CN114298424A - Carbon asset management method based on artificial intelligence and block chain technology - Google Patents
Carbon asset management method based on artificial intelligence and block chain technology Download PDFInfo
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Abstract
The invention provides a carbon asset management method based on artificial intelligence and a block chain technology, which comprises the following steps: step A, acquiring quota carbon assets obtained by enterprise distribution; b, acquiring equipment production information and equipment emission information; step C, acquiring emission reduction carbon assets of enterprises according to the emission reduction amount of the equipment; and step D, processing according to the emission reduction carbon assets of the enterprise and the output values of the equipment to obtain the carbon asset management output optimal value of the enterprise, and step E, generating a request by the cloud server according to the associated characteristic information to obtain a corresponding production key and generating a corresponding emission reduction strategy according to the output optimal value. The invention can obtain the optimal carbon asset management method of the enterprise by comprehensively evaluating the emission reduction capacity and the emission reduction benefits of the enterprise, so as to solve the problem of low overall benefits of the enterprise caused by single carbon asset management mode of the existing enterprise.
Description
Technical Field
The invention relates to the technical field of carbon emission reduction, in particular to a carbon asset management method based on artificial intelligence and a block chain technology.
Background
Carbon assets refer to quota emissions, emission reduction credits and related activities that may directly or indirectly affect an organization's greenhouse gas emissions, generated under a forced carbon emissions trading mechanism or a voluntary carbon emissions trading mechanism. Blockchains are a term of art in information technology. In essence, the system is a shared database, and the data or information stored in the shared database has the characteristics of 'unforgeability', 'whole-course trace', 'traceability', 'public transparency', 'collective maintenance', and the like. Based on the characteristics, the block chain technology lays a solid 'trust' foundation, creates a reliable 'cooperation' mechanism and has wide application prospect. Artificial intelligence, abbreviated in english as AI. The method is a new technical science for researching and developing theories, methods, technologies and application systems for simulating, extending and expanding human intelligence.
In the existing carbon emission reduction process, enterprises cannot well balance production scale expansion, investment of emission reduction equipment and reduction of carbon emission, so that the enterprises need to buy carbon assets to make up for the excessive parts when the carbon emission exceeds the standard, and the increase of the overall benefit of the enterprises for finally reducing the carbon emission cost is not in direct proportion to the increase of sales volume, so that a method for reasonably controlling and adjusting the carbon assets of the enterprises is lacked, and the emission reduction technology relates to the trade secret of the enterprises and is difficult to popularize.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a carbon asset management method based on artificial intelligence and a block chain technology, which can obtain the optimal carbon asset management method of an enterprise by comprehensively evaluating the emission reduction amount and the emission reduction benefits of the equipment of the enterprise, so as to solve the problem of low overall benefit of the enterprise caused by a single carbon asset management mode of the existing enterprise.
In order to achieve the purpose, the invention is realized by the following technical scheme: a carbon asset management method based on artificial intelligence and a block chain technology comprises the following steps:
step A, acquiring quota carbon assets obtained by enterprise distribution;
step B, generating equipment production information and equipment emission information in real time; the equipment production information reflects the production working state of equipment corresponding to an enterprise, and the equipment emission information reflects the carbon emission condition of the equipment corresponding to the enterprise; generating associated characteristic information according to the association relation corresponding to the equipment emission information and the equipment production information, and encrypting the equipment production information to generate a production ciphertext and a production key; sending the production ciphertext to a plurality of different terminals where enterprises are located, taking the associated characteristic information as an index, and simultaneously producing a secret key to be stored locally;
c, training the cloud server side according to the equipment emission information and the equipment production information to generate a theoretical emission model, uploading the equipment production information in real time by a terminal where the enterprise is located to obtain the theoretical emission information, calculating the emission reduction amount of the equipment according to the difference value of the theoretical emission information and the equipment emission information, and obtaining the emission reduction carbon assets of the enterprise according to the emission reduction amount of the equipment;
step D, processing according to the emission reduction carbon assets of the enterprises and the output values of the equipment to obtain the optimal value of the carbon asset management output of the enterprises, and calling corresponding associated characteristic information according to the optimal value;
and E, the cloud server generates a request according to the associated characteristic information to obtain a corresponding production key, and generates a corresponding emission reduction strategy according to the output optimal value.
