponding to each green certificate as candidate sellers; a prediction module, used to determine the historical price transaction data of the green certificates of the candidate sellers, and make predictions based on the historical price transaction data to obtain the predicted price of the green certificates of each candidate seller; a determination module, used to determine the expected price range of the buyer, and determine the best seller from the candidate sellers based on the expected price range of the buyer and the predicted price of each candidate seller; a generation module, used to match the buyer and the best seller, generate a transaction certificate between the buyer and the best seller based on the matching result, and store the transaction certificate on the blockchain; and a management module, used to manage the green certificate transaction between the buyer and the best seller on the blockchain based on the transaction certificate.

[0036] In summary, this invention provides a blockchain-based method and system for managing green certificate transactions, comprising: creating green certificates equivalent to the amount of electricity generated based on the power generation record data of the seller, and storing them on the blockchain; determining the power generation gap of the buyer, and determining green certificates equivalent to the power generation gap to identify corresponding candidate sellers; determining the historical price transaction data of the candidate sellers' green certificates, and predicting the predicted price of each candidate seller's green certificate based on the historical price transaction data; determining the buyer's expected price range, and determining the optimal seller based on the expected price range and the predicted prices of each candidate seller; matching the buyer and the optimal seller, generating transaction certificates based on the matching results, and storing them on the blockchain; and managing green certificate transactions on the blockchain based on the transaction certificates. This invention improves the efficiency, transparency, and credibility of green certificate transactions, and significantly reduces market friction and trust costs.

[0037] Finally, it should be noted that those skilled in the art can obviously make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims and their equivalents, this invention also intends to include these modifications and variations.

[0038] The above description is merely one embodiment of the present invention, and should not be construed as limiting the scope of the invention. Any structural changes made based on the present invention, as long as they do not depart from the essence of the invention, should be considered as falling within the protection scope of the present invention and subject to its restrictions. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process and related descriptions of the platform described above can be referred to the corresponding processes in the foregoing platform embodiments, and will not be repeated here.

[0039] The term "comprising" or any other similar term is intended to cover non-exclusive inclusion, such that a process, platform, article, or device / platform that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to those processes, platforms, articles, or devices / platforms.

[0040] The technical solutions of the present invention have been described in conjunction with the accompanying drawings and further embodiments. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to closely related technical features, and the technical solutions resulting from such changes or substitutions will all fall within the scope of protection of the present invention.

[0041] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention.

Claims

1. A blockchain-based method for managing green certificate transactions, characterized in that, include: Obtain the power generation record data of the seller, create a green certificate equivalent to the amount of power generated based on the power generation record data, and store the green certificate on the blockchain; Identify the power generation gap of the purchaser, and based on the power generation gap, determine the green certificates that correspond to the power generation gap, and identify the sellers corresponding to each green certificate as candidate sellers; Determine the historical price transaction data of the green certificates of the candidate sellers, and make predictions based on the historical price transaction data to obtain the predicted price of the green certificates of each candidate seller. Determine the buyer's expected price range, and select the best seller from the candidate sellers based on the buyer's expected price range and the projected prices of each candidate seller; The system matches buyers with the best sellers, generates a transaction certificate between the buyers and the best sellers based on the matching results, and stores the transaction certificate on the blockchain. Green certificate transactions between buyers and best sellers are managed on the blockchain based on transaction certificates.

2. A blockchain-based green certificate transaction management method according to claim 1, characterized in that, The process of obtaining the power generation record data of the seller, creating a green certificate based on the power generation record data that corresponds to the amount of power generated, and storing the green certificate on the blockchain includes: Obtain the power generation record data of the seller, verify the power generation record data, and determine the power generation of the seller based on the power generation record data after verification; A green certificate equivalent to the amount of electricity generated by the seller is created and stored on the blockchain.

3. A blockchain-based green certificate transaction management method according to claim 2, characterized in that, The process of determining the power generation gap of the purchaser, identifying green certificates equivalent to the power generation gap based on the power generation gap, and identifying the sellers corresponding to each green certificate as candidate sellers includes: Determine the buyer's own electricity consumption and existing green certificates, determine the equivalent existing power generation based on the existing green certificates, and determine the buyer's power generation gap based on its own electricity consumption and existing power generation. Determine the seller's green certificate, determine the equivalent power generation based on the green certificate, and screen green certificates whose power generation is greater than or equal to the power generation gap. Calculate the difference between the power generation equivalent to the selected green certificates and the power generation gap, and determine the sellers corresponding to green certificates with a difference less than a preset threshold as candidate sellers.

