CN115796385A - Multi-dimensional carbon accounting method, system, equipment and storage medium - Google Patents

Abstract

The application discloses a multi-dimensional carbon computing method, a system, equipment and a storage medium, wherein the method comprises the following steps: configuring basic information required by a carbon computing algorithm adapted to a target object; establishing a statistical dimension and an organization structure of the target object; automatically matching a carbon calculation algorithm applicable to each statistical dimension according to the organization structure; and acquiring data to be checked of the target object, checking through the carbon checking algorithm after the cooperativity check is completed according to the basic information, and outputting a carbon emission result. According to the multidimensional carbon accounting method, historical data are used for achieving automatic checking of the carbon emission data, so that the accounting result is more accurate, and the accuracy of the carbon accounting result is improved.

Description

A multi-dimensional carbon accounting method, system, device and storage medium

technical field

The present application relates to the technical field of carbon accounting, in particular to a multi-dimensional carbon accounting method, system, device and storage medium.

Background technique

As a large carbon emitter, the industrial sector urgently needs to find out the carbon background and make a good carbon plan. At present, industrial enterprises monitor and collect various carbon data related to carbon emissions, such as water, electricity and other energy consumption, sewage discharge, motor vehicle exhaust, ambient air quality, hazardous solid waste, personnel activities, etc., and obtain the carbon emission value of the enterprise through calculation. . However, this is because carbon emission accounting methods cannot achieve multi-dimensional accounting. When planning green energy-saving transformation, enterprises cannot effectively find key nodes or factors that affect their own carbon emissions. The cost and effectiveness of transformation are difficult to achieve the original goals of enterprises. The lack or incompleteness of carbon accounting results in low accuracy.

Contents of the invention

The technical problem to be solved in this application is to overcome the defects that the carbon emission accounting method in the prior art cannot realize multi-dimensional accounting, and the lack or incompleteness of historical data leads to the low accuracy of carbon accounting results, and provide a multi-dimensional carbon accounting Method, system, device and storage medium.

The application solves the above-mentioned technical problems through the following technical solutions:

This application provides a multi-dimensional carbon accounting method, including:

Basic information required to configure the carbon accounting algorithm adapted to the target audience;

Establish the statistical dimension and organizational structure of the target object;

Automatically match the carbon accounting algorithm applicable to each of the statistical dimensions according to the organizational structure;

The data to be accounted of the target object is collected, and the calculation is performed through the carbon accounting algorithm after the synergy verification is completed according to the basic information, and the carbon emission result is output.

Optionally, the multi-dimensional carbon accounting method also includes:

Use the carbon emission prediction model to predict carbon emission data.

Optionally, the basic information required for configuring the carbon accounting algorithm adapted to the target object includes:

According to the region and industry of the target object, automatically select the policy standard applicable to the target object, and configure the basic information according to the general accounting guidelines, the basic information includes the calculation of emission factors and activity data involved in the target object formula.

Optionally, the completion of the coordination verification includes:

Analyzing the synergy between the historical carbon emission data of the target object and carbon dioxide emission, and completing the verification of the data to be calculated;

The accounting through the carbon accounting algorithm includes:

When the range of change of the data to be accounted is within the allowable range of change, the data to be accounted for is calculated by the carbon accounting algorithm;

Otherwise, feed back to the target object for correction or supplementary proof materials.

Optionally, when the statistical dimension is a park, the multi-dimensional carbon accounting method further includes:

Obtain the public facilities of the park;

The carbon emission data generated by the enterprises of various dimensions under the park, the carbon emission data generated by the electricity and heat of public facilities in the park, and the carbon emission data generated by the vegetation in the park through photosynthesis are aggregated to form the carbon emission data of the park. row data.

Optionally, the carbon emission prediction model is used to predict carbon emission data, including:

Generate a carbon emission prediction model through time series prediction based on historical carbon emission data and carbon emission data after synergy analysis;

Use the carbon emission prediction model to display carbon emission data in graphs and predict trends, so as to realize carbon emission prediction for years without guidelines.

This application provides a multi-dimensional carbon accounting system, including:

The algorithm configuration module is used to configure the basic information required by the carbon accounting algorithm adapted to the target object;

A structure construction module, used to establish the statistical dimension and organizational structure of the target object;

The algorithm configuration module is also used to automatically match the carbon accounting algorithm applicable to each of the statistical dimensions according to the organizational structure;

The verification and accounting module is used to collect the data to be accounted for of the target object, perform calculation through the carbon accounting algorithm after completing the synergy verification according to the basic information, and output the carbon emission result.

