Carbon data statistical method, device and equipment and storage medium
By customizing carbon indicators, statistical subjects and indicator configurations, combined with the current and historical data of the underlying subject, efficient carbon data statistics are achieved, solving the high cost and low flexibility problems caused by hard coding in the existing technology.
Patent Information
- Application Number
- CN202411606936.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-12
- Publication Date
- 2025-03-04
AI Technical Summary
In the prior art, carbon emission data statistics are hard-coded, resulting in large workload and poor flexibility, and the inability to effectively reduce the cost of carbon data statistics.
By determining the carbon index, statistical subject and indicator configuration, including the statistical dimensions and data forms of the underlying subject and the integrated subject, the current carbon data of the underlying subject is obtained, and the current carbon data statistical results are calculated based on historical statistical results and data forms.
It realizes efficient statistics and update carbon data based on user-defined carbon indicators, statistical subjects and indicator configurations, reducing statistical costs and improving flexibility.
Smart Images
Figure CN119558520A_ABST
Abstract
Description
Technical Field
[0001] Embodiments of the present invention relate to the field of computer technology, and in particular to a carbon data statistics method, device, equipment and storage medium. Background Art
[0002] As society pays more attention to sustainable development, companies' performance in environmental protection is increasingly valued by consumers and investors. Carbon asset management platforms can showcase companies' efforts in emission reduction and sustainable development and enhance their brand image. At the same time, carbon asset management platforms can help companies systematically manage carbon emission data, thereby optimizing resource allocation and reducing operating costs. There are many types of carbon emission data sources for thermal power companies, and carbon asset management platforms need to summarize and compile the huge amount of data.
[0003] In the prior art, the system usually uses a hard-coded method to perform carbon emission data statistics, which not only has a large workload but also has poor flexibility.
[0004] Therefore, there is an urgent need for a carbon data statistics method to improve the statistical efficiency of carbon emission data and reduce statistical costs. Summary of the invention
[0005] The present invention provides a carbon data statistics method, device, equipment and storage medium to reduce the carbon data statistics cost.
[0006] In a first aspect, an embodiment of the present invention provides a carbon data statistics method, comprising:
[0007] Determine carbon indicators, statistical subjects and indicator configuration, wherein the statistical subjects include underlying subjects and integrated subjects, and the indicator configuration includes statistical dimensions of each statistical subject and the data format corresponding to each statistical dimension;
[0008] Determine the minimum statistical dimension of each of the underlying entities for the carbon index according to the statistical dimension of each of the statistical entities;
[0009] Acquire current carbon data of each of the underlying entities based on the minimum statistical dimension of each of the underlying entities for the carbon index;
[0010] According to the current carbon data of each underlying entity, the historical carbon data statistical results of each statistical entity for the carbon index in each statistical dimension and the data format corresponding to each statistical dimension, the current carbon data statistical results of each statistical entity for the carbon index in each statistical dimension are determined.
[0011] The technical solution of the embodiment of the present invention provides a carbon data statistics method, including: determining carbon indicators, statistical subjects and indicator configuration, wherein the statistical subjects include underlying subjects and integrated subjects, and the indicator configuration includes statistical dimensions of each statistical subject and data formats corresponding to each statistical dimension; determining the minimum statistical dimension of each underlying subject for the carbon indicator based on the statistical dimensions of each statistical subject; obtaining the current carbon data of each underlying subject based on the minimum statistical dimension of each underlying subject for the carbon indicator; determining the current carbon data statistical results of each statistical subject for the carbon indicator in each statistical dimension based on the current carbon data of each underlying subject, the historical carbon data statistical results of each statistical subject for the carbon indicator in each statistical dimension and the data formats corresponding to each statistical dimension. The above technical scheme can first determine the carbon index, statistical subject and indicator configuration according to the user input information or user file information, and realize the user-specific configuration of the carbon index, statistical subject and indicator configuration. Secondly, the minimum statistical dimension of each underlying subject for the carbon index can be determined according to the statistical dimension of each statistical subject. Then, the current carbon data of each underlying subject can be obtained according to the minimum statistical dimension of each underlying subject for the carbon index corresponding to the carbon index, so as to realize the acquisition of the original carbon data. Then, according to the current carbon data of each underlying subject, the historical carbon data statistical results of each statistical subject for the carbon index in each statistical dimension and the data form corresponding to each statistical dimension, the current carbon data statistical results of each statistical subject for the carbon index in each statistical dimension can be determined, so as to realize the determination of the current carbon data statistical results of each statistical subject for the carbon index in each statistical dimension based on the carbon index, statistical subject and indicator configuration configured by the user in a targeted manner.
[0012] Furthermore, the carbon index includes at least one of carbon emission data, carbon quota data, carbon emission reduction data and carbon trading data; the statistical dimensions include at least one of hourly, daily, weekly, monthly and annually; the data is in the form of assignment, or calculation and calculation method.
[0013] Furthermore, the minimum statistical dimension of each underlying subject for the carbon indicator is determined according to the statistical dimension of each statistical subject, including: determining the minimum statistical dimension among the statistical dimensions of each statistical subject as the minimum statistical dimension of each underlying subject for the carbon indicator.
[0014] Furthermore, the current carbon data of each of the underlying entities is obtained based on the minimum statistical dimension of each of the underlying entities for the carbon index, including: determining the real-time carbon data of each of the underlying entities in the operation records of each of the underlying entities; and determining the current carbon data of each of the underlying entities according to the real-time carbon data of each of the underlying entities and the minimum statistical dimension for the carbon index.