Further, the equipment production information includes a production value of the equipment, the equipment emission information includes a value of carbon emission of the equipment, and the step B further includes the substeps of:
a step B1, wherein the step B1 includes dividing the carbon emission facility of the enterprise; dividing the equipment with the carbon emission amount greater than or equal to a first emission threshold value into first-stage carbon emission equipment; dividing the equipment with the carbon emission amount greater than or equal to a second emission threshold value and smaller than a first emission threshold value into second-stage carbon emission equipment; dividing the carbon emission equipment with the carbon emission amount less than the second emission threshold into third-stage carbon emission equipment;
step B2, the step B2 includes obtaining a first yield value of maximum output of the first stage carbon emission facility, a second yield value of maximum output of the second stage carbon emission facility, and a third yield value of maximum output of the third stage carbon emission facility;
step B3, the step B3 includes obtaining a first stage carbon emission plant maximum reduction throughput and a corresponding carbon reduction capacity, a second stage carbon emission plant maximum reduction throughput and a corresponding carbon reduction capacity, and a third stage carbon emission plant maximum reduction throughput and a corresponding carbon reduction capacity.
Further, the step C further comprises the following sub-steps:
step C1, wherein the step C1 comprises substituting the maximum reduction output of the first-stage carbon emission equipment and the corresponding carbon reduction amount into a first emission reduction carbon asset formula to obtain a first-stage emission reduction carbon asset value;
step C2, wherein the step C2 comprises substituting the maximum reduction output of the secondary carbon emission equipment and the corresponding carbon reduction amount into a secondary emission reduction carbon asset formula to obtain a secondary emission reduction carbon asset value;
and C3, wherein the step C3 comprises the step of substituting the maximum reduction output of the third-level carbon emission equipment and the corresponding carbon reduction amount into a third emission reduction carbon asset formula to obtain a third-level emission reduction carbon asset value.
Further, the first emission abatement carbon asset formula is configured to:
the first emission abatement carbon asset formula is configured to:
the first emission abatement carbon asset formula is configured to:
tz1 is a first-stage emission reduction carbon asset value, C1max and Tjc1 are a maximum reduction output and a corresponding carbon emission reduction capacity of a first-stage carbon emission device, a1 is a first-stage emission reduction optimization coefficient, Tz2 is a second-stage emission reduction carbon asset value, C2max and Tjc2 are a maximum reduction output and a corresponding carbon emission reduction capacity of a second-stage carbon emission device, a2 is a second-stage emission reduction optimization coefficient, Tz3 is a third-stage emission reduction carbon asset value, C3max and Tjc3 are a maximum reduction output and a corresponding carbon emission reduction capacity of a third-stage carbon emission device, and a3 is a third-stage emission reduction optimization coefficient.
Step D1, wherein the step D1 includes substituting the first output value and the first stage emission reduction carbon asset value into a first stage carbon emission formula to obtain a first stage output value;
substituting the second output value and the second emission reduction carbon asset value into a second carbon emission formula to obtain a second output value;
and substituting the third yield value and the third stage emission reduction carbon asset value into a third stage carbon emission formula to obtain a third stage yield value.
Further, the first stage carbon emission formula is configured to:
the second stage carbon emission formula is configured as:
the second stage carbon emission formula is configured as:
wherein Cc1 is a first-stage output value, Cz1 is a first output value, b1 is a first output proportion value, Cc2 is a second-stage output value, Cz2 is a second output value, b2 is a second output proportion value, Cc3 is a third-stage output value, Cz3 is a third output value, and b1 is a third output proportion value.
Further, the step D also includes a step D2, the step D2 includes adding the first stage optimal yield value, the second stage optimal yield value and the third stage optimal yield value to obtain a first total carbon emission value;
and substituting the first total carbon emission value and the quota carbon asset into a quota over ratio formula to obtain a quota difference value.
