Carbon accounting amount calculation method for industrial production

Abstract

The invention discloses a carbon accounting amount calculation method for industrial production, and belongs to the technical field of industrial production, and the method comprises the following steps: S1, data collection and processing: collecting and processing industrial production carbon emission monitoring real-time data; s2, model construction and optimization: constructing and optimizing an industrial production carbon accounting amount calculation model, and determining an optimal industrial production carbon accounting amount calculation model; and S3, carbon accounting amount calculation: calculating the industrial production carbon accounting amount according to the optimal industrial production carbon accounting amount calculation model, and determining an industrial production carbon accounting amount calculation result. According to the invention, the problems that the carbon accounting amount of industrial production cannot be calculated, the carbon emission condition of industrial production cannot be known and managed in time, and the carbon emission management effect of industrial production is poor are solved. According to the invention, the carbon accounting amount of industrial production can be effectively calculated, the carbon emission condition of industrial production can be known in time, the carbon emission can be managed in time, and the carbon emission management effect of industrial production can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial production, and in particular to a method for calculating carbon accounting amount for industrial production. Background Art

[0002] Industrial production is mainly carried out in factories, where the labor force uses power (fuel, electricity) and mechanical equipment to turn raw materials into products. One raw material can produce different products, and one product may be processed, assembled or combined from multiple raw materials. Among them, industrial production activities will directly and indirectly emit carbon dioxide and its equivalent gases into the atmosphere, which requires carbon accounting calculations. Among them, carbon emission accounting is the basic prerequisite for effectively carrying out various carbon emission reduction tasks and promoting the green transformation of the economy, and is an important support for actively participating in international negotiations on climate change.

[0003] The Chinese patent with publication number CN116298093A discloses a detection system and method for greenhouse gas emissions from industrial production, including a chimney, a uniformly distributed exhaust pipe fixedly connected to the outside of the chimney, a gas concentration sensor fixedly connected to the inside of the exhaust pipe, a top tube fixedly connected to the top of the chimney, a motor arranged inside the top tube, a threaded rod fixedly connected to the end of the motor main shaft, a threaded sleeve spirally connected to the outside of the threaded rod, a fixed sleeve fixedly connected to the outside of the threaded sleeve, a support rod fixedly connected to the outside of the fixed sleeve, and a retaining cylinder fixedly connected to the other end of the support rod; in rainy weather, the motor is continuously started, the motor moves downward, the upper unit exhaust device is in close contact with the lower unit exhaust device, the upper unit exhaust hole is staggered with the lower unit exhaust hole, to ensure that external rainwater is not easy to fall, to ensure that greenhouse gases are discharged through the exhaust pipe, and the gas concentration sensor inside the exhaust pipe can accurately detect the concentration of greenhouse gases; however, the patent has the following defects:

[0004] The existing inability to effectively calculate carbon accounting for industrial production makes it impossible to timely understand the carbon emissions of industrial production and to manage them in a timely manner, resulting in poor results in carbon emissions management for industrial production. Summary of the invention

[0005] The purpose of the present invention is to provide a method for calculating the carbon accounting amount for industrial production, which can effectively calculate the carbon accounting amount for industrial production, timely understand the carbon emissions of industrial production, manage them in a timely manner, improve the carbon emission management effect of industrial production, and solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A method for calculating carbon accounting for industrial production, comprising the following steps:

[0008] S1. Data collection and processing:

[0009] Collect real-time data on industrial production carbon emission monitoring, process the real-time data on industrial production carbon emission monitoring, and determine characteristic data on industrial production carbon emission monitoring;

[0010] S2. Model construction and optimization:

[0011] Construct an industrial production carbon accounting calculation model based on deep learning, optimize the industrial production carbon accounting calculation model based on deep learning, and determine the optimal industrial production carbon accounting calculation model based on deep learning;

[0012] S3. Calculation of carbon accounting amount:

[0013] According to the optimal industrial production carbon accounting calculation model based on deep learning, the industrial production carbon emission monitoring feature data is mined and analyzed, the industrial production carbon accounting amount is calculated, the industrial production carbon accounting amount calculation results based on deep learning are determined, and the industrial production carbon accounting amount calculation report is transmitted to industrial production managers in a visual form.

[0014] Preferably, in S1, real-time data of industrial production carbon emission monitoring is collected, and the following operations are performed:

[0015] Continuously monitor and collect real-time data on the concentration of carbon dioxide and its equivalent gases emitted directly and indirectly into the atmosphere during fossil fuel combustion, electricity consumption, and heat consumption in industrial production activities to obtain data on industrial production carbon emission concentrations;

[0016] Continuously monitor and collect real-time data on the flow rate of carbon dioxide and its equivalent gases emitted directly and indirectly into the atmosphere during fossil fuel combustion, electricity consumption, and heat consumption in industrial production activities, and obtain data on the flow rate of industrial production carbon emissions;

[0017] Among them, the real-time data of industrial production carbon emission monitoring is determined based on the industrial production carbon emission concentration data and the industrial production carbon emission flow rate data.