[0015] Further, according to the current carbon data of each underlying entity, the historical carbon data statistical results of each statistical entity for the carbon indicator in each statistical dimension and the data form corresponding to each statistical dimension, the current carbon data statistical results of each statistical entity for the carbon indicator in each statistical dimension are determined, including: when the data form corresponding to the statistical dimension of the statistical entity is assignment, the current carbon data of each underlying entity corresponding to the statistical entity is added to the historical carbon data statistical results of the statistical entity for the carbon indicator in the statistical dimension, so as to obtain the current carbon data statistical results of the statistical entity for the carbon indicator in the statistical dimension; when the data form corresponding to the statistical dimension of the statistical entity is calculation and calculation method, the current carbon data of each underlying entity and the historical carbon data statistical results of each statistical entity for the carbon indicator in the statistical dimension are processed based on the calculation method to obtain the current carbon data statistical results of the statistical entity for the carbon indicator in the statistical dimension.
[0016] Furthermore, after determining the current carbon data statistical results of each of the statistical subjects for the carbon index in each of the statistical dimensions, it also includes: storing the current carbon data statistical results of each of the statistical subjects for the carbon index in each of the statistical dimensions based on a data table.
[0017] Furthermore, after determining the current carbon data statistical results of each of the statistical entities for the carbon indicators in each of the statistical dimensions, it also includes: after receiving an acquisition request, determining the carbon data statistical results corresponding to the acquisition request in the data table according to the acquisition parameters contained in the acquisition request, and displaying the carbon data statistical results based on the front-end page.
[0018] In a second aspect, an embodiment of the present invention further provides a carbon data statistics device, including:
[0019] A determination module, used to determine carbon indicators, statistical subjects and indicator configuration, wherein the statistical subjects include underlying subjects and integrated subjects, and the indicator configuration includes statistical dimensions of each statistical subject and the data form corresponding to each statistical dimension;
[0020] An execution module, configured to determine the minimum statistical dimension of each of the underlying entities for the carbon index according to the statistical dimension of each of the statistical entities;
[0021] An acquisition module, configured to acquire current carbon data of each of the underlying entities based on the minimum statistical dimension of each of the underlying entities for the carbon index;
[0022] A statistical module is used to determine the current carbon data statistical results of each statistical subject for the carbon index in each statistical dimension based on the current carbon data of each underlying subject, the historical carbon data statistical results of each statistical subject for the carbon index in each statistical dimension, and the data format corresponding to each statistical dimension.
[0023] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the carbon data statistical method as described in any one of the first aspects.
[0024] In a fourth aspect, an embodiment of the present invention further provides a storage medium comprising computer executable instructions, wherein the computer executable instructions, when executed by a computer processor, are used to execute the carbon data statistical method as described in any one of the first aspects.
[0025] In a fifth aspect, the present application provides a computer program product, which includes computer instructions. When the computer instructions are executed on a computer, the computer executes the carbon data statistical method provided in the first aspect.
[0026] It should be noted that the above computer instructions may be stored in whole or in part on a computer-readable storage medium, wherein the computer-readable storage medium may be packaged together with the processor of the carbon data statistics device, or may be packaged separately from the processor of the carbon data statistics device, which is not limited in this application.
[0027] The description of the second, third, fourth and fifth aspects in this application can refer to the detailed description of the first aspect; and the beneficial effects of the description of the second, third, fourth and fifth aspects can refer to the beneficial effect analysis of the first aspect, which will not be repeated here.
[0028] In this application, the name of the above-mentioned carbon data statistics device does not limit the device or functional module itself. In actual implementation, these devices or functional modules may appear with other names. As long as the functions of each device or functional module are similar to those of this application, they belong to the scope of the claims of this application and their equivalent technologies.
[0029] These and other aspects of the present application will become more apparent from the following description. BRIEF DESCRIPTION OF THE DRAWINGS
[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.
[0031] Figure 1 A flow chart of a carbon data statistics method provided by an embodiment of the present invention;
[0032] Figure 2 A flow chart of another carbon data statistics method provided by an embodiment of the present invention;
[0033] Figure 3 A schematic diagram of the structure of a carbon data statistics device provided by an embodiment of the present invention;
[0034] Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0035] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.
[0036] The term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.
[0037] The terms "first" and "second" and the like in the specification and drawings of this application are used to distinguish different objects, or to distinguish different processing of the same object, rather than to describe a specific order of objects.
[0038] In addition, the terms "including" and "having" and any variations thereof mentioned in the description of the present application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.
[0039] It should be mentioned before discussing exemplary embodiments in more detail that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe various operations (or steps) as sequential processes, many operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of various operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to methods, functions, procedures, subroutines, subprograms, etc. In addition, the embodiments in the present invention and the features in the embodiments can be combined with each other without conflict.
[0040] It should be noted that, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.
[0041] In the description of the present application, unless otherwise specified, “plurality” means two or more.
[0042] Figure 1 This is a flow chart of a carbon data statistics method provided by an embodiment of the present invention. This embodiment is applicable to situations where the cost of carbon data statistics needs to be reduced. The method can be executed by a carbon data statistics device, such as Figure 1 As shown, the specific steps include:
[0043] Step 110: Determine carbon indicators, statistical entities, and indicator configuration.
[0044] Among them, the indicator configuration of the statistical subject includes the statistical dimensions of each statistical subject and the data format corresponding to each statistical dimension.