Optionally, the system also includes a prediction module;

The prediction module is used to predict carbon emission data using a carbon emission prediction model.

The present application also provides a computer device, including a memory and a processor, the memory stores a computer program, and the processor implements the steps of the method when executing the computer program.

The present application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of any one of the above-mentioned methods are implemented.

The multi-dimensional carbon accounting method of this application, by configuring the basic information required by the carbon accounting algorithm adapted to the target object; establishing the statistical dimension and organizational structure of the target object, can help companies find out their carbon background and effectively find carbon emissions that affect their own The key nodes or factors of the target object can reduce the cost of transformation; automatically match the carbon accounting algorithm applicable to each of the statistical dimensions according to the organizational structure; collect the data to be accounted for the target object and complete the collaborative calibration based on the basic information After the verification, the carbon accounting algorithm is used for accounting, the carbon emission results are output, and the historical data is used to realize the automatic verification of the carbon emission data, so that the accounting results are more accurate and the accuracy of the carbon accounting results is improved.

Description of drawings

Fig. 1 is the flowchart of the multi-dimensional carbon accounting method of an embodiment of the present application;

Fig. 2 is a flowchart of a multi-dimensional carbon accounting method for industrial enterprises according to an embodiment of the present application;

Fig. 3 is a flow chart of a multi-dimensional carbon accounting method for a steel production enterprise according to an embodiment of the present application;

Figure 4 is a schematic diagram of the accounting method of "GB/T 32151.5-2015 Greenhouse Gas Emission Accounting and Reporting Requirements Part 5: Iron and Steel Production Enterprises";

Figure 5 is a graph of the forecast simulation curve for the current and future carbon emission data of iron and steel production enterprises;

FIG. 6 is a block diagram of a multi-dimensional carbon accounting system according to an embodiment of the present application;

FIG. 7 is a block diagram of a multi-dimensional carbon accounting system according to an embodiment of the present application;

Fig. 8 is a block diagram of a multi-dimensional carbon accounting system for industrial enterprises according to an embodiment of the present application.

Detailed ways

The present application is further described below by means of examples, but the present application is not limited thereto within the scope of the examples.

As shown in Figure 1, this application provides a flowchart of a multi-dimensional carbon accounting method. The multi-dimensional carbon accounting method includes the following steps:

Step S10, configuring the basic information required by the carbon accounting algorithm adapted to the target object;

Step S11, establishing the statistical dimension and organizational structure of the target object;

Step S12, automatically matching the carbon accounting algorithm applicable to each statistical dimension according to the organizational structure;

Step S13 , collect the data to be accounted for of the target object, perform the calculation through the carbon accounting algorithm after completing the synergy verification according to the basic information, and output the carbon emission result.

The target objects of this embodiment include industrial enterprises, and may also include enterprises in other industries. Therefore, the multi-dimensional carbon accounting method of this embodiment can be applied to the multi-dimensional carbon accounting method for industrial enterprises, and can also be applied to the carbon accounting of other industries.

The multi-dimensional carbon accounting method of this embodiment, by configuring the basic information required by the carbon accounting algorithm adapted to the target object; establishing the statistical dimension and organizational structure of the target object, can help enterprises find out their carbon background and effectively find out the factors that affect their own carbon emissions. Key nodes or factors to reduce the cost of transformation; automatically match the carbon accounting algorithm applicable to each statistical dimension according to the organizational structure; collect the data to be accounted for the target object and perform accounting through the carbon accounting algorithm after completing the synergy verification based on the basic information. Output carbon emission results, use historical data to realize automatic verification of carbon emission data, make accounting results more accurate, and improve the accuracy of carbon accounting results.

In an optional implementation manner, the multi-dimensional carbon accounting method further includes: using a carbon emission prediction model to predict carbon emission data. By predicting the trend of carbon emission data, it is possible to carry out carbon emission trial calculations for years without guidelines.

