A carbon emission analysis method, system, device and storage medium

Abstract

The application discloses a kind of carbon emission analysis method, system, equipment and storage medium, belong to carbon emission analysis field, including data acquisition module, carbon emission calculation and analysis module, order and carbon emission association module, carbon emission optimization module, the data acquisition module, carbon emission calculation and analysis module, order and carbon emission association module, carbon emission optimization module are sequentially communicated connection;The data acquisition module is used to collect enterprise order data within quarter, fuel consumption data, equipment operating parameter and power consumption data;Invent a kind of carbon emission analysis method, system, equipment and storage medium, can compare actual and preset carbon emission threshold value, and understand the reason of exceeding, in addition, by establishing carbon emission and order relationship model, can effectively simplify calculation and plan order quantity, to optimize production process, reach the effect of helping enterprise accurate analysis carbon emission problem.

Description

Technical Field

[0001] The present invention belongs to the field of carbon emission analysis, and specifically relates to a carbon emission analysis method, system, equipment and storage medium. Background Art

[0002] As the world actively responds to climate change, carbon emissions have become a focus of attention. As countries continue to strengthen their carbon emissions regulations, companies are facing increasingly stringent carbon emission restrictions. Accurately analyzing and effectively controlling carbon emissions is crucial for companies to reduce operating costs, enhance their environmental image, and achieve sustainable development.

[0003] The Chinese patent provides a carbon emission analysis method, system, computer equipment and storage medium, with the publication number CN114077788A, which includes obtaining the consumption of various types of fuels and the annual electricity consumption of the power system in the reporting year, and calculating the transmission and distribution transportation loss; calculating the corresponding fossil fuel activity data on the power generation side according to the consumption of various types of fuels; calculating the corresponding carbon dioxide emissions generated by the combustion of fossil fuels on the power generation side, the carbon dioxide emissions generated by the transmission and distribution transportation loss and the carbon dioxide emissions generated by electricity consumption through a preset energy conversion model; and converting the carbon dioxide emissions generated by the combustion of fossil fuels on the power generation side, the transmission and distribution transportation loss and the carbon dioxide emissions generated by electricity consumption into the carbon dioxide emissions generated by the transmission and distribution transportation loss. The sum of the carbon dioxide emissions generated by transmission losses and electricity consumption is output as the final carbon dioxide emissions. However, this method tracks and measures the carbon emissions generated during the entire life cycle of power production to achieve the statistics of carbon dioxide emissions. However, this method does not directly link actual orders with carbon emissions. As a result, when arranging production orders, companies cannot accurately know the specific impact of the order quantity on carbon emissions, which can easily lead to excessive carbon emissions. At the same time, when calculating carbon emissions, the steps are cumbersome and inefficient, and it is impossible to quickly derive carbon emissions based on order data, which is not conducive to timely adjustment of production strategies by companies.

[0004] In addition, the existing carbon emission analysis system has many shortcomings. Specifically, some systems are not accurate enough in predicting carbon emissions. They simply make estimates based on historical data and fail to fully consider the various complex factors in actual production. This leads to a large deviation between the preset carbon emission threshold and the actual situation, and cannot effectively guide the company's production operations. When the direct actual carbon emissions differ greatly from the predicted values ​​and the preset thresholds, it is difficult to accurately analyze whether the reason for the excess is the order quantity or equipment problems, and thus targeted measures cannot be taken in a timely manner, affecting the subsequent work process. Summary of the Invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention provides a carbon emission analysis method, system, device and storage medium, which enable relevant personnel of enterprises to conveniently analyze carbon emission issues.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A carbon emission analysis system includes a data acquisition module, a carbon emission calculation and analysis module, an order and carbon emission association module, and a carbon emission optimization module, wherein the data acquisition module, the carbon emission calculation and analysis module, the order and carbon emission association module, and the carbon emission optimization module are sequentially communicatively connected;

[0008] The data collection module is used to collect the company's quarterly order data, fuel consumption data, equipment operating parameters and power consumption data;

[0009] The carbon emissions calculation and analysis module is used to calculate the direct actual carbon emissions value and the indirect actual carbon emissions value, and compare the direct actual carbon emissions value with the quarterly preset direct carbon emissions threshold, and compare the indirect actual carbon emissions value with the quarterly preset indirect carbon emissions threshold. When the actual value is within the quarterly preset carbon emissions threshold, further analyze the error between the actual carbon emissions value and the carbon emissions forecast value to correct the carbon emissions forecast value and modify the carbon emissions threshold for the next quarter accordingly;

[0010] The order and carbon emission association module associates the order data with the carbon emission value when the actual value is within the quarterly preset direct carbon emission threshold range, establishes a relationship model between the carbon emission value and the order, and plans the order based on the established relationship model between the carbon emission value and the order to optimize the carbon emissions.