[0045] Carbon indicators are carbon data that need to be counted in carbon asset management. The statistical subject can be understood as the subject that needs to conduct carbon data statistics, including the underlying subject and the integrated subject. The underlying subject can be understood as the subject that can obtain the original carbon data, and the integrated subject is the subject other than the underlying subject in the statistical subject. The indicator configuration is used to determine the statistical method of each statistical subject for the statistical results of the carbon indicator, that is, it can include the statistical dimensions of each statistical subject for the carbon indicator and the data format corresponding to each statistical dimension.
[0046] Specifically, the user's statistical requirements for carbon indicators can be determined according to the user input information or the user file information, that is, the carbon indicators can be determined. The user's statistical requirements for subjects can also be determined according to the user input information or the user file information, that is, the statistical subjects can be determined. The user's statistical requirements for each statistical subject can also be determined according to the user input information or the user file information, that is, the statistical dimensions of each statistical subject and the data form of each statistical dimension can be determined.
[0047] In the embodiment of the present invention, the carbon index, statistical subject and index configuration are determined according to user input information or user file information, thereby realizing user-specific configuration of the carbon index, statistical subject and index configuration.
[0048] Step 120: Determine the minimum statistical dimension of each of the underlying entities for the carbon index according to the statistical dimension of each of the statistical entities.
[0049] The statistics of the carbon indicators of the statistical subjects need to rely on the original carbon data of the underlying subjects. Therefore, in order to determine the statistical results of the carbon indicators of each statistical subject in each statistical dimension, the statistical dimension based on the original carbon data obtained from each underlying subject needs to be no greater than the minimum statistical dimension of each statistical subject.
[0050] Specifically, after determining the statistical dimension of each statistical subject, the minimum statistical dimension of each underlying subject for the carbon indicator can be determined according to the minimum dimension among the minimum statistical dimensions of each statistical subject, and the minimum statistical dimension of each underlying subject for the carbon indicator is not greater than the minimum dimension among the minimum statistical dimensions of each statistical subject.
[0051] In the embodiment of the present invention, the minimum statistical dimension of each underlying subject for the carbon index is determined according to the statistical dimension of each statistical subject.
[0052] Step 130: Acquire current carbon data of each underlying entity based on the minimum statistical dimension of each underlying entity for the carbon index.
[0053] Specifically, after determining the minimum statistical dimension of each underlying entity for the carbon index, the current carbon data of each underlying entity can be obtained based on the minimum statistical dimension. For example, when the carbon index is carbon emission data, the underlying entities are boilers, steam turbines and generators. When the minimum statistical entity is hourly, the carbon emission data of the boilers, steam turbines and generators in the current hour can be obtained. Specifically, the real-time carbon emission data of the boilers, steam turbines and generators can be determined based on the flow sensors arranged at the emission outlets of the boilers, steam turbines and generators, and then the carbon emission data of the current hour can be determined based on the real-time carbon emission data. When the carbon index is carbon trading data, the underlying entity is the power generation enterprise, and the minimum statistical dimension is day and hour. The carbon trading data of the power generation enterprise on that day can be obtained. Specifically, the real-time carbon trading data of the power generation enterprise can be obtained based on the internal system of the power generation enterprise, and then the carbon trading data of the day can be determined based on the real-time carbon emission data.
[0054] In the embodiment of the present invention, the current carbon data of each underlying subject is obtained according to the minimum statistical dimension of the carbon index corresponding to each underlying subject for the carbon index, so as to obtain the original carbon data.
[0055] Step 140: Determine the current carbon data statistical results of each statistical subject for the carbon index in each statistical dimension based on the current carbon data of each underlying subject, the historical carbon data statistical results of each statistical subject for the carbon index in each statistical dimension, and the data format corresponding to each statistical dimension.
[0056] Carbon data statistics is a real-time process. Each time the original carbon data is obtained, the historical carbon data statistical results can be updated based on the original carbon data to determine the current carbon data statistical results.
[0057] Specifically, first, the historical carbon data statistical results of each statistical subject for carbon indicators in each statistical dimension and the data format corresponding to each statistical dimension can be determined; secondly, the current carbon data statistical results of each statistical subject for carbon indicators in each statistical dimension can be determined in the data format corresponding to each statistical dimension of each statistical subject based on the current carbon data of each underlying subject.
[0058] In the embodiment of the present invention, the current carbon data statistical results of each statistical subject for the carbon indicator in each statistical dimension are determined based on the carbon indicator, statistical subject and indicator configuration configured by the user in a targeted manner.
[0059] The carbon data statistics method provided by the embodiment of the present invention includes: determining carbon indicators, statistical subjects and indicator configuration, wherein the statistical subjects include underlying subjects and integrated subjects, and the indicator configuration includes statistical dimensions of each statistical subject and data formats corresponding to each statistical dimension; determining the minimum statistical dimension of each underlying subject for the carbon indicator based on the statistical dimensions of each statistical subject; obtaining the current carbon data of each underlying subject based on the minimum statistical dimension of each underlying subject for the carbon indicator; determining the current carbon data statistical results of each statistical subject for the carbon indicator in each statistical dimension based on the current carbon data of each underlying subject, the historical carbon data statistical results of each statistical subject for the carbon indicator in each statistical dimension and the data formats corresponding to each statistical dimension. The above technical scheme can first determine the carbon index, statistical subject and indicator configuration according to the user input information or user file information, and realize the user-specific configuration of the carbon index, statistical subject and indicator configuration. Secondly, the minimum statistical dimension of each underlying subject for the carbon index can be determined according to the statistical dimension of each statistical subject. Then, the current carbon data of each underlying subject can be obtained according to the minimum statistical dimension of each underlying subject for the carbon index corresponding to the carbon index, so as to realize the acquisition of the original carbon data. Then, according to the current carbon data of each underlying subject, the historical carbon data statistical results of each statistical subject for the carbon index in each statistical dimension and the data form corresponding to each statistical dimension, the current carbon data statistical results of each statistical subject for the carbon index in each statistical dimension can be determined, so as to realize the determination of the current carbon data statistical results of each statistical subject for the carbon index in each statistical dimension based on the carbon index, statistical subject and indicator configuration configured by the user in a targeted manner.