In an optional implementation, step S10 includes: automatically selecting the policy standards applicable to the target object according to the region and industry where the target object is located, and configuring basic information according to the general accounting guidelines. The basic information includes the target object. Emission factors and activity data calculation formulas. Taking industrial enterprises as an example, by automatically selecting the policy standards applicable to industrial enterprises and configuring the involved emission factors and activity data calculation formulas according to the general accounting guidelines, it can help enterprises reduce the workload of filling in activity data and speed up the enterprises' calculation of non-production carbon emissions. Real-time understanding of the platoon.

In an optional implementation, steps S11 and S12 include: establishing statistical dimensions and organizational structures required by industrial enterprises, and automatically matching carbon accounting algorithms applicable to each dimension according to the established structures. Specifically: according to the energy consumption granularity required by the enterprise for carbon accounting, establish a multi-dimensional structure, such as a five-level structure of enterprise-factory-workshop-production line-equipment. Each level of architecture adapts to the algorithm it applies to. When each level of architecture adapts to its applicable algorithm, it will multiply the existing accounting results by the correction factor a, and the value of a is the ratio of the consumption of a unit standard product to the consumption of this production. In order to make the calculated carbon emission results W ₁ , W ₂ , W ₃ , W ₄ , and W ₅ (respectively corresponding to the enterprise-factory-workshop-production line-equipment) comply with the hierarchical cumulative relationship in the architecture. If the highest dimension is the park, you need to fill in and enter the public facilities in the park. By quickly establishing multi-dimensional architectural relationships among parks, enterprises, factories, workshops, and equipment and visually displaying them, it is possible to achieve rapid multi-dimensional carbon accounting, help enterprises find out their carbon background, accelerate enterprises' understanding of real-time carbon emissions, and deepen energy consumption. Granularity control; automatically match the carbon accounting algorithm applicable to each dimension through the architecture to modify and configure the latest algorithm within the industry, region, and enterprise to ensure that the accounting data meets the requirements of carbon emission reporting.

In an optional implementation, the synergy verification is completed in step S13, including: analyzing the synergy between the historical carbon emission data of the target object and carbon dioxide emissions, and completing the verification of the data to be accounted; in step S13, passing The carbon accounting algorithm is used for accounting, including: when the change range of the data to be accounted is within the allowable range of change, the accounting data is calculated through the carbon accounting algorithm; otherwise, it is fed back to the target object for correction or supplementary proof materials.

Specifically, the synergy verification is performed on the basic data imported manually or automatically entered by data collection, and the basic data is the data to be calculated. By analyzing the synergy between the company's carbon emission regional data and CO ₂ emissions in previous years, the rationality and consistency of the carbon emission data is verified. If the change range of the carbon emission is within the allowable change range, enter In the accounting stage, if it is not within the allowable range, it will be fed back to the enterprise for correction or supplementary proof materials. In particular, the specific algorithm of the synergy analysis in this embodiment is that if the carbon emission produced by an enterprise is C ₁ and the range of change is n ₁ , if the range of change is within n, then the carbon emission accounting of the enterprise is reasonable. The specific calculation method for the range of change is:

In the formula, C ₀ is the calculation result of the last change period; x _i is the amount of the i-th production fuel; y _i is the loss coefficient, which is the consumption of the i-th production fuel in unit standard product and the consumption of this production _ki represents the quality of the i-th production fuel; j _i represents the unit emission factor of the i-th production fuel; E is the consumed electricity; _ef is the emission factor of the unit electricity in the area.

The above-mentioned variation range n is set by the enterprise itself, and the value includes a value less than or equal to 3, and may also include other numbers greater than 3.

In an optional implementation, when the statistical dimension is the park, the multi-dimensional carbon accounting method also includes: obtaining the public facilities of the park; The carbon emission data generated by the heat and the carbon emission data generated by the photosynthesis of the vegetation in the park are aggregated to form the carbon emission data of the park.

Specifically, calculate the carbon dioxide emissions of the enterprise in previous years, and issue an accounting report. In particular, if the highest level is the park level, the calculation result is obtained by aggregation of multi-dimensional low-dimensional data. For the carbon emission data that has been verified through collaborative analysis, a carbon emission report is automatically generated in the corresponding organizational structure based on the configured algorithm, showing the established carbon factors and carbon emissions for each dimension.

