Carbon emission analysis method, system and equipment and storage medium

Abstract

The invention discloses a carbon emission analysis method, system and device, and a storage medium, and belongs to the field of carbon emission analysis, and the system comprises a data collection module, a carbon emission calculation and analysis module, an order and carbon emission correlation 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 in communication connection in sequence; the data acquisition module is used for acquiring order data, fuel consumption data, equipment operation parameters and power consumption data of an enterprise in quarters; according to the carbon emission analysis method, system and equipment and the storage medium, the actual and preset carbon emission threshold values can be analyzed and compared, the exceeding reason can be known, in addition, by establishing the carbon emission and order relation model, calculation and order number planning can be effectively simplified, the production process is optimized, and the production efficiency is improved. And the effect of assisting an enterprise to accurately analyze the carbon emission problem is achieved.

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, device and storage medium. Background Art

[0002] Against the backdrop of the world's active response to climate change, the issue of carbon emissions has become the focus of attention from all sectors. With the continuous strengthening of carbon emission supervision by various countries, enterprises are facing increasingly stringent carbon emission restriction requirements. Accurately analyzing and effectively controlling carbon emissions is of crucial significance for enterprises to reduce operating costs, enhance their environmental protection image, and achieve sustainable development.

[0003] A Chinese patent provides a carbon emission analysis method, system, computer device and storage medium, with the publication number CN114077788A, including obtaining the consumption of various fuels and the annual electricity consumption within the reporting year of the power system, and calculating the transmission and distribution losses; calculating the corresponding fossil fuel activity data on the power generation side based on the consumption of various fuels; calculating the carbon dioxide emissions generated by the combustion of fossil fuels on the power generation side, the carbon dioxide emissions generated by transmission and distribution losses, and the carbon dioxide emissions generated by electricity consumption through a preset energy conversion model; and outputting the sum of the carbon dioxide emissions generated by the combustion of fossil fuels on the power generation side, the carbon dioxide emissions generated by transmission and distribution losses, and the carbon dioxide emissions generated by electricity consumption 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 associate actual orders with carbon emissions, so that when enterprises arrange production orders, they cannot accurately know the specific impact of the order quantity on carbon emissions, and it is easy to have overproduction resulting in carbon emission exceedance. At the same time, when calculating carbon emissions, the steps are cumbersome and the efficiency is low, and the carbon emissions cannot be quickly obtained based on order data, which is not conducive to enterprises adjusting production strategies in a timely manner.

[0004] In addition, existing carbon emission analysis systems have many deficiencies. Specifically, some systems are not accurate enough in predicting carbon emissions, simply estimating based on historical data and failing to fully consider various complex factors in actual production. This results in a large deviation between the preset carbon emission threshold and the actual situation, and cannot effectively guide the production operation of enterprises. When the difference between the actual carbon emissions and the predicted value and the preset threshold is large, it is also difficult to accurately analyze whether the reason for the exceedance is the order quantity or equipment problems, so that 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. For this purpose, the present invention provides a carbon emission analysis method, system, device and storage medium, enabling relevant personnel in enterprises to conveniently analyze carbon emission problems.

[0006] 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. 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 for communication.

[0008] The data acquisition module is used to collect order data, fuel consumption data, equipment operation parameters, and power consumption data within a quarter of an enterprise.

[0009] The carbon emission calculation and analysis module is used to calculate the direct actual carbon emission value and the indirect actual carbon emission value, 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 range, further analyze the error between the actual carbon emission amount value and the carbon emission prediction value, use it to correct the carbon emission prediction value, and modify the next quarter's carbon emission threshold accordingly.

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

[0011] Further, the process of the carbon emission calculation and analysis module calculating the direct actual carbon emission value and the indirect actual carbon emission value, comparing the direct actual carbon emission value with the quarterly preset direct carbon emission threshold, comparing the indirect actual carbon emission value with the quarterly preset indirect carbon emission threshold, further analyzing the error between the actual carbon emission amount value and the carbon emission prediction value when the actual value is within the quarterly preset carbon emission threshold range, using it to correct the carbon emission prediction value, and modifying the next quarter's carbon emission threshold accordingly is as follows:

[0012] It is used to calculate the direct actual carbon emission value and the indirect actual carbon emission value, 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 range, further analyze the error between the actual carbon emission value and the predicted carbon emission value, which is used to correct the predicted carbon emission value. Finally, use the corrected predicted carbon emission value combined with the exponential smoothing method to dynamically adjust the direct carbon emission quota threshold A for the next quarter and the indirect carbon emission quota threshold C for the next quarter;

[0013] If the direct actual carbon emission exceeds the quarterly preset direct carbon emission threshold or the total indirect carbon emission exceeds the quarterly preset indirect carbon emission threshold, further analyze the reasons for the carbon emission exceeding the standard.

