CN116402661A - Carbon asset management system - Google Patents
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Abstract
The invention provides a carbon asset management system, which screens and obtains the management data of a target object related to carbon activities, so as to obtain carbon activity track data, and is used for carrying out whole-course characterization on the carbon activities of the target object, accurately estimating carbon emission information corresponding to the carbon activities of the target object, judging whether the current carbon emission quota asset of the target object is sufficient or not according to the carbon emission quota asset information of the target object, thereby providing reliable basis for carrying out carbon asset transaction on the target object, adaptively adjusting the carbon activity realization state of the target object, facilitating the target object to save the carbon emission quota asset consumption of the target object, realizing the optimal configuration of the carbon emission quota asset, pertinently improving the management activities of the target object, and improving the predictability and reliability of carbon asset management.
Description
Technical Field
The invention relates to the technical field of carbon resource treatment, in particular to a carbon asset management system.
Background
With the growing concern about climate problems, carbon emissions have become an important reference factor in human daily life. The business production activities of enterprises are a main source of carbon emissions, and in order to suppress the development of climate warming, it is necessary to control the carbon emissions of the business production activities of enterprises. Therefore, the corresponding carbon emission quota is set for the enterprise, so that the enterprise can plan the self-operation production activity according to the self-allocated carbon emission quota in daily operation production activity. Meanwhile, a novel transaction activity of carbon transaction is derived, namely, corresponding transaction of carbon assets such as carbon emission quota and the like can be carried out among enterprises, so that circulation of the carbon emission quota is realized. The existing enterprises directly conduct transactions of carbon emission quota, do not combine with actual operation and production activities of the enterprises, conduct predictive transaction planning on the carbon emission quota, and reduce predictability and reliability of enterprise carbon asset management.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention provides a carbon asset management system, which screens and obtains the operation data of a target object related to carbon activities, so as to obtain carbon activity track data, and is used for carrying out whole-course characterization on the carbon activities of the target object, so as to accurately estimate carbon emission information corresponding to the carbon activities of the target object, judge whether the current carbon emission quota asset of the target object is sufficient or not according to the carbon emission quota asset information of the target object, thereby providing reliable basis for carrying out carbon asset transaction on the target object, adaptively adjusting the carbon activity realization state of the target object, facilitating the target object to save the carbon emission quota asset consumption of the target object, realizing the optimal configuration of the carbon emission quota asset, pertinently improving the operation activities of the target object, and improving the predictability and reliability of carbon asset management.
The present invention provides a carbon asset management system comprising:
the management data collection module is used for obtaining management data of the target object in a preset time period;
the management data screening module is used for carrying out identification processing on the management data and screening the management data to obtain the management data related to the carbon activities;
the carbon activity track analysis module is used for analyzing and processing the operation data related to the carbon activity to obtain carbon activity track data related to the operation data of the carbon activity;
the carbon emission estimation module is used for carrying out big data prediction processing on the carbon activity track data and estimating carbon emission information corresponding to carbon activity of the target object in a preset time period;
the carbon asset orchestration module is used for judging whether the target object is in a carbon emission quota asset sufficient state currently according to the carbon emission information and the carbon emission quota asset information of the target object;
the carbon asset transaction management module is used for carrying out carbon asset transaction according to the judging result of the sufficient state of the carbon emission quota asset;
and the carbon activity adjusting module is used for adjusting the carbon activity realization state of the target object according to the judging result of the carbon emission quota asset sufficiency state.
Further, the business data collection module obtains business data of the target object within a preset time period, including:
acquiring historical operation data of a target object, and extracting average occurrence frequency of specific type operation activity behaviors of the target object from the historical operation data;
determining the length of a preset time period corresponding to the business data of the obtained target object based on the average occurrence frequency of the specific type historical business activity behaviors, so that the business data of the obtained target object at least comprises record data corresponding to a preset number of characteristic type business activity behaviors;
and performing redundant data elimination processing on the obtained business data of the target object in the preset time period.
Further, the operation data screening module performs identification processing on the operation data, screens the operation data to obtain operation data related to carbon activities, and includes:
acquiring respective data content characteristics of all business sub-data contained in the business data, and classifying all business sub-data according to the data content characteristics to obtain business sub-data sets respectively corresponding to different types of business activities;
and carrying out keyword recognition processing on all the business sub-data contained in the business sub-data set, if the business sub-data contains the preset keywords, determining that the corresponding business sub-data set belongs to the business sub-data set related to the carbon activity, and marking the business sub-data containing the preset keywords.
