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

Abstract

The application discloses a multi-dimensional carbon accounting method, system, device and storage medium. The method comprises the following steps: configuring basic information required by a carbon accounting algorithm adapted to a target object; establishing statistical dimensions and an organizational structure of the target object; automatically matching a carbon accounting algorithm applicable to each statistical dimension according to the organizational structure; collecting to-be-accounted data of the target object, and performing accounting on the to-be-accounted data through the carbon accounting algorithm after completing a collaborative verification according to the basic information, and outputting carbon emission results. The multi-dimensional carbon accounting method uses historical data to realize automatic verification of carbon emission data, so that the accounting result is more accurate, and the accuracy of the carbon accounting result is improved.

Description

Technical Field

[0001] This application relates to the field of carbon accounting technology, and in particular to a multi-dimensional carbon accounting method, system, device and storage medium. Background Technology

[0002] As major carbon emitters, the industrial sector urgently needs to understand its carbon footprint and develop effective carbon planning. Currently, industrial enterprises monitor and collect various carbon-related data, including energy consumption (water, electricity, gas, etc.), wastewater discharge, vehicle exhaust, ambient air quality, hazardous solid waste, and human activities, to calculate their carbon emissions. However, this carbon emission accounting method cannot achieve multi-dimensional accounting. When planning green and energy-saving renovations, enterprises cannot effectively identify the key nodes or factors affecting their carbon emissions. The cost and effectiveness of these renovations often fail to meet the original goals. Furthermore, the lack or incompleteness of historical data leads to low accuracy in carbon accounting results. Summary of the Invention

[0003] The technical problem to be solved by this application is to overcome the shortcomings of existing carbon emission accounting methods, which cannot achieve multi-dimensional accounting and whose accuracy is low due to the lack or incompleteness of historical data. This application provides a multi-dimensional carbon accounting method, system, device and storage medium.

[0004] This application solves the above-mentioned technical problems through the following technical solution:

[0005] This application provides a multi-dimensional carbon accounting method, including:

[0006] Basic information required to configure the carbon accounting algorithm adapted to the target object;

[0007] Establish the statistical dimensions and organizational structure of the target object;

[0008] The appropriate carbon accounting algorithm for each statistical dimension is automatically matched based on the organizational structure.

[0009] The system collects the target object's data to be calculated and performs the calculation using the carbon accounting algorithm after completing the collaboration verification based on the basic information, outputting the carbon emission result.

[0010] Optionally, the multidimensional carbon accounting method further includes:

[0011] Carbon emission prediction models are used to predict carbon emission data.

[0012] Optionally, the basic information required for configuring the carbon accounting algorithm adapted to the target object includes:

[0013] Based on the region and industry of the target object, the applicable policy standards are automatically selected, and the basic information is configured according to the general accounting guidelines. The basic information includes the emission factors and activity data calculation formulas involved in the target object.

[0014] Optionally, the completion of the collaboration verification includes:

[0015] The synergy between the historical carbon emission data and carbon dioxide emissions of the target object is analyzed to verify the data to be calculated.

[0016] The calculation using the carbon accounting algorithm includes:

[0017] When the variation range of the data to be calculated is within the allowable variation range, the carbon accounting algorithm is used to calculate the data to be calculated.

[0018] Otherwise, feedback will be sent to the target object for correction or supplementary supporting materials.

[0019] Optionally, when the statistical dimension is the industrial park, the multi-dimensional carbon accounting method further includes:

[0020] Obtain information about the public facilities in the park;

[0021] The carbon emission data of the park is formed by aggregating the carbon emission data generated by enterprises under the park, the carbon emission data generated by electricity and heat consumption of public facilities in the park, and the carbon emission data generated by vegetation in the park through photosynthesis.

[0022] Optionally, the step of using a carbon emission prediction model to predict carbon emission data includes:

[0023] A carbon emission prediction model is generated through time series prediction based on historical carbon emission data and carbon emission data after collaborative analysis.

[0024] Carbon emission prediction models are used to visualize carbon emission data and predict trends, enabling carbon emission forecasts for years without guidelines.

[0025] This application provides a multi-dimensional carbon accounting system, including:

[0026] The algorithm configuration module is used to configure the basic information required for the carbon accounting algorithm adapted to the target object;

[0027] The architecture construction module is used to establish the statistical dimensions and organizational structure of the target object;

[0028] The algorithm configuration module is also used to automatically match the applicable carbon accounting algorithm for each statistical dimension according to the organizational structure;

[0029] The verification and calculation module is used to collect the data to be calculated of the target object and, based on the basic information, perform calculation through the carbon calculation algorithm after completing the collaborative verification, and output the carbon emission result.