[0011] Furthermore, the carbon emission calculation and analysis module is used to calculate the direct actual carbon emission value and the indirect actual carbon emission value, and compare the direct actual carbon emission value with the quarterly preset direct carbon emission threshold, and compare the indirect actual carbon emission value with the quarterly preset indirect carbon emission threshold. When the actual value is within the quarterly preset carbon emission threshold, the error between the actual carbon emission value and the carbon emission forecast value is further analyzed to correct the carbon emission forecast value, and the carbon emission threshold for the next quarter is modified accordingly. The process is as follows:

[0012] It is used to calculate the actual direct carbon emissions value and the actual indirect carbon emissions value, and compare the actual direct carbon emissions value with the quarterly preset direct carbon emissions threshold, and compare the actual indirect carbon emissions value with the quarterly preset indirect carbon emissions threshold. When the actual value is within the quarterly preset carbon emissions threshold, the error between the actual carbon emissions value and the carbon emissions forecast value is further analyzed to correct the carbon emissions forecast value. Finally, the corrected carbon emissions forecast value is used in combination with the exponential smoothing method to dynamically adjust the direct carbon emissions limit threshold A and the indirect carbon emissions limit threshold C for the next quarter;

[0013] If actual direct carbon emissions exceed the quarterly preset direct carbon emission threshold or the total indirect carbon emissions exceed the quarterly preset indirect carbon emission threshold, further analysis will be conducted on the reasons for the excessive carbon emissions.

[0014] Furthermore, the process of dynamically adjusting the direct carbon emission limit threshold A and the indirect carbon emission limit threshold C for the next quarter by using the final modified carbon emission forecast value in combination with the exponential smoothing method is as follows:

[0015] The revised quarterly direct carbon emission forecast value is combined with exponential smoothing to dynamically adjust the next quarter's direct carbon emission limit threshold A. The specific formula is:

[0016] A=α·F1+(1-α)·A t ;

[0017] Among them, F1 is the revised quarterly direct carbon emission forecast value, A t is the direct carbon emission limit threshold for the current quarter, α is the smoothing coefficient, and its value range is 0<α<1, which is used to weigh the revised direct carbon emission forecast value F1 and the direct carbon emission limit threshold A for the current quarter. t its significance in the calculation of the next quarter's quota threshold;

[0018] The revised quarterly indirect carbon emissions forecast value is combined with exponential smoothing to dynamically adjust the next quarter's indirect carbon emissions limit threshold C. The specific formula is:

[0019] C=β·F2+(1-β)·C t ;

[0020] Among them, F2 is the revised quarterly indirect carbon emission forecast value, C t is the direct carbon emission limit threshold for the current quarter, β is the smoothing coefficient, and its value range is 0<β<1, which is used to weigh the revised indirect carbon emission forecast value F2 and the direct carbon emission limit threshold C for the current quarter. t The importance of the quota threshold in the calculation of the next quarter.

[0021] Furthermore, when the actual direct carbon emissions exceed the quarterly preset direct carbon emissions threshold, or when the total indirect carbon emissions exceed the quarterly preset indirect carbon emissions threshold, the process of further analyzing the cause of the carbon emissions exceeding the threshold is as follows:

[0022] When direct actual carbon emissions exceed the quarterly preset direct carbon emissions threshold, direct estimated carbon emissions are calculated based on the information collected from all orders within the quarter. The specific formula is:

[0023]

[0024] Among them, E n1 For the direct estimated carbon emissions after calculation, F1 k is the expected consumption of the kth fuel, C k is the carbon emission coefficient of the kth fuel, m is the number of fuel types;

[0025] Calculate direct actual carbon emissions, the specific formula is:

[0026]

[0027] Among them, E n is the actual carbon emissions after calculation, F k is the actual consumption of the kth fuel, C k is the carbon emission coefficient of the kth fuel, m is the number of fuel types;

[0028] When the total indirect carbon emissions exceed the quarterly preset indirect carbon emissions threshold, the indirect estimated emissions are calculated using the following formula:

[0029] E a =A1·EF;

[0030] Among them, E a is the calculated indirect estimated carbon emissions, A1 is the estimated electricity consumption, and EF is the electricity emission factor;

[0031] To calculate indirect actual carbon emissions, the specific formula is:

[0032] E b =A2·EF;

[0033] Among them, E b is the calculated indirect actual carbon emissions, A2 is the actual electricity consumption, and EF is the electricity emission factor;

[0034] Compare the actual carbon emissions value with the calculated carbon emissions value. If the difference between the actual data and the calculated data is within ±5%-±10%, it means that the difference is normal and the carbon emissions data exceeds the standard due to an increase in the number of orders. Calculate the specific deviation and reduce the direct carbon emissions limit threshold B for the next quarter based on the deviation;

[0035] When the difference between the actual data and the calculated data exceeds ±5%-±10%, it indicates that the difference is abnormal. Calculate the energy conversion efficiency of the company's existing single operating equipment and compare the calculated energy conversion efficiency with the preset conversion efficiency. When the equipment efficiency deviation is ≥15%, it indicates that there is a problem with the equipment conversion efficiency. At this time, combine the equipment operating parameters including temperature and power to determine the problem equipment;

[0036] When both direct and indirect carbon emissions exceed the standard and the direct carbon emissions exceed the standard due to an increase in orders, the cause of the indirect carbon emissions exceeding the standard is directly determined to be an increase in orders, the specific deviation of the indirect carbon emissions is calculated, and the indirect carbon emissions limit threshold for the next quarter is lowered based on the deviation; when the direct carbon emissions exceed the standard due to equipment conversion efficiency, the cause of the direct and indirect carbon emissions exceeding the standard is determined to be an equipment problem. When indirect carbon emissions exceed the standard and direct carbon emissions do not exceed the standard, the electricity carbon emissions and process carbon emissions are further analyzed, the production process is optimized based on the analysis results, and the indirect carbon emissions limit threshold for the next quarter is lowered.