Further, the carbon activity trajectory analysis module analyzes and processes the operation data related to the carbon activity to obtain carbon activity trajectory data related to the operation data of the carbon activity, and the analysis module comprises:
analyzing and processing the management data related to the carbon activities, and determining the characteristic information of the carbon activities of all management sub-data contained in the management data related to the carbon activities; wherein the carbon activity characteristic information comprises carbon activity type information and carbon activity occurrence time information;
and based on the carbon activity characteristic information, integrating and arranging all business sub-data belonging to the same carbon activity according to the sequence of the occurrence time of the carbon activity to form carbon activity track data.
Further, the carbon emission amount estimation module performs big data prediction processing on the carbon activity track data, estimates carbon emission information corresponding to carbon activity of a target object in a preset time period, and includes:
acquiring a carbon activity data training set, and classifying the carbon activity data training set based on the carbon activity type to obtain a carbon activity data training subset related to different types of carbon activities;
extracting data characteristics of each piece of carbon activity data contained in each piece of carbon activity data training subset, and constructing and obtaining feature vectors of each piece of carbon activity data training subset; wherein the data characteristic refers to the carbon emission corresponding to each carbon activity data;
training the deep learning model based on the feature vectors of all the carbon activity data training subsets to obtain a carbon emission estimated model;
and carrying out big data prediction processing on the carbon activity track data by using the carbon emission prediction model, estimating carbon emission information corresponding to all carbon activities of the target object in a preset time period, and carrying out identification processing on the carbon activity names of the carbon emission information.
Further, the carbon emission estimation module further selects other carbon activity data of a plurality of known carbon emission information different from the data in the carbon activity data training subset, and performs accuracy verification on the carbon emission estimation model, wherein the process is as follows:
step S1, verifying whether the selected other carbon activity data meets the requirement different from the data in the carbon activity data training subset according to the selected other carbon activity data of a plurality of known carbon emission information and the carbon activity data in the carbon activity data training subset by using the following formula (1),
in the above formula (1), R (a) represents a determination value of whether the selected a-th other carbon activity data satisfies a requirement different from that of the data in the carbon activity data training subset; s is S 16 (a) A 16-ary form representing selected a-th other carbon activity data; z is Z 16 (k) A 16-ary form representing the kth carbon activity data in the training subset of carbon activity data; [] 10 Representing the conversion of the value in brackets to a 10-ary number; k represents the total number of carbon activity data in the carbon activity data training subset;
if R (a) =1, then it indicates that the selected a-th other carbon activity data meets the requirement;
if R (a) =0, then it indicates that the selected a-th other carbon activity data does not meet the requirement;
reserving other carbon activity data of the known carbon emission information meeting the requirements, and eliminating other carbon activity data of the known carbon emission information not meeting the requirements;
step S2, estimating the carbon emission information in the preset time period by using the reserved other carbon activity data of the known carbon emission information and the carbon emission estimation model, and comparing the carbon emission information in the preset time period with the known carbon emission information according to the estimated carbon emission information in the preset time period by using the following formula (2) to obtain the estimation accuracy of the carbon emission estimation model,
in the above formula (2), X represents the estimation accuracy of the carbon emission estimation model; s is(s) 16 (i) Representing the satisfaction of the screening in the step S1The 16 th form of the required i-th other carbon activity data; m [ s ] 16 (i)]The carbon emission estimated model is used for estimating the carbon emission of the ith other carbon activity data meeting the requirements screened in the step A1 in a preset time period; m [ s ] 16 (i)]Representing known carbon emission in a preset time period corresponding to the ith other carbon activity data meeting the requirements screened in the step S1; y represents a preset accurate threshold, namely that the estimated value and the actual value are not different, namely that the estimation is accurate, and otherwise, the estimation is inaccurate; the absolute value is calculated by the expression; q { } represents the judging function, if the expression in the brackets is true, the function value of the judging function is 1, and if the expression in the brackets is false, the function value of the judging function is 0; n represents the total number of other carbon activity data meeting the requirements screened in the step S1;
step S3, judging whether the carbon emission estimation model needs to continue iteration or not according to the estimation accuracy of the carbon emission estimation model by using the following formula (3), if so, controlling the minimum number of iterations,
in the above formula (3), G represents the minimum number of continuing iterations of the carbon emission estimation model; g 0 Representing the minimum number of iterations of the preset model, namely, if the carbon emission estimation model needs to be iterated, the minimum number of iterations is not less than G 0 Secondary times;
representing an upward rounding.