[0014] Furthermore, the process of finally using the corrected predicted carbon emission value combined with the exponential smoothing method to dynamically adjust the direct carbon emission quota threshold A for the next quarter and the indirect carbon emission quota threshold C for the next quarter is as follows:

[0015] Combine the corrected quarterly direct carbon emission prediction value with exponential smoothing to dynamically adjust the direct carbon emission quota threshold A for the next quarter. The specific formula is:

[0016] A = α·F1 + (1 - α)·A t ;

[0017] Among them, F1 is the corrected quarterly direct carbon emission prediction value, and A t is the direct carbon emission quota threshold for the current quarter. α is the smoothing coefficient, and its value range is 0 < α < 1, which is used to weigh the importance of the corrected direct carbon emission prediction value F1 and the direct carbon emission quota threshold A for the current quarter t in the calculation of the quota threshold for the next quarter;

[0018] Combine the corrected quarterly indirect carbon emission prediction value with exponential smoothing to dynamically adjust the indirect carbon emission quota threshold C for the next quarter. The specific formula is:

[0019] C = β·F2 + (1 - β)·C t ;

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

[0021] Further, when the direct actual 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 reasons for the carbon emissions exceeding the standard is as follows:

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

[0023]

[0024] Among them, E n1 is the calculated direct projected carbon emissions, F1 k is the projected consumption of the k-th fuel, C k is the carbon emission coefficient of the k-th fuel, and m is the number of fuel types;

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

[0026]

[0027] Among them, E n is the calculated actual carbon emissions, F k is the actual consumption of the k-th fuel, C k is the carbon emission coefficient of the k-th fuel, and m is the number of fuel types;

[0028] When the total indirect carbon emissions exceed the quarterly preset indirect carbon emissions threshold, calculate the indirect projected emissions. The specific formula is:

[0029] E a = A1·EF;

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

[0031] Calculate the 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 emission value with the calculated carbon emission value. When the difference between the actual data and the calculated data is within ±5% - ±10%, it indicates that the difference is normal and the carbon emission data exceeds the standard due to the increase in the number of orders. Calculate the specific deviation and reduce the direct carbon emission limit threshold B for the next quarter according to 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 existing single operating equipment of the enterprise, and compare the calculated energy conversion efficiency with the preset conversion efficiency. When the equipment efficiency deviation ≥ 15%, it indicates that there is a problem with the equipment conversion efficiency. At this time, combine the equipment operation parameters including temperature and power to determine the problematic equipment;

[0036] When both the direct carbon emissions and the indirect carbon emissions exceed the standard and the direct carbon emissions exceed the standard due to an increase in orders, directly determine that the reason for the excess indirect carbon emissions is the increase in orders, calculate the specific deviation of the indirect carbon emissions, calculate the specific deviation, and reduce the indirect carbon emission limit threshold for the next quarter according to the deviation; when the direct carbon emissions exceed the standard due to the equipment conversion efficiency, directly determine that the reason for the excess of the direct and indirect carbon emissions is the equipment problem. When the indirect carbon emissions exceed the standard and the direct carbon emissions do not exceed the standard, further analyze the electricity carbon emissions and the process carbon emissions, and optimize the production process according to the analysis results, and reduce the indirect carbon emission limit threshold for the next quarter.

[0037] Further, in the order and carbon emission association module, when the actual value is within the range of the quarterly preset direct carbon emission threshold, associate the order data with the carbon emission value, establish a relationship model between the carbon emission value and the order, and according to the established relationship model between the carbon emission value and the order, plan the order, and the process of optimizing the carbon emissions is as follows:

[0038] There is a linear relationship between the single order quantity x and the carbon emission value y, and the specific formula is:

[0039] y = β0 + β1x + e;

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

[0041] Estimate the parameters β0 and β1 by the least squares method, and the specific formula is as follows:

[0042]

[0043] There is a non - linear relationship between the single order quantity x and the carbon emission value y, and the specific formula is:

[0044]

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

[0046] According to the established relationship model between carbon emission values and orders, plan the orders and optimize the processing of carbon emissions.

