Carbon emission calculation method and device based on power consumption data

Abstract

This invention provides a method and apparatus for calculating carbon emissions based on electricity consumption data, belonging to the field of carbon emission technology. The method includes: acquiring electricity consumption data and actual output of a target enterprise during the calculation period; inputting the electricity consumption data and actual output into a preset calculation model corresponding to the industry to which the target enterprise belongs, to obtain the proportion of the target enterprise's indirect carbon emissions in the total carbon emissions during the calculation period; acquiring the average power supply carbon emission factor of the region where the target enterprise is located; calculating the target enterprise's indirect carbon emissions during the calculation period based on the electricity consumption data and the average power supply carbon emission factor; and calculating the target enterprise's total carbon emissions during the calculation period based on the indirect carbon emissions and the proportion. This invention can improve the accuracy of carbon emission calculation for enterprises and accurately monitor their carbon emissions.

Description

Technical Field

[0001] This invention relates to the field of carbon emission technology, and in particular to a method and apparatus for calculating carbon emissions based on electricity consumption data. Background Technology

[0002] With socio-economic development, carbon dioxide emissions have gradually increased, leading to global warming and a series of related problems. Establishing and improving a green, low-carbon, and circular economic system is crucial for achieving the green and low-carbon transformation of industries. Therefore, accurate monitoring of the carbon emissions of various enterprises is necessary.

[0003] Currently, carbon emission calculations are mainly conducted using the following methods: emission factor method, material balance method, measured method, and industry-based method. However, the emission factor method suffers from a lag in carbon monitoring due to the inability to obtain real-time data on the consumption of some fossil fuels used in carbon accounting, making real-time monitoring difficult. The material balance method requires detailed engineering analysis, making it challenging to implement. The measured method is complex, and data acquisition is relatively difficult; different data sources can lead to significant errors in the obtained carbon emission figures. When using industry-based methods, it is difficult to consider the differences in energy composition among enterprises within the industry, affecting the accuracy of carbon emission calculations.

[0004] Therefore, there is an urgent need for a method that can accurately measure a company's carbon emissions. Summary of the Invention

[0005] This invention provides a method and apparatus for calculating carbon emissions based on electricity consumption data, thereby improving the accuracy of carbon emission calculations for enterprises.

[0006] In a first aspect, embodiments of the present invention provide a method for calculating carbon emissions based on electricity consumption data, including:

[0007] Obtain the target company's electricity consumption data and actual output during the measurement period;

[0008] Input the electricity consumption data and actual output into the preset calculation model corresponding to the industry of the target enterprise to obtain the proportion of the target enterprise's indirect carbon emissions in the total carbon emissions during the calculation period.

[0009] Obtain the average carbon emission factor for electricity supply in the region where the target company is located;

[0010] Based on electricity consumption data and average power supply carbon emission factor, calculate the indirect carbon emissions of the target enterprise during the measurement period;

[0011] Based on the amount and proportion of indirect carbon emissions, the total carbon emissions of the target enterprise during the measurement period are calculated.

[0012] In one possible implementation, obtaining the target company's actual output during the measurement period includes:

[0013] Obtain the unit product power consumption of the target company, which is the electricity consumption corresponding to the production of one unit of product by the target company;

[0014] Based on electricity consumption data and unit product power consumption, calculate the actual output of the target enterprise during the measurement period.

[0015] In one possible implementation, the training process for the pre-defined model for calculating the percentage of the target company's industry is as follows:

[0016] Obtain historical electricity consumption, historical output, and historical total carbon emissions of all enterprises within the target enterprise's industry and region within a preset historical period;

[0017] Based on historical electricity consumption data and average power supply carbon emission factor, calculate the historical indirect carbon emissions of each enterprise within the historical period.

[0018] Calculate the historical percentage of each enterprise's historical indirect carbon emissions in the total historical carbon emissions over a given period;

[0019] The preset machine learning model is trained based on historical electricity consumption, historical output, and historical proportion to obtain the proportion calculation model corresponding to the industry of the target enterprise.

[0020] In one possible implementation, for each enterprise, the historical percentage of its indirect carbon emissions in the total historical carbon emissions over a given period is calculated, including:

[0021] The historical timeframe is divided into multiple historical periods of preset duration;

[0022] For each historical period, calculate the first proportion of the enterprise's historical indirect carbon emissions in the corresponding historical total carbon emissions during that historical period;

[0023] Calculate the standard deviation of the first proportion and check whether the standard deviation is less than a preset threshold;

[0024] If it is less than 1%, then the average of the first percentage is determined as the historical percentage of the enterprise's historical indirect carbon emissions in the historical total carbon emissions within the historical period.