[0018] Preferably, in S1, collecting real-time data on industrial production carbon emissions monitoring also includes:

[0019] Extract the concentration ratio value of carbon dioxide monitored in real time;

[0020] Obtaining a concentration index parameter of carbon dioxide according to the carbon dioxide concentration ratio value;

[0021] The concentration index parameter of carbon dioxide is obtained by the following formula:

[0022]

[0023] Where S represents the concentration index parameter of carbon dioxide; n represents the number of data collection times of carbon dioxide concentration; P ci Indicates the concentration ratio of carbon dioxide corresponding to the i-th concentration data collection; P ck Indicates the preset reference value of carbon dioxide concentration ratio; P cmax and P cmin Indicates the maximum and minimum values ​​of the carbon dioxide concentration ratio during the n-time data collection process; P cz It represents the middle value of the carbon dioxide concentration ratio during the n-time data collection process;

[0024] Comparing the concentration index parameter of the carbon dioxide with a preset concentration index parameter threshold;

[0025] When the concentration index parameter of carbon dioxide exceeds the preset concentration index parameter threshold, the data collection frequency of the flow rate of carbon dioxide and its equivalent gas is adjusted.

[0026] Preferably, when the concentration index parameter of carbon dioxide exceeds the preset concentration index parameter threshold, the data collection frequency of the flow rate of carbon dioxide and its equivalent gas is adjusted, including:

[0027] When the concentration index parameter of the carbon dioxide exceeds the preset concentration index parameter threshold, extracting the current flow rate of the carbon dioxide and its equivalent gas;

[0028] Extract the flow rate data corresponding to carbon dioxide in the historical detection records;

[0029] Retrieve the data collection frequency of the current flow rate of carbon dioxide and its equivalent gas;

[0030] Adjusting the data collection frequency of the current flow rate of carbon dioxide and its equivalent gas according to the current flow rate of carbon dioxide and its equivalent gas and the flow rate data corresponding to carbon dioxide in combination with the concentration index parameter of carbon dioxide;

[0031] Among them, the data collection frequency of the adjusted flow rate is obtained by the following formula:

[0032]

[0033] Wherein, F represents the data collection frequency of the flow rate after adjustment; f represents the data collection frequency of the flow rate before adjustment; S represents the concentration index parameter of carbon dioxide; S y Indicates the preset concentration index parameter threshold; V b represents the flow rate standard deviation corresponding to the flow rate data corresponding to carbon dioxide in the historical detection records except the current flow rate of carbon dioxide and its equivalent gas; V sIndicates the current flow rate of carbon dioxide and its equivalent gas; V ck Indicates the preset reference value of the flow rate of carbon dioxide; V max and V min It indicates the flow rate corresponding to the maximum and minimum values ​​of the carbon dioxide concentration ratio during the n-time data collection process.

[0034] Preferably, in S1, the real-time data of industrial production carbon emission monitoring is processed to perform the following operations:

[0035] Obtain real-time data on industrial production carbon emissions monitoring;

[0036] Clean and process the real-time data of industrial production carbon emission monitoring, including:

[0037] Conduct consistency checks on real-time data on industrial production carbon emissions monitoring;

[0038] Check whether the real-time data of industrial production carbon emission monitoring meets the requirements according to the reasonable value range and mutual relationship of each parameter in the real-time data of industrial production carbon emission monitoring;

[0039] Remove inconsistent data that is beyond the normal range, logically unreasonable or contradictory in the real-time data of industrial production carbon emission monitoring;

[0040] Process invalid and missing values ​​of real-time data of industrial production carbon emission monitoring;

[0041] According to the calculation requirements of carbon accounting for industrial production, the real-time data of industrial production carbon emission monitoring are checked one by one to determine whether there are invalid values ​​and missing values ​​in the real-time data of industrial production carbon emission monitoring;

[0042] Remove invalid values ​​and missing values ​​in the real-time data of industrial production carbon emission monitoring that are useless for calculating the carbon accounting amount used in industrial production;

[0043] Determine real-time data on industrial production carbon emissions monitoring that is useful for industrial production carbon accounting calculations.

[0044] Preferably, in S1, the real-time data of industrial production carbon emission monitoring is processed, and the following operations are further performed:

[0045] Obtain real-time data on industrial production carbon emissions monitoring that is useful for calculating carbon accounting for industrial production;

[0046] Convert and process the real-time data of industrial production carbon emission monitoring that is useful for calculating the carbon accounting amount for industrial production, and eliminate the dimensional differences between the real-time data of industrial production carbon emission monitoring;

[0047] Determine standardized real-time data for industrial production carbon emissions monitoring;

[0048] Extract features from standardized real-time data of industrial production carbon emission monitoring;

[0049] Extract features that reflect the calculation of carbon accounting for industrial production;

[0050] Determine the characteristic data for industrial production carbon emission monitoring.

