CN116596671A - Trading method of blockchain carbon trading system considering benefits of campus enterprises - Google Patents

Trading method of blockchain carbon trading system considering benefits of campus enterprises Download PDF

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CN116596671A
CN116596671A CN202310574794.1A CN202310574794A CN116596671A CN 116596671 A CN116596671 A CN 116596671A CN 202310574794 A CN202310574794 A CN 202310574794A CN 116596671 A CN116596671 A CN 116596671A
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carbon
transaction
enterprise
price
blockchain
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王凌晨
杨涛
王瑜
胡波
孙耀杰
郭懿涵
朱子钰
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Fudan University
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Abstract

The invention relates to a trading method of a blockchain carbon trading system for taking benefits of a campus enterprise into account, wherein a carbon track recording module is used for recording carbon data measured by a plurality of sensors, and a carbon emission management module adopts distributed carbon points and green points as initial values of the enterprise; the carbon price prediction module includes: acquiring carbon transaction price data, and carrying out normalization pretreatment; constructing a long-short memory neural network and performing model training; inputting historical carbon price data in the model to predict carbon transaction price, and giving initiative to enterprises to select an optimal transaction strategy; the carbon transaction management module includes: acquiring enterprise data and distributing initial carbon coins; reporting a carbon transaction plan and encrypting information by an enterprise; conducting carbon transaction auction among enterprises; and after the auction is finished, each enterprise settles the transaction and updates the account. Aiming at a park, the invention provides a decentralised transaction mode for enterprises, realizes point-to-point transaction by using a blockchain, improves transaction efficiency, enhances data transparency, promotes energy conservation and emission reduction of the enterprises, and realizes sustainable development.

Description

Trading method of blockchain carbon trading system considering benefits of campus enterprises
Technical Field
The invention belongs to the technical field of carbon transaction, and particularly relates to a transaction method of a blockchain carbon transaction system considering benefits of a campus enterprise.
Background
With the increasing severity of global warming and climate change problems, the problem of carbon emissions is becoming more and more of a concern. To address this problem, more and more organizations and governments are beginning to employ carbon trade ways to reduce carbon emissions. However, the traditional carbon transaction has the problems of asymmetric and opaque information, so that the market price is inaccurate, fairness and fairness are lost, and enterprises are difficult to adjust self transaction decisions; the carbon trade market also has a plurality of intermediaries and complex trade processes, which results in high trade cost and reduces the enthusiasm of enterprises to participate in carbon trade. In addition, transaction data is easy to tamper, so that the integrity of enterprises can be affected to a certain extent, and the healthy and stable development of markets is not facilitated.
Meanwhile, a mode of setting a centralization mechanism is adopted in a park to conduct carbon transaction, and a certain transaction fee needs to be charged, so that the transaction cost can be increased, and the transaction efficiency and competitiveness are reduced; secondly, the management and maintenance are inconvenient, and the use cost of enterprise users is increased; the market is also lack of flexibility, so that the diversity and application prospect of the trade are limited, and the market development and innovation are not facilitated.