In particular, if there is currently no policy document at the park level to specify the applicable algorithm, the algorithm selected in this solution is obtained by aggregating the data of each sub-dimension under the park. The specific aggregation method is: Divide the carbon emission T of the park into three categories, namely production carbon emission T ₁ , public carbon emission T ₂ , and green carbon sink T ₃ . The park's carbon emissions are the sum of the three types of carbon emissions. Among them, the production carbon emission is the sum of the carbon emission results of the subordinate enterprises in all dimensions; the public carbon emission is the carbon emission generated by the electricity and heat consumption of public facilities in the park, which is calculated using the ipcc (United Nations Intergovernmental Panel on Climate Change) standard; the green carbon emission Sink refers to the amount of carbon dioxide absorbed by the vegetation in the park through photosynthesis, and is calculated according to the forestry carbon sink measurement method. The data aggregation formula of each sub-dimension is as follows:

T＝T ₁ +T ₂ -T ₃

T ₃ =v _f ×δ×ρ×γ

In the formula, M _i is the final carbon emission result of each enterprise in the park in step S11; AD _i is the unit energy consumption of public facilities; EF _i is the emission factor corresponding to the energy of public facilities; GWP is the global warming trend, which can be found in ipcc Query in the guide; v _f is tree stock volume, δ is biomass expansion coefficient, ρ is bulk density, and γ is carbon content.

In an optional implementation, the carbon emission prediction model is used to predict carbon emission data, including: generating a carbon emission prediction model through time series prediction based on historical carbon emission data and carbon emission data after synergy analysis; using The carbon emission prediction model displays carbon emission data in graphs and predicts trends, so as to realize carbon emission prediction for years without guidelines.

In this embodiment, various types of data are analyzed and evaluated on the obtained carbon emission data, and the carbon dioxide emission of the enterprise in a certain period of time in the future is calculated according to the results of the analysis and evaluation. Specifically: according to the existing carbon accounting results, that is, the historical carbon accounting results of the enterprise and the synergy analysis results in step S13, a carbon emission prediction model is generated through time series prediction. According to the carbon emission prediction model, a more reasonable and accurate prediction of the future carbon emissions of the enterprise can be made before the corresponding index documents are issued.

The generation process of establishing the carbon emission prediction model is as follows:

Step 1: Assume X0 is the original non-negative sequence:

X ₀ ＝{x _(0,1) ,x _(0,2) ,…,x _(0,n) }

Where x _(0,k) ≥ 0, k=1,2,…,25

The sequence can be generated by using accumulation

X ₀ ＝{x _(0,1) ,x _(0,2) ,…,x _(0,n) }

generate sequence X ₁

X ₁ ＝{x _(1,1) ,x _(1,2) ,…,x _(1,n) }

in

The second step: use the generated sequence X ₁ to establish the general form of the model:

x _(0,k) + a*z _(1,k) = b (1)

Expressed as a differential equation as follows:

Z1 generates a sequence for the immediate mean of X1:

Z ₁ ＝{z _(1,1) ,z _(1,2) ,…,z _(1,n) }

in

z _(1,k) ＝0.5*x _(1,k) +0.5*x _(1,k-1) ，k＝1,2,…,25 (3)

In the gray differential equation model, a and b are the parameters to be estimated, which are the development recovery number and the endogenous control recovery number respectively; the least square estimation parameter list of the gray differential equation satisfies:

σ＝(a,b) ^T ＝(B ^T *B) ^- 1*B ^T *Y (4)

Y is a column vector, B is a construction matrix

Step Three: Build a Carbon Prediction Model

Combining the above (1), (3) and (4) to solve the formula (2):

because

x _(1,0) = x _(0,1)

Therefore, the established carbon emission prediction model is as follows

Step 4: Calculate the reduction value of the original data to obtain the carbon prediction model:

x _(0,k+1) ＝x _(1,k+1) -x _(1,k) ，k＝1,2,…,n

The multi-dimensional carbon accounting method in this embodiment makes full use of the new generation of interconnection technology, establishes a carbon prediction model through the analysis of regional energy consumption, carbon emissions, historical carbon accounting results of enterprises, and production consumption, and completes the year without guidelines And future carbon accounting trial calculations, help companies improve their own efficiency in the use of various energy sources, take the road of clean, low-carbon, safe and efficient utilization, and promote the development of "low-carbon manufacturing".