[0051] Preferably, in S2, a deep learning-based industrial production carbon accounting calculation model is constructed, and the following operations are performed:

[0052] Collect historical data on industrial production carbon emissions monitoring based on the calculation requirements of industrial production carbon accounting;

[0053] Divide the historical data of industrial production carbon emission monitoring to determine the training set and test set for carbon accounting calculation;

[0054] Select a convolutional neural network model framework suitable for calculating carbon accounting for industrial production;

[0055] Based on the carbon accounting calculation training set, the selected convolutional neural network model framework suitable for carbon accounting calculation for industrial production is trained;

[0056] A deep learning-based calculation model for industrial production carbon accounting was determined.

[0057] Preferably, in S2, the industrial production carbon accounting calculation model based on deep learning is optimized, and the following operations are performed:

[0058] Obtain a deep learning-based industrial production carbon accounting calculation model;

[0059] Based on the carbon accounting calculation test set, the performance test and evaluation of the industrial production carbon accounting calculation model based on deep learning was carried out;

[0060] Determine the performance test evaluation results based on the industrial production carbon accounting calculation model;

[0061] According to the performance test evaluation results of the industrial production carbon accounting calculation model, the industrial production carbon accounting calculation model based on deep learning is mined and analyzed;

[0062] Determine the parameter adjustment optimization scheme based on the industrial production carbon accounting calculation model;

[0063] According to the parameter adjustment optimization scheme based on the industrial production carbon accounting calculation model, the parameters of the industrial production carbon accounting calculation model based on deep learning are adjusted and optimized;

[0064] Determine the optimal deep learning-based industrial production carbon accounting calculation model.

[0065] Preferably, in S3, the characteristic data of industrial production carbon emission monitoring are mined and analyzed to calculate the industrial production carbon accounting amount, and the following operations are performed:

[0066] Obtaining industrial production carbon emission monitoring characteristic data;

[0067] Input the industrial production carbon emission monitoring characteristic data into the optimal industrial production carbon accounting calculation model based on deep learning;

[0068] According to the optimal industrial production carbon accounting calculation model based on deep learning, the industrial production carbon emission monitoring feature data is mined and analyzed to calculate the industrial production carbon accounting amount;

[0069] Determine the calculation results of industrial production carbon accounting based on deep learning.

[0070] Preferably, in S3, the industrial production carbon accounting amount calculation report is transmitted to the industrial production management personnel in a visual form, and the following operations are performed:

[0071] Obtain the calculation results of industrial production carbon accounting based on deep learning;

[0072] Generate an industrial production carbon accounting calculation report based on the industrial production carbon accounting calculation results based on deep learning and combined with the industrial production carbon emission monitoring characteristic data;

[0073] The industrial production carbon accounting calculation report is transmitted to the industrial production management personnel in a visual form, so that the industrial production management personnel can make timely adjustments and management of the industrial production carbon emissions based on the industrial production carbon accounting calculation report.

[0074] Compared with the prior art, the present invention has the following beneficial effects:

[0075] The present invention collects real-time data of industrial production carbon emission monitoring, processes the real-time data of industrial production carbon emission monitoring, determines the characteristic data of industrial production carbon emission monitoring, and constructs an industrial production carbon accounting amount calculation model based on deep learning according to the calculation requirements of industrial production carbon accounting amount. By optimizing the industrial production carbon accounting amount calculation model based on deep learning, the optimal industrial production carbon accounting amount calculation model based on deep learning is determined. According to the optimal industrial production carbon accounting amount calculation model based on deep learning, the characteristic data of industrial production carbon emission monitoring are mined and analyzed to calculate the industrial production carbon accounting amount, determine the calculation result of the industrial production carbon accounting amount based on deep learning, and generate an industrial production carbon accounting amount calculation report. The industrial production carbon accounting amount calculation report is transmitted to industrial production management personnel in a visual form, so that the industrial production management personnel can make timely adjustments and management of the industrial production carbon emission situation, can effectively calculate the carbon accounting amount of industrial production, can timely understand the industrial production carbon emission situation, can timely manage it, and can improve the industrial production carbon emission management effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 The present invention is a flow chart of the method for calculating the carbon accounting amount for industrial production. DETAILED DESCRIPTION

[0077] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0078] In order to solve the existing problem of inability to effectively calculate carbon emissions from industrial production, which makes it impossible to timely understand the carbon emissions from industrial production and manage them in a timely manner, resulting in poor management effects of industrial carbon emissions, please refer to Figure 1 , this embodiment provides the following technical solutions:

[0079] A method for calculating carbon accounting for industrial production, comprising the following steps:

[0080] S1. Data collection and processing:

[0081] Collect real-time data on industrial production carbon emission monitoring, process the real-time data on industrial production carbon emission monitoring, and determine characteristic data on industrial production carbon emission monitoring;

