CN116433377A - Block chain-based carbon asset transaction method and system - Google Patents
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Abstract
The invention provides a carbon asset transaction method and system based on a blockchain, wherein the method comprises the following steps: the method comprises the steps that a main institution calculates quota basic quantity of carbon emission of the year, issues a first pass corresponding to the carbon emission quota on a blockchain according to the quota basic quantity, and directly transfers the first pass to a virtual account of each key emission unit; the main institution predicts the superscalar quantity of the carbon emission of the year, if the superscalar quantity is positive, the second evidence of the carbon emission quota and the purchase unit price of the second evidence are issued on the blockchain according to the superscalar quantity, and each key emission unit selects whether to purchase the second evidence; the main authorities issue a third certificate of carbon emission quota and initial purchase unit price, price adding amplitude and maximum unit price of the third certificate according to the preset quota adjustment amount, and bid and purchase the third certificate on the blockchain by each key emission unit. The invention is beneficial to the management of the carbon emission process by the main authorities, and can lead the carbon emission quota to be more reasonable.
Description
Technical Field
The invention belongs to the technical field of blockchains, and particularly relates to a blockchain-based carbon asset transaction method and system.
Background
The existing carbon asset transaction method is generally managed by adopting a centralized system architecture and a management control system, and the method is easy to cause fraudulent activities, so that the carbon asset transaction management difficulty is high.
Disclosure of Invention
The invention aims to provide a carbon asset transaction method and system based on a blockchain, which are used for solving the technical problem of high difficulty in carbon asset transaction management in the prior art.
In order to achieve the above object, the present invention provides a blockchain-based carbon asset transaction method, which includes:
the method comprises the steps that a main institution calculates quota basic quantity of carbon emission of the year, issues a first pass corresponding to the carbon emission quota on a blockchain according to the quota basic quantity, and directly transfers the first pass to virtual accounts of all key emission units;
the main institution predicts the superscalar amount of the carbon emission of the year, if the superscalar amount is positive, a second pass of the carbon emission quota and the purchase unit price of the second pass are issued on the blockchain according to the superscalar amount, and whether the second pass is purchased or not is selected by each key emission unit;
the main institution issues a third certificate of carbon emission quota according to the preset quota adjustment amount, and the initial purchase unit price, the price adding amplitude and the maximum unit price of the third certificate, and the third certificate is purchased in a bidding way on the blockchain by each key emission unit.
In one possible implementation, the method for the authorities to calculate the quota base for the annual carbon emissions is:
accounting the historical carbon emission of each key emission unit;
and determining the quota basic quantity of the annual carbon emission according to the historical carbon emission quantity.
In one possible implementation, accounting for historical carbon emissions for a certain key emission unit includes:
determining preset categories of all target generator sets according to fuel types and unit capacities of all target generator sets in the key emission units; the target generator set refers to a generator set which is incorporated into quota management in each key emission unit;
determining a preset carbon accounting model corresponding to each target generator set according to the preset category to which each target generator set belongs;
performing carbon accounting on each target generator set based on a preset carbon accounting model corresponding to each target generator set to obtain a carbon accounting result of each target generator set;
and determining the historical carbon emission of the key emission unit according to the carbon accounting result of each target generator set.
In one possible implementation, the determining the quota base amount of the annual carbon emissions from the historical carbon emissions includes:
determining the same-ratio change rate of the carbon emission in each historical year according to the historical carbon emission;
determining an initial quota base amount of carbon emissions of the present year according to the same ratio change rate and the historical emissions of the last year;
determining a quota base amount of carbon emissions for the present year by s=min (s 1, s2×δ);
s is the quota basic quantity, s1 is the initial quota basic quantity, s2 is a preset maximum quota quantity, delta is a preset coefficient, and 0< delta <1.
In one possible implementation, the method for the authorities to predict superscalar carbon emissions for the present year is:
acquiring historical electricity consumption and historical heat consumption of a supply area corresponding to each key emission unit, and determining the annual carbon emission increment according to the historical electricity consumption and the historical heat consumption; wherein the supply area comprises a power supply area and a heat supply area;
acquiring a historical new energy utilization rate and a historical carbon emission optimization rate of each key emission unit, and determining the carbon emission reduction of the year according to the historical new energy utilization rate and the historical carbon emission optimization rate;
an superscalar amount of carbon emissions in the present year is determined based on the carbon emission increment amount and the carbon emission decrement amount.