[0025] In one possible implementation, the average carbon emission factor for electricity supply in the region where the target enterprise is located is obtained, including:

[0026] Obtain the first electricity carbon emissions and the first electricity generation of the power grid area corresponding to the target company's location within a historical period;

[0027] Calculate the ratio of the first electricity carbon emission to the first power generation to obtain the average power supply carbon emission factor for the region where the target company is located.

[0028] In one possible implementation, after calculating the target company's corrected carbon emissions for the measurement period based on the second indirect carbon emissions and their proportion, the following is also included:

[0029] Obtain the dynamic carbon emission factor of electricity supply in the region where the target enterprise is located during the measurement period;

[0030] Based on electricity consumption data and dynamic power supply carbon emission factors, calculate the dynamic indirect carbon emissions of the target enterprise during the measurement period;

[0031] Calculate the difference between dynamic indirect carbon emissions and indirect carbon emissions, and check whether the difference is greater than a preset difference.

[0032] If the value is greater than the target value, the total carbon emissions are adjusted based on the dynamic indirect carbon emissions to obtain the adjusted carbon emissions of the target company during the calculation period.

[0033] In one possible implementation, the power grid area comprises multiple sub-regions;

[0034] Obtain the dynamic carbon emission factor of electricity supply in the region where the target enterprise is located during the measurement period, including:

[0035] Identify the target sub-region corresponding to the target company;

[0036] Obtain the second electricity carbon emissions, second electricity generation, input electricity, and output electricity for the target sub-region during the measurement period;

[0037] Based on the second electricity carbon emissions, the second power generation, the input power and the output power, calculate the dynamic power supply carbon emission factor of the target enterprise's region during the measurement period.

[0038] In one possible implementation, the dynamic power supply carbon emission factor for the target enterprise's region during the measurement period is calculated based on the second electricity carbon emission, the second power generation, the input power, and the output power, including:

[0039] according to Calculate the dynamic carbon emission factor of electricity supply in the region where the target enterprise is located during the measurement period;

[0040] Wherein, EF2 represents the dynamic power supply carbon emission factor of the target enterprise's region during the measurement period, C2 represents the second electricity carbon emission of the target sub-region during the measurement period, E2 represents the second power generation of the target sub-region during the measurement period, and E c,i E represents the output power transmitted from the target sub-region to sub-region i during the measurement period. r,iEF represents the input power received by the target sub-region i during the measurement period. i This represents the dynamic power supply carbon emission factor of sub-region i during the measurement period.

[0041] Secondly, embodiments of the present invention provide a carbon emission calculation device based on electricity consumption data, comprising:

[0042] The first acquisition module is used to acquire the target company's electricity consumption data and actual output during the calculation period;

[0043] The calculation module is used to input electricity consumption data and actual output into the preset calculation model corresponding to the industry of the target enterprise, so as to obtain the proportion of the target enterprise's indirect carbon emissions in the total carbon emissions during the calculation period.

[0044] The second acquisition module is used to acquire the average carbon emission factor of electricity supply in the region where the target enterprise is located.

[0045] The first calculation module is used to calculate the indirect carbon emissions of the target enterprise during the measurement period based on electricity consumption data and average power supply carbon emission factor.

[0046] The second calculation module is used to calculate the total carbon emissions of the target enterprise during the measurement period based on the indirect carbon emissions and their proportion.

[0047] In one possible implementation, the first acquisition module is specifically used for:

[0048] Obtain the unit product power consumption of the target company, which is the electricity consumption corresponding to the production of one unit of product by the target company;

[0049] Based on electricity consumption data and unit product power consumption, calculate the actual output of the target enterprise during the measurement period.

[0050] The beneficial effects of the embodiments of the present invention compared with the prior art are as follows:

[0051] This invention calculates the proportion of a target company's indirect carbon emissions in its total carbon emissions by using its electricity consumption data and actual output during the measurement period. This proportion clarifies the differences in energy composition among different companies in the same industry, allowing for accurate calculation of the target company's total carbon emissions during the measurement period by combining the calculated indirect carbon emissions with the calculated proportion. This avoids inaccurate carbon emission calculations caused by different companies using different energy sources. Furthermore, by using a proportion calculation model corresponding to the target company's industry, the invention predicts the proportion of the target company's indirect carbon emissions in its total carbon emissions during the measurement period. This proportion calculation model is universal for all companies in the same industry, eliminating the need to build and train models for each company, thus reducing the process of building prediction models and providing a basis for monitoring the carbon emissions of various companies within the monitoring area. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 This is an application scenario diagram of the carbon emission calculation method based on electricity consumption data provided in the embodiments of the present invention;

[0054] Figure 2 This is a flowchart illustrating the implementation of the carbon emission calculation method based on electricity consumption data provided in this embodiment of the invention.