[0060] Figure 2 This is a flow chart of another carbon data statistics method provided by an embodiment of the present invention. This embodiment is specific based on the above embodiment. Figure 2 As shown, in this embodiment, the method may further include:
[0061] Step 210: Determine carbon indicators, statistical subjects, and indicator configuration.
[0062] Among them, the carbon indicators include at least one of carbon emission data, carbon quota data, carbon emission reduction data and carbon trading data; the statistical dimensions include at least one of hourly, daily, weekly, monthly and annually; the data form is assignment, or calculation and calculation method.
[0063] When the carbon index is carbon emission data, the underlying entities may include boilers, steam turbines and generators, and the integrated entities may include units, power generation companies and power generation groups. When the carbon index is carbon trading data, the underlying entity may be a power generation company, and the integrated entity may be a power generation group.
[0064] The data format corresponding to each statistical dimension can be understood as the calculation method for determining the statistical results of the statistical subject for carbon indicators in each statistical dimension.
[0065] Specifically, the carbon index can be determined according to the user input information or user file information, that is, the index identifier, index name, index alias and index unit corresponding to the carbon index can be determined, wherein the index name is a descriptive text for the index identifier, for example, carbon emission data, the index identifier is unique, for example, emission_c, and the index alias is a supplement to the index name. The statistical subject can also be determined according to the user input information or user file information, for example, boilers, steam turbines, generators, units, power generation enterprises and power generation groups, etc. The statistical dimensions of each statistical subject and the data form of each statistical dimension can also be determined according to the user input information or user file information. For example, the statistical dimensions can include every minute, every hour, every day, every week, every month, every quarter, every year, etc. The data form of the statistical dimension can be understood as the value logic of the carbon index, which can be assignment or calculation. The assignment is directly determined by input without any processing, and the calculation is determined by calculation.
[0066] When the data form of the statistical dimension of the statistical subject is calculated, the system provides multiple operation modes according to the preset multiple operation modes: arithmetic operators: +, -, *, / ; logical operators: =, ! =, >, <, > =, < =; relational operators: &&, ||, !; functions: abs(), if(), max(), min(), avg(), sum(), round() and the calculation mode in the data form of the statistical dimension of the statistical subject determines the corresponding calculation formula.
[0067] Table 1 is a relationship table of carbon index-statistical subject-statistical dimension-data form-statistical result and calculation formula, as shown in Table 1, including the data form of each statistical subject and each statistical dimension and the corresponding formula and statistical result. For example, the calculation formula for the daily carbon emission data of the unit can be determined as: sum (boiler-carbon emission data-day, turbine-carbon emission data-day, generator-carbon emission data-day).
[0068] Table 1
[0069]
[0070]
[0071]
[0072] In the embodiment of the present invention, the carbon index, statistical subject and index configuration are determined according to user input information or user file information, thereby realizing user-specific configuration of the carbon index, statistical subject and index configuration.
[0073] Step 220: Determine the minimum statistical dimension of each of the underlying entities for the carbon index according to the statistical dimension of each of the statistical entities.
[0074] In one implementation, step 220 may specifically include:
[0075] The minimum statistical dimension among the statistical dimensions of each of the statistical subjects is determined as the minimum statistical dimension of each of the underlying subjects for the carbon index.
[0076] Specifically, after determining the statistical dimensions of each statistical subject, the minimum statistical dimension of each statistical subject can be determined, and the minimum statistical dimensions of each statistical subject can be compared. The minimum statistical dimension of each underlying subject for the carbon index is determined according to the minimum dimension of the minimum statistical dimensions of each statistical subject, and the minimum statistical dimension of each underlying subject for the carbon index is not greater than the minimum dimension of the minimum statistical dimensions of each statistical subject. In order to reduce the amount of data calculation, the minimum dimension of the minimum statistical dimensions of each statistical subject can be determined as the minimum statistical dimension of each underlying subject for the carbon index.
[0077] In the embodiment of the present invention, the minimum statistical dimension of each underlying subject for the carbon index is determined according to the statistical dimension of each statistical subject.
[0078] Step 230: Acquire current carbon data of each underlying entity based on the minimum statistical dimension of each underlying entity for the carbon index.
[0079] In one implementation, step 230 may specifically include:
[0080] Determine the real-time carbon data of each underlying entity in the operation record of each underlying entity; determine the current carbon data of each underlying entity according to the real-time carbon data of each underlying entity and the minimum statistical dimension for the carbon index.