Further, the carbon asset orchestration module determines, according to the carbon emission information and the carbon emission allowance asset information of the target object, whether the target object is currently in a carbon emission allowance asset sufficiency state, including:
comparing the carbon emission information corresponding to all the carbon activities with the carbon emission allowance asset of the target object, and judging that the carbon emission amount corresponding to each carbon activity is less than or equal to the carbon emission allowance asset value of the carbon activity; if yes, determining that the target object is in a carbon emission quota sufficient state under the corresponding carbon activity; if not, determining that the target object is not in a carbon emission quota sufficient state under the corresponding carbon activity;
performing secondary allocation of carbon emission allowance assets to all carbon activities not in a carbon emission allowance asset sufficiency state based on remaining carbon emission allowance asset values of all carbon activities in the carbon emission allowance asset sufficiency state; and judging whether the whole target object is in a carbon emission quota asset sufficiency state or not according to the secondary distribution result.
Further, the carbon asset transaction management module is configured to perform a carbon asset transaction according to a result of determining the sufficient status of the carbon emission quota asset, and includes:
if the whole target object is in a carbon emission quota asset sufficient state, generating a carbon asset transaction offer according to the total residual value of the current carbon emission quota asset of the target object; according to the carbon emission quota asset holding condition of other target objects, sending the carbon asset transaction offer to other target objects meeting the preset carbon emission quota asset holding condition;
if the whole target object is not in the carbon emission quota asset sufficient state, generating a carbon asset transaction request according to the current carbon emission quota asset total gap value of the target object; and according to the carbon emission quota asset consumption conditions of other target objects, the carbon asset transaction request can be sent to the other target objects meeting the preset carbon emission quota asset consumption conditions.
Further, the carbon activity adjustment module adjusts a carbon activity implementation state of a target object according to a determination result of the carbon emission quota asset sufficiency state, including:
if the whole target object is not in the carbon emission quota asset sufficient state currently, acquiring a carbon activity type of which the target object is not in the carbon emission quota asset sufficient state currently, and reducing the scale and/or the initiation frequency of the carbon activity corresponding to the carbon activity type.
Compared with the prior art, the carbon asset management system screens and obtains the management data of the carbon activity related to the target object, so as to obtain the carbon activity track data, and the carbon asset management system is used for carrying out the whole-course characterization on the carbon activity of the target object, so as to accurately estimate the carbon emission information corresponding to the carbon activity of the target object, judge whether the current carbon emission quota asset of the target object is sufficient or not according to the carbon emission quota asset information of the target object, thereby providing reliable basis for carrying out carbon asset transaction on the target object, adaptively adjusting the carbon activity realization state of the target object, facilitating the target object to save the carbon emission quota asset consumption of the target object, realizing the optimal configuration of the carbon emission quota asset, pertinently improving the management activity of the target object, and improving the predictability and reliability of carbon asset management.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a carbon asset management system according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a schematic structure of a carbon asset management system according to an embodiment of the present invention is shown. The carbon asset management system includes:
the management data collection module is used for obtaining management data of the target object in a preset time period;
the management data screening module is used for carrying out identification processing on the management data and screening the management data to obtain the management data related to the carbon activity;
the carbon activity track analysis module is used for analyzing and processing the operation data related to the carbon activity to obtain carbon activity track data related to the operation data of the carbon activity;
the carbon emission estimation module is used for carrying out big data prediction processing on the carbon activity track data and estimating carbon emission information corresponding to carbon activity of the target object in a preset time period;
the carbon asset orchestration module is used for judging whether the target object is in a carbon emission quota asset sufficient state currently according to the carbon emission information and the carbon emission quota asset information of the target object;
the carbon asset transaction management module is used for carrying out carbon asset transaction according to the judging result of the sufficient state of the carbon emission quota asset;
and the carbon activity adjusting module is used for adjusting the carbon activity realization state of the target object according to the judging result of the carbon emission quota asset sufficiency state.
The beneficial effects of the technical scheme are as follows: the carbon asset management system screens and obtains the operation data of the target object related to the carbon activity, so as to obtain the carbon activity track data, is used for carrying out the whole-course characterization on the carbon activity of the target object, accurately estimates the carbon emission information corresponding to the carbon activity of the target object, and combines the carbon emission quota asset information of the target object to judge whether the current carbon emission quota asset of the target object is sufficient or not, thereby providing reliable basis for carrying out carbon asset transaction on the target object, and also can adaptively adjust the carbon activity realization state of the target object, so that the target object is convenient to save the carbon emission quota asset consumption of the target object, realize the optimal configuration of the carbon emission quota asset, improve the operation activity of the target object in a targeted way, and improve the predictability and reliability of carbon asset management.