[0037] Furthermore, the order and carbon emission association module associates the order data with the carbon emission value when the actual value is within the quarterly preset direct carbon emission threshold range, establishes a relationship model between the carbon emission value and the order, and plans the order based on the established relationship model between the carbon emission value and the order. The process of optimizing carbon emission processing is as follows:

[0038] A linear relationship is established between the single order quantity x and the carbon emission value y. The specific formula is:

[0039] y=β0+β1x+e;

[0040] Where β0 is the intercept, β1 is the slope, and e is the random error term;

[0041] The parameters β0 and β1 are estimated by the least squares method. The specific formula is as follows:

[0042]

[0043] A nonlinear relationship is established between the single order quantity x and the carbon emission value y. The specific formula is:

[0044]

[0045] Among them, β0 is the intercept, β1 is the first-order coefficient, which reflects the linear change of carbon emissions y when the order volume x increases by one unit, β2, β3, ..., β n , these are the coefficients of higher-order terms, and e is the random error term;

[0046] Based on the established relationship model between carbon emission values ​​and orders, orders are planned and carbon emission processing is optimized.

[0047] Furthermore, the process of planning orders and optimizing carbon emissions based on the established relationship model between carbon emissions and orders is as follows:

[0048] When the direct actual carbon emissions value is within the quarterly preset direct carbon emissions threshold, the next quarter's preset threshold A is modified and the established relationship model between carbon emissions values ​​and orders is used to obtain the scheduled order volume data A1 for the next quarter;

[0049] When the direct actual carbon emissions value exceeds the quarterly preset direct carbon emissions threshold and is caused by an increase in the number of orders, the modified direct carbon emissions limit threshold B for the next quarter will be substituted into the established relationship model between carbon emissions value and order to obtain the scheduled order volume data B1 for the next quarter; when the direct actual carbon emissions value exceeds the quarterly preset direct carbon emissions threshold and is caused by equipment operation, the scheduled order volume data B1 for the next quarter will be allocated to normal equipment.

[0050] A carbon emission analysis method, the specific steps are as follows:

[0051] S1. Collect the company's quarterly order data, fuel consumption data, and electricity consumption data;

[0052] S2. Calculate carbon emissions data;

[0053] S3. Compare direct actual carbon emissions data and indirect carbon emissions data with their respective quarterly thresholds;

[0054] S4. When the carbon emissions are below the quarterly threshold, the error between the predicted carbon emissions and the actual carbon emissions is analyzed and used to correct the carbon emissions forecast value for the next quarter, and further adjust the limit thresholds for direct carbon emissions and indirect carbon emissions for the next quarter respectively;

[0055] S5. When the carbon emissions exceed the quarterly threshold, analyze the reasons for the increase. If the increase is related to the number of orders, reduce the direct carbon emissions limit threshold and indirect carbon emissions limit threshold for the next quarter respectively. If the increase is related to equipment operating efficiency, identify the problematic equipment based on the equipment operating parameters.

[0056] S6. Establish the relationship between order quantity and emission data, obtain the order data for the next quarter based on the direct carbon emission limit threshold for the next quarter, and optimize the carbon emissions.

[0057] A device for analyzing carbon emissions, comprising a memory and a processor, wherein the memory stores a computer program capable of being loaded by the processor and executing the system described above;

[0058] A computer storage medium storing a computer program that can be loaded by a processor and executed by the system described above

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] 1. The present invention compares the quarterly direct actual carbon emissions and indirect actual carbon emissions with their respective quarterly preset carbon emission thresholds. When the quarterly direct actual carbon emissions and indirect actual carbon emissions are within their respective carbon emission thresholds, the direct actual carbon emissions and indirect actual carbon emissions are further compared and analyzed with the quarterly predicted carbon emissions values, and the comparisons are used to revise the carbon emission forecast for the next quarter. This not only makes the predicted carbon emissions data more accurate, but also makes the preset threshold for the next quarter, which is modified based on the predicted values, more in line with the actual situation.

[0061] When direct carbon emissions and indirect carbon emissions exceed the preset threshold range, the reasons for the excess carbon emissions are analyzed. If the excess direct carbon emissions are caused by the number of orders, it means that the equipment is operating normally, and the excess indirect carbon emissions are also due to the number of orders. Therefore, the quarterly direct carbon emissions limit threshold and the quarterly indirect carbon emissions limit threshold are lowered. If the excess carbon emissions are caused by equipment problems, the problem equipment is identified based on the received equipment data.

[0062] 2. By establishing a relationship model between carbon emission values ​​and orders, the present invention can facilitate the planning of subsequent orders and also simplify the carbon emission calculation steps. Carbon emission data can be quickly obtained by obtaining the order quantity.