[0055] Figure 3 This is a schematic diagram showing the location of the power grid area corresponding to the target enterprise provided in this embodiment of the invention;

[0056] Figure 4 This is a schematic diagram of the carbon emission calculation device based on electricity consumption data provided in an embodiment of the present invention. Detailed Implementation

[0057] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of the invention with unnecessary detail.

[0058] To make the objectives, technical solutions, and advantages of the present invention clearer, specific embodiments will be described below in conjunction with the accompanying drawings.

[0059] When monitoring the carbon emissions of various enterprises in a region, carbon emissions are usually predicted directly based on the industry to which the enterprise belongs, without taking into account the differences in the energy composition of various enterprises within the industry, which leads to low accuracy in the predicted carbon emissions.

[0060] Based on this, embodiments of the present invention provide a method for calculating carbon emissions based on electricity consumption data, in order to improve the accuracy of carbon emission calculations for various enterprises. See also Figure 1 The diagram shown illustrates the application scenario of the carbon emission measurement method based on electricity consumption data. The monitoring area includes multiple industries, with each industry corresponding to multiple enterprises. A, B, C, D... represent different industries within the monitoring area, A1, A2, A3... represent different enterprises in industry A, and B1, B2, B3... represent different enterprises in industry B.

[0061] The carbon emission calculation method based on electricity consumption data provided in this invention specifically calculates the carbon emissions of a single enterprise within a monitoring area. For details, please refer to [link / reference needed]. Figure 2 The flowchart illustrating the carbon emission calculation method based on electricity consumption data is detailed below:

[0062] Step S201: Obtain the target company's electricity consumption data and actual output during the calculation period.

[0063] In this embodiment, the electricity consumption data mainly refers to the electricity data purchased by the target company.

[0064] Step S202: Input the electricity consumption data and actual output into the preset calculation model corresponding to the industry of the target enterprise to obtain the proportion of the target enterprise's indirect carbon emissions in the total carbon emissions during the calculation period.

[0065] In this embodiment, for the same industry, different enterprises use different energy compositions, different raw materials, or different process steps, which will lead to different carbon emissions for different enterprises. Therefore, the electricity consumption data and actual output of enterprises are selected to reflect the differences between enterprises, thereby reducing the error in carbon emission calculation and improving the accuracy of carbon emission calculation.

[0066] Because the percentage calculation model is used to calculate the percentage corresponding to the target enterprise, the calculation can be carried out after obtaining electricity consumption data and actual output, which can achieve real-time calculation and thus ensure the real-time nature of carbon emission calculation and monitoring.

[0067] Step S203: Obtain the average carbon emission factor for electricity supply in the region where the target enterprise is located.

[0068] In this embodiment, the average power supply carbon emission factor is the average power supply carbon emission factor of the power grid area corresponding to the target enterprise.

[0069] Step S204: Calculate the indirect carbon emissions of the target enterprise during the measurement period based on electricity consumption data and average power supply carbon emission factor.

[0070] In this embodiment, indirect carbon emissions mainly refer to the carbon emissions generated by the electricity purchased by the target company.

[0071] Optionally, the indirect carbon emissions of the target enterprise during the measurement period can be calculated according to C = E × EF; where C represents the indirect carbon emissions of the target enterprise during the measurement period, E represents the electricity consumption of the target enterprise during the measurement period, and EF represents the average carbon emission factor of electricity supply in the region where the target enterprise is located.

[0072] Step S205: Calculate the total carbon emissions of the target enterprise during the measurement period based on the indirect carbon emissions and their proportion.

[0073] This invention calculates the proportion of a target company's indirect carbon emissions in its total carbon emissions by using its electricity consumption data and actual output during the measurement period. This proportion clarifies the differences in energy composition among different companies in the same industry, allowing for accurate calculation of the target company's total carbon emissions during the measurement period by combining the calculated indirect carbon emissions with the calculated proportion. This avoids inaccurate carbon emission calculations caused by different companies using different energy sources. Furthermore, by using a proportion calculation model corresponding to the target company's industry, the invention predicts the proportion of the target company's indirect carbon emissions in its total carbon emissions during the measurement period. This proportion calculation model is universal for all companies in the same industry, eliminating the need to build and train models for each company, thus reducing the process of building prediction models and providing a basis for monitoring the carbon emissions of various companies within the monitoring area.

[0074] In one possible implementation, step S201, obtaining the target company's actual output during the measurement period, can be detailed as follows:

[0075] Obtain the unit product power consumption of the target company, which is the electricity consumption corresponding to the production of one unit of product by the target company;

[0076] Based on electricity consumption data and unit product power consumption, calculate the actual output of the target enterprise during the measurement period.

[0077] In this embodiment, since enterprise production requires a certain process and time, it may not be possible to directly obtain the actual output of the target enterprise during the measurement period. Therefore, the actual output of the target enterprise during the measurement period can be calculated by the unit product power consumption.