4. A blockchain-based green certificate transaction management method according to claim 3, characterized in that, The formula for calculating the power generation gap is: ， Where L represents the power generation gap, D represents the electricity consumption, and T represents the existing power generation.

5. A blockchain-based green certificate transaction management method according to claim 3, characterized in that, The process of determining the historical price transaction data of green certificates for candidate sellers and making predictions based on this historical price transaction data to obtain the predicted price of green certificates for each candidate seller includes: Identify the historical price transaction data of the candidate sellers' green certificates and extract the data characteristics of the historical price transaction data; A dataset is constructed based on historical price transaction data and corresponding data characteristics, and the dataset is input into a preset neural network model to build an initial model for transaction price prediction; The dataset is divided into training and test sets according to a preset ratio, and the training and test sets are then input into the initial model for predicting transaction prices. The initial model for predicting transaction prices is trained and tested until it meets the preset convergence conditions, thus obtaining the transaction price prediction model. Based on the transaction price prediction model, predictions are made to obtain the predicted price.

6. A blockchain-based green certificate transaction management method according to claim 5, characterized in that, The process of determining the buyer's expected price range and selecting the best seller from among the candidate sellers based on the buyer's expected price range and the predicted prices of each candidate seller includes: Determine the buyer's expected price range and screen candidate sellers whose predicted prices fall within the expected price range; The predicted price and the equivalent power generation of the green certificate for each candidate seller are determined, and the difference between the predicted price and the lowest price in the expected price range is calculated to obtain the first difference. The difference between the equivalent power generation of the green certificate and the power generation gap is calculated to obtain the second difference. The first difference and the second difference are evaluated and values ​​are obtained respectively to obtain the first evaluation value and the second evaluation value. Based on the first evaluation value and the second evaluation value, the comprehensive evaluation value of each candidate seller is determined. The candidate seller with the highest overall evaluation value among all candidate sellers is selected and determined as the best seller among all candidate sellers.

7. A blockchain-based green certificate transaction management method according to claim 6, characterized in that, The formula for calculating the comprehensive evaluation value of the candidate seller is as follows: ， Where L is the comprehensive evaluation value of the candidate seller, α is the first preset weight, X is the first evaluation value, β is the second preset weight, and Y is the second evaluation value.

8. A blockchain-based green certificate transaction management method according to claim 6, characterized in that, The process of matching the buyer and the best seller, generating a transaction certificate between the buyer and the best seller based on the matching result, and storing the transaction certificate on the blockchain includes: Identify the nodes on the blockchain where the buyer and the best seller are located, and match the buyer and the best seller based on their respective nodes; Based on the matching results, a transaction certificate is generated between the buyer and the best seller. The transaction certificate includes the transaction hash, transaction timestamp, buyer ID, seller ID, green certificate ID, and transaction price, and is stored on the blockchain.

9. A blockchain-based green certificate transaction management method according to claim 8, characterized in that, The transaction management of green certificate transactions between the buyer and the best seller based on transaction certificates on the blockchain includes: Based on the transaction certificate, ownership of the green certificate of the best seller is transferred to the buyer on the blockchain node; The green certificate of the best seller on the blockchain node will be revoked, and a new green certificate corresponding to the green certificate of the best seller will be created on the blockchain node of the buyer. All information in the green certificate transaction process is stored on the blockchain.

10. A blockchain-based green certificate transaction management system, characterized in that, include: The acquisition module is used to acquire the power generation record data of the seller, create a green certificate equivalent to the amount of power generated based on the power generation record data, and store the green certificate on the blockchain; The calculation module is used to determine the power generation gap of the buyer, and based on the power generation gap, determine the green certificates equivalent to the power generation gap, and determine the sellers corresponding to each green certificate as candidate sellers. The prediction module is used to determine the historical price transaction data of the green certificates of the candidate sellers, and make predictions based on the historical price transaction data to obtain the predicted price of the green certificates of each candidate seller. The determination module is used to determine the buyer's expected price range and, based on the buyer's expected price range and the predicted prices of each candidate seller, to determine the best seller from the candidate sellers. The generation module is used to match buyers and best sellers, generate a transaction certificate between buyers and best sellers based on the matching results, and store the transaction certificate on the blockchain. The management module is used to manage green certificate transactions between buyers and best sellers on the blockchain based on transaction certificates.

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