[0063] The present invention establishes a relationship model between carbon emission values ​​and orders and calculates with preset carbon emission values ​​to obtain the number of orders arranged for the next quarter, so that enterprises can make full use of resources while meeting carbon emission requirements and avoid the problem of excessive carbon emissions due to overproduction. In addition, by arranging orders with precise amounts, the production process can also be effectively optimized. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 is a block diagram of a carbon emission analysis system of the present invention;

[0065] Figure 2 The carbon emission analysis process of the present invention Figure 1 ;

[0066] Figure 3 The carbon emission analysis process of the present invention Figure 2 . DETAILED DESCRIPTION

[0067] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0068] like Figure 1-Figure 3 As shown, it includes a data acquisition module, a carbon emission calculation and analysis module, an order and carbon emission association module, and a carbon emission optimization module. The data acquisition module, the carbon emission calculation and analysis module, the order and carbon emission association module, and the carbon emission optimization module are sequentially connected in communication;

[0069] Data collection module, used to collect quarterly order data, fuel consumption data, equipment operating parameters, and power consumption data;

[0070] The carbon emissions calculation and analysis module is used to calculate the actual direct carbon emissions values ​​and the actual indirect carbon emissions values, and compare the actual direct carbon emissions values ​​with the quarterly preset direct carbon emissions threshold, and compare the actual indirect carbon emissions values ​​with the quarterly preset indirect carbon emissions threshold. When the actual values ​​are within the quarterly preset carbon emissions threshold, the module further analyzes the error between the actual carbon emissions values ​​and the carbon emissions forecast values, and uses this to correct the carbon emissions forecast values ​​and modify the carbon emissions threshold for the next quarter accordingly.

[0071] In this embodiment, the carbon emissions calculation and analysis module is used to calculate the direct actual carbon emissions value and the indirect actual carbon emissions value, and compare the direct actual carbon emissions value with the quarterly preset direct carbon emissions threshold, and compare the indirect actual carbon emissions value with the quarterly preset indirect carbon emissions threshold. When the actual value is within the quarterly preset carbon emissions threshold, the module further analyzes the error between the actual carbon emissions value and the carbon emissions forecast value to correct the carbon emissions forecast value, and accordingly, the carbon emissions threshold for the next quarter is modified as follows:

[0072] It is used to calculate the actual direct carbon emissions value and the actual indirect carbon emissions value, and compare the actual direct carbon emissions value with the quarterly preset direct carbon emissions threshold, and compare the actual indirect carbon emissions value with the quarterly preset indirect carbon emissions threshold. When the actual value is within the quarterly preset carbon emissions threshold, the error between the actual carbon emissions value and the carbon emissions forecast value is further analyzed to correct the carbon emissions forecast value. Finally, the corrected carbon emissions forecast value is used in combination with the exponential smoothing method to dynamically adjust the direct carbon emissions limit threshold A and the indirect carbon emissions limit threshold C for the next quarter;

[0073] In this embodiment, the process of dynamically adjusting the next quarter's direct carbon emission limit threshold A and the next quarter's indirect carbon emission limit threshold C using the revised carbon emission forecast value combined with the exponential smoothing method is as follows:

[0074] The revised quarterly direct carbon emission forecast value is combined with exponential smoothing to dynamically adjust the next quarter's direct carbon emission limit threshold A. The specific formula is:

[0075] A=α·F1+(1-α)·A t ;

[0076] Among them, F1 is the revised quarterly direct carbon emission forecast value, A t is the direct carbon emission limit threshold for the current quarter, α is the smoothing coefficient, and its value range is 0<α<1, which is used to weigh the revised direct carbon emission forecast value F1 and the direct carbon emission limit threshold A for the current quarter. t its significance in the calculation of the next quarter's quota threshold;

[0077] The revised quarterly indirect carbon emissions forecast value is combined with exponential smoothing to dynamically adjust the next quarter's indirect carbon emissions limit threshold C. The specific formula is:

[0078] C=β·F2+(1-β)·C t ;

[0079] Among them, F2 is the revised quarterly indirect carbon emission forecast value, C t is the direct carbon emission limit threshold for the current quarter, β is the smoothing coefficient, and its value range is 0<β<1, which is used to weigh the revised indirect carbon emission forecast value F2 and the direct carbon emission limit threshold C for the current quarter. t The importance of the quota threshold in the calculation of the next quarter.

[0080] It should be noted that the exponential smoothing method can fit the characteristics of emissions changing over time, is sensitive to recent fluctuations, and can quickly capture changes in emission trends. When faced with complex and changeable actual indirect carbon emissions, the exponential smoothing method can dynamically adjust the threshold based on new data based on error analysis, so that the threshold is more in line with the actual emission situation, providing a more accurate, reasonable and timely limit reference for carbon emission management in the next quarter.

[0081] If actual direct carbon emissions exceed the quarterly preset direct carbon emission threshold or the total indirect carbon emissions exceed the quarterly preset indirect carbon emission threshold, further analysis will be conducted on the reasons for the excessive carbon emissions.

[0082] In this embodiment, when the actual direct carbon emissions exceed the quarterly preset direct carbon emission threshold, or when the total indirect carbon emissions exceed the quarterly preset indirect carbon emission threshold, the process of further analyzing the cause of the carbon emissions exceeding the threshold is as follows:

[0083] When direct actual carbon emissions exceed the quarterly preset direct carbon emissions threshold, direct estimated carbon emissions are calculated based on the information collected from all orders within the quarter. The specific formula is:

[0084]

[0085] Among them, E n1 For the direct estimated carbon emissions after calculation, F1 k is the expected consumption of the kth fuel, C k is the carbon emission coefficient of the kth fuel, m is the number of fuel types;

[0086] Calculate direct actual carbon emissions, the specific formula is:

[0087]

[0088] Among them, E n is the actual carbon emissions after calculation, F k is the actual consumption of the kth fuel, C k is the carbon emission coefficient of the kth fuel, m is the number of fuel types;