Disclosure of Invention
In order to solve the above problems, the present invention provides a blockchain carbon transaction system and method that takes into account benefits of a campus enterprise, and uses a plurality of characteristics of blockchains, including decentralization, transparency, security, digital assets, smart contracts, etc., to make carbon transactions more efficient, fair and reliable. Specifically, the invention adopts the following technical scheme: the invention provides a trading method of a blockchain carbon trading system considering benefits of a campus enterprise, wherein the blockchain carbon trading system comprises the following steps: the system comprises a carbon track recording module, a carbon emission management module, a carbon price prediction module and a carbon transaction management module;
the carbon track recording module is used for recording carbon data respectively measured by the ground sensor and the airborne sensor and transmitting the carbon data to the blockchain platform for storage;
the carbon emission management module is used for distributing carbon points to enterprises so as to quantify carbon emission intensity, further distributing green points according to the carbon points to serve as transaction varieties in carbon transaction, and simultaneously carrying out carbon emission credit clearing;
the carbon price prediction module is used for predicting the carbon transaction price in the transaction period and giving initiative to enterprises so as to select an optimal transaction strategy;
the carbon transaction management module is used for distributing carbon coins, trading green points on a blockchain by utilizing the carbon coins, and carrying out uplink storage on transaction data;
the transaction method comprises the following specific steps:
(1) Arranging a ground sensor at a main discharge port of an enterprise, cruising above the enterprise at regular time by carrying an onboard sensor on an unmanned aerial vehicle, carrying out hash and encryption processing on all carbon data to obtain a hash value and a ciphertext, and uploading the hash value and the ciphertext to a block chain platform;
(2) The enterprise park adopts a double-integration mode to endow an enterprise with an initial value to realize carbon emission management, wherein the double-integration is carbon integration and green integration;
the carbon integral is determined by the power consumption, the power generation amount, the electric carbon emission coefficient and the carbon data of an enterprise, and the carbon data is used as calibration to verify whether the carbon integral of the enterprise is reasonable;
the calculation formula of the carbon integral is as follows:
P c ＝[(E use -E produce )×c]×α
wherein: e (E) use For enterprise power consumption, E produce The power generation capacity of enterprises is achieved, c is an electric carbon emission coefficient, and alpha is a scale factor;
(3) Prediction of carbon price
(3.1) acquiring carbon transaction price sample data, carrying out normalization pretreatment on the carbon transaction price sample data, and dividing the carbon transaction price sample data into a training set, a verification set and a test set;
(3.2) constructing a long-short memory neural network (LSTM), performing model training on the LSTM by using a training set, performing verification by using a verification set, and outputting the precision of the LSTM;
(3.3) predicting on the test dataset using the trained LSTM model, and outputting the carbon trade price;
(4) Performing carbon transaction management
(4.1) acquiring enterprise data, determining an initial carbon coin value by an administrator according to the power consumption of the enterprise at peak and valley, and performing auction transaction on a blockchain platform by a buyer and a seller through the carbon coin;
the calculation formula of the initial carbon coin is as follows:
C＝E peak ×δ 1 +E valley ×δ 2 ，δ 1 ＜δ 2
wherein C is a carbon coin, E peak And E is valley To purchase electricity quantity delta at peak-valley 1 And delta 2 Is a weight coefficient;
and (4.2) reporting the carbon transaction plan, encrypting the two-level information, uploading the two-level information to the blockchain by using a private key signature, and formulating an access strategy according to the first-level information by using an intelligent contract. Automatically executing the access policy through the intelligent contract, wherein the buyer enterprise can only check the second level information of the seller enterprise related to the specific transaction information when the buyer enterprise meets the access policy of the seller enterprise;
(4.3) conducting carbon transaction auction among enterprises, encrypting a piece of bidding information containing fields such as time stamp, transaction serial number, transaction amount and the like according to a seller public key after a buyer has transaction requirements and meets an access strategy, signing by using a private key of the buyer, and sending the bidding information to the seller; the seller decrypts the bid information before the trade expiration time, selects the most satisfactory bidder signature and broadcasts the bid information to the buyer, and can iterate the bid information in the trade time until the auction is finished, and the buyer can not bid any more after the auction is finished;
and (4.4) finishing the auction, calling the intelligent contract by the seller to record transaction information on the blockchain, settling the transaction of each enterprise, and updating the account.
In the invention, the green integral in the step (2) is determined by carbon integral and enterprise carbon emission reduction behaviors, and certain green integral can be replaced by adjusting the energy structure and increasing the carbon emission reduction investment;
the calculation formula of the green integral is as follows:
P green ＝A q -P c +∑P other
wherein P is green For green integral, A q A threshold value initially set for the transaction, the threshold value varying with quarter change, P c Is carbon integral, P other Is the carbon emission reduction behavior of enterprises.
In the invention, the clearing of the track is carried out once in each quarter in the step (2), and an administrator in the blockchain platform carries out the clearing according to the carbon integral degree issued in the planning period;
the carbon credit for the clearance needs to be unregistered in the carbon trading system while giving the business not fulfilling the clearance obligation a strict penalty measure.