In one possible implementation, the determining the annual carbon emission growth from the historical electricity consumption and the historical heat consumption includes:
inputting the historical electricity consumption and the historical heat consumption into a pre-trained carbon emission prediction model to obtain the annual carbon emission prediction value;
the carbon emission increment of the present year is determined based on the predicted amount of carbon emission of the present year and the historical carbon emission amount of the previous year.
In one possible implementation, the determining the annual carbon emission reduction amount according to the historical new energy usage rate and the historical carbon emission optimization rate includes:
inputting the historical new energy utilization rate and the historical carbon emission optimization rate into a pre-trained carbon emission optimization model to obtain the carbon emission reduction ratio of the year;
the carbon emission reduction amount of the present year is determined based on the carbon emission reduction ratio and the historical carbon emission amount of the previous year.
In one possible implementation, the blockchain-based carbon asset trading method further includes:
each of the emphasis discharge units issues a fourth certificate of carbon emission quota and a purchase price of the fourth certificate, which is bid-purchased on a blockchain by other emphasis discharge units than the present emphasis discharge unit.
In one possible implementation, the purchase price of the second pass is no higher than the initial purchase price of the third pass.
In order to achieve the above object, the present invention further provides a blockchain-based carbon asset transaction system for implementing the blockchain-based carbon asset transaction method described above.
The blockchain-based carbon asset transaction method and system provided by the invention have the beneficial effects that:
different from the centralized management method in the prior art, the carbon asset transaction method provided by the embodiment of the invention is realized based on the blockchain, so that the decentralization of the carbon asset transaction is effectively realized, the fairness of the carbon asset transaction is ensured, and the management of the carbon asset transaction is more convenient. On the basis, the embodiment of the invention also provides a plurality of types of pass certificates, and implements a multi-stage pass certificate issuing strategy. Wherein the first evidence is essentially a gratuitous issued carbon emission quota amount which can ensure that each key emission unit obtains a basic emission quota. The second evidence is essentially a paid carbon emission quota amount, which is a predicted superscalar of carbon emission, and can be purchased by each key emission unit according to the situation of the key emission unit, so that the rationality of the carbon emission quota is further ensured. The third evidence is also a paid-out carbon emission allowance amount, which is the allowance of the carbon emission allowance set by the main institution, so as to avoid the situation that the evidence quantity is insufficient as much as possible. That is, the carbon asset transaction method provided by the embodiment of the invention is not only beneficial to the management of the carbon emission process by the main institution, but also can make the carbon emission quota more reasonable and improve the management effectiveness of the main institution.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a blockchain-based carbon asset transaction method according to an embodiment of the invention.
Detailed Description
In order to make the technical problems, technical schemes and beneficial effects to be solved more clear, the invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The invention will be described in further detail with reference to the drawings and the detailed description.
Referring to fig. 1, fig. 1 is a flowchart of a blockchain-based carbon asset transaction method according to an embodiment of the invention, where the blockchain-based carbon asset transaction method includes:
s101: the method comprises the steps that a main institution calculates quota basic quantity of carbon emission of the year, and issues a first certificate corresponding to the carbon emission quota on a blockchain according to the quota basic quantity, and the first certificate is directly transferred into a virtual account of each key emission unit.
In this embodiment, the quota base amount of the carbon emission of the present year may be determined according to the historical carbon emission amount of each historical year, which is essentially the carbon emission amount of the present year obtained by measuring the historical carbon emission amount, on this basis, a certain amount of the first pass may be allocated to each key emission unit according to the carbon emission amount of the present year and the carbon emission condition of each key emission unit, and the corresponding amount of the first pass may be transferred to the virtual account of each key emission unit on the blockchain.
In this embodiment, the first pass represents the carbon emission quota, and the number of the first passes corresponds to the quota base amount. That is, the number of first letters is essentially the ratio of the underlying quota amount to the individual first letter quota amount.