[0089] When the total indirect carbon emissions exceed the quarterly preset indirect carbon emissions threshold, the indirect estimated emissions are calculated using the following formula:

[0090] E a =A1·EF;

[0091] Among them, E a is the calculated indirect estimated carbon emissions, A1 is the estimated electricity consumption, and EF is the electricity emission factor;

[0092] To calculate indirect actual carbon emissions, the specific formula is:

[0093] E b =A2·EF;

[0094] Among them, E b is the calculated indirect actual carbon emissions, A2 is the actual electricity consumption, and EF is the electricity emission factor;

[0095] Compare the actual carbon emissions value with the calculated carbon emissions value. If the difference between the actual data and the calculated data is within ±5%-±10%, it means that the difference is normal and the carbon emissions data exceeds the standard due to an increase in the number of orders. Calculate the specific deviation and reduce the direct carbon emissions limit threshold B for the next quarter based on the deviation;

[0096] When the difference between the actual data and the calculated data exceeds ±5%-±10%, it indicates that the difference is abnormal. Calculate the energy conversion efficiency of the company's existing single operating equipment and compare the calculated energy conversion efficiency with the preset conversion efficiency. When the equipment efficiency deviation is ≥15%, it indicates that there is a problem with the equipment conversion efficiency. At this time, combine the equipment operating parameters including temperature and power to determine the problem equipment;

[0097] When both direct and indirect carbon emissions exceed the standard and the direct carbon emissions exceed the standard due to an increase in orders, the cause of the indirect carbon emissions exceeding the standard is directly determined to be an increase in orders, the specific deviation of the indirect carbon emissions is calculated, and the indirect carbon emissions limit threshold for the next quarter is lowered based on the deviation; when the direct carbon emissions exceed the standard due to equipment conversion efficiency, the cause of the direct and indirect carbon emissions exceeding the standard is determined to be an equipment problem. When indirect carbon emissions exceed the standard and direct carbon emissions do not exceed the standard, the electricity carbon emissions and process carbon emissions are further analyzed, the production process is optimized based on the analysis results, and the indirect carbon emissions limit threshold for the next quarter is lowered.

[0098] It should be noted that the specific steps to determine the problem device are:

[0099] First, calculate the energy conversion efficiency of the equipment. The specific formula is: When η 实际 <0.85η 预设 , determine that the equipment conversion efficiency is abnormal.

[0100] It should be noted that when the actual direct carbon emission value is within the quarterly preset direct carbon emission threshold range, by analyzing the error between the actual and predicted carbon emission values, the predicted emission value can be effectively corrected to make subsequent carbon emission forecasts more accurate, and at the same time, the preset threshold for the next quarter can be reasonably modified to make the threshold setting more in line with the actual situation; and when the actual value exceeds the preset range, the analysis of the reasons for the excessive carbon emissions can help enterprises or relevant departments accurately locate the problem so that targeted measures can be taken in a timely manner.

[0101] It should be noted that after the end of the first quarter, the company's actual direct carbon emissions were 530 tons of carbon dioxide equivalent, exceeding the preset threshold of 500 tons. The order data and fuel consumption data for the first quarter were obtained. The number of orders in the first quarter increased by 20% more than expected, and fuel consumption also increased accordingly. Comparing the actual carbon emissions value with the calculated carbon emissions value, it was found that the difference was within ±8%, indicating that the carbon emissions data exceeded the standard due to the increase in the number of orders. The specific deviation was further calculated:

[0102] (530-500)÷500×100%=6%;

[0103] Lower the direct carbon emission limit threshold B for the next quarter based on the deviation. The carbon emission limit threshold for the second quarter is adjusted to 500×(1-6%)=470 tons of carbon dioxide equivalent;

[0104] The direct actual carbon emissions in the second quarter were 450 tons of carbon dioxide equivalent, which is within the quarterly threshold of 470 tons. Further analysis of the direct actual carbon emissions and the predicted carbon emissions was performed. Multiple order amounts and fuel consumption data for the second quarter were obtained. Based on these multiple orders, the correction parameter between the actual and predicted emissions was 0.95. This correction parameter was used to correct the carbon emissions forecast for the third quarter. Based on the third quarter forecast of 520 tons of carbon dioxide equivalent, the corrected carbon dioxide equivalent was calculated as follows:

[0105] 520×0.95=494 (tons);

[0106] The carbon emission limit threshold for the third quarter is adjusted to 494 tons of carbon dioxide equivalent. The actual direct carbon emissions in the third quarter are 480 tons of carbon dioxide equivalent, which is within the quarterly threshold of 494 tons. Finally, repeat the steps for the second quarter, obtain the revised parameters again, and revise the carbon emission forecast value and limit threshold for the fourth quarter.

[0107] After three quarters of implementation, the company found during its fourth-quarter assessment that the error in its quarterly carbon emissions forecast had dropped from an initial ±15% to ±5%. This demonstrates that the system can effectively dynamically adjust and correct carbon emissions based on actual emissions, improving the accuracy of carbon emissions forecasts and helping companies better manage and reduce carbon emissions.