[0047] Further, the process of planning the orders and optimizing the processing of carbon emissions according to the established relationship model between carbon emission values and orders is as follows:

[0048] When the direct actual carbon emission value is within the quarterly preset direct carbon emission threshold, according to the modified next-quarter preset threshold A, use the established relationship model between carbon emission values and orders to obtain the order quantity data A1 arranged for the next quarter;

[0049] When the direct actual carbon emission value exceeds the quarterly preset direct carbon emission threshold and is caused by an increase in the order quantity, substitute the modified direct carbon emission limit threshold B for the next quarter into the established relationship model between carbon emission values and orders to obtain the order quantity data B1 arranged for the next quarter; when the direct actual carbon emission value exceeds the quarterly preset direct carbon emission threshold and is caused by equipment operation, arrange the order quantity data B1 for the next quarter to normal equipment.

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

[0051] S1. Collect the order data, fuel consumption data, and power consumption data within a quarter of the enterprise;

[0052] S2. Calculate the carbon emission data;

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

[0054] S4. When it is lower than the quarterly threshold, analyze and predict the error between the carbon emission and the actual carbon emission, which is used to correct the carbon emission prediction value for the next quarter, and further adjust the direct carbon emission and indirect carbon emission limit thresholds for the next quarter respectively;

[0055] S5. When it is higher than the quarterly threshold, analyze the reason for the increase in carbon emissions. When the reason for the increase is related to the order quantity, reduce the direct carbon emission limit threshold and the indirect carbon emission limit threshold for the next quarter respectively. When the reason for the increase is related to the equipment operation efficiency, combine the equipment operation parameters to determine the problem equipment;

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

[0057] An analysis device for carbon emissions, including a memory and a processor, and a computer program capable of being loaded and executed by the processor for the above-mentioned system is stored on the memory;

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

[0059] Compared with the prior art, the beneficial effects of the present invention are as follows:

[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 respectively 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 emission values, and are used to correct the predicted carbon emission values for the next quarter. Thus, not only can the predicted carbon emission data be made more accurate, but also the preset thresholds for the next quarter modified according to the predicted values can be more in line with the actual situation;

[0061] When the direct carbon emissions and indirect carbon emissions exceed the preset threshold range, analyze the reasons for the excess carbon emissions. When the reason for the excess direct carbon emissions is due to the order quantity, it indicates that the equipment is operating normally, and the excess indirect carbon emissions are also due to the order quantity. Thus, reduce the quarterly direct carbon emission limit threshold and the quarterly indirect carbon emission limit threshold. When the excess carbon emissions are due to equipment problems, combine the received equipment data to identify the problem equipment;

[0062] 2. By establishing a relationship model between carbon emission values and orders, the present invention can facilitate the planning of subsequent orders, and at the same time can also simplify the calculation steps of carbon emissions. The carbon emission data can be quickly obtained through the obtained order quantity;

[0063] By calculating the relationship model between carbon emission values and orders established by the present invention and the preset carbon emission values, the order arrangement quantity for the next quarter can be obtained, enabling the enterprise to make full use of resources on the premise of meeting the carbon emission requirements, avoiding the problem of excessive carbon emissions caused by overproduction. In addition, through the accurate order arrangement, 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 is the process of carbon emission analysis of the present invention Figure 1 ;

[0066] Figure 3 is the process of carbon emission analysis of the present invention Figure 2 。 DETAILED DESCRIPTION OF THE INVENTION

[0067] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

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

[0069] The data acquisition module is used to collect the order data, fuel consumption data, equipment operation parameters, and power consumption data of the enterprise within a quarter;

[0070] The carbon emission calculation and analysis module is used to calculate the direct actual carbon emission value and the indirect actual carbon emission value, 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 range, further analyze the error between the actual carbon emission value and the carbon emission prediction value, use it to correct the carbon emission prediction value, and modify the carbon emission threshold for the next quarter accordingly;

[0071] In this embodiment, the carbon emission calculation and analysis module is used to calculate the direct actual carbon emission value and the indirect actual carbon emission value, 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 range, further analyze the error between the actual carbon emission value and the carbon emission prediction value, use it to correct the carbon emission prediction value, and modify the carbon emission threshold for the next quarter. The process is as follows:

[0072] It is used to calculate the direct actual carbon emission value and the indirect actual carbon emission value, 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 range, further analyze the error between the actual carbon emission value and the carbon emission prediction value, use it to correct the carbon emission prediction value, and finally use the corrected carbon emission prediction value combined with the exponential smoothing method to dynamically adjust the direct carbon emission limit threshold A for the next quarter and the indirect carbon emission limit threshold C for the next quarter;

[0073] In this embodiment, the process of dynamically adjusting the direct carbon emission limit threshold A for the next quarter and the indirect carbon emission limit threshold C for the next quarter by combining the corrected carbon emission prediction value with the exponential smoothing method is as follows:

[0074] Combine the corrected quarterly direct carbon emission prediction value with exponential smoothing to dynamically adjust the direct carbon emission limit threshold A for the next quarter. The specific formula is:

[0075] A = α·F1+(1 - α)·A t ;

[0076] Where F1 is the corrected quarterly direct carbon emission prediction value, and 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 importance of the corrected direct carbon emission prediction value F1 and the direct carbon emission limit threshold A for the current quarter t in the calculation of the limit threshold for the next quarter;

[0077] Combine the corrected quarterly indirect carbon emission prediction value with exponential smoothing to dynamically adjust the indirect carbon emission limit threshold C for the next quarter. The specific formula is:

[0078] C = β·F2+(1 - β)·C t ;

[0079] Where F2 is the corrected quarterly indirect carbon emission prediction value, and 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 importance of the corrected indirect carbon emission prediction value F2 and the direct carbon emission limit threshold C for the current quarter t in the calculation of the limit threshold for the next quarter.

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

[0081] If the direct actual carbon emission exceeds the quarterly preset direct carbon emission threshold or the total indirect carbon emission exceeds the quarterly preset indirect carbon emission threshold, further analyze the reasons for the carbon emission over - standard.

[0082] In this embodiment, when the direct actual carbon emission exceeds the quarterly preset direct carbon emission threshold, or when the total indirect carbon emission exceeds the quarterly preset indirect carbon emission threshold, the process of further analyzing the reasons for the carbon emission over - standard is as follows:

[0083] When the direct actual carbon emissions exceed the quarterly preset direct carbon emissions threshold, calculate the direct projected carbon emissions based on the information of all orders within the quarter. The specific formula is as follows:

[0084]

[0085] Among them, E n1 is the calculated direct projected carbon emissions, F1 k is the projected consumption of the kth fuel, C k is the carbon emission coefficient of the kth fuel, and m is the number of fuel types;

[0086] Calculate the direct actual carbon emissions. The specific formula is as follows:

[0087]

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

[0089] When the total indirect carbon emissions exceed the quarterly preset indirect carbon emissions threshold, calculate the indirect projected emissions. The specific formula is as follows:

[0090] E a = A1·EF;

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

[0092] Calculate the indirect actual carbon emissions. The specific formula is as follows:

[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. When the difference between the actual data and the calculated data is within ±5% - ±10%, it indicates that the difference is normal and the carbon emissions data exceeds the standard due to the increase in the number of orders. Calculate the specific deviation and reduce the direct carbon emissions limit threshold B for the next quarter according to 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 existing single operating equipment of the enterprise, and compare the calculated energy conversion efficiency with the preset conversion efficiency. When the equipment efficiency deviation ≥ 15%, it indicates that there is a problem with the equipment conversion efficiency. At this time, combine the equipment operation parameters including temperature and power to determine the problematic equipment;

[0097] When both the direct carbon emissions and the indirect carbon emissions exceed the standard and the direct carbon emissions exceed the standard due to an increase in orders, directly determine that the reason for the excess of indirect carbon emissions is the increase in orders, calculate the specific deviation of the indirect carbon emissions, calculate the specific deviation, and reduce the threshold value of the indirect carbon emission limit for the next quarter according to the deviation; when the direct carbon emissions exceed the standard due to the equipment conversion efficiency, directly determine that the reason for the excess of the direct and indirect carbon emissions is the equipment problem. When the indirect carbon emissions exceed the standard and the direct carbon emissions do not exceed the standard, further analyze the electricity carbon emissions and the process carbon emissions, and optimize the production process according to the analysis results, and reduce the threshold value of the indirect carbon emission limit for the next quarter.