Further, the quota over ratio formula is configured to: pc ═ c1 × (Tpz 1-Tpe); where Pc is a quota difference value, Tpz1 is a first total carbon emission value, Tpe is a quota carbon asset, and c1 is a quota difference conversion coefficient.
Further, the step D further includes a step D3, the step D3 includes when the quota difference value is greater than the first quota difference threshold; at this point the carbon emissions of the enterprise are already greater than government matched carbon emissions, and therefore self-adjusting proportions of each need to be selected from primary, secondary and tertiary plants.
Substituting the quota difference value and the first-stage output value into a first-stage optimal output formula to obtain a first-stage optimal output value, substituting the quota difference value and the second-stage output value into a second-stage optimal output formula to obtain a second-stage optimal output value, and substituting the quota difference value and the third-stage output value into a third-stage optimal output formula to obtain a third-stage optimal output value;
and adding the first-stage optimal output value, the second-stage optimal output value and the third-stage optimal output value to obtain a carbon asset management output optimal value.
Further, the first-stage optimal yield formula is configured to:
the first-stage optimal yield formula is configured as:
the first-stage optimal yield formula is configured as:
czy1 is the first-level optimal output value, d1 is the first optimal output coefficient, Czy2 is the second-level optimal output value, d2 is the second optimal output coefficient, Czy3 is the third-level optimal output value, and d3 is the third optimal output coefficient.
The invention has the beneficial effects that: the quota carbon assets obtained by the distribution of an enterprise are obtained, and then the emission of carbon emission equipment and the output value of the equipment generated in the production of the enterprise are obtained; then acquiring emission reduction carbon assets of enterprises according to the emission reduction capacity of the equipment; and finally, processing according to the emission reduction carbon assets of the enterprise and the output values of the equipment to obtain the optimal carbon asset management output value of the enterprise, wherein the design can comprehensively evaluate the emission reduction capacity and the emission reduction benefit of the equipment of the enterprise to obtain the optimal carbon asset management method of the enterprise, and can find balance points in the aspects of production and carbon emission reduction for the enterprise on the basis of ensuring the lowest production scale of the enterprise, so that the rationality of carbon asset management of the enterprise on the basis of enlarging the production scale is ensured, the upgrading of emission reduction technology is promoted, and the comprehensive benefit of the enterprise is improved.
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Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a general flow chart of the method steps of the present invention;
FIG. 2 is a flow chart of substeps of step B of the present invention;
FIG. 3 is a flow diagram of substeps of step C of the present invention;
FIG. 4 is a flow chart of substeps of step D of the present invention.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
Referring to fig. 1 to 4, a carbon asset management method based on artificial intelligence and a block chain technology specifically includes the following steps:
step A, acquiring quota carbon assets obtained by enterprise distribution; acquiring quota carbon assets distributed by enterprises; quota carbon assets generally fall within the carbon emission standards for distribution to each business, below which additional carbon assets need not be purchased and above which additional carbon assets need to be purchased to make up. The carbon currency is used for realizing the allocation of talking assets, the management is carried out through the carbon currency, different quota carbon assets are configured according to different corresponding fields of the output value of each enterprise, the method and the system aim to realize the sharing and optimization of emission reduction technology in an artificial intelligence mode, so that the environmental protection technology can be managed in a carbon currency mode.
The optimization of the energy-saving technology information is realized, and the three problems are mainly related to 1, the energy-saving technology information has technical confidentiality, enterprises have no motivation to share the energy-saving technology, 2, the energy-saving technology has pertinence, and differences possibly exist according to different devices and production processes, so that the energy-saving technology cannot be pertinently matched, and 3, the energy-saving technology cannot be shared on the cloud as a technical secret, so that a large information hidden danger is caused. In order to solve the above three problems, the following steps are provided.