[0030] Optionally, the system further includes a prediction module;

[0031] The prediction module is used to predict carbon emission data using a carbon emission prediction model.

[0032] This application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method.

[0033] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described above.

[0034] This application's multi-dimensional carbon accounting method, by configuring the basic information required for a carbon accounting algorithm suitable for the target object; establishing the statistical dimensions and organizational structure of the target object, can help enterprises understand their carbon footprint, effectively identify key nodes or factors affecting their own carbon emissions, and reduce the cost of transformation; automatically matching the applicable carbon accounting algorithm for each statistical dimension according to the organizational structure; collecting the target object's data to be accounted for and, after completing the collaborative verification based on the basic information, performing the carbon accounting calculation through the carbon accounting algorithm, outputting carbon emission results, and using historical data to achieve automatic verification of carbon emission data, making the accounting results more accurate and improving the accuracy rate of carbon accounting results. Attached Figure Description

[0035] Figure 1 This is a flowchart of a multidimensional carbon accounting method according to an embodiment of this application;

[0036] Figure 2 A flowchart illustrating a multi-dimensional carbon accounting method for industrial enterprises, as an embodiment of this application;

[0037] Figure 3 A flowchart illustrating a multi-dimensional carbon accounting method for steel production enterprises, as described in one embodiment of this application;

[0038] Figure 4 This is a schematic diagram illustrating the accounting method for "GB / T 32151.5-2015 Greenhouse Gas Emissions Accounting and Reporting Requirements Part 5: Steel Production Enterprises";

[0039] Figure 5 This is a simulated graph showing the predicted carbon emissions of steel production enterprises for the current year and in the future.

[0040] Figure 6This is a schematic diagram of the modules of a multidimensional carbon accounting system according to an embodiment of this application;

[0041] Figure 7 This is a schematic diagram of the modules of a multidimensional carbon accounting system according to an embodiment of this application;

[0042] Figure 8 This is a schematic diagram of a multi-dimensional carbon accounting system for industrial enterprises, according to one embodiment of this application. Detailed Implementation

[0043] The present application is further illustrated below by way of embodiments, but this does not limit the present application to the scope of the embodiments.

[0044] like Figure 1 As shown, this application provides a flowchart of a multi-dimensional carbon accounting method, which includes the following steps:

[0045] Step S10: Configure the basic information required for the carbon accounting algorithm adapted to the target object;

[0046] Step S11: Establish the statistical dimensions and organizational structure of the target object;

[0047] Step S12: Automatically match the applicable carbon accounting algorithm for each statistical dimension based on the organizational structure;

[0048] Step S13: Collect the target object's data to be calculated and, based on the basic information, perform the calculation using the carbon accounting algorithm after completing the collaborative verification, and output the carbon emission results.

[0049] The target audience of this embodiment includes industrial enterprises, but may also include enterprises in other industries. Therefore, the multi-dimensional carbon accounting method of this embodiment is applicable to multi-dimensional carbon accounting methods for industrial enterprises, and may also be applicable to carbon accounting in other industries.

[0050] This embodiment of the multi-dimensional carbon accounting method, by configuring the basic information required for the carbon accounting algorithm adapted to the target object; establishing the statistical dimensions and organizational structure of the target object, can help enterprises understand their carbon footprint, effectively identify key nodes or factors affecting their own carbon emissions, and reduce the cost of transformation; automatically matching the applicable carbon accounting algorithm for each statistical dimension according to the organizational structure; collecting the target object's data to be accounted for and performing the carbon accounting algorithm after completing the collaborative verification based on the basic information, outputting the carbon emission results, and using historical data to achieve automatic verification of the carbon emission data, making the accounting results more accurate and improving the accuracy rate of carbon accounting results.

[0051] In one optional implementation, the multi-dimensional carbon accounting method further includes: using a carbon emission prediction model to predict carbon emission data. By predicting trends in carbon emission data, carbon emission calculations can be performed for years without guidelines.

[0052] In one optional implementation, step S10 includes: automatically selecting the applicable policy standards for the target object based on its region and industry, and configuring basic information according to the general accounting guidelines. The basic information includes the emission factors and activity data calculation formulas related to the target object. Taking industrial enterprises as an example, by automatically selecting the applicable policy standards and configuring the relevant emission factors and activity data calculation formulas according to the general accounting guidelines, enterprises can reduce the workload of reporting activity level data and accelerate their real-time understanding of non-production carbon emissions.