In the invention, the last week of each month is set as the trading week in the park in the step (3), and the predicted carbon trading price of the next week is output by inputting the market carbon trading price of the last three weeks of the month in the trained model;
the enterprises select the most appropriate trading strategy according to the prediction of the carbon trading price and the self-demand of the enterprises, and the trading strategy is used for maximizing the benefits of the enterprises in the park.
In the invention, the predicted carbon price output by the carbon price prediction module is the real market price, and the conversion ratio of the predicted carbon price to the carbon coin distributed by an enterprise is 1:1.
in the present invention, the two levels of information in step (4.2) include:
the first level information includes enterprise type preference, green integral value lower limit, carbon integral value lower limit, and the like;
the second level of information includes sales plan amount, minimum/maximum price, auction deadline, business address, etc.
In the present invention, the hash chain formed by the transaction in step (4.4) includes:
the first part of seller encrypts the uploaded two-level information and signs the private key;
the second part of the buyer bidding information comprises a time stamp, a transaction serial number, a transaction amount and other fields and a buyer private key signature;
the third portion of the sellers determines the private key signature after the transaction party.
In the present invention, in the step (1), the onboard sensor is a carbon dioxide sensor mounted on an unmanned aerial vehicle.
The invention has the beneficial effects that:
according to the blockchain carbon transaction system and method for considering benefits of the campus enterprises, which are provided by the invention, the blockchain system is built by adopting the modules of carbon track recording, carbon emission management, carbon price prediction, carbon transaction management and the like, all carbon tracks of the campus enterprises are uplinked, and the data transparency and management efficiency are improved. The double-point mode is adopted to endow double points with more functions, so that the attractive force of transaction is enhanced, and meanwhile, the long and short memory neural network algorithm is adopted to predict the market carbon price, so that enterprises are helped to select the optimal transaction strategy, such as changing the energy utilization structure, reducing carbon emission and the like. The peak-valley electricity consumption is used for distributing initial carbon coins, so that enterprises are led to change electricity consumption habits, and electricity consumption load transfer is realized. Meanwhile, an asymmetric encryption algorithm is adopted in the system to ensure data security, and the form of setting an access strategy and a three-time signature is adopted to improve the enthusiasm of each enterprise for double-integration acquisition. The method can effectively improve the enthusiasm of enterprises for participating in carbon transaction, promote green sustainable development of parks, reduce carbon emission, realize point-to-point transaction of enterprises, greatly improve transaction efficiency and realize traceability of transactions.
Drawings
FIG. 1 is a schematic diagram of a blockchain carbon trading system in consideration of benefits of a campus enterprise according to embodiment 1 of the present invention;
FIG. 2 is a flowchart of a method for predicting price of carbon transaction based on LSTM algorithm provided in embodiment 1 of the present invention;
FIG. 3 is a graph of predicted price results of carbon transactions based on LSTM algorithm provided in example 1 of the present invention;
FIG. 4 is a flowchart of a blockchain carbon trading method that accounts for campus enterprise benefits according to embodiment 1 of the present invention;
fig. 5 is a schematic diagram of a hash chain formed in a transaction auction process according to embodiment 1 of the present invention.
Detailed Description
Embodiments of a blockchain carbon trading system and method that accounts for campus enterprise benefits in accordance with the present invention are described in detail below with reference to the accompanying drawings.
Example 1:
FIG. 1 is a schematic diagram of a block chain carbon trading system that accounts for campus enterprise benefits according to an embodiment of the present invention.
As shown in fig. 1, a blockchain carbon trading system and method for considering benefits of a campus enterprise according to an embodiment of the present invention includes: the system comprises a carbon track recording module, a carbon emission management module, a carbon price prediction module and a carbon transaction management module;
the carbon track recording module is used for recording carbon data measured by the multiple sensors and transmitting the carbon data to the blockchain platform for storage.