Step B, generating equipment production information and equipment emission information in real time; the equipment production information reflects the production working state of equipment corresponding to an enterprise, and the equipment emission information reflects the carbon emission condition of the equipment corresponding to the enterprise; generating associated characteristic information according to the association relation corresponding to the equipment emission information and the equipment production information, and encrypting the equipment production information to generate a production ciphertext and a production key; sending the production ciphertext to a plurality of different terminals where enterprises are located, taking the associated characteristic information as an index, and simultaneously producing a secret key to be stored locally; firstly, corresponding information collection is configured at an enterprise end, of course, equipment production information includes equipment basic parameter information, such as equipment model, equipment function, power, basic emission and the like, and also includes real-time detection information, such as monitoring of equipment working state information, current and voltage detection in the actual production process of equipment, the working state of detection equipment in a certain working content, and the equipment emission information can be detected in real time through an emission monitoring related sensor, so that the dynamic relationship between the local equipment working state and carbon emission can be obtained in real time, theoretically, some results can be obtained through transverse comparison of the dynamic relationship, for example, two users both include A \ B \ C \ D equipment, but one more E equipment is provided for the user, and if the carbon emission of the user is low, the E equipment is very likely to be emission reduction equipment, if the carbon emission of the user is higher, the equipment E may be equipment with higher carbon emission and can be optimized, if the two users are different in working state, for example, the equipment A is operated intermittently, if the carbon emission result is lower, the technology for intermittent operation can be judged to be technology for reducing carbon emission, although the technology information collection can be compared and used for making energy-saving technology reference each other, there is a problem that because the production process of an enterprise relates to secret information, the comparison can be carried out if the technology secret information is disclosed but not disclosed, and the emission information itself can not disclose the process content of the enterprise, so that the collection can be carried out, so in the step, firstly, a correlation characteristic is generated for the production information of the equipment and the emission information of the equipment, and the correlation characteristic information aims to provide an index, the strategy for generating the associated characteristic information is that the characteristic extraction is firstly carried out on the equipment production information by taking the carbon emission change as the basis through a learning model, then, corresponding adjustment weight is set according to the carbon emission change in real time, so that the incidence relation between the local carbon emission and the equipment working characteristics is obtained, the incidence relation is used as incidence characteristic information, the related characteristic information does not record any production content, but is used as an index of the correlation relationship between the carbon emission change and the production, meanwhile, by encrypting the production information, the generated key is stored locally and cannot be sent to the cloud server, the cryptographs are sent in a distributed mode through the cloud server, each cryptograph is stored to different enterprise terminals, and the ciphertext is indexed through the associated characteristic information, so that the safety of production information is ensured, and the matching can be performed according to the carbon emission condition of an enterprise according to the associated characteristic information.
Referring to fig. 2, the equipment production information includes a production value of the equipment, and the equipment emission information includes a value of carbon emission of the equipment, step B1, the carbon emission equipment of the enterprise is divided; dividing the equipment with the carbon emission amount greater than or equal to a first emission threshold value into first-stage carbon emission equipment; dividing the equipment with the carbon emission amount greater than or equal to a second emission threshold value and smaller than a first emission threshold value into second-stage carbon emission equipment; dividing the carbon emission equipment with the carbon emission amount less than the second emission threshold into third-stage carbon emission equipment; the division of enterprise equipment is necessary, so that when carbon emission reduction needs to be performed on certain equipment, emission reduction standards can be distinguished, generally speaking, equipment with large carbon emission can perform emission reduction with a large amount, and equipment with small carbon emission is usually in a full-load production state, so that the proportion of carbon emission reduction and the final carbon emission reduction are small, and therefore the factor needs to be considered when carbon emission reduction distribution is performed.
Step B2, obtaining a first output value of the maximum output of the first-stage carbon emission equipment, a second output value of the maximum output of the second-stage carbon emission equipment and a third output value of the maximum output of the third-stage carbon emission equipment; the output value of each level of equipment represents the benefit value which can be output by the equipment, and can be obtained by comprehensively evaluating the overall benefit of an enterprise.