Preferably, the business data collection module obtains business data of the target object within a preset time period, including:
acquiring historical operation data of a target object, and extracting average occurrence frequency of specific type operation activity behaviors of the target object from the historical operation data;
determining the length of a preset time period corresponding to the business data of the obtained target object based on the average occurrence frequency of the specific type of historical business activity behaviors, so that the business data of the obtained target object at least comprises record data corresponding to a preset number of characteristic type business activity behaviors;
and performing redundant data elimination processing on the obtained business data of the target object in the preset time period.
The beneficial effects of the technical scheme are as follows: the target objects such as enterprises relate to different business categories, so that corresponding business data are generated. The whole process from the initiation to the end of each operation activity generates operation data matched with the operation activity, and the carbon emission track condition of the operation activity can be obtained by analyzing the operation data. However, not all the operation activities may generate carbon emissions, and the average occurrence frequency of the specific type of operation activities (i.e., how long the specific type of operation activities occur in average intervals) in the history operation process of the target object is determined by first acquiring the history operation data of the target object and then performing identification screening on the history operation data for the specific type of operation activities (i.e., the operation activities that generate carbon emissions). And determining the length of a preset time period corresponding to the operation data of the obtained target object by taking the average occurrence frequency of the operation activities of the specific type as a reference, and ensuring that the operation data obtained in the preset time period at least comprises the record data corresponding to the operation activities which can generate carbon emission, thereby ensuring the effectiveness of the obtained operation data.
Preferably, the operation data screening module performs identification processing on the operation data, and screens the operation data to obtain the operation data related to the carbon activity, including:
acquiring respective data content characteristics of all business sub-data contained in the business data, and classifying and processing all business sub-data according to the data content characteristics to obtain business sub-data sets respectively corresponding to different types of business activities;
and carrying out keyword recognition processing on all business sub-data contained in the business sub-data set, if the business sub-data contains preset keywords, determining that the corresponding business sub-data set belongs to the business sub-data set related to the carbon activity, and marking the business sub-data containing the preset keywords.
The beneficial effects of the technical scheme are as follows: by the method, the business sub-data is classified based on the data content characteristics of all the business sub-data contained in the obtained business data, wherein the data content characteristics can be, but are not limited to, the behavior name content of the business activity behavior related to each business sub-data, and all the business sub-data of each business sub-data set obtained by classification belong to the same business activity behavior, so that a comprehensive basis is provided for the carbon activity condition of the subsequent business activity behavior. In addition, keyword recognition processing is performed on all the business sub-data contained in each business sub-data set, and whether the business sub-data contains keywords associated with carbon activities or not is determined, so that the part, which relates to the carbon activities, in each business sub-data can be selectively marked.
Preferably, the carbon activity trajectory analysis module analyzes and processes the operation data related to the carbon activity to obtain carbon activity trajectory data related to the operation data of the carbon activity, and the analysis module comprises:
analyzing and processing the management data related to the carbon activities, and determining the carbon activity characteristic information of all management sub-data contained in the management data related to the carbon activities; wherein the carbon activity characteristic information comprises carbon activity type information and carbon activity occurrence time information;
based on the carbon activity characteristic information, all business sub-data belonging to the same carbon activity are integrated and arranged according to the sequence of the occurrence time of the carbon activity to form carbon activity track data.
The beneficial effects of the technical scheme are as follows: the process of initiating the business activity by the target object involves a plurality of different action steps, each action step can correspondingly generate business sub-data, and the carbon activity characteristic information of each business sub-data is extracted, so that the carbon activity condition of each business sub-data can be accurately identified, and the carbon activity track data (namely, the activity track data of carbon emission generated by the business activity initiated by the target object) can be integrated and arranged by all the business sub-data, thereby comprehensively and accurately representing the carbon activity of the target object.
Preferably, the carbon emission amount estimation module performs big data prediction processing on the carbon activity trajectory data, estimates carbon emission information corresponding to carbon activity of the target object in a preset time period, and includes:
acquiring a carbon activity data training set, classifying the carbon activity data training set based on the carbon activity type, and obtaining a carbon activity data training subset related to different types of carbon activities;
extracting data characteristics of each piece of carbon activity data contained in each piece of carbon activity data training subset, and constructing and obtaining feature vectors of each piece of carbon activity data training subset; wherein the data characteristic refers to the carbon emission corresponding to each carbon activity data;
training the deep learning model based on the feature vectors of all the carbon activity data training subsets to obtain a carbon emission estimated model;
and carrying out big data prediction processing on the carbon activity track data by utilizing the carbon emission prediction model, estimating carbon emission information corresponding to all carbon activities of the target object in a preset time period, and carrying out identification processing on the carbon activity names of the carbon emission information.