[0078] Specifically, the actual output of the target company during the measurement period can be calculated using Q = k × E, where Q represents the actual output of the target company during the measurement period, k represents the unit product power consumption of the target company, and E represents the electricity consumption data of the target company during the measurement period.

[0079] Optionally, since the target company's historical electricity consumption and historical output are readily available, the unit product electricity consumption can be calculated using the target company's historical electricity consumption and historical output.

[0080] In one possible implementation, the training process for the pre-defined model for calculating the percentage of the target company's industry is as follows:

[0081] Obtain historical electricity consumption, historical output, and historical total carbon emissions of all enterprises within the target enterprise's industry and region within a preset historical period;

[0082] Based on historical electricity consumption data and average power supply carbon emission factor, calculate the historical indirect carbon emissions of each enterprise within the historical period.

[0083] Calculate the historical percentage of each enterprise's historical indirect carbon emissions in the total historical carbon emissions over a given period;

[0084] The preset machine learning model is trained based on historical electricity consumption, historical output, and historical proportion to obtain the proportion calculation model corresponding to the industry of the target enterprise.

[0085] In this embodiment, the model is trained by using the historical electricity consumption, historical output, and historical proportion of each enterprise in the same industry to obtain the proportion calculation model of the industry. This model can be applied to each enterprise in the industry without the need to train a prediction model for each enterprise separately, which can reduce the complexity of the training process. Furthermore, when monitoring the carbon emissions of each enterprise in the monitoring area, the proportion of each enterprise can be quickly calculated, thereby obtaining the carbon emissions of each enterprise.

[0086] The average power supply carbon emission factor is the same as the average power supply carbon emission factor in step S204. By using the same carbon emission factor, it can be ensured that the indirect carbon emissions and proportions calculated subsequently correspond, thereby ensuring the accuracy of the calculated total carbon emissions.

[0087] In addition, the preset duration (i.e. the duration of the historical period) can be set to the same duration as the measurement period.

[0088] In one possible implementation, for each enterprise, the historical percentage of its indirect carbon emissions in the total historical carbon emissions over a given period is calculated, including:

[0089] The historical timeframe is divided into multiple historical periods of preset duration;

[0090] For each historical period, calculate the first proportion of the enterprise's historical indirect carbon emissions in the corresponding historical total carbon emissions during that historical period;

[0091] Calculate the standard deviation of the first proportion and check whether the standard deviation is less than a preset threshold;

[0092] If it is less than 1%, then the average of the first percentage is determined as the historical percentage of the enterprise's historical indirect carbon emissions in the historical total carbon emissions within the historical period.

[0093] In this embodiment, the energy structure or process steps of an enterprise may change, and correspondingly, the proportion of the enterprise's indirect carbon emissions in the total carbon emissions will also change. Therefore, based on the consideration that this proportion may change, the proportion is calculated for different time periods to obtain the enterprise's proportion more accurately, and at the same time, the training set of the proportion calculation model can be expanded.

[0094] If the standard deviation of the first proportion of the same enterprise is less than the preset threshold, it means that the proportion of the enterprise has not changed significantly, that is, the energy structure or process steps of the enterprise have not changed significantly. Accordingly, the average value of the first proportion can be used to represent the proportion of the enterprise to accurately obtain the proportion of the enterprise.

[0095] If the standard deviation of the first percentage of the same enterprise is greater than the preset threshold, it means that the percentage of the enterprise has changed within the historical period, that is, the energy structure or process steps of the enterprise have changed. Therefore, the same percentage cannot be used to represent the percentage of the enterprise within the historical period. Instead, the percentage of the enterprise in the corresponding historical period can be determined separately according to the divided historical period. In addition, determining the percentage of the enterprise in each historical period can increase the amount of data in the training set. At the same time, the change in percentage can also increase the richness of the data in the training set.

[0096] In one possible implementation, step S203, obtaining the average carbon emission factor for electricity supply in the region where the target enterprise is located, can be detailed as follows:

[0097] Obtain the first electricity carbon emissions and the first electricity generation of the power grid area corresponding to the target company's location within a historical period;

[0098] Calculate the ratio of the first electricity carbon emission to the first power generation to obtain the average power supply carbon emission factor for the region where the target company is located.

[0099] In this embodiment, the average power supply carbon emission factor used is the average power supply carbon emission factor of the power grid area corresponding to the region where the target enterprise is located. This allows the same power supply carbon emission factor to be used when calculating carbon emissions for each enterprise, avoiding inaccurate calculations caused by differences in power supply carbon emission factors.

[0100] When monitoring the carbon emissions of enterprises, the monitoring is usually carried out on enterprises within a certain region. For example, all enterprises in a province, all enterprises in a city, or all enterprises in an industrial park can be monitored. Therefore, it is sufficient to obtain the carbon emission factor of the power supply area corresponding to that region.