[0108] Substituting the carbon emission limit threshold for the third quarter into the model, we obtain the order volume data A1 for the third quarter to be 800 orders. Similarly, substituting the direct carbon emission limit threshold B for the second quarter into the relationship model between carbon emission values ​​and orders, we obtain the order volume data B1 for the second quarter to be 750 orders. The actual direct carbon emissions for this quarter exceeded the threshold. Analysis shows that this was caused by equipment operation problems. Using the same number of production equipment, carbon emissions are expected to be reduced by 20% due to the higher energy conversion efficiency of normal equipment.

[0109] The order and carbon emission association module associates order data with carbon emission values ​​when the actual value is within the quarterly preset direct carbon emission threshold range, establishes a relationship model between carbon emission values ​​and orders, and plans orders based on the established relationship model between carbon emission values ​​and orders to optimize carbon emissions;

[0110] In this embodiment, the order and carbon emissions association module associates the order data with the carbon emissions value when the actual value is within the quarterly preset direct carbon emissions threshold range, establishes a relationship model between the carbon emissions value and the order, and plans the order based on the established relationship model between the carbon emissions value and the order. The process of optimizing carbon emissions processing is as follows:

[0111] A linear relationship is established between the single order quantity x and the carbon emission value y. The specific formula is:

[0112] y=β0+β1x+e;

[0113] Where β0 is the intercept, β1 is the slope, and e is the random error term;

[0114] The parameters β0 and β1 are estimated by the least squares method. The specific formula is as follows:

[0115]

[0116] A nonlinear relationship is established between the single order quantity x and the carbon emission value y. The specific formula is:

[0117]

[0118] Among them, β0 is the intercept, β1 is the first-order coefficient, which reflects the linear change of carbon emissions y when the order volume x increases by one unit, β2, β3, ..., β n , these are the coefficients of higher-order terms, and e is the random error term;

[0119] It should be noted that for the order of polynomial regression, the original data set is first randomly divided into k non-overlapping subsets, and for each order n, k iterations are performed. In each iteration, k-1 subsets are selected as training sets, and the remaining subset is used as the validation set. The training set is used to train the n-order polynomial regression model, and then the mean square error (MSE) is calculated on the validation set. The errors of k iterations are averaged to obtain the cross-validation error of the polynomial model of this order. Finally, the order with the smallest cross-validation error is selected as the final polynomial order.

[0120] It should be noted that the least squares method is used for linear modeling of orders and carbon emissions, combined with the nonlinear characteristics of order quantity in production scenarios, and polynomial regression is further introduced to solve the limitations of traditional linear models in complex production environments.

[0121] It should be noted that the linear model and nonlinear model of the relationship between orders and emissions are established. The linear model is suitable for situations where the production process is relatively stable and the input and output relationship of various production factors is relatively fixed. The nonlinear model is suitable for situations where the changes in order volume show complex patterns, such as seasonal fluctuations, cyclical changes, or are affected by a combination of factors.

[0122] Based on the established relationship model between carbon emission values ​​and orders, orders are planned and carbon emission processing is optimized.

[0123] In this embodiment, based on the established relationship model between carbon emission values ​​and orders, the order planning and carbon emission optimization process is as follows:

[0124] When the direct actual carbon emissions value is within the quarterly preset direct carbon emissions threshold, the next quarter's preset threshold A is modified and the established relationship model between carbon emissions values ​​and orders is used to obtain the scheduled order volume data A1 for the next quarter;

[0125] When the direct actual carbon emissions value exceeds the quarterly preset direct carbon emissions threshold and is caused by an increase in the number of orders, the modified direct carbon emissions limit threshold B for the next quarter will be substituted into the established relationship model between carbon emissions value and order to obtain the scheduled order volume data B1 for the next quarter; when the direct actual carbon emissions value exceeds the quarterly preset direct carbon emissions threshold and is caused by equipment operation, the scheduled order volume data B1 for the next quarter will be allocated to normal equipment.

[0126] It should be noted that by calculating the relationship between the change in order volume and the change in threshold volume and drawing a table, the corresponding relationship between the percentage increase in order volume and the percentage decrease in threshold volume can be obtained. Finally, the specific relationship that when the order quantity increases by X%, threshold B decreases by Y% can be obtained, which further facilitates the modification of threshold B.

[0127] It should be noted that equipment operating efficiency will lead to energy waste and increase energy consumption. The additional energy consumption will significantly increase carbon emissions. Therefore, using equipment with normal operating efficiency to process orders can reduce carbon emissions and thus optimize carbon emissions.

[0128] A device for analyzing carbon emissions includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute any of the above systems.

[0129] A computer storage medium stores a computer program that can be loaded by a processor and executed by any of the above systems.

[0130] In summary, the present application compares the quarterly direct actual carbon emission, indirect actual carbon emission and the respective quarterly preset carbon emission threshold value, when the quarterly direct actual carbon emission and indirect actual carbon emission are within the respective carbon emission threshold value, then the direct actual carbon emission, indirect actual carbon emission and the quarterly predicted carbon emission value are further compared and analyzed, and are used to correct the carbon emission prediction value of the next quarter, so that the predicted carbon emission data is more accurate, and the preset threshold value of the next quarter modified according to the prediction value can also be more in line with the actual situation; when the direct carbon emission and indirect carbon emission exceed the preset threshold range, the reason for the carbon emission exceeding is analyzed, when the reason for the direct carbon emission exceeding is caused by the order quantity, it indicates that the equipment running state is normal, and the indirect carbon emission exceeding is also caused by the order quantity, so that the quarterly direct carbon emission limit threshold and the quarterly indirect carbon emission limit threshold are reduced, when the carbon emission exceeding is caused by equipment problems, the problem equipment is identified in combination with the received equipment data; the present application can facilitate planning of subsequent orders by establishing a carbon emission value and order relationship model, and can also simplify the calculation steps of carbon emission, and the carbon emission data can be quickly obtained through the obtained order quantity; the present application can obtain the order arrangement quantity of the next quarter by calculating the preset carbon emission value through the established carbon emission value and order relationship model, so that the enterprise can fully utilize resources under the premise of meeting the carbon emission requirement, avoid the problem of carbon emission exceeding caused by excessive production, and in addition, the production process can also be effectively optimized through accurate order arrangement.