[0053] In one optional implementation, steps S11 and S12 include: establishing the statistical dimensions and organizational structure required for the industrial enterprise's carbon accounting calculations, and automatically matching the applicable carbon accounting algorithm for each dimension based on the established structure. Specifically, based on the energy consumption granularity required for the enterprise's carbon accounting, a multi-dimensional structure is established, such as a five-level structure of enterprise-factory-workshop-production line-equipment. Each level of the structure will adapt to its applicable algorithm. When each level of the structure adapts to its applicable algorithm, the existing accounting results will be multiplied by a correction factor 'a', where 'a' is the ratio of the consumption of a unit of standard product to the consumption of this production. This ensures that the calculated carbon emission results W1, W2, W3, W4, W5 (corresponding to enterprise-factory-workshop-production line-equipment, respectively) conform to the cumulative relationship of the levels in the structure. If the highest dimension is the industrial park, then the public facilities of the park need to be reported and entered. By quickly establishing and visually displaying the multi-dimensional architectural relationships of parks, enterprises, factories, workshops, and equipment, rapid multi-dimensional carbon accounting can be achieved, helping enterprises to understand their carbon footprint, accelerate their understanding of real-time carbon emissions, and deepen their control over energy consumption granularity. The architecture automatically matches the applicable carbon accounting algorithms for each dimension to correct and configure the latest algorithms within the industry, region, and enterprise, ensuring that the accounting data meets the requirements of carbon emission reports.

[0054] In one optional implementation, step S13 includes completing the synergy verification, which involves analyzing the synergy between the historical carbon emission data and carbon dioxide emissions of the target object to complete the verification of the data to be calculated; step S13 includes performing calculations using a carbon accounting algorithm, which involves performing calculations on the data to be calculated using a carbon accounting algorithm when the change range of the data to be calculated is within the allowable range; otherwise, feedback is given to the target object for correction or supplementary supporting materials.

[0055] Specifically, a collaborative verification is performed on the basic data that is manually imported or automatically entered through data collection. This basic data is the data to be calculated. By analyzing the synergy between the company's carbon emission regional data and CO2 emissions from previous years, the rationality and consistency of the carbon emission data are verified. If the change in carbon emissions is within the allowable range, the calculation phase begins; otherwise, feedback is provided to the company for correction or supplementary supporting materials. In particular, the specific algorithm for the synergy analysis in this embodiment is as follows: if a company produces a product that generates carbon emissions C1 with a change range of n1, and the change range is within n, then the company's carbon emission calculation is reasonable. The specific method for calculating the change range is as follows:

[0056]

[0057]

[0058] In the formula, C0 is the result calculated in the previous cycle; x i y represents the amount of the i-th type of production fuel used; i is the loss coefficient, which is the ratio of the consumption of the i-th production fuel per unit of standard product to the consumption in that production run; k i Represents the mass of the i-th type of production fuel; j i Represents the unit emission factor of the i-th production fuel; E is the electricity consumed; e f This is the emission factor per unit of electricity in this region.

[0059] The variation range n mentioned above is set by the enterprise itself, and the value can include numbers less than or equal to 3, or other numbers greater than 3.

[0060] In one optional implementation, when the statistical dimension is the park, the multi-dimensional carbon accounting method further includes: acquiring the park's public facilities; and aggregating the carbon emission data generated by enterprises under the park in each dimension, the carbon emission data generated by the park's public facilities through electricity and heat consumption, and the carbon emission data generated by the park's vegetation through photosynthesis to form the park's carbon emission data.

[0061] Specifically, the company's annual carbon dioxide emissions are calculated, and an accounting report is generated. In particular, if the highest level is the industrial park level, the calculation result is derived from the aggregation of multi-dimensional, low-dimensional data. For carbon emission data that has undergone collaborative analysis and verification, a carbon emission report is automatically generated within the corresponding organizational structure based on the configured algorithm, displaying the carbon factor and carbon emission amount for each established dimension.