[0101] When obtaining the average power supply carbon emission factor, it can be calculated using the carbon emissions and power generation of the corresponding power grid area, or the power supply carbon emission factor of the corresponding area can be directly used online.

[0102] In one possible implementation, after calculating the target company's total carbon emissions during the measurement period based on indirect carbon emissions and their proportion in step S205, the method further includes:

[0103] Obtain the dynamic carbon emission factor of electricity supply in the region where the target enterprise is located during the measurement period;

[0104] Based on electricity consumption data and dynamic power supply carbon emission factors, calculate the dynamic indirect carbon emissions of the target enterprise during the measurement period;

[0105] Calculate the difference between dynamic indirect carbon emissions and indirect carbon emissions, and check whether the difference is greater than a preset difference.

[0106] If the value is greater than the target value, the total carbon emissions are adjusted based on the dynamic indirect carbon emissions to obtain the adjusted carbon emissions of the target company during the calculation period.

[0107] In this embodiment, the power supply carbon emission factor for the entire power grid region is used when calculating the enterprise's indirect carbon emissions. However, due to the large size of the power grid region and the differences in power supply carbon emission factors among its various sub-regions, directly using the average power supply carbon emission factor for the entire power grid region may result in inaccurate indirect carbon emissions calculations. Furthermore, the average power supply carbon emission factor is a historical carbon emission factor for the power grid region; as time changes, the energy used for power generation may also change, consequently altering the corresponding power supply carbon emission factor.

[0108] Based on this, after obtaining the total carbon emissions of the target enterprise, the indirect carbon emissions are corrected by obtaining the dynamic power supply carbon emission factor corresponding to the region where the target enterprise is located, thereby improving the accuracy of calculating indirect carbon emissions.

[0109] If the difference between dynamic indirect carbon emissions and indirect carbon emissions is greater than a preset difference, it indicates a significant error in the calculation of indirect carbon emissions, requiring appropriate correction. Specifically, correcting the total carbon emissions can be done by replacing the indirect carbon emissions in the total carbon emissions with dynamic indirect carbon emissions, resulting in the corrected carbon emissions.

[0110] If the difference between dynamic indirect carbon emissions and indirect carbon emissions is not greater than the preset difference, it means that the error between the two is small and no correction is needed.

[0111] In one possible implementation, the power grid area comprises multiple sub-regions.

[0112] In this embodiment, see Figure 3 The diagram shows the location of the target enterprise corresponding to the power grid area. The power grid area includes multiple sub-areas, namely sub-area a, sub-area b, sub-area c, etc. The enterprises in the detection area are located in each sub-area. Specifically, enterprises A1, B1, B2 and C1 are all located in sub-area a, enterprises A2, C2 and C3 are all located in sub-area b, and enterprises A3 and B3 are all located in sub-area c.

[0113] Obtain the dynamic carbon emission factor of electricity supply in the region where the target enterprise is located during the measurement period, including:

[0114] Identify the target sub-region corresponding to the target company;

[0115] Obtain the second electricity carbon emissions, second electricity generation, input electricity, and output electricity for the target sub-region during the measurement period;

[0116] Based on the second electricity carbon emissions, the second power generation, the input power and the output power, calculate the dynamic power supply carbon emission factor of the target enterprise's region during the measurement period.

[0117] In this embodiment, the dynamic power supply carbon emission factor corresponding to the target enterprise is the dynamic power supply carbon emission factor of the sub-region where the target enterprise is located. For example, if the target enterprise is A1 and the corresponding sub-region is sub-region a, then the dynamic power supply carbon emission factor of the target enterprise is the power supply carbon emission factor of sub-region a.

[0118] When calculating the dynamic power supply carbon emission factor for a sub-region, the calculation is performed using the corresponding sub-region's electricity carbon emissions and power supply. Since there is an exchange of electricity between different sub-regions, it is necessary to consider the input and output electricity of each sub-region in order to accurately calculate the dynamic power supply carbon emission factor.

[0119] Optional, can be based on Calculate the dynamic carbon emission factor of electricity supply in the region where the target enterprise is located during the measurement period;

[0120] Wherein, EF2 represents the dynamic power supply carbon emission factor of the target enterprise's region during the measurement period, C2 represents the second electricity carbon emission of the target sub-region during the measurement period, E2 represents the second power generation of the target sub-region during the measurement period, and E c,i E represents the output power transmitted from the target sub-region to sub-region i during the measurement period. r,i EF represents the input power received by the target sub-region i during the measurement period. i This represents the dynamic power supply carbon emission factor of sub-region i during the measurement period.