[0082] In this embodiment, real-time data of industrial production carbon emission monitoring is collected, and the following operations are performed:

[0083] Continuously monitor and collect real-time data on the concentration of carbon dioxide and its equivalent gases emitted directly and indirectly into the atmosphere during fossil fuel combustion, electricity consumption, and heat consumption in industrial production activities to obtain data on industrial production carbon emission concentrations;

[0084] Continuously monitor and collect real-time data on the flow rate of carbon dioxide and its equivalent gases emitted directly and indirectly into the atmosphere during fossil fuel combustion, electricity consumption, and heat consumption in industrial production activities, and obtain data on the flow rate of industrial production carbon emissions;

[0085] Among them, the real-time data of industrial production carbon emission monitoring is determined based on the industrial production carbon emission concentration data and the industrial production carbon emission flow rate data.

[0086] Specifically, in S1, collecting real-time data on industrial production carbon emissions monitoring also includes:

[0087] Extract the concentration ratio value of carbon dioxide monitored in real time;

[0088] Obtaining a concentration index parameter of carbon dioxide according to the carbon dioxide concentration ratio value;

[0089] The concentration index parameter of carbon dioxide is obtained by the following formula:

[0090]

[0091] Where S represents the concentration index parameter of carbon dioxide; n represents the number of data collection times of carbon dioxide concentration; P ci Indicates the concentration ratio of carbon dioxide corresponding to the i-th concentration data collection; P ck Indicates the preset reference value of carbon dioxide concentration ratio; P cmax and P cmin Indicates the maximum and minimum values ​​of the carbon dioxide concentration ratio during the n-time data collection process; P cz It represents the middle value of the carbon dioxide concentration ratio during the n-time data collection process;

[0092] Comparing the concentration index parameter of the carbon dioxide with a preset concentration index parameter threshold;

[0093] When the concentration index parameter of carbon dioxide exceeds the preset concentration index parameter threshold, the data collection frequency of the flow rate of carbon dioxide and its equivalent gas is adjusted.

[0094] The technical effect of the above technical solution is: by real-time monitoring of the concentration ratio of carbon dioxide, the solution can instantly obtain the carbon emissions in the production process, which is crucial for timely responding to environmental changes and taking corresponding measures. The extracted concentration index parameter is obtained by the above calculation formula, which takes into account multiple factors such as the number of data collection, the concentration value collected each time, the preset reference value, the maximum value, the minimum value and the intermediate value, thereby improving the accuracy and representativeness of the data. The solution includes a step of comparing the calculated carbon dioxide concentration index parameter with the preset threshold value, which provides a basis for dynamic monitoring and management. When the concentration index parameter exceeds the preset threshold value, the solution can automatically adjust the frequency of data collection of the flow rate of carbon dioxide and its equivalent gas, which means that when the emission is abnormal or the potential risk increases, the system can collect data more frequently to more accurately assess the emission situation and take corresponding emission reduction measures. Through precise monitoring and dynamic adjustment, the solution helps enterprises to detect abnormal carbon emissions in a timely manner, so as to take effective measures to reduce unnecessary emissions, which is of great significance for achieving environmental protection and energy conservation and emission reduction goals. Long-term precise monitoring and dynamic management can also help enterprises optimize production processes and procedures, improve energy efficiency and reduce resource waste. The solution achieves intelligent processing and analysis of carbon emission data through calculation formulas and preset threshold settings, reducing the need for manual intervention and judgment. The function of automatically adjusting the frequency of data collection also improves work efficiency and response speed, allowing enterprises to manage carbon emissions more efficiently.

[0095] In summary, this technical solution provides a comprehensive and effective means of monitoring carbon emissions in industrial production processes through real-time monitoring, precise calculation, dynamic adjustment and intelligent management, which helps enterprises achieve the goals of environmental protection, energy conservation and emission reduction, and sustainable development.

[0096] Specifically, when the concentration index parameter of carbon dioxide exceeds the preset concentration index parameter threshold, the data collection frequency of the flow rate of carbon dioxide and its equivalent gas is adjusted, including:

[0097] When the concentration index parameter of the carbon dioxide exceeds the preset concentration index parameter threshold, extracting the current flow rate of the carbon dioxide and its equivalent gas;

[0098] Extract the flow rate data corresponding to carbon dioxide in the historical detection records;

[0099] Retrieve the data collection frequency of the current flow rate of carbon dioxide and its equivalent gas;

[0100] Adjusting the data collection frequency of the current flow rate of carbon dioxide and its equivalent gas according to the current flow rate of carbon dioxide and its equivalent gas and the flow rate data corresponding to carbon dioxide in combination with the concentration index parameter of carbon dioxide;

[0101] Among them, the data collection frequency of the adjusted flow rate is obtained by the following formula:

[0102]

[0103] Wherein, F represents the data collection frequency of the flow rate after adjustment; f represents the data collection frequency of the flow rate before adjustment; S represents the concentration index parameter of carbon dioxide; S y Indicates the preset concentration index parameter threshold; V b represents the flow rate standard deviation corresponding to the flow rate data corresponding to carbon dioxide in the historical detection records except the current flow rate of carbon dioxide and its equivalent gas; V s Indicates the current flow rate of carbon dioxide and its equivalent gas; V ck Indicates the preset reference value of the flow rate of carbon dioxide; V max and V min It indicates the flow rate corresponding to the maximum and minimum values ​​of the carbon dioxide concentration ratio during the n-time data collection process.