[0062] Specifically, if there is currently no applicable algorithm specified in policy documents at the park level, the algorithm selected in this plan is derived from the aggregation of data from various sub-dimensions within the park. The specific aggregation method is as follows: Park carbon emissions T are divided into three categories: production carbon emissions T1, public carbon emissions T2, and green carbon sinks T3. Park carbon emissions are the sum of these three categories. Specifically, production carbon emissions are the sum of the carbon emissions from all enterprises within the park; public carbon emissions are the carbon emissions generated by electricity and heat consumption in the park's public facilities, calculated using IPCC (Intergovernmental Panel on Climate Change) standards; and green carbon sinks are the amount of carbon dioxide absorbed by the park's vegetation through photosynthesis, calculated according to forestry carbon sink measurement methods. The aggregation formulas for each sub-dimension are as follows:

[0063] T = T1 + T2 - T3

[0064]

[0065] T3 = v f ×δ×ρ×γ

[0066] In the formula M i For the final carbon emission results of each enterprise in the park in step S11; AD i That is, the unit energy consumption of public facilities; EF i This refers to the emission factor corresponding to energy consumption in public facilities; GWP represents the global warming trend, which can be found in the IPCC guidelines; v f δ represents tree stock volume, ρ represents biomass expansion coefficient, ρ represents volumetric density, and γ represents carbon content.

[0067] In one optional implementation, carbon emission prediction models are 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 collaborative analysis; and using the carbon emission prediction model to display carbon emission data in charts and predict trends, so as to achieve carbon emission prediction for years without guidelines.

[0068] In this embodiment, the obtained carbon emission data is analyzed and evaluated using various methods. Based on the analysis and evaluation results, the company's carbon dioxide emissions over a certain period of time are calculated. Specifically, based on existing carbon accounting results, namely the company's historical carbon accounting results and the synergy analysis results in step S13, a carbon emission prediction model is generated through time series forecasting. According to the carbon emission prediction model, a more reasonable and accurate prediction of the company's future carbon emissions can be made before the corresponding indicator documents are issued.

[0069] The process of generating a carbon emission prediction model is as follows:

[0070] Step 1: Assume X0 is the original non-negative sequence:

[0071] X0={x(0,1) ,x (0,2) ,…,x (0,n)}

[0072] Where x (0,k) ≥0, k=1,2,…,25

[0073] Sequences can be generated by accumulation.

[0074] X0={x (0,1) ,x (0,2) ,…,x (0,n)}

[0075] Generate sequence X1

[0076] X1={x (1,1) ,x (1,2) ,…,x (1,n)}

[0077] in

[0078] Step 2: Use the previously generated sequence X1 to establish the general form of the model:

[0079] x (0,k) +a*z (1,k) =b (1)

[0080] The following can be expressed using a differential equation:

[0081]

[0082] Z1 is the sequence generated from the nearest neighbor mean of X1:

[0083] Z1={z (1,1) ,z (1,2) ,…,z (1,n)}

[0084] in

[0085] z (1,k) =0.5*x (1,k) +0.5*x (1,k-1) , k=1,2,…,25 (3)

[0086] In the grey differential equation model, a and b are the parameters to be estimated, representing the developmental recovery number and the endogenous control recovery number, respectively; the least squares estimation parameter sequence of the grey differential equation satisfies:

[0087] σ=(a,b) T = (B T *B) - 1*B T *Y (4)

[0088] Y is a column vector, and B is the construction matrix.

[0089]

[0090]

[0091] Step 3: Constructing a carbon prediction model

[0092] Solving equation (2) by combining (1), (3), and (4) above, we get:

[0093]

[0094] because

[0095] x (1,0) =x (0,1)

[0096] Therefore, the carbon emission prediction model is established as follows:

[0097]

[0098] Step 4: Obtain the restored values ​​from the original data to get the carbon prediction model.

[0099] x (0,k+1) =x (1,k+1) -x (1,k) k = 1, 2, ..., n

[0100] The multi-dimensional carbon accounting method in this embodiment makes full use of next-generation Internet technology. By analyzing regional energy consumption, carbon emissions, historical carbon accounting results of enterprises, and production consumption, a carbon prediction model is established. The carbon accounting trial calculations are completed for years without guidelines and for the future. This helps improve the efficiency of enterprises in using various energy sources, promotes clean, low-carbon, safe and efficient utilization, and advances the development of "low-carbon manufacturing".

[0101] like Figure 2 As shown, in one optional embodiment, a multi-dimensional carbon accounting method for industrial enterprises includes the following steps:

[0102] Step S21: Select the calculation method and configure the algorithm;

[0103] Step S22: The accounting framework is determined, and the algorithm adapts.

[0104] Step S23: Verify the calculation results data; the data verification process is the same as the above-mentioned collaborative verification, and will not be repeated here.

[0105] Step S24: Issuance of carbon emission report;

[0106] Step S25: Carbon data analysis;

[0107] Step S26: Carbon prediction model establishment. The specific model establishment process is the same as above and will not be repeated here.