And step B3, obtaining the maximum reduction output of the first-stage carbon emission equipment and the corresponding carbon emission reduction amount, the maximum reduction output of the second-stage carbon emission equipment and the corresponding carbon emission reduction amount, and the maximum reduction output of the third-stage carbon emission equipment and the corresponding carbon emission reduction amount, and when an enterprise can meet the lowest guaranteed production requirement, obtaining the maximum reduction output and the corresponding carbon emission reduction amount after each stage of equipment can reduce power production or energy consumption production.
C, training the cloud server side according to the equipment emission information and the equipment production information to generate a theoretical emission model, uploading the equipment production information in real time by a terminal where the enterprise is located to obtain the theoretical emission information, calculating the emission reduction amount of the equipment according to the difference value of the theoretical emission information and the equipment emission information, and obtaining the emission reduction carbon assets of the enterprise according to the emission reduction amount of the equipment; the step is to train a theoretical discharge model, the theoretical discharge model is analyzed according to actual discharge and corresponding production information to obtain the optimal discharge, and different discharge standards are set according to different devices and different production values, so that the abnormal discharge condition can be easily found, carbon discharge can be promoted, and the targeted management of different enterprises can be realized. Before encryption, the cloud end processes each actual device emission information and device production information and classifies according to the device production information, so that a standard emission value is obtained through calculation, theoretical emission information can be calculated according to the device emission information uploaded by an enterprise, then emission reduction capacity is obtained, emission reduction carbon assets are obtained through the emission reduction capacity, targeted monitoring and management are achieved, and the enterprise can find problems in carbon emission at the first time.
Referring to fig. 3, in step C1, substituting the maximum reduction output of the first-stage carbon emission facility and the corresponding carbon reduction amount into a first emission reduction carbon asset formula to obtain a first-stage emission reduction carbon asset value; step C2, substituting the maximum reduction output of the secondary carbon emission equipment and the corresponding carbon emission reduction amount into a secondary emission reduction carbon asset formula to obtain a secondary emission reduction carbon asset value; and step C3, substituting the maximum reduction output of the third-level carbon emission equipment and the corresponding carbon emission reduction amount into a third-level emission reduction carbon asset formula to obtain a third-level emission reduction carbon asset value. The first-level carbon emission reduction asset value, the second-level carbon emission reduction asset value and the third-level carbon emission reduction asset value can represent the correspondingly reduced carbon emission amount after the output is reduced, and the benefits which can be achieved by carbon emission reduction can be represented by comprehensively comparing the reduced carbon emission amount with the output value.
The first emission abatement carbon asset formula is configured to:
the first emission abatement carbon asset formula is configured to:
the first emission abatement carbon asset formula is configured to:
tz1 is a first-stage emission reduction carbon asset value, C1max and Tjc1 are a first-stage emission reduction carbon asset maximum reduction output and a corresponding carbon reduction amount of the first-stage carbon emission equipment, a1 is a first-stage emission reduction optimization coefficient, Tz2 is a second-stage emission reduction carbon asset value, C2max and Tjc2 are a second-stage carbon emission equipment maximum reduction output and a corresponding carbon reduction amount, a2 is a second-stage emission reduction optimization coefficient, Tz3 is a third-stage emission reduction carbon asset value, C3max and Tjc3 are a third-stage carbon emission equipment maximum reduction output and a corresponding carbon reduction amount, a3 is a third-stage emission reduction optimization coefficient, a1, a2 and a3 are all greater than zero, the settings of a1, a2 and a3 are set based on a ratio of the maximum reduction output and the corresponding carbon reduction amount of each stage of the equipment, wherein the maximum reduction output of each stage of the carbon emission equipment is set based on an enterprise's own production reduction operating condition, and the corresponding reduction of carbon reduction energy consumption of each stage of the corresponding carbon reduction equipment,
step D, processing according to the emission reduction carbon assets of the enterprises and the output values of the equipment to obtain the optimal value of the carbon asset management output of the enterprises, and calling corresponding associated characteristic information according to the optimal value; the enterprise obtains an optimal output value according to calculation, the optimal output value is the emission reduction amount corresponding to different equipment, and the enterprise does not have a way to collect technology to complete emission reduction, so that relevant associated characteristic information can be called through the emission reduction amount, the associated characteristic information can be used as an index to obtain a corresponding emission reduction technology, for example, the emission reduction technology corresponding to the equipment A, and a plurality of technologies and implementation modes can be used as references according to different emission reduction amounts.