[0098] It should be noted that the specific steps to determine the problematic equipment are as follows:

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

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

[0101] It should be noted that after the end of the first quarter, the enterprise statistically calculated that the direct actual carbon emissions were 530 tons of carbon dioxide equivalent, exceeding the preset threshold range of 500 tons. Obtain the order data and fuel consumption data for the first quarter. The number of orders in the first quarter increased by 20% compared with the expected value, and the fuel consumption also increased accordingly. Compare the actual carbon emission value with the calculated carbon emission value and find that the difference is within ±8%. This indicates that the excess carbon emission data is caused by the increase in the number of orders. Further calculate the specific deviation:

[0102] (530 - 500) ÷ 500 × 100% = 6%;

[0103] Reduce 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 emission in the second quarter is 450 tons of carbon dioxide equivalent, which is within the quarterly threshold of 470 tons. Further analyze the values of the direct actual carbon emission and the predicted carbon emission, and obtain the data of multiple order amounts and fuel consumption within the second quarter. The correction parameter for the actual emission and the predicted emission obtained from multiple orders is 0.95. Use the obtained correction parameter to correct the carbon emission prediction value for the third quarter; According to the predicted carbon emission in the third quarter being 520 tons of carbon dioxide equivalent, calculate the corrected carbon dioxide equivalent:

[0105] 520×0.95 = 494 (tons);

[0106] Adjust the carbon emission limit threshold for the third quarter to 494 tons of carbon dioxide equivalent, and the direct actual carbon emission in the third quarter is 480 tons of carbon dioxide equivalent, which is within the quarterly threshold of 494 tons. Finally, repeat the steps of the second quarter, obtain the correction parameter again and correct the carbon emission prediction value and the limit threshold for the fourth quarter;

[0107] After three quarters of implementation, when the enterprise conducts an assessment in the fourth quarter, it is found that the quarterly carbon emission prediction error has decreased from the initial ±15% to ±5%. This indicates that the system can effectively make dynamic adjustments and corrections according to the direct actual carbon emission situation, improve the accuracy of carbon emission prediction, and help the enterprise better manage carbon emissions and carry out emission reduction work;

[0108] Substitute the carbon emission limit threshold for the third quarter into this model, and the order quantity data A1 arranged for the third quarter is 800 orders. Similarly, substitute the direct carbon emission limit threshold B for the second quarter into the relationship model between carbon emission values and orders, and the order quantity data B1 arranged for the second quarter is 750 orders. And the direct actual carbon emission in this quarter exceeds the threshold. After analysis, it is caused by equipment operation problems. Using the same number of production equipment, since the energy conversion efficiency of normal equipment is higher, it is expected that the carbon emission will be reduced by 20%.

[0109] Order and carbon emission association module. When the actual value is within the quarterly preset direct carbon emission threshold range, associate the order data with the carbon emission value, establish a relationship model between the carbon emission value and the order, and plan the order according to the established relationship model between the carbon emission value and the order to optimize the carbon emission;

[0110] In this embodiment, for the order and carbon emission association module, when the actual value is within the range of the quarterly preset direct carbon emission threshold, the order data is associated with the carbon emission value, a relationship model between the carbon emission value and the order is established, and based on the established relationship model between the carbon emission value and the order, the order is planned, and the process of optimizing the carbon emission processing is as follows:

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

[0112] y = β0 + β1x + e;

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

[0114] Estimate the parameters β0 and β1 by the least squares method, and the specific formula is as follows:

[0115]

[0116] A non-linear relationship exists between the single order quantity x and the carbon emission value y, and the specific formula is:

[0117]

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

[0119] It should be noted that for the order of the polynomial regression, first randomly divide the original data set into k non-overlapping subsets, and for each order n, perform k iterations. In each iteration, select k - 1 subsets as the training set, and the remaining one subset as the validation set. Use the training set to train the nth-order polynomial regression model, and then calculate the mean square error MSE on the validation set. Take the average of the errors of the k iterations to obtain the cross-validation error of the polynomial model of this order. Finally, select the order with the smallest cross-validation error as the final polynomial order.

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

[0121] It should be noted that linear models and non-linear models of the relationship between orders and emissions are established. The linear model is applicable to situations where the production process is relatively stable and the input-output relationships of various production factors are relatively fixed. The non-linear model is applicable to situations where the change in the order volume shows complex patterns, such as seasonal fluctuations, periodic changes, or being affected by a combination of multiple factors.

[0122] According to the established relationship model between carbon emission values and orders, plan the orders and optimize the carbon emission processing.