[0081] Specifically, first, the real-time carbon data of each underlying subject can be determined in the operation records of each underlying subject. For example, when the carbon index is carbon emission data, the underlying subject is the boiler, steam turbine and generator, and the real-time carbon emission data of the boiler, steam turbine and generator can be obtained from the operation records of the boiler, steam turbine and generator; when the carbon index is carbon quota data, the underlying subject is the power generation enterprise, and the daily average carbon quota data of the power generation enterprise can be obtained from the operation records of the internal system of the power generation enterprise. Secondly, the real-time carbon data of each underlying subject can be counted according to the minimum statistical dimension of each underlying subject for the carbon index to determine the current carbon data of each underlying subject. For example, the minimum statistical dimension of carbon emission data for boilers, steam turbines and generators is day and hour, and the carbon emission data of the day can be counted according to the real-time carbon emission data of boilers, steam turbines and generators to determine the current carbon data of boilers, steam turbines and generators; the minimum statistical dimension of carbon quota data for power generation enterprises is day and hour, and the daily average carbon quota data of power generation enterprises can be determined as the current carbon data.
[0082] In the embodiment of the present invention, the real-time carbon data of the underlying subject and the minimum statistical dimension of the carbon index of the underlying subject obtained according to the operation record of the underlying subject are used to determine the current carbon data of each underlying subject and obtain the original carbon data.
[0083] Step 240: Determine the current carbon data statistical results of each statistical subject for the carbon index in each statistical dimension based on the current carbon data of each underlying subject, the historical carbon data statistical results of each statistical subject for the carbon index in each statistical dimension, and the data format corresponding to each statistical dimension.
[0084] In one implementation, step 240 may specifically include:
[0085] When the data form corresponding to the statistical dimension of the statistical subject is assignment, the current carbon data of each underlying subject corresponding to the statistical subject is added to the historical carbon data statistical result of the statistical subject for the carbon index in the statistical dimension, so as to obtain the current carbon data statistical result of the statistical subject for the carbon index in the statistical dimension; when the data form corresponding to the statistical dimension of the statistical subject is calculation and calculation method, the current carbon data of each underlying subject and the historical carbon data statistical result of each statistical subject for the carbon index in the statistical dimension are processed based on the calculation method to obtain the current carbon data statistical result of the statistical subject for the carbon index in the statistical dimension.
[0086] The data table stores the carbon data statistical results of each statistical subject for carbon indicators in each statistical dimension.
[0087] Specifically, after determining the historical carbon data statistical results of each statistical subject for carbon indicators in each statistical dimension in the data table, the current carbon data statistical results of each statistical subject for carbon indicators in each statistical dimension are calculated according to the calculation formula corresponding to the data form corresponding to each statistical dimension of each statistical subject based on the current carbon data of each underlying subject.
[0088] For example, when the carbon indicator is carbon emission data and the statistical dimensions include hourly, daily, weekly, monthly and annual, we can first determine the historical carbon emission data statistics of boilers, steam turbines, generators, units, power generation enterprises and power generation groups at hourly, daily, weekly, monthly and annual intervals, as well as the corresponding data formats at hourly, daily, weekly, monthly and annual intervals (the hourly data format is assignment, the daily, weekly, monthly and annual data format is calculation, the daily calculation method is to superimpose the hourly data within the day, the weekly calculation method is to superimpose the daily data within the current week, and the monthly calculation method is to superimpose the daily data within the current week. The calculation method for each year is to superimpose the weekly data of the current month, and the calculation method for each year is to superimpose the monthly data of the current year). Secondly, the historical carbon emission data statistics of boilers, steam turbines, generators, units, power generation enterprises and power generation groups on an hourly, daily, weekly, monthly and annual basis can be updated in the corresponding data form on an hourly, daily, weekly, monthly and annual basis to obtain the current carbon emission data statistics of boilers, steam turbines, generators, units, power generation enterprises and power generation groups on an hourly, daily, weekly, monthly and annual basis. For example, the carbon emission data of the boiler, steam turbine and generator in the current hour can be added to the historical carbon emission data statistics of the boiler, steam turbine and generator in each hour to obtain the current carbon emission data statistics of the boiler, steam turbine and generator in each hour; the carbon emission data of the boiler in the current hour and the historical carbon emission data statistics of the boiler on the day can be summed to obtain the current carbon emission data statistics of the boiler on the day; the current carbon emission data statistics of the boiler, steam turbine and generator on the day can be summed, and the summed result and the historical carbon emission data statistics of the generator set on the day can be summed to obtain the current carbon emission data statistics of the generator set on the day.
[0089] In actual applications, after determining the current carbon data of each underlying entity, when the data form corresponding to the statistical dimension of the statistical entity is calculated, the historical carbon data statistical results of the statistical dimension of the statistical entity for the carbon index and the current carbon data of each underlying entity are calculated according to the calculation formula of the data form corresponding to the statistical dimension of the statistical entity to obtain the current carbon data statistical results of the statistical dimension of the statistical entity for the carbon index.
[0090] In the embodiment of the present invention, the current carbon data statistical results of each statistical subject for the carbon indicator in each statistical dimension are determined based on the carbon indicator, statistical subject and indicator configuration configured by the user in a targeted manner.
[0091] Step 250: storing the current carbon data statistical results of each statistical subject for the carbon index in each statistical dimension based on the data table.
[0092] Specifically, the current carbon data statistical results of each statistical subject for each carbon indicator in each statistical dimension can be stored based on the data table. Table 2 is a table of current carbon data statistical results where the carbon indicator is carbon emission data and the statistical dimension is daily. As shown in Table 2, a row of data represents the current carbon data statistical results of boilers, steam turbines, generators, units, power generation enterprises and power generation groups in one day.
[0093] Table 2
[0094]
[0095] In the embodiment of the present invention, the storage of the current carbon data statistical results of the statistical subject for the carbon index in each statistical dimension is achieved based on the data table.