The carbon emission management module is used for distributing carbon points to enterprises so as to quantify carbon emission intensity, further distributing green points according to the carbon points to serve as transaction varieties, and simultaneously carrying out carbon emission credit clearing.
The carbon price prediction module is used for predicting the carbon transaction price in the transaction period and giving initiative to enterprises to select the optimal transaction strategy.
The carbon transaction management module is used for distributing carbon coins, the carbon coins are used as transaction media to conduct carbon transactions of buyers and sellers in the blockchain, the carbon coins are needed to be used for purchasing green integration, and transaction data are stored in a uplink mode.
Further, the carbon track recording module includes:
the carbon data is commonly measured by a ground sensor and an on-board sensor. And fusing the measured carbon data by using an atmospheric transmission model, a transport model based on the Lagrangian principle and a Bayesian inversion algorithm.
The ground sensor is arranged at a main discharge port of an enterprise, the unmanned aerial vehicle carries the carbon dioxide sensor to cruise above the enterprise at regular time, all data are hashed and encrypted to obtain a hash value and a ciphertext, and the hash value and the ciphertext are uploaded to the blockchain. And labeling the carbon track of the park enterprise by using a block chain technology. The decentralization feature of blockchain technology ensures that all participants can see and monitor the carbon trajectory information on the platform, thereby creating a transparent, trusted system. In this way, the underlying data is provided for subsequent carbon transactions.
Further, the carbon emission management module includes:
the park adopts a double-integral mode to endow the enterprise with initial values, and double-integral is carbon integral and green integral.
The carbon integral is determined by the power consumption, the power generation capacity, the electric carbon emission coefficient and the carbon data of the enterprise. The carbon historical data of the enterprises are indirectly calculated through the electricity purchasing quantity of the enterprises in the park, the carbon historical data are converted into carbon points, meanwhile, the carbon data are used as calibration, and whether the carbon points of the enterprises are reasonable or not is verified.
The carbon integral calculation formula is as follows:
P c ＝[(E use -E produce )×c]×α
wherein E is use For enterprise power consumption, E produce And c is an electric carbon emission coefficient, and alpha is a scale factor.
Further, the trade varieties in the carbon trade system are green credits and are determined by carbon credits and enterprise carbon emission reduction behaviors. The carbon emission reduction behavior comprises the steps of adjusting an energy structure, increasing carbon emission reduction investment, and actively reporting and providing a proof in a system after an enterprise has corresponding emission reduction behaviors, wherein a manager can issue a certain green integral after verification.
The calculation formula of the green integral is as follows:
P green ＝A q -P c +∑P other
wherein P is green For green integral, A q Threshold initially set for transaction (threshold varies from quarter to quarter, fourth quarter threshold is minimum), P c Is carbon integral, P other Is the carbon emission reduction behavior of enterprises.
Further, the implementation clearance payment in the carbon emission management module is specifically as follows:
once per quarter for the clearing of the performance, an administrator in the blockchain platform performs the clearing according to the carbon credits issued in the planning cycle.
The carbon credit for the clearance needs to be unregistered in the carbon trading system while giving the business not fulfilling the clearance obligation a strict penalty measure.
FIG. 2 is a flowchart of a method for predicting a price of a carbon transaction based on an LSTM algorithm according to an embodiment of the present invention;
as shown in fig. 2, the carbon price prediction module includes the steps of:
step S1, acquiring carbon transaction price sample data, carrying out normalization pretreatment on the data, normalizing the data to be in the range of (0, 1), and dividing 80% of the data into a training set, 10% into a verification set and 10% into a test set.
Step S2, constructing a long-short memory neural network (LSTM), setting the feature number of input data to be 4, setting the number of hidden neural network units to be 200, setting the initial learning rate to be 0.001 and setting the batch size to be 50, and training; training is carried out on the training set by using the training set, verification is carried out by using the verification set, and meanwhile, the mean square error of the training set is output to check the effect.
And S3, predicting on the test data set by using the trained LSTM model, and outputting the carbon transaction price.