[0104] The technical effect of the above technical solution is: by real-time monitoring of the concentration ratio of carbon dioxide, the solution can instantly obtain the carbon emissions in the production process, which is crucial for timely responding to environmental changes and taking corresponding measures. The extracted concentration index parameter is obtained by the above calculation formula, which takes into account multiple factors such as the number of data collection, the concentration value collected each time, the preset reference value, the maximum value, the minimum value and the intermediate value, thereby improving the accuracy and representativeness of the data. The solution includes a step of comparing the calculated carbon dioxide concentration index parameter with the preset threshold value, which provides a basis for dynamic monitoring and management. When the concentration index parameter exceeds the preset threshold value, the solution can automatically adjust the frequency of data collection of the flow rate of carbon dioxide and its equivalent gas, which means that when the emission is abnormal or the potential risk increases, the system can collect data more frequently to more accurately assess the emission situation and take corresponding emission reduction measures. Through precise monitoring and dynamic adjustment, the solution helps enterprises to detect abnormal carbon emissions in a timely manner, so as to take effective measures to reduce unnecessary emissions, which is of great significance for achieving environmental protection and energy conservation and emission reduction goals. Long-term precise monitoring and dynamic management can also help enterprises optimize production processes and procedures, improve energy efficiency and reduce resource waste. The solution achieves intelligent processing and analysis of carbon emission data through calculation formulas and preset threshold settings, reducing the need for manual intervention and judgment. The function of automatically adjusting the frequency of data collection also improves work efficiency and response speed, allowing enterprises to manage carbon emissions more efficiently.

[0105] In summary, this technical solution provides a comprehensive and effective means of monitoring carbon emissions in industrial production processes through real-time monitoring, precise calculation, dynamic adjustment and intelligent management, which helps enterprises achieve the goals of environmental protection, energy conservation and emission reduction, and sustainable development.

[0106] In this embodiment, the real-time data of industrial production carbon emission monitoring is processed, and the following operations are performed:

[0107] Obtain real-time data on industrial production carbon emissions monitoring;

[0108] Clean and process the real-time data of industrial production carbon emission monitoring, including:

[0109] Conduct consistency checks on real-time data on industrial production carbon emissions monitoring;

[0110] Check whether the real-time data of industrial production carbon emission monitoring meets the requirements according to the reasonable value range and mutual relationship of each parameter in the real-time data of industrial production carbon emission monitoring;

[0111] Remove inconsistent data that is beyond the normal range, logically unreasonable or contradictory in the real-time data of industrial production carbon emission monitoring;

[0112] Process invalid and missing values ​​of real-time data of industrial production carbon emission monitoring;

[0113] According to the calculation requirements of carbon accounting for industrial production, the real-time data of industrial production carbon emission monitoring are checked one by one to determine whether there are invalid values ​​and missing values ​​in the real-time data of industrial production carbon emission monitoring;

[0114] Remove invalid values ​​and missing values ​​in the real-time data of industrial production carbon emission monitoring that are useless for calculating the carbon accounting amount used in industrial production;

[0115] Identify real-time data on industrial production carbon emissions monitoring that is useful for industrial production carbon accounting calculations;

[0116] Obtain real-time data on industrial production carbon emissions monitoring that is useful for calculating carbon accounting for industrial production;

[0117] Convert and process the real-time data of industrial production carbon emission monitoring that is useful for calculating the carbon accounting amount for industrial production, and eliminate the dimensional differences between the real-time data of industrial production carbon emission monitoring;

[0118] Determine standardized real-time data for industrial production carbon emissions monitoring;

[0119] Extract features from standardized real-time data of industrial production carbon emission monitoring;

[0120] Extract features that reflect the calculation of carbon accounting for industrial production;

[0121] Determine the characteristic data for industrial production carbon emission monitoring.