S102: the main authorities predict the superscalar amount of the carbon emission of the year, if the superscalar amount is positive, the second pass of the carbon emission quota and the purchase unit price of the second pass are issued on the blockchain according to the superscalar amount, and whether the second pass is purchased or not is selected by each key emission unit.
In this embodiment, a dynamic quota amount, i.e. a superscalar, is also set. The excess is mainly used for representing the possible carbon emission excess condition of each key emission unit in the year, and can be predicted by a main management unit according to the historical electricity consumption/historical heat consumption of the supply area of each key emission unit. On the basis, the main management unit can issue a batch of paid second certificates according to the carbon emission exceeding condition, so that each key emission unit can purchase the second certificates according to the self emission condition, and the distribution of carbon emission quota can be more reasonably realized.
In this embodiment, the second license represents the carbon emission quota, and the number of the second license corresponds to the superscalar amount. That is, the number of second certificates is essentially the ratio of the superscalar to the individual second certificate quota amount.
S103: the main authorities issue a third certificate of carbon emission quota and initial purchase unit price, price adding amplitude and maximum unit price of the third certificate according to the preset quota adjustment amount, and bid and purchase the third certificate on the blockchain by each key emission unit.
In this embodiment, in order to avoid that the first pass and the second pass do not reach the ideal carbon emission quota effect, the main unit may preset a certain quota adjustment amount, that is, a certain carbon emission quota allowance, so as to avoid the situation that the number of passes is insufficient, and further ensure the rationality of the carbon emission quota.
In this embodiment, the bid purchase of the third ticket may be implemented by setting up an intelligent contract.
In the present embodiment, in order to secure the benefit of each of the emphasis discharge units, the cost of each of the emphasis discharge units can be reduced, and the purchase unit price of the second pass can be set to be not higher than the initial purchase unit price of the third pass.
In this embodiment, after the first certificate is directly transferred to the virtual account of each key emission unit, the blockchain-based carbon asset transaction method may further include:
the number of first passes of the virtual account transferred to each of the accent discharge units is verified.
In this embodiment, after the first pass is allocated, the allocation of the first pass may be checked to ensure the accuracy of the allocation of the first pass.
From the above description, unlike the centralized management method in the prior art, the carbon asset transaction method provided by the embodiment of the invention is realized based on the blockchain, so that the decentralization of the carbon asset transaction is effectively realized, the fairness of the carbon asset transaction is ensured, and the management of the carbon asset transaction is more convenient. On the basis, the embodiment of the invention also provides a plurality of types of pass certificates, and implements a multi-stage pass certificate issuing strategy. Wherein the first evidence is essentially a gratuitous issued carbon emission quota amount which can ensure that each key emission unit obtains a basic emission quota. The second evidence is essentially a paid carbon emission quota amount, which is a predicted superscalar of carbon emission, and can be purchased by each key emission unit according to the situation of the key emission unit, so that the rationality of the carbon emission quota is further ensured. The third evidence is also a paid-out carbon emission allowance amount, which is the allowance of the carbon emission allowance set by the main institution, so as to avoid the situation that the evidence quantity is insufficient as much as possible. That is, the carbon asset transaction method provided by the embodiment of the invention is not only beneficial to the management of the carbon emission process by the main institution, but also can make the carbon emission quota more reasonable and improve the management effectiveness of the main institution.
In one possible implementation, the method for the authorities to calculate the quota base for the annual carbon emissions is:
the historical carbon emissions of each of the key emission units are accounted for.
The quota base amount of the annual carbon emission is determined from the historical carbon emission amounts of the respective key emission units.
In the present embodiment, the quota base amount of the annual carbon emission may be determined from the historical carbon emission amounts of the respective key emission units. On this basis, the proportion of the first pass assigned to each of the emphasis units may also be determined based on the proportion of the historical carbon emission amount of each of the emphasis units.
In one possible implementation, accounting for historical carbon emissions for a certain key emission unit includes:
and determining the preset category of each target generator set according to the fuel type and the set capacity of each target generator set in the key emission unit. The target generator set refers to a generator set which is incorporated into quota management in each key emission unit.