As shown in Figure 2, in an optional embodiment, a multi-dimensional carbon accounting method for industrial enterprises includes the following steps:

Step S21, selecting the accounting method and configuring the algorithm;

Step S22, the accounting framework is determined, and the algorithm is adaptive;

Step S23, data verification of the calculation results; the data verification process is the same as the above synergy verification, and will not be repeated here.

Step S24, carbon emission report is issued;

Step S25, carbon data analysis;

Step S26, establishing a carbon prediction model. The specific model building process is the same as above and will not be repeated here.

Taking a steel production company as an example, the implementation process of the multi-dimensional carbon accounting method is introduced in detail below: the steel production company has multiple sub-factories, and its energy granularity for carbon emission The accounting steps are shown in Figure 3, including:

S31: According to the industry and region of the enterprise, use the algorithm configuration tool to configure the calculation methods involved in the guide to obtain the carbon emission data generated by various energy sources. Specifically, select "GB/T 32151.5-2015 Greenhouse Gas Emission Accounting and Reporting Requirements Part 5: Iron and Steel Production Enterprises", refer to Figure 4, the daily production of this enterprise uses tar, crude benzene, coke, anthracite, limestone, white cloud Produce fuels such as stone and pig iron, purchase electricity and heat for equipment operation, use algorithm configuration tools to configure the calculation methods involved in the guide, and obtain carbon emission data generated by various energy sources. Figure 4 shows that iron and steel production enterprises go through the coking process, sintering/pelletizing process to form sinter and pellets, and then go through the ironmaking process to form molten iron, and then go through the refining process to form crude steel, and then go through the steel rolling process to form steel.

S32. Establish a three-level structure of enterprise-factory-production line according to the energy granularity that the enterprise needs to count. Specifically, referring to Figure 4, it can be seen that the enterprise has five production lines of coking, sintering, ironmaking, refining, and steel rolling. In this way, a three-dimensional structure of enterprise-factory-production line is established.

S33. According to the carbon emission data released by the region where the enterprise is located in the year and the carbon emission data imported by the enterprise, a synergistic analysis is carried out to complete the data verification. Collaborative analysis refers to the analysis of energy consumption, enterprise output, and regional carbon emissions.

S34. For carbon emission data, a carbon emission report is automatically generated based on the configured algorithm and framework, showing the fuel combustion emissions, process emissions, purchased electricity emissions, output electricity emissions, solid-state Carbon product emissions, and summarize and display the total carbon emissions.

S35. Based on the carbon accounting results of the enterprise, perform graphical statistical analysis.

S36. Based on the historical carbon accounting results of the enterprise and the synergy analysis results in step S33, a carbon emission prediction model is established through time series prediction, and the current and future carbon emissions of the enterprise are calculated and predicted. The predictions made according to the established carbon emission prediction model are shown in Table 1 below:

Table 1 Simulation results of the carbon emission prediction model

It can be seen from Table 1 that using the simulated value of carbon emission data y predicted by the carbon emission prediction model can realize the graphic display and trend prediction of carbon emission data.

According to the data in Table 1, the simulation curve in Figure 5 can be drawn. It can be seen from Fig. 5 that the carbon emission data curve predicted by the carbon emission prediction model (2GM (1,1 simulation curve) in Fig. 5) is basically consistent with the original carbon emission data curve (original curve 1 in Fig. 5). Chart display and trend forecasting of carbon emission data.

At the same time, using the carbon emission forecasting model, the relevant forecast results for the next five months are shown in Table 2 below:

Table 2 Prediction results of the y value of the carbon emission prediction model

It can be seen from Table 2 that the carbon emission prediction model can be used to conduct carbon emission trial calculations for years without guidelines.

As shown in Figure 6, this application provides a multi-dimensional carbon accounting system, including:

Algorithm configuration module 1, used to configure the basic information required by the carbon accounting algorithm adapted to the target object;

Architecture construction module 2, used to establish the statistical dimension and organizational structure of the target object;

The algorithm configuration module 1 is also used to automatically match the carbon accounting algorithm applicable to each statistical dimension according to the organizational structure;

The verification and accounting module 3 is used to collect the data to be accounted for of the target object and perform calculation through the carbon accounting algorithm after completing the synergy verification according to the basic information, and output the carbon emission results.

The target objects of this embodiment include industrial enterprises, and may also include enterprises in other industries. Therefore, the multi-dimensional carbon accounting system of this embodiment can be applied to the multi-dimensional carbon accounting system for industrial enterprises, and can also be applied to the carbon accounting of other industries.