The beneficial effects of the technical scheme are as follows: by the method, the deep learning model is trained by taking the carbon activity data training set as a reference, so that the carbon emission prediction model obtained by training can accurately predict and distinguish marks the carbon emission according to different types of operation activities of the target object, and a reliable basis is provided for subsequent carbon asset management.
Preferably, the carbon emission estimation module further selects other carbon activity data of a plurality of known carbon emission information different from the data in the training subset of carbon activity data, and performs accuracy verification on the carbon emission estimation model, wherein the process is as follows:
step S1, verifying whether the selected other carbon activity data meets the requirement different from the data in the carbon activity data training subset according to the selected other carbon activity data of a plurality of known carbon emission information and the carbon activity data in the carbon activity data training subset by using the following formula (1),
in the above formula (1), R (a) represents a determination value of whether the selected a-th other carbon activity data satisfies a requirement different from that of the data in the carbon activity data training subset; s is S 16 (a) A 16-ary form representing selected a-th other carbon activity data; z is Z 16 (k) A 16-ary form representing the kth carbon activity data in the training subset of carbon activity data; [] 10 Representing the conversion of the value in brackets to a 10-ary number; k represents the total number of carbon activity data in the carbon activity data training subset;
if R (a) =1, then it indicates that the selected a-th other carbon activity data meets the requirement;
if R (a) =0, then it indicates that the selected a-th other carbon activity data does not meet the requirement;
reserving other carbon activity data of the known carbon emission information meeting the requirements, and eliminating other carbon activity data of the known carbon emission information not meeting the requirements;
step S2, estimating the carbon emission information in the preset time period by using the reserved other carbon activity data of the known carbon emission information and using the carbon emission estimation model, and then comparing the carbon emission information in the preset time period with the known carbon emission information according to the estimated carbon emission information in the preset time period by using the following formula (2) to obtain the estimation accuracy of the carbon emission estimation model,
in the above formula (2), X represents the estimation accuracy of the carbon emission estimation model; s is(s) 16 (i) A 16 th system form of the i-th other carbon activity data which meets the requirements and is screened in the step S1 is shown; m [ s ] 16 (i)]The carbon emission estimated model is used for estimating the carbon emission of the ith other carbon activity data meeting the requirements screened in the step A1 in a preset time period; m [ s ] 16 (i)]Representing known carbon emission in a preset time period corresponding to the ith other carbon activity data meeting the requirements screened in the step S1; y represents a preset accurate threshold, namely that the estimated value and the actual value are not different, namely that the estimation is accurate, and otherwise, the estimation is inaccurate; the absolute value is calculated by the expression; q { } represents the judging function, if the expression in the brackets is true, the function value of the judging function is 1, and if the expression in the brackets is false, the function value of the judging function is 0; n represents the total number of other carbon activity data meeting the requirements screened in the step S1;
step S3, judging whether the carbon emission estimation model needs to continue iteration according to the estimation accuracy of the carbon emission estimation model by using the following formula (3), if so, controlling the minimum number of iterations,
in the above formula (3), G represents the minimum number of continuous iterations of the carbon emission estimation model; g 0 Representing the minimum number of iterations of the predetermined model, i.e., if the carbon emission estimation model needs to be iteratedThe iteration times are least than G 0 Secondary times;
representing an upward rounding.
The beneficial effects of the technical scheme are as follows: using the above formula (1), verifying whether the selected other carbon activity data meets the different requirements with the data in the carbon activity data training subset according to the selected other carbon activity data of the plurality of known carbon emission information and the carbon activity data in the carbon activity data training subset, thereby ensuring the difference between the checked data and the sample data and ensuring the reliability of the check; then, by utilizing the formula (2), according to the estimated carbon emission information in the preset time period and the known carbon emission information, the estimated accuracy of the carbon emission estimated model is obtained, so that the estimated condition of the model is known, and the model is convenient to further optimize; and finally, judging whether the carbon emission estimated model needs to be iterated continuously or not according to the estimated accuracy of the carbon emission estimated model by utilizing the formula (3), and if so, controlling the minimum number of iterations of the carbon emission estimated model, so as to increase the reliable iteration number and ensure the estimated accuracy of the model.