Referring to fig. 4, in step D1, the first output value and the first carbon emission reduction asset value are substituted into the first carbon emission formula to obtain a first output value; the first stage output value represents a preferred output value of the first stage plant based on consideration of the output value and emission reduction.
Substituting the second output value and the second emission reduction carbon asset value into a second carbon emission formula to obtain a second output value; the second stage output value represents a preferred output value of the second stage equipment based on consideration of the output value and emission reduction.
And substituting the third yield value and the third stage emission reduction carbon asset value into a third stage carbon emission formula to obtain a third stage yield value. The tertiary output value represents a preferred output value of the tertiary plant based on consideration of the output value and emission reduction.
The first stage carbon emission formula is configured as:
the second stage carbon emission formula is configured as:
the second stage carbon emission formula is configured as:
wherein Cc1 is a first-stage output value, Cz1 is a first output value, b1 is a first output proportion value, Cc2 is a second-stage output value, Cz2 is a second output value, b2 is a second output proportion value, Cc3 is a third-stage output value, Cz3 is a third output value, b1 is a third output proportion value, wherein the first output value, the second output value and the third output value are based on the output benefits of each enterprise in the production processCorresponding to the production value of each level of equipment, b1, b2 and b3 are all larger than zero based on the production comprehensive setting of each enterprise.
Step D2, adding the first-stage optimal output value, the second-stage optimal output value and the third-stage optimal output value to obtain a first carbon emission total value; and substituting the first total carbon emission value and the quota carbon asset into a quota over ratio formula to obtain a quota difference value.
The quota-over-ratio formula is configured as: pc ═ c1 × (Tpz 1-Tpe); where Pc is a quota difference value, Tpz1 is a first total carbon emission value, Tpe is a quota carbon asset, and c1 is a quota difference conversion coefficient. c1 is greater than zero, c1 is used for balancing the difference between the first total carbon emission value and the quota carbon asset, and if the first total carbon emission value is greater than the quota carbon asset and reaches a certain value, carbon emission reduction needs to be performed through equipment of the enterprise.
Step D3, when the quota difference value is greater than the first quota difference threshold; at this point the carbon emissions of the enterprise are already greater than government matched carbon emissions, and therefore self-adjusting proportions of each need to be selected from primary, secondary and tertiary plants. The first quota difference threshold represents a highest overproof carbon emission value of the enterprise, and if the quota difference value is larger than the first quota difference threshold, carbon emission reduction needs to be performed by regulating and controlling equipment of the enterprise.
Substituting the quota difference value and the first-stage output value into a first-stage optimal output formula to obtain a first-stage optimal output value, substituting the quota difference value and the second-stage output value into a second-stage optimal output formula to obtain a second-stage optimal output value, and substituting the quota difference value and the third-stage output value into a third-stage optimal output formula to obtain a third-stage optimal output value; and adding the first-stage optimal output value, the second-stage optimal output value and the third-stage optimal output value to obtain a carbon asset management output optimal value.
The first-stage optimal yield formula is configured as:
the first-stage optimal yield formula is configured as:
the first-stage optimal yield formula is configured as:
czy1 is a first-stage optimal yield value, d1 is a first optimal yield coefficient, Czy2 is a second-stage optimal yield value, d2 is a second optimal yield coefficient, Czy3 is a third-stage optimal yield value, and d3 is a third optimal yield coefficient, wherein d1, d2 and d3 are all larger than zero, and the set standard is determined according to the proportion between the optimal yield value and the quota difference value of each stage of equipment.