The multi-dimensional carbon accounting system of this embodiment configures the basic information required by the carbon accounting algorithm adapted to the target object through the algorithm configuration module 1; the architecture construction module 2 establishes the statistical dimension and organizational structure of the target object, which can help enterprises find out the carbon family background , effectively find the key nodes or factors that affect its own carbon emissions, and reduce the cost of transformation; the algorithm configuration module 1 also automatically matches the carbon accounting algorithm applicable to each statistical dimension according to the organizational structure; the verification and accounting module 3 collects the target objects to be accounted The data is calculated through the carbon accounting algorithm after the synergy verification is completed according to the basic information, and the carbon emission results are output. The historical data is used to realize the automatic verification of the carbon emission data, which makes the accounting results more accurate and improves the accuracy of the carbon accounting results. Rate.

In an optional implementation manner, as shown in FIG. 7 , the system further includes a prediction module 4; the prediction module 4 is used to predict carbon emission data using a carbon emission prediction model. The trend prediction of carbon emission data is carried out through the forecast module 4, and the trial calculation of carbon emission can be carried out for years without guidelines.

A specific example is used below to illustrate: As shown in Figure 8, a multi-dimensional carbon accounting system for industrial enterprises includes: algorithm configuration unit 11, architecture construction unit 21, data acquisition unit 31, input verification unit 32, carbon emissions Accounting unit 33 , analysis and prediction unit 41 . The algorithm configuration module 1 includes an algorithm configuration unit 11, the architecture construction module 2 includes an architecture construction unit 21, the verification and accounting module 3 includes a data collection unit 31, an input verification unit 32 and a carbon emission accounting unit 33, and the prediction module 4 includes an analysis and prediction unit 41.

The algorithm configuration unit 11 is used for adaptive configuration of carbon accounting methods. In an optional implementation, the algorithm configuration unit 11 is used to automatically select the policy standards applicable to the target object according to the region and industry where the target object is located, and configure the basic information according to the general accounting guideline. The basic information includes the target object related to Emission factors and activity data calculation formulas obtained. Taking industrial enterprises as an example, by automatically selecting the policy standards applicable to industrial enterprises and configuring the involved emission factors and activity data calculation formulas according to the general accounting guidelines, it can help enterprises reduce the workload of filling in activity data and speed up the enterprises' calculation of non-production carbon emissions. Real-time understanding of the platoon.

The architecture construction unit 21 is used for the architecture construction of the organizational structure of industrial enterprises and the required accounting scope. In an optional embodiment, the structure construction unit 21 establishes the statistical dimensions and organizational structure required by industrial enterprises, and the algorithm configuration unit 11 is also used to automatically match the carbon accounting algorithm applicable to each dimension according to the set structure. Specifically: according to the granularity of energy consumption required by the enterprise for carbon accounting, establish a multi-dimensional structure, such as a five-level structure of enterprise-factory-workshop-production line-equipment. Each level of architecture adapts to the algorithm it applies to. When each level of architecture adapts to its applicable algorithm, it will multiply the existing accounting results by the correction factor a, and the value of a is the ratio of the consumption of a unit standard product to the consumption of this production. In order to make the calculated carbon emission results W ₁ , W ₂ , W ₃ , W ₄ , and W ₅ (respectively corresponding to the enterprise-factory-workshop-production line-equipment) conform to the hierarchical cumulative relationship in the framework. If the highest dimension is the park, you need to fill in and enter the public facilities in the park. By quickly establishing multi-dimensional architectural relationships among parks, enterprises, factories, workshops, and equipment and visually displaying them, it is possible to achieve rapid multi-dimensional carbon accounting, help enterprises find out their carbon background, accelerate enterprises' understanding of real-time carbon emissions, and deepen energy consumption. Granularity control; automatically match the carbon accounting algorithm applicable to each dimension through the architecture, so as to modify and configure the latest algorithm within the industry, region, and enterprise, and ensure that the accounting data meets the requirements of carbon emission reporting.