Preferably, the carbon asset orchestration module determines, according to the carbon emission information and the carbon emission allowance asset information of the target object, whether the target object is currently in a carbon emission allowance asset sufficiency state, including:
comparing the carbon emission information corresponding to all the carbon activities with the carbon emission allowance asset of the target object, and judging that the carbon emission amount corresponding to each carbon activity is less than or equal to the carbon emission allowance asset value of the carbon activity; if yes, determining that the target object is in a carbon emission quota sufficient state under the corresponding carbon activity; if not, determining that the target object is not in a carbon emission quota sufficient state under the corresponding carbon activity;
performing secondary allocation of carbon emission allowance assets to all carbon activities not in a carbon emission allowance asset sufficiency state based on remaining carbon emission allowance asset values of all carbon activities in the carbon emission allowance asset sufficiency state; and judging whether the whole target object is in a carbon emission quota asset sufficient state or not according to the result of the secondary distribution.
The beneficial effects of the technical scheme are as follows: by the method, the carbon emission information corresponding to all the carbon activities is compared with the carbon emission quota asset of the target object, whether the carbon emission quota asset of the target object is sufficient or not is comprehensively judged, and the carbon emission quota asset of different operation activities of the target object is secondarily distributed, so that the balanced distribution of the carbon emission quota asset in the target object is realized.
Preferably, the carbon asset transaction management module is configured to perform a carbon asset transaction according to a result of determining the sufficient status of the carbon emission quota asset, and includes:
if the whole target object is in a carbon emission quota asset sufficient state, generating a carbon asset transaction offer according to the total residual value of the current carbon emission quota asset of the target object; according to the carbon emission quota asset holding condition of other target objects, sending the carbon asset transaction offer to other target objects meeting the preset carbon emission quota asset holding condition; the other target object satisfying the predetermined carbon emission allowance asset holding condition may be, but is not limited to, a target object that is not currently in a carbon emission allowance asset sufficient state as a whole;
if the whole target object is not in the carbon emission quota asset sufficient state, generating a carbon asset transaction request according to the current carbon emission quota asset total gap value of the target object; according to the carbon emission quota asset consumption conditions of other target objects, the carbon asset transaction request can be sent to the other target objects meeting the preset carbon emission quota asset consumption conditions; the other target object satisfying the preset carbon credit asset consumption condition may be, but is not limited to, a target object that is currently in a carbon credit asset sufficiency state as a whole.
The beneficial effects of the technical scheme are as follows: by the method, under the condition that the whole object is in the carbon emission quota asset sufficient state and the whole object is not in the carbon emission quota asset sufficient state, carbon asset transaction offer and carbon asset transaction request are carried out, accurate carbon asset transaction is conveniently carried out on other proper object objects, and transaction circulation efficiency and accuracy of the carbon emission quota asset among different object objects are improved.
Preferably, the carbon activity adjustment module adjusts the carbon activity implementation state of the target object according to the judging result of the carbon emission quota asset sufficiency state, including:
if the whole target object is not in the carbon emission quota asset sufficient state currently, acquiring a carbon activity type of which the target object is not in the carbon emission quota asset sufficient state currently, and reducing the scale and/or the initiation frequency of the carbon activity corresponding to the carbon activity type.
The beneficial effects of the technical scheme are as follows: by the method, when the whole target object is not in the carbon emission allowance asset sufficient state currently, the carbon activity behaviors of the target object which are not in the carbon emission allowance asset sufficient state currently are compressed in the activity scale and/or the initiation frequency, so that the scale and/or the occurrence frequency of the corresponding carbon activity behaviors are reduced, and the corresponding carbon emission is reduced.