FIG. 3 is a graph of a predicted price for a carbon transaction based on the LSTM algorithm according to an embodiment of the present invention.
As shown in fig. 3, according to the method provided by the carbon price prediction module of the present invention, the guangdong carbon quota data is specifically selected for exemplary study, the data is obtained from the guangzhou carbon emission rights exchange center, and the total is 1989 data from day 19 in 12 in 2013 to day 31 in 2023. Historical carbon price data is input in this example and forecast data is output. Referring to fig. 3, which shows real data of carbon prices for the last year and predicts carbon prices for the last two months, the mean square error is 0.0021 after 300 iterations.
In the method, the last week of each month is set as the trading week, the historical carbon price data of the local market is used as input data to train a carbon price prediction model, the market carbon trading price of the last three weeks of the month is input, the predicted carbon trading price of the next week is output, and the reliability and the authenticity shown by the example result prove that the method can realize carbon price prediction and can be applied to different parks.
The enterprises select the most appropriate trading strategy according to the prediction of the carbon trading price and the self-demand of the enterprises, and the trading strategy is used for maximizing the benefits of the enterprises in the park.
Further, the predicted carbon price output by the carbon price prediction module is a market real price, and the conversion ratio of the predicted carbon price to the carbon coin distributed by the enterprise is 1:1. the enterprise trades the required green credits in the blockchain platform through the carbon coin.
FIG. 4 is a flow chart of a blockchain carbon trading method that accounts for campus enterprise benefits according to embodiments of the present invention;
as shown in fig. 4, the carbon transaction management module includes the steps of:
step S1, enterprise data are acquired, an enterprise main body records in a market supervision organization and registers on a blockchain platform, and only enterprises meeting admission conditions can conduct transactions. And meanwhile, an administrator determines an initial carbon coin value according to the electricity consumption of the enterprise during peak-valley, and buyers and sellers conduct auction transactions on the blockchain platform through the carbon coin.
The initial carbon coin calculation formula is as follows:
C＝E peak ×δ 1 +E valley ×δ 2 ，δ 1 ＜δ 2
wherein C is a carbon coin, E peak And E is valley To purchase electricity quantity delta at peak-valley 1 And delta 2 Is a weight coefficient. The larger the electricity quantity purchased by the enterprise in the valley, the more the carbon coins are initially distributed, the more the transaction capital is, otherwise, the enterprise is driven to adjust the electricity load, and sustainable development is realized.
And S2, reporting the carbon transaction plan by the enterprise, encrypting the two-level information, uploading the two-level information to the blockchain by using the private key signature, and formulating an access strategy according to the first-level information by using the intelligent contract. The access policy is automatically executed by the intelligent contract, and the buyer enterprise can view the second level information of the seller enterprise about the specific transaction information when the buyer enterprise satisfies the access policy of the seller enterprise.
Step S3, conducting carbon transaction auction among enterprises, encrypting a piece of bidding information containing fields such as a time stamp, a transaction serial number, transaction amount and the like according to a seller public key after a buyer has transaction requirements and meets an access strategy, signing by using a private key of the buyer, and sending the bidding information to the seller; the seller decrypts the bid information before the trade expiration time and selects the most satisfactory bidder signature and broadcasts to the buyer, and the bid information can be iterated in the trade time until the auction ends, after which the buyer can not bid any more. Finally signing the order through the intelligent contract, wherein the calculation formula of the final transaction price is as follows:
P price ＝αX 1 +(1-α)X 2
wherein P is price For the price of the transaction (carbon coin), α is a weighting factor, usually 1/2, X 1 For the asking price of the seller enterprise X 2 Bid for buyer business only when X 2 ＞X 1 The transaction may occur, otherwise the transaction fails. The transaction amount is a smaller value of the two-party transaction plan.
And S4, after the auction is finished, broadcasting transaction information, voting by all nodes of the blockchain, indicating that the transaction verification is passed when the nodes exceed 2/3 of all nodes according to the voting condition of the nodes, calling an intelligent contract by a seller to record the transaction information on the blockchain, settling the transaction of each enterprise, and updating the account.