[0122] It should be noted that the real-time data of industrial production carbon emission monitoring is obtained, cleaned and processed, and the real-time data of industrial production carbon emission monitoring that is useful for calculating the carbon accounting amount for industrial production is determined; the real-time data of industrial production carbon emission monitoring that is useful for calculating the carbon accounting amount for industrial production is converted and processed to eliminate the dimensional differences between the real-time data of industrial production carbon emission monitoring, and determine the standardized real-time data of industrial production carbon emission monitoring; feature extraction is performed on the standardized real-time data of industrial production carbon emission monitoring to extract features that can reflect the calculation of the carbon accounting amount for industrial production, and determine the characteristic data of industrial production carbon emission monitoring; it is convenient for the subsequent mining and analysis of the characteristic data of industrial production carbon emission monitoring according to the optimal industrial production carbon accounting amount calculation model based on deep learning, the industrial production carbon accounting amount is calculated, and the industrial production carbon accounting amount is determined. The calculation results of the industrial production carbon accounting amount are determined.

[0123] S2. Model construction and optimization:

[0124] Construct an industrial production carbon accounting calculation model based on deep learning, optimize the industrial production carbon accounting calculation model based on deep learning, and determine the optimal industrial production carbon accounting calculation model based on deep learning;

[0125] In this embodiment, a deep learning-based industrial production carbon accounting calculation model is constructed, and the following operations are performed:

[0126] Collect historical data on industrial production carbon emissions monitoring based on the calculation requirements of industrial production carbon accounting;

[0127] Divide the historical data of industrial production carbon emission monitoring to determine the training set and test set for carbon accounting calculation;

[0128] Select a convolutional neural network model framework suitable for calculating carbon accounting for industrial production;

[0129] Based on the carbon accounting calculation training set, the selected convolutional neural network model framework suitable for carbon accounting calculation for industrial production is trained;

[0130] A deep learning-based calculation model for industrial production carbon accounting was determined.

[0131] In this embodiment, the industrial production carbon accounting calculation model based on deep learning is optimized, and the following operations are performed:

[0132] Obtain a deep learning-based industrial production carbon accounting calculation model;

[0133] Based on the carbon accounting calculation test set, the performance test and evaluation of the industrial production carbon accounting calculation model based on deep learning was carried out;

[0134] Determine the performance test evaluation results based on the industrial production carbon accounting calculation model;

[0135] According to the performance test evaluation results of the industrial production carbon accounting calculation model, the industrial production carbon accounting calculation model based on deep learning is mined and analyzed;

[0136] Determine the parameter adjustment optimization scheme based on the industrial production carbon accounting calculation model;

[0137] According to the parameter adjustment optimization scheme based on the industrial production carbon accounting calculation model, the parameters of the industrial production carbon accounting calculation model based on deep learning are adjusted and optimized;

[0138] Determine the optimal deep learning-based industrial production carbon accounting calculation model.

[0139] S3. Calculation of carbon accounting amount:

[0140] According to the optimal industrial production carbon accounting calculation model based on deep learning, the industrial production carbon emission monitoring feature data is mined and analyzed, the industrial production carbon accounting amount is calculated, the industrial production carbon accounting amount calculation results based on deep learning are determined, and the industrial production carbon accounting amount calculation report is transmitted to industrial production managers in a visual form.

[0141] In this embodiment, the industrial production carbon emission monitoring characteristic data is mined and analyzed to calculate the industrial production carbon accounting amount, and the following operations are performed:

[0142] Obtaining industrial production carbon emission monitoring characteristic data;

[0143] Input the industrial production carbon emission monitoring characteristic data into the optimal industrial production carbon accounting calculation model based on deep learning;

[0144] According to the optimal industrial production carbon accounting calculation model based on deep learning, the industrial production carbon emission monitoring feature data is mined and analyzed to calculate the industrial production carbon accounting amount;

[0145] Determine the calculation results of industrial production carbon accounting based on deep learning.

[0146] In this embodiment, the industrial production carbon accounting amount calculation report is transmitted to the industrial production management personnel in a visual form, and the following operations are performed:

[0147] Obtain the calculation results of industrial production carbon accounting based on deep learning;

[0148] Generate an industrial production carbon accounting calculation report based on the industrial production carbon accounting calculation results based on deep learning and combined with the industrial production carbon emission monitoring characteristic data;

[0149] The industrial production carbon accounting calculation report is transmitted to the industrial production management personnel in a visual form, so that the industrial production management personnel can make timely adjustments and management of the industrial production carbon emissions based on the industrial production carbon accounting calculation report.

[0150] In summary, by collecting real-time data of industrial production carbon emission monitoring, processing the real-time data of industrial production carbon emission monitoring, determining the characteristic data of industrial production carbon emission monitoring, and according to the calculation requirements of industrial production carbon accounting quantity, constructing an industrial production carbon accounting quantity calculation model based on deep learning, optimizing the industrial production carbon accounting quantity calculation model based on deep learning, determining the optimal industrial production carbon accounting quantity calculation model based on deep learning, mining and analyzing the industrial production carbon emission monitoring characteristic data according to the optimal industrial production carbon accounting quantity calculation model based on deep learning, calculating the industrial production carbon accounting quantity, determining the industrial production carbon accounting quantity calculation results based on deep learning, and generating an industrial production carbon accounting quantity calculation report, transmitting the industrial production carbon accounting quantity calculation report to industrial production managers in a visual form, so that industrial production managers can make timely adjustments to the industrial production carbon emission situation, can effectively calculate the carbon accounting quantity of industrial production, can timely understand the industrial production carbon emission situation, can timely manage it, and can improve the industrial production carbon emission management effect.