[0108] The following uses a steel production company as an example to illustrate the implementation process of a multi-dimensional carbon accounting method: This steel production company has multiple subsidiary plants, and its carbon emission statistics are only granular at the plant level. The multi-dimensional carbon accounting steps are as follows: Figure 3 As shown, it includes:

[0109] S31: Based on the enterprise's industry and region, configure the calculation methods mentioned in the guidelines using the algorithm configuration tool to obtain carbon emission data for various energy sources. Specifically, select "GB / T 32151.5-2015 Greenhouse Gas Emissions Accounting and Reporting Requirements Part 5: Steel Production Enterprises," and refer to... Figure 4 The company uses fuels such as coal tar, crude benzene, coke, anthracite, limestone, dolomite, and pig iron in its daily production. It also purchases electricity and heat for equipment operation. The company uses an algorithm configuration tool to configure the calculation methods involved in the guidelines to obtain carbon emission data for various energy sources. Figure 4 The process involves washing coal and other materials in steel production enterprises, which undergoes coking and sintering / pelletizing processes to form sintered ore and pelletized ore. Then, it undergoes ironmaking to form molten iron, refining to form crude steel, and finally rolling to form steel products.

[0110] S32. Based on the energy granularity that the enterprise needs to collect statistics on, establish a three-tiered architecture of enterprise-factory-production line. For details, refer to... Figure 4 It can be seen that the company has five production lines: coking, sintering, ironmaking, refining, and steel rolling, thus establishing a three-level structure of enterprise-factory-production line.

[0111] S33. Conduct a collaborative analysis based on the carbon emission data published by the region where the company is located in that year and the carbon emission data submitted by the company to complete the data verification. The collaborative analysis involves analyzing energy consumption in relation to the company's output and the regional carbon emission level.

[0112] S34. For carbon emission data, carbon emission reports are automatically generated based on the configured algorithm and architecture, showing the emissions from fuel combustion, process emissions, purchased electricity emissions, output electricity emissions, and carbon sequestration products from two dimensions: enterprise and factory, and summarizing and displaying the total carbon emissions.

[0113] S35. Based on the company's carbon accounting results, conduct graphical statistical analysis.

[0114] S36. Based on the company's historical carbon accounting results and the synergy analysis results in step S33, a carbon emission prediction model is established through time series forecasting to calculate and predict the company's carbon emissions for the current year and future years. The predictions made based on the established carbon emission prediction model are shown in Table 1 below:

[0115] Table 1 Simulation results of the carbon emission prediction model

[0116]

[0117]

[0118] As shown in Table 1, the simulated carbon emission data y predicted by the carbon emission prediction model can be used to display carbon emission data in charts and predict trends.

[0119] Based on the data in Table 1, we can conclude that... Figure 5 The simulated curve in the image. (From...) Figure 5 It can be seen that the carbon emission data curve predicted using the carbon emission prediction model ( Figure 5 The 2GM(1,1 simulated curve) and the original carbon emission data curve ( Figure 5 The original curves are basically consistent, enabling the visualization and trend prediction of carbon emission data.

[0120] Meanwhile, the carbon emission prediction model yielded the following forecast results for the next five months, as shown in Table 2:

[0121] Table 2. Prediction results of y-values ​​from the carbon emission prediction model.

[0122]

[0123] As can be seen from Table 2, carbon emission prediction models can be used to perform carbon emission calculations for years without guidelines.

[0124] like Figure 6 As shown, this application provides a multi-dimensional carbon accounting system, including:

[0125] Algorithm configuration module 1 is used to configure the basic information required for the carbon accounting algorithm adapted to the target object;

[0126] Architecture construction module 2 is used to establish the statistical dimensions and organizational structure of the target object;

[0127] Algorithm configuration module 1 is also used to automatically match the appropriate carbon accounting algorithm for each statistical dimension based on the organizational structure;

[0128] The verification and accounting module 3 is used to collect the data to be calculated of the target object and perform accounting through the carbon accounting algorithm after completing the collaborative verification based on the basic information, and output the carbon emission results.

[0129] The target audience of this embodiment includes industrial enterprises, but can also include enterprises in other industries. Therefore, the multi-dimensional carbon accounting system of this embodiment is applicable to multi-dimensional carbon accounting systems for industrial enterprises, and can also be applied to carbon accounting in other industries.