As can be seen from the foregoing embodiments, the carbon asset management system screens and obtains the operation data of the target object related to the carbon activity, so as to obtain the carbon activity track data, which is used for performing the whole-process characterization on the carbon activity of the target object, so as to accurately estimate the carbon emission information corresponding to the carbon activity of the target object, and determine whether the current carbon emission quota asset of the target object is sufficient or not according to the carbon emission quota asset information of the target object, thereby providing a reliable basis for the target object to perform the carbon asset transaction, and also adaptively adjusting the carbon activity realization state of the target object, so that the target object is convenient to save the carbon emission quota asset consumption of itself, realize the optimal configuration of the carbon emission quota asset, improve the operation activity of the target object with pertinence, and improve the predictability and reliability of the carbon asset management.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (9)
1. A carbon asset management system, comprising:
the management data collection module is used for obtaining management data of the target object in a preset time period;
the management data screening module is used for carrying out identification processing on the management data and screening the management data to obtain the management data related to the carbon activities;
the carbon activity track analysis module is used for analyzing and processing the operation data related to the carbon activity to obtain carbon activity track data related to the operation data of the carbon activity;
the carbon emission estimation module is used for carrying out big data prediction processing on the carbon activity track data and estimating carbon emission information corresponding to carbon activity of the target object in a preset time period;
the carbon asset orchestration module is used for judging whether the target object is in a carbon emission quota asset sufficient state currently according to the carbon emission information and the carbon emission quota asset information of the target object;
the carbon asset transaction management module is used for carrying out carbon asset transaction according to the judging result of the sufficient state of the carbon emission quota asset;
and the carbon activity adjusting module is used for adjusting the carbon activity realization state of the target object according to the judging result of the carbon emission quota asset sufficiency state.
2. The carbon asset management system of claim 1, wherein:
the business data collection module obtains business data of a target object in a preset time period, and the business data collection module comprises:
acquiring historical operation data of a target object, and extracting average occurrence frequency of specific type operation activity behaviors of the target object from the historical operation data;
determining the length of a preset time period corresponding to the business data of the obtained target object based on the average occurrence frequency of the specific type historical business activity behaviors, so that the business data of the obtained target object at least comprises record data corresponding to a preset number of characteristic type business activity behaviors;
and performing redundant data elimination processing on the obtained business data of the target object in the preset time period.
3. The carbon asset management system of claim 1, wherein:
the management data screening module performs identification processing on the management data, screens the management data to obtain the management data related to carbon activities, and comprises the following steps:
acquiring respective data content characteristics of all business sub-data contained in the business data, and classifying all business sub-data according to the data content characteristics to obtain business sub-data sets respectively corresponding to different types of business activities;
and carrying out keyword recognition processing on all the business sub-data contained in the business sub-data set, if the business sub-data contains the preset keywords, determining that the corresponding business sub-data set belongs to the business sub-data set related to the carbon activity, and marking the business sub-data containing the preset keywords.
4. The carbon asset management system of claim 1, wherein:
the carbon activity track analysis module analyzes and processes the management data related to the carbon activity to obtain carbon activity track data related to the management data of the carbon activity, and the carbon activity track analysis module comprises:
analyzing and processing the management data related to the carbon activities, and determining the characteristic information of the carbon activities of all management sub-data contained in the management data related to the carbon activities; wherein the carbon activity characteristic information comprises carbon activity type information and carbon activity occurrence time information;
and based on the carbon activity characteristic information, integrating and arranging all business sub-data belonging to the same carbon activity according to the sequence of the occurrence time of the carbon activity to form carbon activity track data.
5. The carbon asset management system of claim 1, wherein:
the carbon emission estimation module performs big data prediction processing on the carbon activity track data, estimates carbon emission information corresponding to carbon activity of a target object in a preset time period, and comprises the following steps:
acquiring a carbon activity data training set, and classifying the carbon activity data training set based on the carbon activity type to obtain a carbon activity data training subset related to different types of carbon activities;
extracting data characteristics of each piece of carbon activity data contained in each piece of carbon activity data training subset, and constructing and obtaining feature vectors of each piece of carbon activity data training subset; wherein the data characteristic refers to the carbon emission corresponding to each carbon activity data;
training the deep learning model based on the feature vectors of all the carbon activity data training subsets to obtain a carbon emission estimated model;
and carrying out big data prediction processing on the carbon activity track data by using the carbon emission prediction model, estimating carbon emission information corresponding to all carbon activities of the target object in a preset time period, and carrying out identification processing on the carbon activity names of the carbon emission information.