[0131] In the embodiments of the present application, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and the division of modules can be different from the above. For example, the division of modules can be performed in a different manner, or some or all of the modules can be combined into one module, or some or all of the modules can be split into multiple modules. The modules displayed as separate components can or can not be physically separate, and the modules displayed as components that are combined can or can not be combined physically. The components of the above-described apparatus embodiments can be implemented in a form of a software program or a combination of hardware and software, and can be stored in any medium, such as a computer-readable medium, a computer program product, a memory, etc.

[0132] The above embodiments are only used to illustrate the technical method of the present application but not limit the present application. Although the present application is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical method of the present application.

Claims

1. A carbon emission analysis system, characterized by: It includes a data acquisition module, a carbon emission calculation and analysis module, an order and carbon emission association module, and a carbon emission optimization module, wherein the data acquisition module, the carbon emission calculation and analysis module, the order and carbon emission association module, and the carbon emission optimization module are sequentially connected in communication; The data collection module is used to collect the company's quarterly order data, fuel consumption data, equipment operating parameters and power consumption data; The carbon emissions calculation and analysis module is used to calculate the direct actual carbon emissions value and the indirect actual carbon emissions value, and compare the direct actual carbon emissions value with the quarterly preset direct carbon emissions threshold, and compare the indirect actual carbon emissions value with the quarterly preset indirect carbon emissions threshold. When the actual value is within the quarterly preset carbon emissions threshold, further analyze the error between the actual carbon emissions value and the carbon emissions forecast value to correct the carbon emissions forecast value and modify the carbon emissions threshold for the next quarter accordingly; It is used to calculate the direct actual carbon emission values ​​and the indirect actual carbon emission values, and compare the direct actual carbon emission values ​​with the quarterly preset direct carbon emission threshold, and compare the indirect actual carbon emission values ​​with the quarterly preset indirect carbon emission threshold. When the actual value is within the quarterly preset carbon emission threshold, the error between the actual carbon emission value and the carbon emission forecast value is further analyzed to correct the carbon emission forecast value. Finally, the corrected carbon emission forecast value is used in combination with the exponential smoothing method to dynamically adjust the direct carbon emission limit threshold for the next quarter. and the next quarter's indirect carbon emissions allowance threshold ; If actual direct carbon emissions exceed the quarterly preset direct carbon emission threshold or total indirect carbon emissions exceed the quarterly preset indirect carbon emission threshold, further analysis will be conducted on the reasons for the excessive carbon emissions; The order and carbon emission association module associates the order data with the carbon emission value when the actual value is within the quarterly preset direct carbon emission threshold range, establishes a relationship model between the carbon emission value and the order, and plans the order based on the established relationship model between the carbon emission value and the order to optimize the carbon emissions.

2. A carbon emission analysis system according to claim 1, characterized in that: The final revised carbon emissions forecast value is combined with the exponential smoothing method to dynamically adjust the direct carbon emissions limit threshold for the next quarter. and the next quarter's indirect carbon emissions allowance threshold The process is as follows: Combine the revised quarterly direct carbon emission forecast value with exponential smoothing to dynamically adjust the next quarter's direct carbon emission limit threshold , the specific formula is: ； in, is the revised quarterly direct carbon emissions forecast value, is the direct carbon emission limit threshold for the current quarter, Is the smoothing coefficient, the value range is 0< <1, used to weigh the revised direct carbon emissions forecast and the current quarter's direct carbon emissions allowance threshold its significance in the calculation of the next quarter's quota threshold; The revised quarterly indirect carbon emissions forecast value is combined with exponential smoothing to dynamically adjust the indirect carbon emissions limit threshold for the next quarter. , the specific formula is: ； in, is the revised quarterly indirect carbon emissions forecast value, is the direct carbon emission limit threshold for the current quarter, Is the smoothing coefficient, the value range is 0< <1, used to weigh the revised indirect carbon emissions forecast and the current quarter's direct carbon emissions allowance threshold The importance of the quota threshold in the calculation of the next quarter.