[0096] Step 260: After receiving the acquisition request, determine the carbon data statistical result corresponding to the acquisition request in the data table according to the acquisition parameters included in the acquisition request, and display the carbon data statistical result based on the front-end page.
[0097] The acquisition parameters included in the acquisition request may include at least one of a statistical subject, a time range, a carbon index, and the like.
[0098] Specifically, after receiving the acquisition request, the acquisition parameters contained in the acquisition request can be determined, and then the carbon data statistical results corresponding to the acquisition request can be determined in the data table according to the acquisition parameters contained in the acquisition request. The carbon data statistical results corresponding to the acquisition request can also be displayed based on the front-end page. Of course, the carbon data statistical results can be displayed based on a preset chart.
[0099] The front-end page only needs to pass the acquisition parameters based on the acquisition request to obtain the required carbon data statistics. In addition, the required charts can be drawn without any other code investment in the back-end, reducing development costs.
[0100] In the embodiment of the present invention, it is achieved to determine in a data table the carbon data statistical result corresponding to the acquisition request and to visualize the carbon data statistical result.
[0101] The carbon data statistics method provided by the embodiment of the present invention includes: determining carbon indicators, statistical subjects and indicator configuration; determining the minimum statistical dimension of each underlying subject for the carbon indicator according to the statistical dimension of each statistical subject; acquiring the current carbon data of each underlying subject based on the minimum statistical dimension of each underlying subject for the carbon indicator; determining the current carbon data statistical results of each statistical subject for the carbon indicator in each statistical dimension according to the current carbon data of each underlying subject, the historical carbon data statistical results of each statistical subject for the carbon indicator in each statistical dimension and the data form corresponding to each statistical dimension; storing the current carbon data statistical results of each statistical subject for the carbon indicator in each statistical dimension based on a data table; after receiving an acquisition request, determining the carbon data statistical results corresponding to the acquisition request in the data table according to the acquisition parameters contained in the acquisition request, and displaying the carbon data statistical results based on a front-end page. The above technical solution can first determine the carbon index, statistical subject and indicator configuration according to the user input information or user file information, and realize the user-specific configuration of the carbon index, statistical subject and indicator configuration. Secondly, the minimum statistical dimension of each underlying subject for the carbon index can be determined according to the statistical dimension of each statistical subject. Then, the current carbon data of each underlying subject can be obtained according to the minimum statistical dimension of each underlying subject for the carbon index corresponding to the carbon index, so as to obtain the original carbon data. Then, the current carbon data statistical results of each statistical subject for the carbon index in each statistical dimension can be determined according to the current carbon data of each underlying subject, the historical carbon data statistical results of each statistical subject for the carbon index in each statistical dimension, and the data form corresponding to each statistical dimension, so as to realize the determination of the current carbon data statistical results of each statistical subject for the carbon index in each statistical dimension based on the carbon index, statistical subject and indicator configuration configured by the user. The current carbon data statistical results of the statistical subject for the carbon index in each statistical dimension can also be stored in the data table. After receiving the acquisition request, the carbon data statistical results corresponding to the acquisition request are determined in the data table, and the carbon data statistical results are displayed based on the front-end page.
[0102] Users can customize carbon indicators according to their own needs to meet special requirements. They can also adjust statistical dimensions and data formats to achieve personalized customization of carbon indicators. It has strong flexibility and high customizability. In addition, no additional back-end investment is required to achieve carbon data statistics, reducing statistical costs.
[0103] Figure 3 This is a schematic diagram of the structure of a carbon data statistics device provided by an embodiment of the present invention, which can be applied to situations where the cost of carbon data statistics needs to be reduced. The device can be implemented by software and / or hardware and is generally integrated in an electronic device, such as a computer device.
[0104] like Figure 3 As shown, the device comprises:
[0105] The determination module 310 is used to determine the carbon index, the statistical subject and the index configuration, wherein the statistical subject includes the underlying subject and the integrated subject, and the index configuration includes the statistical dimension of each statistical subject and the data form corresponding to each statistical dimension;
[0106] An execution module 320 is used to determine the minimum statistical dimension of each of the underlying entities for the carbon index according to the statistical dimension of each of the statistical entities;
[0107] An acquisition module 330 is used to acquire current carbon data of each of the underlying entities based on the minimum statistical dimension of each of the underlying entities for the carbon index;
[0108] The statistical module 340 is used to determine the current carbon data statistical results of each statistical subject for the carbon index in each statistical dimension based on the current carbon data of each underlying subject, the historical carbon data statistical results of each statistical subject for the carbon index in each statistical dimension, and the data format corresponding to each statistical dimension.