Further, the two levels of information in step S2 include:
the first level information includes enterprise type preference, green integral value lower limit, carbon integral value lower limit, and the like;
the second level of information includes sales plan amount, minimum/maximum price, auction deadline, business address, etc.
Fig. 5 is a schematic diagram of a hash chain formed in a transaction auction process according to an embodiment of the present invention.
As shown in fig. 5, the hash chain formed by the transaction in step S4 includes:
the first part of seller encrypts the uploaded two-level information and signs the private key;
the second part of the buyer bidding information comprises a time stamp, a transaction serial number, a transaction amount and other fields and a buyer private key signature;
the third portion of the sellers determines the private key signature after the transaction party.

Claims (8)

1. A trading method of a blockchain carbon trading system that accounts for campus enterprise benefits, the blockchain carbon trading system comprising: the system comprises a carbon track recording module, a carbon emission management module, a carbon price prediction module and a carbon transaction management module;
the carbon track recording module is used for recording carbon data respectively measured by the ground sensor and the airborne sensor and transmitting the carbon data to the blockchain platform for storage;
the carbon emission management module is used for distributing carbon points to enterprises so as to quantify carbon emission intensity, further distributing green points according to the carbon points to serve as transaction varieties in carbon transaction, and simultaneously carrying out carbon emission credit clearing;
the carbon price prediction module is used for predicting the carbon transaction price in the transaction period and giving initiative to enterprises so as to select an optimal transaction strategy;
the carbon transaction management module is used for distributing carbon coins, trading green points on a blockchain by utilizing the carbon coins, and carrying out uplink storage on transaction data;
the transaction method comprises the following specific steps:
(1) Arranging a ground sensor at a main discharge port of an enterprise, cruising above the enterprise at regular time by carrying an onboard sensor on an unmanned aerial vehicle, carrying out hash and encryption processing on all carbon data to obtain a hash value and a ciphertext, and uploading the hash value and the ciphertext to a block chain platform;
(2) The enterprise park adopts a double-integration mode to endow an enterprise with an initial value to realize carbon emission management, wherein the double-integration is carbon integration and green integration;
the carbon integral is determined by the power consumption, the power generation amount, the electric carbon emission coefficient and the carbon data of an enterprise, and the carbon data is used as calibration to verify whether the carbon integral of the enterprise is reasonable;
the calculation formula of the carbon integral is as follows:
P c ＝[(E use -E produce )×c]×α
wherein: e (E) use For enterprise power consumption, E produce The power generation capacity of enterprises is achieved, c is an electric carbon emission coefficient, and alpha is a scale factor;
(3) Prediction of carbon price
(3.1) acquiring carbon transaction price sample data, carrying out normalization pretreatment on the carbon transaction price sample data, and dividing the carbon transaction price sample data into a training set, a verification set and a test set;
(3.2) constructing a long-short memory neural network (LSTM), performing model training on the LSTM by using a training set, performing verification by using a verification set, and outputting the precision of the LSTM;
(3.3) predicting on the test dataset using the trained LSTM model, and outputting the carbon trade price;
(4) Performing carbon transaction management
(4.1) acquiring enterprise data, determining an initial carbon coin value by an administrator according to the power consumption of the enterprise at peak and valley, and performing auction transaction on a blockchain platform by a buyer and a seller through the carbon coin;
the calculation formula of the initial carbon coin is as follows:
C＝E peak ×δ 1 +E valley ×δ 2 ，δ 1 ＜δ 2
wherein C is a carbon coin, E peak And E is valley To purchase electricity quantity delta at peak-valley 1 And delta 2 Is a weight coefficient;
and (4.2) reporting the carbon transaction plan, encrypting the two-level information, uploading the two-level information to the blockchain by using a private key signature, and formulating an access strategy according to the first-level information by using an intelligent contract. Automatically executing the access policy through the intelligent contract, wherein the buyer enterprise can only check the second level information of the seller enterprise related to the specific transaction information when the buyer enterprise meets the access policy of the seller enterprise;
(4.3) conducting carbon transaction auction among enterprises, encrypting a piece of bidding information containing time stamp, transaction serial number, transaction amount and transaction amount fields according to a seller public key after a buyer has transaction requirements and meets an access strategy, signing by using a private key of the buyer, and sending the bidding information to the seller; the seller decrypts the bid information before the trade expiration time, selects the most satisfactory bidder signature and broadcasts the bid information to the buyer, and can iterate the bid information in the trade time until the auction is finished, and the buyer can not bid any more after the auction is finished;
and (4.4) finishing the auction, calling the intelligent contract by the seller to record transaction information on the blockchain, settling the transaction of each enterprise, and updating the account.