6. The carbon asset management system of claim 5, wherein:
the carbon emission estimation module also selects other carbon activity data of a plurality of known carbon emission information which are different from the data in the carbon activity data training subset, and performs accuracy verification on the carbon emission estimation model, wherein the process is as follows:
step S1, verifying whether the selected other carbon activity data meets the requirement different from the data in the carbon activity data training subset according to the selected other carbon activity data of a plurality of known carbon emission information and the carbon activity data in the carbon activity data training subset by using the following formula (1),
in the above formula (1), R (a) represents a determination value of whether the selected a-th other carbon activity data satisfies a requirement different from that of the data in the carbon activity data training subset; s is S 16 (a) A 16-ary form representing selected a-th other carbon activity data; z is Z 16 (k) A 16-ary form representing the kth carbon activity data in the training subset of carbon activity data; [] 10 Representing the conversion of the value in brackets to a 10-ary number; k represents the total number of carbon activity data in the carbon activity data training subset;
if R (a) =1, then it indicates that the selected a-th other carbon activity data meets the requirement;
if R (a) =0, then it indicates that the selected a-th other carbon activity data does not meet the requirement;
reserving other carbon activity data of the known carbon emission information meeting the requirements, and eliminating other carbon activity data of the known carbon emission information not meeting the requirements;
step S2, estimating the carbon emission information in the preset time period by using the reserved other carbon activity data of the known carbon emission information and the carbon emission estimation model, and comparing the carbon emission information in the preset time period with the known carbon emission information according to the estimated carbon emission information in the preset time period by using the following formula (2) to obtain the estimation accuracy of the carbon emission estimation model,
in the above formula (2), X represents the estimation accuracy of the carbon emission estimation model; s is(s) 16 (i) A 16 th system form of the i-th other carbon activity data which meets the requirements and is screened in the step S1 is shown; m [ s ] 16 (i)]Representing the ith other carbon meeting the requirements screened in the step A1 in a preset time period by using the carbon emission estimation modelCarbon emissions of the activity data; m [ s ] 16 (i)]Representing known carbon emission in a preset time period corresponding to the ith other carbon activity data meeting the requirements screened in the step S1; y represents a preset accurate threshold, namely that the estimated value and the actual value are not different, namely that the estimation is accurate, and otherwise, the estimation is inaccurate; the absolute value is calculated by the expression; q { } represents the judging function, if the expression in the brackets is true, the function value of the judging function is 1, and if the expression in the brackets is false, the function value of the judging function is 0; n represents the total number of other carbon activity data meeting the requirements screened in the step S1;
step S3, judging whether the carbon emission estimation model needs to continue iteration or not according to the estimation accuracy of the carbon emission estimation model by using the following formula (3), if so, controlling the minimum number of iterations,
in the above formula (3), G represents the minimum number of continuing iterations of the carbon emission estimation model;
G 0 representing the minimum number of iterations of the preset model, namely, if the carbon emission estimation model needs to be iterated, the minimum number of iterations is not less than G 0 Secondary times;
representing an upward rounding.
7. The carbon asset management system of claim 1, wherein:
the carbon asset orchestration module determines, according to the carbon emission information and carbon emission allowance asset information of the target object, whether the target object is currently in a carbon emission allowance asset sufficiency state, including:
comparing the carbon emission information corresponding to all the carbon activities with the carbon emission allowance asset of the target object, and judging that the carbon emission amount corresponding to each carbon activity is less than or equal to the carbon emission allowance asset value of the carbon activity; if yes, determining that the target object is in a carbon emission quota sufficient state under the corresponding carbon activity; if not, determining that the target object is not in a carbon emission quota sufficient state under the corresponding carbon activity;
performing secondary allocation of carbon emission allowance assets to all carbon activities not in a carbon emission allowance asset sufficiency state based on remaining carbon emission allowance asset values of all carbon activities in the carbon emission allowance asset sufficiency state; and judging whether the whole target object is in a carbon emission quota asset sufficiency state or not according to the secondary distribution result.
8. The carbon asset management system of claim 1, wherein:
the carbon asset transaction management module is configured to perform a carbon asset transaction according to a result of determining the sufficient status of the carbon emission quota asset, and includes:
if the whole target object is in a carbon emission quota asset sufficient state, generating a carbon asset transaction offer according to the total residual value of the current carbon emission quota asset of the target object; according to the carbon emission quota asset holding condition of other target objects, sending the carbon asset transaction offer to other target objects meeting the preset carbon emission quota asset holding condition;
if the whole target object is not in the carbon emission quota asset sufficient state, generating a carbon asset transaction request according to the current carbon emission quota asset total gap value of the target object; and according to the carbon emission quota asset consumption conditions of other target objects, the carbon asset transaction request can be sent to the other target objects meeting the preset carbon emission quota asset consumption conditions.
9. The carbon asset management system of claim 1, wherein:
the carbon activity adjustment module adjusts the carbon activity realization state of the target object according to the judging result of the carbon emission quota asset sufficiency state, and comprises:
if the whole target object is not in the carbon emission quota asset sufficient state currently, acquiring a carbon activity type of which the target object is not in the carbon emission quota asset sufficient state currently, and reducing the scale and/or the initiation frequency of the carbon activity corresponding to the carbon activity type.
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