And determining a preset carbon accounting model corresponding to each target generator set according to the preset category to which each target generator set belongs.
And performing carbon accounting on each target generator set based on a preset carbon accounting model corresponding to each target generator set to obtain a carbon accounting result of each target generator set.
And determining the historical carbon emission of the key emission unit according to the carbon accounting result of each target generator set.
In this embodiment, the power generating units may be classified according to the fuel type and the unit capacity of the power generating units, to obtain a preset classification. For example, the generator components can be divided into four classes:
a first preset classification: conventional coal-fired units above 300MW grade;
a second preset classification: conventional coal-fired units below 300WM grade;
third preset classification: unconventional coal-fired units (including coal-fired circulating fluidized bed units) such as coal gangue, coal slime, coal water slurry and the like;
fourth preset classification: a gas turbine unit.
On the basis, a carbon accounting model can be built for each preset classification generator set in advance, and the carbon accounting model corresponding to each preset classification is obtained.
On the basis, when the historical carbon emission of a certain key emission unit is determined, the carbon accounting model corresponding to each target generator set can be determined according to the preset classification of each target generator set in the key emission unit. Based on the above, carbon emission accounting can be performed on the target generator sets of different preset classifications in the key emission unit, and based on the carbon emission accounting, the carbon accounting results of each target generator set can be obtained.
In this embodiment, after determining the carbon accounting results of each target generator set, the carbon accounting results of each target generator set are summed up, so as to obtain the historical emission of the key emission unit.
Based on the above method, the historical emission amount of each key emission unit can be calculated step by step. On this basis, the quota base amount of carbon emissions for the present year can be determined from the historical carbon emissions of each of the key emission units.
In one possible implementation, determining the quota base amount of annual carbon emissions from the historical carbon emissions for each of the key emission units includes:
and determining the same-ratio change rate of the carbon emission in each historical year according to the historical carbon emission of each key emission unit.
An initial quota base for the current year of carbon emissions is determined based on the rate of change of the same ratio and the historical emissions of the previous year.
The quota base amount of carbon emissions for the present year is determined by s=min (s 1, s2×δ).
S is a quota basic quantity, s1 is an initial quota basic quantity, s2 is a preset maximum quota quantity, delta is a preset coefficient, and 0< delta <1.
In the present embodiment, the rate of change of the carbon emissions of each historical year with respect to the previous year may be determined from the historical carbon emissions of each key emission unit, resulting in a plurality of rates of change of the same ratio.
On this basis, the initial quota base quantity of the carbon emission of the year is determined according to the same ratio change rate and the historical emission quantity of the last year, and can be described as follows:
and determining an average homoratio change rate according to the plurality of homoratio change rates.
The initial quota base amount for the annual carbon emissions was determined by s1=s1' ×ζ%.
Where s1' is the historical emission of the last year of the present year, ζ% is the average same ratio change rate.
On the basis, the initial quota basic quantity of the carbon emission of the year is determined according to the same ratio change rate and the historical emission of the last year, and can also be detailed as follows:
and training based on the multiple same-ratio change rates to obtain a deep learning model, wherein the deep learning model is used for predicting the same-ratio change rate of the current year according to the input same-ratio change rates of the first three years.
And extracting the same-ratio change rate of the first three years of the current year, and inputting the same-ratio change rate of the first three years of the current year into the deep learning model to obtain the same-ratio change rate of the current year.
The initial quota base amount for the annual carbon emissions is determined by s1=s1' ×θ%.
Where s1' is the historical emissions of the last year of the present year, and θ% is the rate of change of the same ratio of the present year.
In this embodiment, considering the influence of various environmental policies, a certain maximum quota amount may be preset, and on this basis, it is required to ensure that the final quota base amount is smaller than the maximum quota amount, and therefore, the quota base amount of carbon emission in the present year may be determined by s=mim (s 1, s2×δ).
In one possible implementation, the method for the authorities to predict superscalar carbon emissions for the present year is:
and acquiring the historical electricity consumption and the historical heat consumption of the supply area corresponding to each key emission unit, and determining the carbon emission increment of the year according to the historical electricity consumption and the historical heat consumption. Wherein the supply area comprises a power supply area and a heat supply area.