[0151] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0152] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for calculating carbon accounting for industrial production, characterized in that: The steps include: S1. Data collection and processing: Collect real-time data on industrial production carbon emission monitoring, process the real-time data on industrial production carbon emission monitoring, and determine characteristic data on industrial production carbon emission monitoring; S2. Model construction and optimization: Construct an industrial production carbon accounting calculation model based on deep learning, optimize the industrial production carbon accounting calculation model based on deep learning, and determine the optimal industrial production carbon accounting calculation model based on deep learning; S3. Calculation of carbon accounting amount: According to the optimal industrial production carbon accounting calculation model based on deep learning, the industrial production carbon emission monitoring feature data is mined and analyzed, the industrial production carbon accounting amount is calculated, the industrial production carbon accounting amount calculation results based on deep learning are determined, and the industrial production carbon accounting amount calculation report is transmitted to industrial production managers in a visual form.

2. The method for calculating carbon accounting for industrial production according to claim 1, characterized in that: In S1, real-time data of industrial production carbon emission monitoring is collected, and the following operations are performed: Continuously monitor and collect real-time data on the concentration of carbon dioxide and equivalent gases emitted directly and indirectly into the atmosphere during fossil fuel combustion, electricity consumption, and heat consumption in industrial production activities to obtain data on industrial production carbon emission concentrations; Continuously monitor and collect real-time data on the flow rate of carbon dioxide and its equivalent gases emitted directly and indirectly into the atmosphere during fossil fuel combustion, electricity consumption, and heat consumption in industrial production activities, and obtain data on the flow rate of industrial production carbon emissions; Among them, the real-time data of industrial production carbon emission monitoring is determined based on the industrial production carbon emission concentration data and the industrial production carbon emission flow rate data.

3. The method for calculating carbon accounting for industrial production according to claim 2, characterized in that: In S1, collecting real-time data on industrial production carbon emissions monitoring also includes: Extract the concentration ratio value of carbon dioxide monitored in real time; Obtaining a concentration index parameter of carbon dioxide according to the carbon dioxide concentration ratio value; The concentration index parameter of carbon dioxide is obtained by the following formula: Where S represents the concentration index parameter of carbon dioxide; n represents the number of data collection times of carbon dioxide concentration; P ci Indicates the concentration ratio of carbon dioxide corresponding to the i-th concentration data collection; P ck Indicates the preset reference value of carbon dioxide concentration ratio; P cmax and P cmin Indicates the maximum and minimum values ​​of the carbon dioxide concentration ratio during the n-time data collection process; P cz It represents the middle value of the carbon dioxide concentration ratio during the n-time data collection process; Comparing the concentration index parameter of the carbon dioxide with a preset concentration index parameter threshold; When the concentration index parameter of carbon dioxide exceeds the preset concentration index parameter threshold, the data collection frequency of the flow rate of carbon dioxide and its equivalent gas is adjusted.

4. A method for calculating carbon accounting for industrial production according to claim 3, characterized in that: When the concentration index parameter of the carbon dioxide exceeds the preset concentration index parameter threshold, the data collection frequency of the flow rate of the carbon dioxide and its equivalent gas is adjusted, including: When the concentration index parameter of the carbon dioxide exceeds the preset concentration index parameter threshold, extracting the current flow rate of the carbon dioxide and its equivalent gas; Extract the flow rate data corresponding to carbon dioxide in the historical detection records; Retrieve the data collection frequency of the current flow rate of carbon dioxide and its equivalent gas; Adjusting the data collection frequency of the current flow rate of carbon dioxide and its equivalent gas according to the current flow rate of carbon dioxide and its equivalent gas and the flow rate data corresponding to carbon dioxide in combination with the concentration index parameter of carbon dioxide; Among them, the data collection frequency of the adjusted flow rate is obtained by the following formula: Wherein, F represents the data collection frequency of the flow rate after adjustment; f represents the data collection frequency of the flow rate before adjustment; S represents the concentration index parameter of carbon dioxide; S y Indicates the preset concentration index parameter threshold; V b represents the flow rate standard deviation corresponding to the flow rate data corresponding to carbon dioxide in the historical detection records except the current flow rate of carbon dioxide and its equivalent gas; V s Indicates the current flow rate of carbon dioxide and its equivalent gas; V ck Indicates the preset reference value of the flow rate of carbon dioxide; V max and V min It indicates the flow rate corresponding to the maximum and minimum values ​​of the carbon dioxide concentration ratio during the n-time data collection process.