[0121] In this embodiment, the dynamic power supply carbon emission factor of the target enterprise's region during the measurement period is actually the dynamic power supply carbon emission factor of the target sub-region during the measurement period.

[0122] This invention calculates the proportion of a target company's indirect carbon emissions in its total carbon emissions by analyzing its electricity consumption and actual output during the measurement period. This proportion clarifies the differences in energy composition among different companies within the same industry, allowing for accurate calculation of the target company's total carbon emissions during the measurement period by combining the calculated indirect carbon emissions with the calculated proportion. This avoids inaccurate carbon emission calculations caused by different companies using different energy sources. Furthermore, the invention uses a proportion calculation model corresponding to the target company's industry to predict the proportion of its indirect carbon emissions in the total carbon emissions during the measurement period. This proportion calculation model is universally applicable to all companies within the same industry. This method eliminates the need to build and train models for each enterprise, reducing the time required to establish predictive models and providing a basis for monitoring the carbon emissions of each enterprise within the monitoring area. By using the same average electricity supply carbon emission factor in both the training and total carbon emission calculation phases of the proportion calculation model, the calculated proportions and indirect carbon emissions are correlated, ensuring the accuracy of the total carbon emission calculation. By calculating the dynamic indirect carbon emissions of the target enterprise during the measurement period using the dynamic electricity supply carbon emission factor corresponding to the sub-region where the target enterprise is located, and correcting the total carbon emissions, the method avoids the problem of inaccurate average electricity supply carbon emission factors, thereby improving the accuracy of the final carbon emission figures for the enterprise.

[0123] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0124] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0125] Figure 4A schematic diagram of the carbon emission calculation device based on electricity consumption data provided in an embodiment of the present invention is shown. For ease of explanation, only the parts related to the embodiment of the present invention are shown, and are described in detail below:

[0126] like Figure 4 As shown, the carbon emission calculation device 40 based on electricity consumption data includes:

[0127] The first acquisition module 41 is used to acquire the target enterprise's electricity consumption data and actual output during the calculation period;

[0128] The calculation module 42 is used to input electricity consumption data and actual output into the preset calculation model corresponding to the industry of the target enterprise, so as to obtain the proportion of the target enterprise's indirect carbon emissions in the total carbon emissions during the calculation period.

[0129] The second acquisition module 43 is used to acquire the average carbon emission factor of electricity supply in the region where the target enterprise is located.

[0130] The first calculation module 44 is used to calculate the indirect carbon emissions of the target enterprise during the measurement period based on electricity consumption data and average power supply carbon emission factor.

[0131] The second calculation module 45 is used to calculate the total carbon emissions of the target enterprise during the measurement period based on the indirect carbon emissions and their proportion.

[0132] In one possible implementation, the first acquisition module 41 is specifically used for:

[0133] Obtain the unit product power consumption of the target company, which is the electricity consumption corresponding to the production of one unit of product by the target company;

[0134] Based on electricity consumption data and unit product power consumption, calculate the actual output of the target enterprise during the measurement period.

[0135] In one possible implementation, the training process for the pre-defined model for calculating the percentage of the target company's industry is as follows:

[0136] Obtain historical electricity consumption, historical output, and historical total carbon emissions of all enterprises within the target enterprise's industry and region within a preset historical period;

[0137] Based on historical electricity consumption data and average power supply carbon emission factor, calculate the historical indirect carbon emissions of each enterprise within the historical period.

[0138] Calculate the historical percentage of each enterprise's historical indirect carbon emissions in the total historical carbon emissions over a given period;

[0139] The preset machine learning model is trained based on historical electricity consumption, historical output, and historical proportion to obtain the proportion calculation model corresponding to the industry of the target enterprise.

[0140] In one possible implementation, for each enterprise, the historical percentage of its indirect carbon emissions in the total historical carbon emissions over a given period is calculated, including:

[0141] The historical timeframe is divided into multiple historical periods of preset duration;

[0142] For each historical period, calculate the first proportion of the enterprise's historical indirect carbon emissions in the corresponding historical total carbon emissions during that historical period;

[0143] Calculate the standard deviation of the first proportion and check whether the standard deviation is less than a preset threshold;

[0144] If it is less than 1%, then the average of the first percentage is determined as the historical percentage of the enterprise's historical indirect carbon emissions in the historical total carbon emissions within the historical period.

[0145] In one possible implementation, the second acquisition module 43 is specifically used for:

[0146] Obtain the first electricity carbon emissions and the first electricity generation of the power grid area corresponding to the target company's location within a historical period;

[0147] Calculate the ratio of the first electricity carbon emission to the first power generation to obtain the average power supply carbon emission factor for the region where the target company is located.