[0130] The multi-dimensional carbon accounting system in this embodiment configures the basic information required by the carbon accounting algorithm for the target object through the algorithm configuration module 1; the architecture construction module 2 establishes the statistical dimensions and organizational structure of the target object, which can help enterprises understand their carbon footprint, effectively find the key nodes or factors affecting their own carbon emissions, and reduce the cost of transformation; the algorithm configuration module 1 also automatically matches the applicable carbon accounting algorithm for each statistical dimension according to the organizational structure; the verification and accounting module 3 collects the data to be calculated of the target object and performs accounting through the carbon accounting algorithm after completing the collaborative verification based on the basic information, outputs the carbon emission results, and uses historical data to realize the automatic verification of carbon emission data, making the accounting results more accurate and improving the accuracy rate of carbon accounting results.

[0131] In one alternative implementation, such as Figure 7 As shown, the system also includes a prediction module 4; the prediction module 4 is used to predict carbon emission data using a carbon emission prediction model. By predicting the trend of carbon emission data through the prediction module 4, carbon emission calculations can be performed for years without guidelines.

[0132] The following is a specific example to illustrate this: Figure 8 As shown, a multi-dimensional carbon accounting system for industrial enterprises includes: an algorithm configuration unit 11, an architecture construction unit 21, a data acquisition unit 31, an input verification unit 32, a carbon emission accounting unit 33, and an analysis and prediction unit 41. The algorithm configuration module 1 includes the algorithm configuration unit 11, the architecture construction module 2 includes the architecture construction unit 21, the verification and accounting module 3 includes the data acquisition unit 31, the input verification unit 32, and the carbon emission accounting unit 33, and the prediction module 4 includes the analysis and prediction unit 41.

[0133] The algorithm configuration unit 11 is used for adaptive configuration of the carbon accounting method. In one optional embodiment, the algorithm configuration unit 11 is used to automatically select the applicable policy standards for the target object based on its region and industry, and configure basic information according to the general accounting guidelines. The basic information includes the emission factors and activity data calculation formulas involved in the target object. Taking industrial enterprises as an example, by automatically selecting the applicable policy standards for industrial enterprises and configuring the relevant emission factors and activity data calculation formulas according to the general accounting guidelines, enterprises can reduce the workload of reporting activity level data and accelerate their real-time understanding of non-production carbon emissions.

[0134] The architecture construction unit 21 is used for constructing the organizational structure and required accounting scope of industrial enterprises. In one optional implementation, the architecture construction unit 21 establishes the statistical dimensions and organizational structure required for the industrial enterprise to be measured, and the algorithm configuration unit 11 is also used to automatically match the applicable carbon accounting algorithm for each dimension according to the established architecture. Specifically, based on the energy consumption granularity required for the enterprise to perform carbon accounting, a multi-dimensional architecture is established, such as a five-level architecture of enterprise-factory-workshop-production line-equipment. Each level of architecture will adapt to its applicable algorithm. When each level of architecture adapts to its applicable algorithm, the existing accounting result will be multiplied by a correction factor a, where a is the ratio of the consumption of a unit of standard product to the consumption of this production. This ensures that the calculated carbon emission results W1, W2, W3, W4, W5 (corresponding to enterprise-factory-workshop-production line-equipment respectively) conform to the cumulative relationship of the levels in the architecture. If the highest dimension is the industrial park, then the public facilities of the park need to be filled in and entered. By quickly establishing and visually displaying the multi-dimensional architectural relationships of parks, enterprises, factories, workshops, and equipment, rapid multi-dimensional carbon accounting can be achieved, helping enterprises to understand their carbon footprint, accelerate their understanding of real-time carbon emissions, and deepen their control over energy consumption granularity. The architecture automatically matches the applicable carbon accounting algorithms for each dimension to correct and configure the latest algorithms within the industry, region, and enterprise, ensuring that the accounting data meets the requirements of carbon emission reports.

[0135] The data acquisition unit 31 is used to collect accounting data of industrial enterprises;

[0136] The input verification unit 32 is used to automatically verify carbon emission data, making the calculation results more accurate. In one optional embodiment, the input verification unit 32 is used to analyze the synergy between the historical carbon emission data and carbon dioxide emissions of the target object, and complete the verification of the data to be calculated; when the change range of the data to be calculated is within the allowable change range, the data to be calculated is calculated by the carbon accounting algorithm; otherwise, feedback is given to the target object for correction or supplementary supporting materials.

[0137] Specifically, a collaborative verification is performed on the basic data that is manually imported or automatically entered through data collection. This basic data is the data to be calculated. By analyzing the synergy between the company's carbon emission regional data and CO2 emissions from previous years, the rationality and consistency of the carbon emission data are verified. If the change in carbon emissions is within the allowable range, the calculation phase begins; otherwise, feedback is provided to the company for correction or supplementary supporting materials. In particular, the specific algorithm for the synergy analysis in this embodiment is as follows: if a company produces a product that generates carbon emissions C1 with a change range of n1, and the change range is within n, then the company's carbon emission calculation is reasonable. The specific method for calculating the change range is as described above and will not be repeated here.