5. The method for calculating carbon accounting for industrial production according to claim 2, characterized in that: In S1, the real-time data of industrial production carbon emission monitoring is processed, and the following operations are performed: Obtain real-time data on industrial production carbon emissions monitoring; Clean and process the real-time data of industrial production carbon emission monitoring, including: Conduct consistency checks on real-time data on industrial production carbon emissions monitoring; Check whether the real-time data of industrial production carbon emission monitoring meets the requirements according to the reasonable value range and mutual relationship of each parameter in the real-time data of industrial production carbon emission monitoring; Remove inconsistent data that is beyond the normal range, logically unreasonable or contradictory in the real-time data of industrial production carbon emission monitoring; Process invalid and missing values ​​of real-time data of industrial production carbon emission monitoring; According to the calculation requirements of carbon accounting for industrial production, the real-time data of industrial production carbon emission monitoring are checked one by one to determine whether there are invalid values ​​and missing values ​​in the real-time data of industrial production carbon emission monitoring; Remove invalid values ​​and missing values ​​in the real-time data of industrial production carbon emission monitoring that are useless for calculating the carbon accounting amount used in industrial production; Determine real-time data on industrial production carbon emissions monitoring that is useful for industrial production carbon accounting calculations.

6. A method for calculating carbon accounting for industrial production according to claim 5, characterized in that: In S1, the real-time data of industrial production carbon emission monitoring is processed, and the following operations are performed: Obtain real-time data on industrial production carbon emissions monitoring that is useful for calculating carbon accounting for industrial production; Convert and process the real-time data of industrial production carbon emission monitoring that is useful for calculating the carbon accounting amount for industrial production, and eliminate the dimensional differences between the real-time data of industrial production carbon emission monitoring; Determine standardized real-time data for industrial production carbon emissions monitoring; Extract features from standardized real-time data of industrial production carbon emission monitoring; Extract features that reflect the calculation of carbon accounting for industrial production; Determine the characteristic data for industrial production carbon emission monitoring.

7. A method for calculating carbon accounting for industrial production according to claim 6, characterized in that: In S2, a deep learning-based industrial production carbon accounting calculation model is constructed, and the following operations are performed: Collect historical data on industrial production carbon emissions monitoring based on the calculation requirements of industrial production carbon accounting; Divide the historical data of industrial production carbon emission monitoring to determine the training set and test set for carbon accounting calculation; Select a convolutional neural network model framework suitable for calculating carbon accounting for industrial production; Based on the carbon accounting calculation training set, the selected convolutional neural network model framework suitable for carbon accounting calculation for industrial production is trained; A deep learning-based calculation model for industrial production carbon accounting was determined.

8. A method for calculating carbon accounting for industrial production according to claim 7, characterized in that: In S2, the industrial production carbon accounting calculation model based on deep learning is optimized, and the following operations are performed: Obtain a deep learning-based industrial production carbon accounting calculation model; Based on the carbon accounting calculation test set, the performance test and evaluation of the industrial production carbon accounting calculation model based on deep learning was carried out; Determine the performance test evaluation results based on the industrial production carbon accounting calculation model; According to the performance test evaluation results of the industrial production carbon accounting calculation model, the industrial production carbon accounting calculation model based on deep learning is mined and analyzed; Determine the parameter adjustment optimization scheme based on the industrial production carbon accounting calculation model; According to the parameter adjustment optimization scheme based on the industrial production carbon accounting calculation model, the parameters of the industrial production carbon accounting calculation model based on deep learning are adjusted and optimized; Determine the optimal deep learning-based industrial production carbon accounting calculation model.

9. A method for calculating carbon accounting for industrial production according to claim 8, characterized in that: In S3, the characteristic data of industrial production carbon emission monitoring are mined and analyzed, and the industrial production carbon accounting amount is calculated, and the following operations are performed: Obtaining industrial production carbon emission monitoring characteristic data; Input the industrial production carbon emission monitoring characteristic data into the optimal industrial production carbon accounting calculation model based on deep learning; According to the optimal industrial production carbon accounting calculation model based on deep learning, the industrial production carbon emission monitoring feature data is mined and analyzed to calculate the industrial production carbon accounting amount; Determine the calculation results of industrial production carbon accounting based on deep learning.

10. A method for calculating carbon accounting for industrial production according to claim 9, characterized in that: In S3, the industrial production carbon accounting calculation report is transmitted to the industrial production management personnel in a visual form, and the following operations are performed: Obtain the calculation results of industrial production carbon accounting based on deep learning; Generate an industrial production carbon accounting calculation report based on the industrial production carbon accounting calculation results based on deep learning and combined with the industrial production carbon emission monitoring characteristic data; The industrial production carbon accounting calculation report is transmitted to the industrial production management personnel in a visual form, so that the industrial production management personnel can make timely adjustments and management of the industrial production carbon emissions based on the industrial production carbon accounting calculation report.

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