[0148] In one possible implementation, the carbon emission calculation device 40 based on electricity consumption data further includes a correction module for:

[0149] Obtain the dynamic carbon emission factor of electricity supply in the region where the target enterprise is located during the measurement period;

[0150] Based on electricity consumption data and dynamic power supply carbon emission factors, calculate the dynamic indirect carbon emissions of the target enterprise during the measurement period;

[0151] Calculate the difference between dynamic indirect carbon emissions and indirect carbon emissions, and check whether the difference is greater than a preset difference.

[0152] If the value is greater than the target value, the total carbon emissions are adjusted based on the dynamic indirect carbon emissions to obtain the adjusted carbon emissions of the target company during the calculation period.

[0153] In one possible implementation, the power grid area comprises multiple sub-regions;

[0154] The correction module is specifically used for:

[0155] Identify the target sub-region corresponding to the target company;

[0156] Obtain the second electricity carbon emissions, second electricity generation, input electricity, and output electricity for the target sub-region during the measurement period;

[0157] Based on the second electricity carbon emissions, the second power generation, the input power and the output power, calculate the dynamic power supply carbon emission factor of the target enterprise's region during the measurement period.

[0158] In one possible implementation, the correction module is specifically used for:

[0159] according to Calculate the dynamic carbon emission factor of electricity supply in the region where the target enterprise is located during the measurement period;

[0160] Wherein, EF2 represents the dynamic power supply carbon emission factor of the target enterprise's region during the measurement period, C2 represents the second electricity carbon emission of the target sub-region during the measurement period, E2 represents the second power generation of the target sub-region during the measurement period, and E c,i E represents the output power transmitted from the target sub-region to sub-region i during the measurement period. r,i EF represents the input power received by the target sub-region i during the measurement period. i This represents the dynamic power supply carbon emission factor of sub-region i during the measurement period.

[0161] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0162] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0163] If integrated modules / units are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0164] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for calculating carbon emissions based on electricity consumption data, characterized in that, include: Obtain the target company's electricity consumption data and actual output during the measurement period; The electricity consumption data and the actual output are input into a preset calculation model corresponding to the industry to which the target enterprise belongs, to obtain the proportion of the target enterprise's indirect carbon emissions in the total carbon emissions during the calculation period. Obtain the average carbon emission factor of electricity supply in the region where the target enterprise is located; Based on the electricity consumption data and the average power supply carbon emission factor, calculate the indirect carbon emissions of the target enterprise during the calculation period; Based on the indirect carbon emissions and the percentage, the total carbon emissions of the target enterprise during the calculation period are calculated. The step of obtaining the average carbon emission factor for electricity supply in the region where the target enterprise is located includes: Obtain the first electricity carbon emissions and the first power generation of the power grid area corresponding to the region where the target enterprise is located within a historical period; Calculate the ratio of the first electricity carbon emissions to the first electricity generation to obtain the average power supply carbon emission factor for the region where the target enterprise is located; After calculating the total carbon emissions of the target enterprise during the measurement period based on the indirect carbon emissions and the proportion, the method further includes: Obtain the dynamic power supply carbon emission factor of the region where the target enterprise is located during the calculation period; Based on the electricity consumption data and the dynamic power supply carbon emission factor, calculate the dynamic indirect carbon emissions of the target enterprise during the calculation period; Calculate the difference between the dynamic indirect carbon emissions and the indirect carbon emissions, and detect whether the difference is greater than a preset difference. If it is greater than the target enterprise's total carbon emissions, the total carbon emissions are corrected based on the dynamic indirect carbon emissions to obtain the corrected carbon emissions for the target enterprise during the calculation period. The power grid area includes multiple sub-regions; Obtaining the dynamic power supply carbon emission factor for the region where the target enterprise is located during the calculation period includes: Determine the target sub-region corresponding to the target enterprise; The second electricity carbon emissions, second power generation, input electricity, and output electricity of the target sub-region during the calculation period are obtained. Based on the second electricity carbon emissions, the second power generation, the input power and the output power, calculate the dynamic power supply carbon emission factor of the region where the target enterprise is located during the calculation period; The step of calculating the dynamic power supply carbon emission factor for the region where the target enterprise is located during the calculation period based on the second electricity carbon emission, the second power generation, the input power, and the output power includes: according to Calculate the dynamic power supply carbon emission factor of the region where the target enterprise is located during the measurement period; in, This indicates the dynamic carbon emission factor of electricity supply in the region where the target enterprise is located during the calculation period. This represents the second electricity carbon emission of the target sub-region during the measurement period. This represents the second power generation of the target sub-region during the measurement period. This indicates that the target sub-region is transmitted to the sub-region during the measurement period. i The output power, This indicates the sub-regions received by the target sub-region during the measurement period. i Input power, Subregion i The dynamic power supply carbon emission factor during the measurement period.