3. The carbon emission analysis system according to claim 1, characterized in that: If the actual direct carbon emissions exceed the quarterly preset direct carbon emission threshold or the total indirect carbon emissions exceed the quarterly preset indirect carbon emission threshold, the process of further analyzing the reasons for the carbon emissions exceeding the threshold is as follows: When direct actual carbon emissions exceed the quarterly preset direct carbon emissions threshold, direct estimated carbon emissions are calculated based on the information collected from all orders within the quarter. The specific formula is: ； in, is the directly estimated carbon emissions after calculation, It is Estimated consumption of fuel, It is The carbon emission coefficient of the fuel, is the number of fuel types; Calculate direct actual carbon emissions, the specific formula is: ； in, is the actual carbon emissions after calculation, It is The actual consumption of fuel, It is The carbon emission coefficient of the fuel, is the number of fuel types; When the total indirect carbon emissions exceed the quarterly preset indirect carbon emissions threshold, the indirect estimated emissions are calculated using the following formula: ； in, is the calculated indirect estimated carbon emissions, To estimate the electricity consumption, is the electricity emission factor; To calculate indirect actual carbon emissions, the specific formula is: ； in, is the calculated indirect actual carbon emissions, is the actual electricity consumption, is the electricity emission factor; Compare the actual carbon emissions value with the calculated carbon emissions value. If the difference between the actual data and the calculated data is within ±5% - ±10%, it means that the difference is normal and the carbon emissions data exceeds the standard due to an increase in the number of orders. Calculate the specific deviation and reduce the direct carbon emissions limit threshold B for the next quarter based on the deviation; When the difference between the actual data and the calculated data exceeds ±5% - ±10%, it indicates an abnormal difference. Calculate the energy conversion efficiency of a single existing operating device in the enterprise and compare the calculated energy conversion efficiency with the preset conversion efficiency. When the equipment efficiency deviation is ≥15%, it indicates that there is a problem with the equipment conversion efficiency. At this time, combine the equipment operating parameters including temperature and power to determine the problem equipment; When both direct and indirect carbon emissions exceed the standard and the direct carbon emissions exceed the standard due to an increase in orders, the cause of the indirect carbon emissions exceeding the standard is directly determined to be an increase in orders, the specific deviation of the indirect carbon emissions is calculated, and the indirect carbon emissions limit threshold for the next quarter is lowered based on the deviation; when the direct carbon emissions exceed the standard due to equipment conversion efficiency, the cause of the direct and indirect carbon emissions exceeding the standard is determined to be an equipment problem. When indirect carbon emissions exceed the standard and direct carbon emissions do not exceed the standard, the electricity carbon emissions and process carbon emissions are further analyzed, the production process is optimized based on the analysis results, and the indirect carbon emissions limit threshold for the next quarter is lowered.

4. A carbon emission analysis system according to claim 1, characterized in that: The order and carbon emission association module associates the order data with the carbon emission value when the actual value is within the quarterly preset direct carbon emission threshold range, establishes a relationship model between the carbon emission value and the order, and plans the order based on the established relationship model between the carbon emission value and the order. The process of optimizing carbon emission processing is as follows: Establish a single order quantity and carbon emissions There is a linear relationship between them, and the specific formula is: ； in, is the intercept, is the slope, is the random error term; Estimate parameters by least squares method and , the specific formula is as follows: ； ； Establish a single order quantity and carbon emissions There is a nonlinear relationship between them, and the specific formula is: ； in, is the intercept, is the first-order coefficient, which reflects the order quantity For every additional unit of carbon emissions The linear change part of , these are the higher-order coefficients, is the random error term; Based on the established relationship model between carbon emission values ​​and orders, orders are planned and carbon emission processing is optimized.

5. A carbon emission analysis system according to claim 4, characterized in that: The process of planning orders and optimizing carbon emissions based on the established relationship model between carbon emissions values ​​and orders is as follows: When the direct actual carbon emissions value is within the quarterly preset direct carbon emissions threshold, the next quarter's preset threshold A is modified and the established relationship model between carbon emissions values ​​and orders is used to obtain the scheduled order volume data A1 for the next quarter; When the direct actual carbon emissions value exceeds the quarterly preset direct carbon emissions threshold and is caused by an increase in the number of orders, the modified direct carbon emissions limit threshold B for the next quarter will be substituted into the established relationship model between carbon emissions value and order to obtain the scheduled order volume data B1 for the next quarter; when the direct actual carbon emissions value exceeds the quarterly preset direct carbon emissions threshold and is caused by equipment operation, the scheduled order volume data B1 for the next quarter will be allocated to normal equipment.

6. A carbon emission analysis method, characterized in that: The specific steps are as follows: S1. Collect the company's quarterly order data, fuel consumption data, and electricity consumption data; S2. Calculate carbon emissions data; S3. Compare direct actual carbon emissions data and indirect carbon emissions data with their respective quarterly thresholds; S4. When the carbon emissions are below the quarterly threshold, the error between the predicted carbon emissions and the actual carbon emissions is analyzed and used to correct the carbon emissions forecast value for the next quarter, and further adjust the limit thresholds for direct carbon emissions and indirect carbon emissions for the next quarter respectively; S5. When the carbon emissions exceed the quarterly threshold, analyze the reasons for the increase. If the increase is related to the number of orders, reduce the direct carbon emissions limit threshold and indirect carbon emissions limit threshold for the next quarter respectively. If the increase is related to equipment operating efficiency, identify the problematic equipment based on the equipment operating parameters. S6. Establish the relationship between order quantity and emission data, obtain the order data for the next quarter based on the direct carbon emission limit threshold for the next quarter, and optimize the carbon emissions.

7. An analytical device for carbon emissions, characterized by: The system comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute the system according to any one of claims 1 to 5.

8. A computer storage medium, characterized in that: The computer program is stored which can be loaded by a processor and execute the system according to any one of claims 1 to 5.

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