And E, the cloud server generates a request according to the associated characteristic information to obtain a corresponding production key, and generates a corresponding emission reduction strategy according to the output optimal value. And step E, obtaining a corresponding production key according to the emission reduction request, and then realizing the sharing of the emission reduction information technology by unlocking the local ciphertext, as an optimal choice, setting an unlocking grade for the production key, wherein the requested enterprise can select the corresponding unlocking grade to disclose different contents, and the emission reduction technology process is shared, if the corresponding effect is actually achieved, and the emission reduction strategy is formed by summarizing the enterprise production information under the permission of the requested enterprise. Preferably, the carbon currency is configured for the enterprise corresponding to the emission reduction strategy according to the emission reduction amount of the enterprise corresponding to the selected emission reduction strategy. Preferably, the step E includes a step E1 of configuring a theoretical emission reduction value for each emission reduction strategy, a step E2 of generating an actual emission reduction value according to an actual emission reduction amount after the emission reduction strategy is executed, and a step E3 of correcting the theoretical emission reduction value according to a difference between the theoretical emission reduction value and the actual emission reduction value.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A carbon asset management method based on artificial intelligence and a block chain technology is characterized by comprising the following steps:
step A, acquiring quota carbon assets obtained by enterprise distribution;
step B, generating equipment production information and equipment emission information in real time; the equipment production information reflects the production working state of equipment corresponding to an enterprise, and the equipment emission information reflects the carbon emission condition of the equipment corresponding to the enterprise; generating associated characteristic information according to the association relation corresponding to the equipment emission information and the equipment production information, and encrypting the equipment production information to generate a production ciphertext and a production key; sending the production ciphertext to a plurality of different terminals where enterprises are located, taking the associated characteristic information as an index, and simultaneously producing a secret key to be stored locally;
c, training the cloud server side according to the equipment emission information and the equipment production information to generate a theoretical emission model, uploading the equipment production information in real time by a terminal where the enterprise is located to obtain the theoretical emission information, calculating the emission reduction amount of the equipment according to the difference value of the theoretical emission information and the equipment emission information, and obtaining the emission reduction carbon assets of the enterprise according to the emission reduction amount of the equipment;
step D, processing according to the emission reduction carbon assets of the enterprises and the output values of the equipment to obtain the optimal value of the carbon asset management output of the enterprises, and calling corresponding associated characteristic information according to the optimal value;
and E, the cloud server generates a request according to the associated characteristic information to obtain a corresponding production key, and generates a corresponding emission reduction strategy according to the output optimal value.
2. The artificial intelligence and blockchain technology based carbon asset management method according to claim 1, wherein the equipment production information includes an equipment production value, the equipment emission information includes an equipment carbon emission value, and the step B further includes the sub-steps of:
a step B1, wherein the step B1 includes dividing the carbon emission facility of the enterprise; dividing the equipment with the carbon emission amount greater than or equal to a first emission threshold value into first-stage carbon emission equipment; dividing the equipment with the carbon emission amount greater than or equal to a second emission threshold value and smaller than a first emission threshold value into second-stage carbon emission equipment; dividing the carbon emission equipment with the carbon emission amount less than the second emission threshold into third-stage carbon emission equipment;
step B2, the step B2 includes obtaining a first yield value of maximum output of the first stage carbon emission facility, a second yield value of maximum output of the second stage carbon emission facility, and a third yield value of maximum output of the third stage carbon emission facility;
step B3, the step B3 includes obtaining a first stage carbon emission plant maximum reduction throughput and a corresponding carbon reduction capacity, a second stage carbon emission plant maximum reduction throughput and a corresponding carbon reduction capacity, and a third stage carbon emission plant maximum reduction throughput and a corresponding carbon reduction capacity.
3. The method for managing carbon assets based on artificial intelligence and blockchain technology as claimed in claim 2, wherein said step C further comprises the following sub-steps:
step C1, wherein the step C1 comprises substituting the maximum reduction output of the first-stage carbon emission equipment and the corresponding carbon reduction amount into a first emission reduction carbon asset formula to obtain a first-stage emission reduction carbon asset value;
step C2, wherein the step C2 comprises substituting the maximum reduction output of the secondary carbon emission equipment and the corresponding carbon reduction amount into a secondary emission reduction carbon asset formula to obtain a secondary emission reduction carbon asset value;
and C3, wherein the step C3 comprises the step of substituting the maximum reduction output of the third-level carbon emission equipment and the corresponding carbon reduction amount into a third emission reduction carbon asset formula to obtain a third-level emission reduction carbon asset value.