[0123] In this embodiment, according to the established relationship model between carbon emission values and orders, the process of planning the orders and optimizing the carbon emission processing is as follows:

[0124] When the direct actual carbon emission value is within the quarterly preset direct carbon emission threshold, according to the modified next-quarter preset threshold A, use the established relationship model between carbon emission values and orders to obtain the order volume data A1 arranged for the next quarter;

[0125] When the direct actual carbon emission value exceeds the quarterly preset direct carbon emission threshold and is caused by an increase in the order quantity, substitute the modified direct carbon emission limit threshold B for the next quarter into the established relationship model between carbon emission values and orders to obtain the order volume data B1 arranged for the next quarter; when the direct actual carbon emission value exceeds the quarterly preset direct carbon emission threshold and is caused by equipment operation, arrange the order volume data B1 for the next quarter to normal equipment.

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

[0127] It should be noted that the equipment operation efficiency will cause energy waste and increase energy consumption. The additional consumed energy will significantly increase the carbon emissions. Therefore, using equipment with normal operation efficiency to process orders can reduce carbon emissions, thereby optimizing the carbon emissions.

[0128] An analysis device for carbon emissions includes a memory and a processor. A computer program capable of being loaded and executed by the processor is stored on the memory and can implement any one of the above systems.

[0129] A computer storage medium stores a computer program capable of being loaded and executed by the processor and can implement any one of the above systems.

[0130] In summary, 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 respectively within their carbon emission thresholds, the direct actual carbon emissions and indirect actual carbon emissions are further compared and analyzed with the quarterly predicted carbon emission values, and are used to correct the predicted carbon emission values for the next quarter. Thus, not only can the predicted carbon emission data be made more accurate, but also the preset thresholds for the next quarter modified according to the predicted values can be more in line with the actual situation; when the direct carbon emissions and indirect carbon emissions exceed the preset threshold range, the reasons for the excess carbon emissions are analyzed. When the reason for the excess direct carbon emissions is due to the order quantity, it indicates that the equipment operation state is normal, and the excess indirect carbon emissions are also due to the order quantity. Thus, the quarterly direct carbon emission limit threshold and the quarterly indirect carbon emission limit threshold are reduced. When the excess carbon emissions are caused by equipment problems, the problem equipment is identified in combination with the received equipment data; by establishing a relationship model between the carbon emission value and the order, the present invention can facilitate the planning of subsequent orders, and at the same time can also simplify the calculation steps of carbon emissions. The carbon emission data can be quickly obtained through the obtained order quantity; by calculating the relationship model between the carbon emission value and the order and the preset carbon emission value, the present invention can obtain the order arrangement quantity for the next quarter, enabling the enterprise to make full use of resources on the premise of meeting the carbon emission requirements and avoid the problem of excessive carbon emissions caused by overproduction. In addition, through the precise order arrangement, the production process can also be effectively optimized.

[0131] In the embodiments provided by the present invention, it should be understood that the disclosed equipment, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of modules is only a logical function division, and there may be other division methods in actual implementation; the modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the method of this embodiment.

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

Claims

1. A carbon emission analysis system, characterized in that: It includes a data collection module, a carbon emission calculation and analysis module, an order and carbon emission association module, and a carbon emission optimization module, wherein the data collection 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 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, further analyze the error between the actual carbon emission value and the carbon emission forecast value to correct the carbon emission forecast value, and modify the carbon emission threshold for the next quarter accordingly; 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 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 value of the next quarter is modified accordingly. The process is as follows: It 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, further analyze the error between the actual carbon emission value and the carbon emission forecast value, and use it to correct the carbon emission forecast value. Finally, use the corrected carbon emission forecast value combined with the exponential smoothing method to dynamically adjust the next quarter's direct carbon emission limit threshold A and the next quarter's indirect carbon emission limit threshold C; If the actual direct carbon emissions exceed the quarterly preset direct carbon emissions threshold or the total indirect carbon emissions exceed the quarterly preset indirect carbon emissions threshold, further analysis will be conducted on the reasons for the excessive carbon emissions.

3. A carbon emission analysis system according to claim 2, characterized in that: 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: 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: A=α·F1+(1-α)·A t ; 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 The importance of the quota threshold calculation for the next quarter; The revised quarterly indirect carbon emission forecast value is combined with exponential smoothing to dynamically adjust the next quarter's indirect carbon emission limit threshold C. The specific formula is: C=β·F2+(1-β)·C t ; 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.