[0138] The carbon emission accounting unit 33 is used to calculate the carbon dioxide emissions of industrial enterprises. In an optional embodiment, when the statistical dimension is the industrial park, the carbon emission accounting unit 33 is also used to obtain the public facilities of the park; and aggregate the carbon emission data generated by enterprises of various dimensions under the park, the carbon emission data generated by electricity and heat consumption of the park's public facilities, and the carbon emission data generated by the park's vegetation through photosynthesis to form the park's carbon emission data.

[0139] Specifically, the company's annual carbon dioxide emissions are calculated, and an accounting report is generated. In particular, if the highest level is the industrial park level, the calculation result is derived from the aggregation of multi-dimensional, low-dimensional data. For carbon emission data that has undergone collaborative analysis and verification, a carbon emission report is automatically generated within the corresponding organizational structure based on the configured algorithm, displaying the carbon factor and carbon emission amount for each established dimension.

[0140] Specifically, if there are currently no applicable algorithms specified in policy documents at the park level, the algorithm selected in this plan is derived from the aggregation of data from various sub-dimensions within the park. The specific aggregation method is as follows: park carbon emissions T are divided into three categories: production carbon emissions T1, public carbon emissions T2, and green carbon sinks T3. Park carbon emissions are the sum of these three categories. Specifically, production carbon emissions are the sum of the carbon emissions from all enterprises within the park; public carbon emissions are the carbon emissions generated by electricity and heat consumption in the park's public facilities, calculated using the IPCC standard; and green carbon sinks are the amount of carbon dioxide absorbed by the park's vegetation through photosynthesis, calculated according to forestry carbon sink measurement methods. The aggregation formulas for each sub-dimension are as described above and will not be repeated here.

[0141] The analysis and prediction unit 41 is used to analyze the collected carbon emission data, including an analysis and prediction model, which can predict subsequent carbon emission data. In an optional embodiment, the analysis and prediction unit 41 is further used to: generate a carbon emission prediction model through time series prediction based on historical carbon emission data and carbon emission data after collaborative analysis; and use the carbon emission prediction model to display carbon emission data in charts and predict trends, so as to achieve carbon emission prediction for years without guidelines.

[0142] In this embodiment, the obtained carbon emission data is analyzed and evaluated using various methods. Based on the analysis and evaluation results, the company's carbon dioxide emissions over a certain period of time are calculated. Specifically, based on existing carbon accounting results, namely the company's historical carbon accounting results and collaborative analysis results, a carbon emission prediction model is generated through time series forecasting. According to the carbon emission prediction model, a more reasonable and accurate prediction of the company's future carbon emissions can be made before the corresponding indicator documents are issued.

[0143] The process of generating the carbon emission prediction model is the same as described above, and will not be repeated here.

[0144] The multi-dimensional carbon accounting system in this embodiment makes full use of next-generation Internet technology. By analyzing regional energy consumption, carbon emissions, historical carbon accounting results of enterprises, and production consumption, a carbon prediction model is established. The system completes carbon accounting trial calculations for years without guidelines and for the future, helping enterprises improve their own efficiency in utilizing various energy sources, take the path of clean, low-carbon, safe and efficient utilization, and promote the development of "low-carbon manufacturing".

[0145] In one embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, the processor executing the computer program as the steps of the above-described method embodiments.

[0146] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method embodiments.

[0147] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0148] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0149] While specific embodiments of the present invention have been described above, those skilled in the art should understand that these are merely illustrative examples, and the scope of protection 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 principles and essence of the present invention, but all such changes and modifications fall within the scope of protection of the present invention.