4. The method of claim 3, wherein the first emission reduction carbon asset formula is configured to:
the first emission abatement carbon asset formula is configured to:
the first emission abatement carbon asset formula is configured to:
tz1 is a first-stage emission reduction carbon asset value, C1max and Tjc1 are a maximum reduction output and a corresponding carbon emission reduction capacity of a first-stage carbon emission device, a1 is a first-stage emission reduction optimization coefficient, Tz2 is a second-stage emission reduction carbon asset value, C2max and Tjc2 are a maximum reduction output and a corresponding carbon emission reduction capacity of a second-stage carbon emission device, a2 is a second-stage emission reduction optimization coefficient, Tz3 is a third-stage emission reduction carbon asset value, C3max and Tjc3 are a maximum reduction output and a corresponding carbon emission reduction capacity of a third-stage carbon emission device, and a3 is a third-stage emission reduction optimization coefficient.
5. The method of claim 4, wherein the step D further comprises a step D1, and the step D1 comprises substituting the first yield value and the first emission-reduction carbon asset value into a first carbon emission formula to obtain a first output value;
substituting the second output value and the second emission reduction carbon asset value into a second carbon emission formula to obtain a second output value;
and substituting the third yield value and the third stage emission reduction carbon asset value into a third stage carbon emission formula to obtain a third stage yield value.
6. A human-based system as claimed in claim 5The carbon asset management method of the industrial intelligence and block chain technology is characterized in that the first-stage carbon emission formula is configured as follows:
the second stage carbon emission formula is configured as:
the second stage carbon emission formula is configured as:
wherein Cc1 is a first-stage output value, Cz1 is a first output value, b1 is a first output proportion value, Cc2 is a second-stage output value, Cz2 is a second output value, b2 is a second output proportion value, Cc3 is a third-stage output value, Cz3 is a third output value, and b1 is a third output proportion value.
7. The method of claim 6, wherein step D further comprises step D2, and step D2 comprises adding the first level optimal yield value, the second level optimal yield value, and the third level optimal yield value to obtain a first total carbon emission value;
and substituting the first total carbon emission value and the quota carbon asset into a quota over ratio formula to obtain a quota difference value.
8. The method of claim 7, wherein the quota over ratio formula is configured to: pc ═ c1 × (Tpz 1-Tpe); where Pc is a quota difference value, Tpz1 is a first total carbon emission value, Tpe is a quota carbon asset, and c1 is a quota difference conversion coefficient.
9. The method of claim 8, wherein said step D further comprises a step D3, said step D3 comprising when the quota difference value is greater than a first quota difference threshold; at this point the carbon emissions of the enterprise are already greater than government matched carbon emissions, and therefore self-adjusting proportions of each need to be selected from primary, secondary and tertiary plants.
Substituting the quota difference value and the first-stage output value into a first-stage optimal output formula to obtain a first-stage optimal output value, substituting the quota difference value and the second-stage output value into a second-stage optimal output formula to obtain a second-stage optimal output value, and substituting the quota difference value and the third-stage output value into a third-stage optimal output formula to obtain a third-stage optimal output value;
and adding the first-stage optimal output value, the second-stage optimal output value and the third-stage optimal output value to obtain a carbon asset management output optimal value.
10. The method of claim 9, wherein the first-stage optimal yield formula is configured to:
the first-stage optimal yield formula is configured as:
the first-stage optimal yield formula is configured as:
czy1 is the first-level optimal output value, d1 is the first optimal output coefficient, Czy2 is the second-level optimal output value, d2 is the second optimal output coefficient, Czy3 is the third-level optimal output value, and d3 is the third optimal output coefficient.
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