And acquiring the historical new energy utilization rate and the historical carbon emission optimization rate of each key emission unit, and determining the annual carbon emission reduction according to the historical new energy utilization rate and the historical carbon emission optimization rate.
The superscalar amount of carbon emissions in the present year is determined based on the carbon emission increase amount and the carbon emission decrease amount.
In the present embodiment, the supply area corresponding to each of the emphasis discharge units refers to the heat supply area and the power supply area of each of the emphasis discharge units.
In this embodiment, to better predict superscalar carbon emissions in the current year, one may start from the sources that affect carbon emissions (i.e., electricity usage and heat usage). That is, the carbon emission growth amount of the present year can be predicted from the historical electricity consumption amount and the historical heat consumption amount of the supply region of each of the important emission units.
In this embodiment, the adjustment of the energy supply of each of the emphasis units and the reduction of carbon emissions caused by the optimization of the operation mode of the generator set of each of the emphasis units are also considered. Therefore, the present embodiment can also predict the carbon emission reduction amount of the present year based on the historical new energy use rate and the historical carbon emission optimization rate of each of the key emission units. The carbon emission optimization rate of a certain key emission unit refers to the ratio of the key emission unit to optimize carbon emission after the key emission unit adjusts the operation mode of the generator set or the power supply/heat supply policy.
In this embodiment, after determining the carbon emission increment and the carbon emission decrement in the present year, the difference between them is an superscalar amount of the present year's carbon emission.
In one possible implementation, determining the annual carbon emission growth from the historical electricity usage and the historical heat usage includes:
and inputting the historical electricity consumption and the historical heat consumption into a pre-trained carbon emission prediction model to obtain the carbon emission prediction quantity of the year.
The carbon emission increment of the present year is determined based on the predicted amount of carbon emission of the present year and the historical carbon emission amount of the previous year.
In the present embodiment, a carbon emission prediction model for predicting the carbon emission amount of the present year from the input historical electricity consumption amount and the historical heat consumption amount may be trained in advance. On the basis, the difference between the predicted carbon emission amount in the current year and the historical carbon emission amount in the last year is the carbon emission increment in the current year. The carbon emission prediction model may be a neural network model or an ensemble learning model.
In one possible implementation, determining the annual carbon emission reduction amount from the historical new energy usage and the historical carbon emission optimization rate includes:
and inputting the historical new energy utilization rate and the historical carbon emission optimization rate into a pre-trained carbon emission optimization model to obtain the annual carbon emission reduction ratio.
The carbon emission reduction amount of the present year is determined based on the carbon emission reduction ratio and the historical carbon emission amount of the previous year.
In the present embodiment, a carbon emission optimization model for predicting a carbon emission reduction ratio from the input new energy usage rate and carbon emission optimization rate may be trained in advance. On the basis, the product of the carbon emission reduction ratio of the present year and the historical carbon emission amount of the last year is the carbon emission reduction amount of the present year. The carbon emission optimization model can be a neural network model or an integrated learning model.
In one possible implementation, the blockchain-based carbon asset trading method further includes:
each of the emphasis discharge units issues a fourth certificate of carbon emission quota and a purchase price of the fourth certificate, and the fourth certificate is bid and purchased on the blockchain by other emphasis discharge units than the present emphasis discharge unit.
In this embodiment, each of the emphasis units may also issue a certificate on the blockchain to effect trading of carbon assets between each of the emphasis units.
In order to achieve the above object, the present invention further provides a blockchain-based carbon asset transaction system for implementing the above blockchain-based carbon asset transaction method.
In this embodiment, a carbon asset transaction system of a blockchain architecture is also provided to implement the carbon asset transaction method in the above embodiment.