Claims

1. A multi-dimensional carbon accounting method, characterized in that, include: The basic information required to configure a carbon accounting algorithm adapted to the target object, which includes industrial enterprises, and the basic information includes the emission factors and activity data calculation formulas involved in the target object; Establish the statistical dimensions and organizational structure of the target object, specifically: establish a multi-dimensional structure based on the energy consumption granularity required for the enterprise to conduct carbon accounting; The appropriate carbon accounting algorithm for each statistical dimension is automatically matched based on the organizational structure. The system collects the target object's data to be calculated and performs carbon accounting based on the basic information after completing the collaboration verification. The carbon emission results are then output. Specifically, each level of architecture calculates the accounting result according to its applicable algorithm and multiplies the accounting result by the correction system to obtain the carbon emission result that conforms to the hierarchical accumulation relationship in the architecture. The system establishes a multi-dimensional architecture relationship and visualizes the carbon emission results. The correction coefficient is the ratio of the consumption of a unit standard product to the consumption of the actual product production. The completion of the collaborative verification includes: The synergy between the historical carbon emission data and carbon dioxide emissions of the target object is analyzed to verify the data to be calculated. The calculation using the carbon accounting algorithm includes: When the variation range of the data to be calculated is within the allowable variation range, the carbon accounting algorithm is used to calculate the data to be calculated. Otherwise, the feedback should be sent to the target object for correction or supplementary supporting materials; The method for calculating the magnitude of change is as follows: In the formula, The carbon emissions generated by a company producing a product, For the range of change, This is the result calculated in the previous cycle of change; Let i be the amount of the i-th type of production fuel used. is the loss coefficient, which is the ratio of the consumption of the i-th type of production fuel per unit of standard product to the consumption in actual product production; Indicates the mass of the i-th type of fuel produced; Represents the unit emission factor of the i-th production fuel; E is the electricity consumed; The emission factor per unit of electricity in the region where the target object is located.

2. The multidimensional carbon accounting method as described in claim 1, characterized in that, The multidimensional carbon accounting method also includes: Carbon emission prediction models are used to predict carbon emission data.

3. The multidimensional carbon accounting method as described in claim 2, characterized in that, The basic information required for configuring the carbon accounting algorithm adapted to the target object includes: Based on the region and industry of the target object, the applicable policy standards are automatically selected, and the basic information is configured according to the general accounting guidelines. The basic information includes the emission factors and activity data calculation formulas involved in the target object.

4. The multidimensional carbon accounting method as described in claim 1, characterized in that, When the statistical dimension is a park, the multi-dimensional carbon accounting method further includes: Obtain information about the public facilities in the park; The carbon emission data of the park is formed by aggregating the carbon emission data generated by enterprises under the park, the carbon emission data generated by electricity and heat consumption of public facilities in the park, and the carbon emission data generated by vegetation in the park through photosynthesis.

5. The multidimensional carbon accounting method as described in claim 2, characterized in that, The method of using a carbon emission prediction model to predict carbon emission data includes: A carbon emission prediction model is generated through time series prediction based on historical carbon emission data and carbon emission data after collaborative analysis. Carbon emission prediction models are used to visualize carbon emission data and predict trends, enabling carbon emission forecasts for years without guidelines.

6. A multi-dimensional carbon accounting system, characterized in that, include: The algorithm configuration module is used to configure the basic information required for the carbon accounting algorithm adapted to the target object, which includes industrial enterprises. The architecture construction module is used to establish the statistical dimensions and organizational structure of the target object. Specifically, it establishes a multi-dimensional architecture based on the energy consumption granularity required for the enterprise to perform carbon accounting. The algorithm configuration module is also used to automatically match the applicable carbon accounting algorithm for each statistical dimension according to the organizational structure; The verification and accounting module is used to collect the data to be calculated of the target object and perform the accounting according to the basic information after completing the collaborative verification, and output the carbon emission result. Specifically, each level of architecture calculates the accounting result according to the algorithm applicable to it, and multiplies the accounting result by the correction system to obtain the carbon emission result that conforms to the hierarchical accumulation relationship in the architecture. It establishes a multi-dimensional architecture relationship and visualizes the carbon emission result. The correction coefficient is the ratio of the consumption of a unit standard product to the consumption of actual product production. The completion of the collaborative verification includes: The synergy between the historical carbon emission data and carbon dioxide emissions of the target object is analyzed to verify the data to be calculated. The calculation using the carbon accounting algorithm includes: When the variation range of the data to be calculated is within the allowable variation range, the carbon accounting algorithm is used to calculate the data to be calculated. Otherwise, the feedback should be sent to the target object for correction or supplementary supporting materials; The method for calculating the magnitude of change is as follows: In the formula, The carbon emissions generated by a company producing a product, For the range of change, This is the result calculated in the previous cycle of change; Let i be the amount of the i-th type of production fuel used. is the loss coefficient, which is the ratio of the consumption of the i-th type of production fuel per unit of standard product to the consumption in actual product production; Indicates the mass of the i-th type of fuel produced; Represents the unit emission factor of the i-th production fuel; E is the electricity consumed; The emission factor per unit of electricity in the region where the target object is located.

7. The multi-dimensional carbon accounting system as described in claim 6, characterized in that, The system also includes a prediction module; The prediction module is used to predict carbon emission data using a carbon emission prediction model.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-6.

Images