The data acquisition unit 31 is used for the collection of industrial enterprise accounting data;

The input verification unit 32 is used to realize the automatic verification of the carbon emission data, so as to make the accounting results more accurate. In an optional embodiment, the input verification unit 32 is used to analyze the synergy between the historical carbon emission data of the target object and carbon dioxide emissions, and complete the verification of the data to be accounted; When within the range of change, the accounting data will be calculated through the carbon accounting algorithm; otherwise, it will be fed back to the target object for correction or supplementary proof materials.

Specifically, the synergy verification is performed on the basic data imported manually or automatically entered by data collection, and the basic data is the data to be calculated. By analyzing the synergy between the company's carbon emission regional data and CO ₂ emissions in previous years, the rationality and consistency of the carbon emission data is verified. If the change range of the carbon emission is within the allowable change range, enter In the accounting stage, if it is not within the allowable range, it will be fed back to the enterprise for correction or supplementary proof materials. In particular, the specific algorithm of the synergy analysis in this embodiment is that if the carbon emission produced by an enterprise is C ₁ and the range of change is n ₁ , if the range of change is within n, then the carbon emission accounting of the enterprise is reasonable. The specific method for calculating the range of change is as described above, and will not be repeated here.

The carbon emission accounting unit 33 is used for accounting of carbon dioxide emissions of industrial enterprises. In an optional implementation, when the statistical dimension is the park, the carbon emission accounting unit 33 is also used to obtain the public facilities of the park; The carbon emission data generated by the heat and the carbon emission data generated by the vegetation in the park through photosynthesis are aggregated to form the carbon emission data of the park.

Specifically, calculate the carbon dioxide emissions of the enterprise in previous years, and issue an accounting report. In particular, if the highest level is the park level, the calculation result is obtained by aggregation of multi-dimensional low-dimensional data. For the carbon emission data that has been verified through collaborative analysis, a carbon emission report is automatically generated in the corresponding organizational structure based on the configured algorithm, showing the established carbon factors and carbon emissions for each dimension.

In particular, if there is currently no policy document at the park level to specify the applicable algorithm, the algorithm selected in this solution is obtained by aggregating the data of each sub-dimension under the park. The specific aggregation method is: Divide the carbon emission T of the park into three categories, namely production carbon emission T ₁ , public carbon emission T ₂ , and green carbon sink T ₃ . The park's carbon emissions are the sum of the three types of carbon emissions. Among them, the production carbon emission is the sum of the carbon emission results of the subordinate enterprises in all dimensions; the public carbon emission is the carbon emission generated by the electricity and heat of the public facilities in the park, and is calculated using the ipcc standard; the green carbon sink is the absorption of the vegetation in the park through photosynthesis The amount of carbon dioxide is calculated according to the forestry carbon sequestration method. The data aggregation formulas of each sub-dimension are as described above, and will not be repeated here.

The analysis and prediction unit 41 is used for the analysis of the collected carbon emission data, including an analysis and prediction model, which can predict the subsequent carbon emission data. In an optional implementation, the analysis and prediction unit 41 is also used to: generate a carbon emission prediction model through time series prediction according to historical carbon emission data and carbon emission data after synergy analysis; Chart display and trend forecasting of emission data, in order to realize carbon emission forecasting for years without guidelines.

In this embodiment, various types of data are analyzed and evaluated on the obtained carbon emission data, and the carbon dioxide emission of the enterprise in a certain period of time in the future is calculated according to the results of the analysis and evaluation. Specifically: according to the existing carbon accounting results, that is, the historical carbon accounting results and synergy analysis results of enterprises, a carbon emission prediction model is generated through time series prediction. According to the carbon emission prediction model, a more reasonable and accurate prediction of the future carbon emissions of the enterprise can be made before the corresponding index documents are released.

The generation process of establishing the carbon emission prediction model is the same as above, and will not be repeated here.

The multi-dimensional carbon accounting system in this embodiment makes full use of the new generation of interconnection technology, establishes a carbon prediction model through the analysis of regional energy consumption, carbon emissions, historical carbon accounting results of enterprises, and production consumption, and completes the year without guidelines And future carbon accounting trial calculations, help companies improve their own efficiency in the use of various energy sources, take the road of clean, low-carbon, safe and efficient utilization, and promote the development of "low-carbon manufacturing".

In one embodiment, a computer device is provided, including a memory and a processor, the memory stores a computer program, and the processor executes the steps of the above-mentioned method embodiments when the computer program is executed.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the foregoing method embodiments are implemented.