2. The carbon emission calculation method based on electricity consumption data according to claim 1, characterized in that, Obtain the target company's actual output during the measurement period, including: Obtain the unit product power consumption of the target enterprise, where the unit product power consumption is the electricity consumption corresponding to the production of one product by the target enterprise; Based on the electricity consumption data and the unit product electricity consumption, the actual output of the target enterprise during the calculation period is calculated.

3. The carbon emission calculation method based on electricity consumption data according to claim 1, characterized in that, The training process for the pre-defined model for calculating the percentage of the target company's industry is as follows: Obtain historical electricity consumption data, historical output data, and historical total carbon emissions data of each enterprise within the target enterprise's industry and the target enterprise's region within a preset historical period; Based on the historical electricity consumption data and the average power supply carbon emission factor, calculate the historical indirect carbon emissions of each enterprise within the historical period. Calculate the historical percentage of each enterprise's historical indirect carbon emissions within the historical period in the total historical carbon emissions; The preset machine learning model is trained based on the historical electricity consumption, historical output, and historical proportion to obtain the proportion calculation model corresponding to the industry to which the target enterprise belongs.

4. The carbon emission calculation method based on electricity consumption data according to claim 3, characterized in that, For each enterprise, calculate the historical percentage of its historical indirect carbon emissions within the stated historical period in the total historical carbon emissions, including: The historical period is divided into multiple historical time periods of preset duration; For each historical period, calculate the first proportion of the enterprise's historical indirect carbon emissions in the corresponding historical total carbon emissions during that historical period; Calculate the standard deviation of the first proportion, and detect whether the standard deviation is less than a preset threshold; If it is less than, then the average of the first percentage is determined to be the historical percentage of the enterprise's historical indirect carbon emissions in the total historical carbon emissions within the historical period.

5. A carbon emission calculation device based on electricity consumption data, characterized in that, include: The first acquisition module is used to acquire the target company's electricity consumption data and actual output during the calculation period; The calculation module is used to input the electricity consumption data and the actual output into a preset calculation model corresponding to the industry to which the target enterprise belongs, so as to obtain the proportion of the target enterprise's indirect carbon emissions in the total carbon emissions during the calculation period. The second acquisition module is used to acquire the average carbon emission factor of electricity supply in the region where the target enterprise is located. The first calculation module is used to calculate the indirect carbon emissions of the target enterprise during the calculation period based on the electricity consumption data and the average power supply carbon emission factor. The second calculation module is used to calculate the total carbon emissions of the target enterprise during the calculation period based on the indirect carbon emissions and the proportion. The second acquisition module is specifically used for: Obtain the first electricity carbon emissions and the first power generation of the power grid area corresponding to the region where the target enterprise is located within a historical period; Calculate the ratio of the first electricity carbon emissions to the first electricity generation to obtain the average power supply carbon emission factor for the region where the target enterprise is located; The correction module is used for: Obtain the dynamic power supply carbon emission factor of the region where the target enterprise is located during the calculation period; Based on the electricity consumption data and the dynamic power supply carbon emission factor, calculate the dynamic indirect carbon emissions of the target enterprise during the calculation period; Calculate the difference between the dynamic indirect carbon emissions and the indirect carbon emissions, and detect whether the difference is greater than a preset difference. If it is greater than the target enterprise's total carbon emissions, the total carbon emissions are corrected based on the dynamic indirect carbon emissions to obtain the corrected carbon emissions for the target enterprise during the calculation period. The power grid area includes multiple sub-regions; The correction module is specifically used for: Determine the target sub-region corresponding to the target enterprise; The second electricity carbon emissions, second power generation, input electricity, and output electricity of the target sub-region during the calculation period are obtained. Based on the second electricity carbon emissions, the second power generation, the input power and the output power, calculate the dynamic power supply carbon emission factor of the region where the target enterprise is located during the calculation period; The correction module is specifically used for: according to Calculate the dynamic power supply carbon emission factor of the region where the target enterprise is located during the measurement period; in, This indicates the dynamic carbon emission factor of electricity supply in the region where the target enterprise is located during the calculation period. This represents the second electricity carbon emission of the target sub-region during the measurement period. This represents the second power generation of the target sub-region during the measurement period. This indicates that the target sub-region is transmitted to the sub-region during the measurement period. i The output power, This indicates the sub-regions received by the target sub-region during the measurement period. i Input power, Subregion i The dynamic power supply carbon emission factor during the measurement period.

6. The carbon emission calculation device based on electricity consumption data according to claim 5, characterized in that, The first acquisition module is specifically used for: Obtain the unit product power consumption of the target enterprise, where the unit product power consumption is the electricity consumption corresponding to the production of one product by the target enterprise; Based on the electricity consumption data and the unit product electricity consumption, the actual output of the target enterprise during the calculation period is calculated.

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