4. A carbon emission analysis system according to claim 2, characterized in that: 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 reasons for the excessive carbon emissions is as follows: When the direct actual carbon emissions exceed the preset direct carbon emissions threshold for the quarter, the direct estimated carbon emissions are calculated based on the information of all orders collected in the quarter. The specific formula is: Among them, E n1 F1 is the direct estimated carbon emissions after calculation. k is the expected consumption of the kth fuel, C k is the carbon emission coefficient of the kth fuel, and m is the number of fuel types; Calculate direct actual carbon emissions, the specific formula is: 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, and m is the number of fuel types; When the total amount of indirect carbon emissions exceeds the quarterly preset indirect carbon emissions threshold, the indirect estimated emissions are calculated using the following formula: E a =A1·EF; Among them, E a is the indirect estimated carbon emissions after calculation, A1 is the estimated electricity consumption, and EF is the electricity emission factor; To calculate indirect actual carbon emissions, the specific formula is: <h2 style=";text-align:left;direction:ltr">E<h2 style=";text-align:left;direction:ltr"> b <h2 style=";text-align:left;direction:ltr"> (A2 EF) Among them, E b is the calculated indirect actual carbon emissions, A2 is the actual electricity consumption, and EF is the electricity emission factor; Compare the actual carbon emission value with the calculated carbon emission value. When the difference between the actual data and the calculated data is within ±5%-±10%, it means that the difference is normal and the carbon emission data exceeds the standard due to the increase in the number of orders. Calculate the specific deviation and reduce the direct carbon emission 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 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; When both direct carbon emissions and indirect carbon emissions exceed the standard and the excess of direct carbon emissions is caused by an increase in orders, the cause of the excess of indirect carbon emissions is directly determined to be an increase in orders, and the specific deviation of the indirect carbon emissions is calculated. The specific deviation is calculated, and the indirect carbon emissions limit threshold for the next quarter is lowered based on the deviation; when the excess of direct carbon emissions is caused by equipment conversion efficiency, the cause of the excess of direct and indirect carbon emissions is determined to be equipment problems. When indirect carbon emissions exceed the standard and direct carbon emissions do not exceed the standard, further analyze the electricity carbon emissions and process carbon emissions, optimize the production process based on the analysis results, and lower the indirect carbon emissions limit threshold for the next quarter.

5. 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: A linear relationship is established between the single order quantity x and the carbon emission value y. The specific formula is: y=β0+β1x+e; Among them, β0 is the intercept, β1 is the slope, and e is the random error term; The parameters β0 and β1 are estimated by the least squares method. The specific formula is as follows: A nonlinear relationship is established between the single order quantity x and the carbon emission value y. The specific formula is: Among them, β0 is the intercept, β1 is the first-order coefficient, which reflects the linear change of carbon emission 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; Based on the established model of the relationship between carbon emission values ​​and orders, orders are planned and carbon emission processing is optimized.

6. A carbon emission analysis system according to claim 5, characterized in that: According to the established relationship model between carbon emission values ​​and orders, the order is planned and the carbon emission processing process is optimized as follows: When the direct actual carbon emission value is within the quarterly preset direct carbon emission threshold, the preset threshold value A for the next quarter is modified, and the established relationship model between carbon emission value and order 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 is 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 arranged to normal equipment.

7. 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 emission data; S3. Compare the direct actual carbon emissions data and indirect carbon emissions data with their respective quarterly thresholds; S4. When it is lower than the quarterly threshold, the error between the predicted carbon emissions and the actual carbon emissions is analyzed to correct the predicted carbon emissions value for the next quarter, and further adjust the limit thresholds of direct carbon emissions and indirect carbon emissions for the next quarter respectively; S5. When it is higher than the quarterly threshold, analyze the reasons for the increase in carbon emissions. When the reason for the increase is related to the number of orders, reduce the direct carbon emission limit threshold and indirect carbon emission limit threshold for the next quarter respectively. When the reason for the increase is related to the equipment operating efficiency, identify the problematic equipment in combination with the equipment operating parameters; S6. Establish the relationship between order quantity and emission data, and obtain the order data for the next quarter based on the direct carbon emission limit threshold for the next quarter to optimize carbon emissions.

8. An analytical device for carbon emissions, characterized in that: 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 6.

9. A computer storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the system as claimed in any one of claims 1 to 6.

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