The present invention is not limited to the above embodiments, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the present invention, and these modifications and substitutions are intended to be included in the scope of the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (10)
1. A blockchain-based carbon asset trading method, comprising:
the method comprises the steps that a main institution calculates quota basic quantity of carbon emission of the year, issues a first pass corresponding to the carbon emission quota on a blockchain according to the quota basic quantity, and directly transfers the first pass to virtual accounts of all key emission units;
the main institution predicts the superscalar amount of the carbon emission of the year, if the superscalar amount is positive, a second pass of the carbon emission quota and the purchase unit price of the second pass are issued on the blockchain according to the superscalar amount, and whether the second pass is purchased or not is selected by each key emission unit;
the main institution issues a third certificate of carbon emission quota according to the preset quota adjustment amount, and the initial purchase unit price, the price adding amplitude and the maximum unit price of the third certificate, and the third certificate is purchased in a bidding way on the blockchain by each key emission unit.
2. The blockchain-based carbon asset trading method of claim 1, wherein the method for the authorities to calculate the quota base for the annual carbon emissions is:
accounting the historical carbon emission of each key emission unit;
and determining the quota basic quantity of the annual carbon emission according to the historical carbon emission quantity.
3. The blockchain-based carbon asset trading method of claim 2, wherein accounting for historical carbon emissions for a certain key emission unit includes:
determining preset categories of all target generator sets according to fuel types and unit capacities of all target generator sets in the key emission units; the target generator set refers to a generator set which is incorporated into quota management in each key emission unit;
determining a preset carbon accounting model corresponding to each target generator set according to the preset category to which each target generator set belongs;
performing carbon accounting on each target generator set based on a preset carbon accounting model corresponding to each target generator set to obtain a carbon accounting result of each target generator set;
and determining the historical carbon emission of the key emission unit according to the carbon accounting result of each target generator set.
4. The blockchain-based carbon asset trading method of claim 2, wherein the determining a quota base for current annual carbon emissions from the historical carbon emissions comprises:
determining the same-ratio change rate of the carbon emission in each historical year according to the historical carbon emission;
determining an initial quota base amount of carbon emissions of the present year according to the same ratio change rate and the historical emissions of the last year;
determining a quota base amount of carbon emissions for the present year by s=min (s 1, s2×δ);
s is the quota basic quantity, s1 is the initial quota basic quantity, s2 is a preset maximum quota quantity, delta is a preset coefficient, and 0< delta <1.
5. The blockchain-based carbon asset trading method of claim 1, wherein the method for the authorities to predict superscalar of annual carbon emissions is:
acquiring historical electricity consumption and historical heat consumption of a supply area corresponding to each key emission unit, and determining the annual carbon emission increment according to the historical electricity consumption and the historical heat consumption; wherein the supply area comprises a power supply area and a heat supply area;
acquiring a historical new energy utilization rate and a historical carbon emission optimization rate of each key emission unit, and determining the carbon emission reduction of the year according to the historical new energy utilization rate and the historical carbon emission optimization rate;
an superscalar amount of carbon emissions in the present year is determined based on the carbon emission increment amount and the carbon emission decrement amount.
6. The blockchain-based carbon asset trading method of claim 5, wherein the determining the annual carbon emission growth based on the historical electricity usage and the historical heat usage comprises:
inputting the historical electricity consumption and the historical heat consumption into a pre-trained carbon emission prediction model to obtain the annual carbon emission prediction value;
the carbon emission increment of the present year is determined based on the predicted amount of carbon emission of the present year and the historical carbon emission amount of the previous year.
7. The blockchain-based carbon asset trading method of claim 5, wherein the determining the current year of carbon emission reduction based on the historical new energy usage and the historical carbon emission optimization rate comprises:
inputting the historical new energy utilization rate and the historical carbon emission optimization rate into a pre-trained carbon emission optimization model to obtain the carbon emission reduction ratio of the year;
the carbon emission reduction amount of the present year is determined based on the carbon emission reduction ratio and the historical carbon emission amount of the previous year.
8. The blockchain-based carbon asset trading method of claim 1, further comprising:
each of the emphasis discharge units issues a fourth certificate of carbon emission quota and a purchase price of the fourth certificate, which is bid-purchased on a blockchain by other emphasis discharge units than the present emphasis discharge unit.
9. The blockchain-based carbon asset transaction method of any of claims 1-8, wherein the purchase price of the second pass is no higher than the initial purchase price of the third pass.
10. A blockchain-based carbon asset trading system for implementing the blockchain-based carbon asset trading method of any of claims 1 to 9.
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