Those of ordinary skill in the art can understand that realizing all or part of the processes in the methods of the above embodiments can be completed by instructing related hardware through computer programs, and the computer programs can be stored in a non-volatile computer-readable storage medium , when the computer program is executed, it may include the procedures of the embodiments of the above-mentioned methods. Wherein, any reference to storage, database or other media used in the various embodiments provided in the present application may include at least one of non-volatile and volatile storage. Non-volatile memory can include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive variable memory (ReRAM), magnetic variable memory (Magnetoresistive Random Access Memory, MRAM), Ferroelectric Random Access Memory (FRAM), Phase Change Memory (Phase Change Memory, PCM), graphene memory, etc. The volatile memory may include random access memory (Random Access Memory, RAM) or external cache memory. As an illustration and not a limitation, the RAM can be in various forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM). The databases involved in the various embodiments provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a blockchain-based distributed database, etc., but is not limited thereto. The processors involved in the various embodiments provided by this application can be general-purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, data processing logic devices based on quantum computing, etc., and are not limited to this.

The technical features of the above embodiments can be combined arbitrarily. To make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be It is considered to be within the range described in this specification.

Although the specific embodiments of the present invention have been described above, those skilled in the art should understand that these are only examples, and the protection scope of the present invention is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principle and essence of the present invention, but these changes and modifications all fall within the protection scope of the present invention.

Claims (10)

1. A method of multidimensional carbon computation, comprising:

configuring basic information required by a carbon computing algorithm adapted to a target object;

establishing a statistical dimension and an organization structure of the target object;

automatically matching a carbon calculation algorithm applicable to each statistical dimension according to the organization structure;

and acquiring data to be checked of the target object, checking through the carbon checking algorithm after the cooperativity check is completed according to the basic information, and outputting a carbon emission result.

2. A multidimensional carbon calculation method as recited in claim 1, further comprising:

carbon emissions data are predicted using a carbon emissions prediction model.

3. The multidimensional carbon computing method of claim 2, wherein the configuring of the basic information required for the target object adapted carbon computing algorithm comprises:

and automatically selecting policy standards applicable to the target object according to the area and industry where the target object is located, and configuring the basic information according to a general accounting guideline, wherein the basic information comprises emission factors and activity data calculation formulas related to the target object.

4. The multi-dimensional carbon computing method of claim 3, wherein the completing a collaborative check comprises:

analyzing the cooperativity of the historical carbon emission data and the carbon dioxide emission of the target object to complete the verification of the data to be calculated;

the performing accounting by the carbon accounting algorithm includes:

when the variation amplitude of the data to be accounted is within an allowable variation range, accounting is carried out on the data to be accounted through the carbon accounting algorithm;

otherwise, feeding back to the target object for correction or supplement of certification materials.

5. The multidimensional carbon calculation method of claim 4, wherein when the statistical dimension is a campus, the multidimensional carbon calculation method further comprises:

acquiring public facilities of the park;

and aggregating carbon row data generated by enterprises of various dimensions under the park, carbon row data generated by using electricity and heat for public facilities of the park and carbon row data generated by photosynthesis of the vegetation of the park to form the carbon row data of the park.

6. The multidimensional carbon computation method of claim 2, wherein the predicting carbon row data using a carbon row prediction model comprises:

generating a carbon row prediction model through time series prediction according to the historical carbon row data and the carbon row data subjected to the collaborative analysis;

and (3) carrying out graph display and trend prediction on the carbon emission data by using the carbon emission prediction model so as to realize carbon emission prediction on the years without guidelines.

7. A multi-dimensional carbon computing system, comprising:

the algorithm configuration module is used for configuring basic information required by a carbon computing algorithm adapted to the target object;

the architecture construction module is used for establishing the statistical dimension and the organization architecture of the target object;

the algorithm configuration module is further used for automatically matching the applicable carbon calculation algorithm of each statistical dimension according to the organization architecture;

and the checking and accounting module is used for acquiring data to be accounted of the target object, performing accounting through the carbon accounting algorithm after the cooperative checking is completed according to the basic information, and outputting a carbon emission result.

8. The multi-dimensional carbon computing system of claim 7, wherein the system further comprises a prediction module;

the prediction module is configured to predict carbon emission data using a carbon emission prediction model.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that,

the processor, when executing the computer program, realizes the steps of the method of any one of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.

Images