2. The trading method of the blockchain carbon trading system considering the benefits of a campus enterprise according to claim 1, wherein in the step (2), the green points are determined by carbon points and the carbon emission reduction behaviors of the enterprise, and a certain green point can be exchanged for a certain green point for adjusting the energy structure and increasing the carbon emission reduction investment;
the calculation formula of the green integral is as follows:
P green ＝A q -P c +∑P other
wherein P is green For green integral, A q A threshold value initially set for the transaction, the threshold value varying with quarter change, P c Is carbon productDivide, P other Is the carbon emission reduction behavior of enterprises.
3. The trading method of the blockchain carbon trading system for the campus enterprise benefit of claim 1, wherein the clearing of the track is performed once every quarter in step (2), and an administrator in the blockchain platform performs the clearing according to the carbon credit issued in the planning cycle;
the carbon credit for the clearance needs to be unregistered in the carbon trading system while giving the business not fulfilling the clearance obligation a strict penalty measure.
4. The trading method of the blockchain carbon trading system for accounting for the benefits of the campus enterprise of claim 1, wherein in step (3) the last week of the month is set as the trading week by the campus, and the predicted carbon trading price of the next week is output by inputting the market carbon trading price of the last three weeks of the month in the trained model;
the enterprises select the most appropriate trading strategy according to the prediction of the carbon trading price and the self-demand of the enterprises, and the trading strategy is used for maximizing the benefits of the enterprises in the park.
5. The trading method of the blockchain carbon trading system that accounts for campus enterprise benefits of claim 1, wherein the predicted carbon price output in the carbon price prediction module is a market true price, and the conversion ratio of the predicted carbon price to the carbon coin allocated by the enterprise is 1:1.
6. the method of claim 1, wherein the two levels of information in step (4.2) include:
the first level information includes enterprise type preference, green integral value lower limit, carbon integral value lower limit, and the like;
the second level of information includes sales plan amount, minimum/maximum price, auction deadline, business address, etc.
7. The blockchain carbon trading system and method for campus enterprise benefit of claim 1, wherein the hash chain formed by the trading in step (4.4) comprises:
the first part of seller encrypts the uploaded two-level information and signs the private key;
the second part of the buyer bidding information comprises a time stamp, a transaction serial number, a transaction amount and other fields and a buyer private key signature;
the third portion of the sellers determines the private key signature after the transaction party.
8. The blockchain carbon trading system and method for campus enterprise benefit of claim 1, wherein the on-board sensor in step (1) is an unmanned aerial vehicle-mounted carbon dioxide sensor.
CN202310574794.1A 2023-05-22 2023-05-22 Trading method of blockchain carbon trading system considering benefits of campus enterprises Pending CN116596671A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117495401A (en) * 2023-10-31 2024-02-02 苏州思萃区块链技术研究所有限公司 Carbon integral management method and system based on blockchain and carbon-verifiable certificate
CN118411181A (en) * 2024-07-02 2024-07-30 中瓷光电(山东)有限公司 Carbon emission data management system

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117495401A (en) * 2023-10-31 2024-02-02 苏州思萃区块链技术研究所有限公司 Carbon integral management method and system based on blockchain and carbon-verifiable certificate
CN118411181A (en) * 2024-07-02 2024-07-30 中瓷光电(山东)有限公司 Carbon emission data management system

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