[0109] The carbon data statistics device provided in this embodiment determines carbon indicators, statistical subjects and indicator configurations, wherein the statistical subjects include underlying subjects and integrated subjects, and the indicator configurations include statistical dimensions of each of the statistical subjects and data formats corresponding to each of the statistical dimensions; the minimum statistical dimensions of each of the underlying subjects for the carbon indicators are determined according to the statistical dimensions of each of the statistical subjects; the current carbon data of each of the underlying subjects is obtained based on the minimum statistical dimensions of each of the underlying subjects for the carbon indicators; and the current carbon data statistical results of each of the statistical subjects for the carbon indicators in each of the statistical dimensions are determined according to the current carbon data of each of the underlying subjects, the historical carbon data statistical results of each of the statistical subjects for the carbon indicators in each of the statistical dimensions, and the data formats corresponding to each of the statistical dimensions. The above technical scheme can first determine the carbon index, statistical subject and indicator configuration according to the user input information or user file information, and realize the user-specific configuration of the carbon index, statistical subject and indicator configuration. Secondly, the minimum statistical dimension of each underlying subject for the carbon index can be determined according to the statistical dimension of each statistical subject. Then, the current carbon data of each underlying subject can be obtained according to the minimum statistical dimension of each underlying subject for the carbon index corresponding to the carbon index, so as to realize the acquisition of the original carbon data. Then, according to the current carbon data of each underlying subject, the historical carbon data statistical results of each statistical subject for the carbon index in each statistical dimension and the data form corresponding to each statistical dimension, the current carbon data statistical results of each statistical subject for the carbon index in each statistical dimension can be determined, so as to realize the determination of the current carbon data statistical results of each statistical subject for the carbon index in each statistical dimension based on the carbon index, statistical subject and indicator configuration configured by the user in a targeted manner.
[0110] In one embodiment, the carbon index includes at least one of carbon emission data, carbon quota data, carbon emission reduction data and carbon trading data; the statistical dimension includes at least one of hourly, daily, weekly, monthly and annually; the data is in the form of assignment, or calculation and calculation method.
[0111] On the basis of the above embodiment, the execution module 320 is specifically used to: determine the minimum statistical dimension among the statistical dimensions of each statistical subject as the minimum statistical dimension of each underlying subject for the carbon index.
[0112] Based on the above embodiment, the acquisition module 330 is specifically used to: determine the real-time carbon data of each underlying entity in the operation record of each underlying entity; determine the current carbon data of each underlying entity based on the real-time carbon data of each underlying entity and the minimum statistical dimension for the carbon index.
[0113] On the basis of the above embodiment, the statistical module 340 is specifically used for: when the data form corresponding to the statistical dimension of the statistical subject is assignment, adding the current carbon data of each underlying subject corresponding to the statistical subject to the historical carbon data statistical result of the statistical subject for the carbon index in the statistical dimension, to obtain the current carbon data statistical result of the statistical subject for the carbon index in the statistical dimension; when the data form corresponding to the statistical dimension of the statistical subject is calculation and calculation method, processing the current carbon data of each underlying subject and the historical carbon data statistical result of each statistical subject for the carbon index in the statistical dimension based on the calculation method, to obtain the current carbon data statistical result of the statistical subject for the carbon index in the statistical dimension.
[0114] Based on the above embodiments, the device also includes: a storage module, which is used to store the current carbon data statistical results of each statistical subject for the carbon indicator in each statistical dimension based on a data table after determining the current carbon data statistical results of each statistical subject for the carbon indicator in each statistical dimension.
[0115] Based on the above embodiment, the device also includes: a request module, which is used to determine the carbon data statistical results corresponding to the acquisition request in the data table according to the acquisition parameters contained in the acquisition request after receiving the acquisition request, and display the carbon data statistical results based on the front-end page.
[0116] The carbon data statistics device provided in the embodiment of the present invention can execute the carbon data statistics method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the carbon data statistics method.
[0117] It is worth noting that in the above-mentioned embodiment of the carbon data statistics device, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be realized; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.
[0118] Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Figure 4 A block diagram of an exemplary electronic device 4 suitable for implementing embodiments of the present invention is shown. Figure 4 The electronic device 4 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.
[0119] like Figure 4As shown, the electronic device 4 is in the form of a general purpose computing electronic device. The components of the electronic device 4 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 connecting different system components (including the system memory 28 and the processing unit 16).
[0120] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.
[0121] The electronic device 4 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 4, including volatile and non-volatile media, removable and non-removable media.
[0122] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 4 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 4 not shown, usually called a "hard drive"). Although Figure 4 Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.
[0123] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.
[0124] The electronic device 4 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), one or more devices that enable a user to interact with the electronic device 4, and / or any device that enables the electronic device 4 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via an input / output (I / O) interface 22. Furthermore, the electronic device 4 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 20. Figure 4 As shown, the network adapter 20 communicates with other modules of the electronic device 4 via the bus 18. It should be understood that although Figure 4 Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 4, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.
[0125] The processing unit 16 executes various functional applications and page displays by running the program stored in the system memory 28, for example, to implement the carbon data statistical method provided in the embodiment of the present invention, the method comprising: determining carbon indicators, statistical subjects and indicator configurations, wherein the statistical subjects include underlying subjects and integrated subjects, and the indicator configurations include statistical dimensions of each statistical subject and data forms corresponding to each statistical dimension; determining the minimum statistical dimension of each underlying subject for the carbon indicator according to the statistical dimension of each statistical subject; obtaining the current carbon data of each underlying subject based on the minimum statistical dimension of each underlying subject for the carbon indicator; determining the current carbon data statistical results of each statistical subject for the carbon indicator in each statistical dimension according to the current carbon data of each underlying subject, the historical carbon data statistical results of each statistical subject for the carbon indicator in each statistical dimension, and the data forms corresponding to each statistical dimension. Of course, those skilled in the art can understand that the processor can also implement the technical solution of the carbon data statistical method provided in any embodiment of the present invention.
[0126] An embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the carbon data statistics method provided by the embodiment of the present invention is implemented, for example, the method comprising: determining a carbon index, a statistical subject and an index configuration, wherein the statistical subject comprises an underlying subject and an integrated subject, and the index configuration comprises a statistical dimension of each of the statistical subjects and a data form corresponding to each of the statistical dimensions; determining a minimum statistical dimension of each of the underlying subjects for the carbon index based on the statistical dimension of each of the statistical subjects; obtaining current carbon data of each of the underlying subjects based on the minimum statistical dimension of each of the underlying subjects for the carbon index; determining current carbon data statistical results of each of the statistical subjects for the carbon index in each of the statistical dimensions based on the current carbon data of each of the underlying subjects, historical carbon data statistical results of each of the statistical subjects for the carbon index in each of the statistical dimensions and the data form corresponding to each of the statistical dimensions.
[0127] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.
[0128] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.
[0129] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
[0130] Computer program code for performing the operations of the present invention may be written in one or more programming languages or a combination thereof, including object-oriented programming languages such as Java, Smalltalk, C++, and conventional procedural programming languages such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).
[0131] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, optionally, they can be implemented by a program code executable by a computer device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.
[0132] In addition, the acquisition, storage, use, and processing of data in the technical solution of the present invention are in compliance with the relevant provisions of national laws and regulations.
[0133] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims
1. A carbon data statistical method, characterized in that: include: Determine carbon indicators, statistical subjects and indicator configuration, wherein the statistical subjects include underlying subjects and integrated subjects, and the indicator configuration includes statistical dimensions of each statistical subject and the data format corresponding to each statistical dimension; Determine the minimum statistical dimension of each of the underlying entities for the carbon index according to the statistical dimension of each of the statistical entities; Acquire current carbon data of each of the underlying entities based on the minimum statistical dimension of each of the underlying entities for the carbon index; According to the current carbon data of each underlying entity, the historical carbon data statistical results of each statistical entity for the carbon index in each statistical dimension and the data format corresponding to each statistical dimension, the current carbon data statistical results of each statistical entity for the carbon index in each statistical dimension are determined.
2. The carbon data statistical method according to claim 1, characterized in that: The carbon index includes at least one of carbon emission data, carbon quota data, carbon emission reduction data and carbon trading data; the statistical dimensions include at least one of hourly, daily, weekly, monthly and annually; the data is in the form of assignment, or calculation and calculation method.
3. The carbon data statistical method according to claim 1, characterized in that: Determining the minimum statistical dimension of each of the underlying entities for the carbon index according to the statistical dimension of each of the statistical entities includes: The minimum statistical dimension among the statistical dimensions of each of the statistical subjects is determined as the minimum statistical dimension of each of the underlying subjects for the carbon index.
4. The carbon data statistical method according to claim 1, characterized in that: Acquiring current carbon data of each of the underlying entities based on the minimum statistical dimension of each of the underlying entities for the carbon index includes: Determining the real-time carbon data of each of the underlying entities in the operation records of each of the underlying entities; The current carbon data of each of the underlying entities is determined according to the real-time carbon data of each of the underlying entities and the minimum statistical dimension for the carbon index.
5. The carbon data statistical method according to claim 1, characterized in that: According to the current carbon data of each underlying subject, the historical carbon data statistical results of each statistical subject for the carbon index in each statistical dimension, and the data format corresponding to each statistical dimension, the current carbon data statistical results of each statistical subject for the carbon index in each statistical dimension are determined, including: When the data form corresponding to the statistical dimension of the statistical subject is assignment, the current carbon data of each of the underlying subjects corresponding to the statistical subject is added to the historical carbon data statistical result of the statistical subject for the carbon index in the statistical dimension, to obtain the current carbon data statistical result of the statistical subject for the carbon index in the statistical dimension; When the data form corresponding to the statistical dimension of the statistical subject is calculation and calculation method, the current carbon data of each underlying subject and the historical carbon data statistical results of each statistical subject for the carbon index in the statistical dimension are processed based on the calculation method to obtain the current carbon data statistical results of the statistical subject for the carbon index in the statistical dimension.
6. The carbon data statistical method according to claim 1, characterized in that: After determining the current carbon data statistical results of each of the statistical subjects for the carbon index in each of the statistical dimensions, the method further includes: The current carbon data statistical results of each statistical subject for the carbon index in each statistical dimension are stored based on the data table.
7. The carbon data statistical method according to claim 6, characterized in that: After determining the current carbon data statistical results of each of the statistical subjects for the carbon index in each of the statistical dimensions, the method further includes: After receiving the acquisition request, the carbon data statistical result corresponding to the acquisition request is determined in the data table according to the acquisition parameters included in the acquisition request, and the carbon data statistical result is displayed based on the front-end page.
8. A carbon data statistics device, characterized in that: include: A determination module, used to determine carbon indicators, statistical subjects and indicator configuration, wherein the statistical subjects include underlying subjects and integrated subjects, and the indicator configuration includes statistical dimensions of each statistical subject and the data form corresponding to each statistical dimension; An execution module, configured to determine the minimum statistical dimension of each of the underlying entities for the carbon index according to the statistical dimension of each of the statistical entities; An acquisition module, configured to acquire current carbon data of each of the underlying entities based on the minimum statistical dimension of each of the underlying entities for the carbon index; A statistical module is used to determine the current carbon data statistical results of each statistical subject for the carbon index in each statistical dimension based on the current carbon data of each underlying subject, the historical carbon data statistical results of each statistical subject for the carbon index in each statistical dimension, and the data format corresponding to each statistical dimension.
9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the carbon data statistical method as described in any one of claims 1-7.
10. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions are used to perform the carbon data statistics method according to any one of claims 1 to 7 when executed by a computer processor.