CN116757732B - Textile enterprise industry carbon emission checking accounting method - Google Patents

Textile enterprise industry carbon emission checking accounting method Download PDF

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CN116757732B
CN116757732B CN202310486201.6A CN202310486201A CN116757732B CN 116757732 B CN116757732 B CN 116757732B CN 202310486201 A CN202310486201 A CN 202310486201A CN 116757732 B CN116757732 B CN 116757732B
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卢萃云
康娟
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South China Institute of Environmental Science of Ministry of Ecology and Environment
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Abstract

The invention discloses a carbon emission checking and accounting method for textile industry, relates to the technical field of textiles, and aims to solve the problem of imperfect calculation of carbon emission data. According to the textile enterprise industry carbon emission check accounting method, the data calculation is carried out according to the accounting of the activity level of fossil fuel combustion and the consumption and average low-level heating value of various fossil fuels in the reporting year, so that the calculation of the activity level data of the ith fossil fuel is more accurate, the target electricity utilization characteristics corresponding to the target time sequence data of each key characteristic in the key characteristic subsets can be quickly obtained by constructing the identification model of each load amount, the operation characteristics of the load amount can be accurately determined, the data acquisition efficiency and accuracy are improved, and the total carbon emission summary data can be optimized and the data quality is improved after the total carbon emission summary data are subjected to forward propagation training and backward propagation training.

Description

Textile enterprise industry carbon emission checking accounting method
Technical Field
The invention relates to the technical field of textiles, in particular to a carbon emission check accounting method for textile enterprises.
Background
As important prop industry of national economy, the textile industry has the characteristics of strong toughness and great potential.
The Chinese patent with publication number of CN108228935A discloses a checking and accounting method for carbon emission of textile industry, which mainly uses a yield splitting principle to relate the proportional relation of product yield with public input amount, calculates the enterprise input amount when producing single textile, thereby calculating the carbon emission of the public input part when producing the product, and adds the carbon emission of the production part and the public part to calculate the total carbon emission of a certain textile single product in the production period, and the patent solves the problem of carbon emission calculation, but has the following problems in actual operation:
1. the emission data calculation is imperfect, and the accuracy is not further improved for the electric power data, resulting in data missing.
2. After data is summarized for the carbon displacement data in the whole textile process flow, further calculation optimization is not performed for summarized data, so that the relevance between the data is reduced, and the data cannot be adjusted according to actual conditions.
Disclosure of Invention
The invention aims to provide a textile enterprise industry carbon emission check accounting method, which is used for calculating data according to accounting of the activity level of fossil fuel combustion and data calculation of consumption and average low-level heating value of various fossil fuels in reporting years, so that the activity level data of the ith fossil fuel can be calculated more accurately, the target electricity utilization characteristic corresponding to the target time sequence data of each key characteristic in a key characteristic subset can be quickly obtained by constructing an identification model of each load amount, the running characteristic of the load amount can be accurately determined, the data acquisition efficiency and accuracy are improved, the total carbon emission summary data can be optimized after forward propagation training and backward propagation training, the data quality is improved, and the problems in the prior art can be solved.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a checking and accounting method for carbon emission of textile industry comprises the following steps:
s1: emission source identification: acquiring data of a carbon emission link and a carbon emission type in the whole spinning process flow;
s2, activity level data acquisition: according to the obtained carbon emission data of each link, calculating the activity level of fossil fuel combustion in the carbon emission data, reporting the consumption of various fossil fuels and the average low-level heating value in the annual period, and obtaining calculated data, and marking the calculated data as horizontal data;
s3, emission factor data acquisition: according to the acquired level data, carrying out data calculation on carbon dioxide emission factor data of fossil fuel combustion in the level data, and marking the acquired data as factor data;
s4, data calculation and analysis: according to the acquired factor data, respectively carrying out data calculation on the fuel combustion emission data, the process emission data, the net purchase power data and the emission of the thermal consumption data in the factor data, carrying out specific data analysis on the net purchase power data, and finally marking the calculated fuel combustion emission data, the process emission data, the net purchase power data and the emission data of the thermal consumption data as integral data;
s5, summarized data optimization: and according to the obtained overall data, carrying out data calculation on the sum of the total carbon dioxide emission amount in the overall data and the emission amount of fossil fuel combustion emission amount data, process emission amount data, net purchase power data and heat consumption data in the overall textile process flow, and optimizing data parameters through calculation optimization.
Preferably, for the identification of the carbon emission link in S1, the method includes:
the process energy emission identification and the material energy emission identification, wherein the process energy emission identification comprises electric energy, water energy, steam energy and coal energy consumed in the whole link;
converting according to carbon dioxide values generated by electric energy, water energy and steam energy in a production unit, and discharging carbon emission values of the electric energy, the water energy and the steam energy, wherein the coal energy converts the carbon emission values of the coal energy according to carbon dioxide generated by a consumption unit;
the material energy source emission identification comprises fuel emission, auxiliary agent emission and auxiliary material emission, and carbon emission values are respectively converted according to carbon dioxide generated in the fuel emission, the auxiliary agent emission and the auxiliary material emission of production consumption.
Preferably, for the type of carbon emission in S1, it includes:
direct and indirect discharge;
wherein direct emissions include fuel combustion, carbonate consumption, refrigerant consumption, and pollutant disposal;
indirect emissions include electrical consumption, thermal consumption and consumption of dyeing auxiliaries other than carbonates;
the type of carbon dioxide emissions is determined by the link of the carbon dioxide emissions.
Preferably, in S2, the calculation of data is performed for the calculation of the activity level of fossil fuel combustion and the consumption amount and the average low-grade heating value of various fossil fuels within the reporting year, including the following formulas:
AD i =NCV i ×FC i
wherein AD is i Expressed as activity level of the ith fossil fuel in megajoules during the accounting and reporting years; NCV (NCV) i The average low heat generation in megajoules per ton for solid or liquid fuels expressed as the ith fuel during the accounting and reporting years; for gaseous fuels, the unit is megajoules/ten thousand cubic meters, FC i Expressed as net consumption of the ith fuel in accounting and reporting years, in tons for solid or liquid fuel and tens of thousands of cubic meters for gaseous fuel using enterprise metering data;
the activity level data of the ith fossil fuel in the last calculated accounting and reporting year is marked as level data.
Preferably, for the data calculation of carbon dioxide emission factor data of the combustion of fossil fuel in S3, the following formula is included:
EF i =CC i ×44/12×10 -6
wherein EF is i Carbon dioxide emissions factor expressed as the ith fossil fuel in grams of carbon dioxide per megajoule; CC (CC) i Carbon content in grams of carbon per megajoule, expressed as the unit heating value of the ith fuel, and 44/12 expressed as the molecular weight ratio between carbon dioxide and carbon;
the carbon dioxide emission factor data from the fossil fuel calculated last is labeled as factor data.
Preferably, for S4, the formula for the process discharge amount data is as follows:
wherein E is Procedure Expressed as process emissions in tons of carbon dioxide over the accounting and reporting years; f (F) i Expressed as the consumption of the ith carbonate in tons during the accounting and reporting years; f (f) i Purity expressed as i-th carbonate, expressed in%, 100% was taken when the business did not make actual measurements; ρ i The utilization rate of the ith carbonate is expressed in percent, 100 percent is taken when the enterprises do not make practical measurement, and 44 is expressed as the relative molecular mass of carbon dioxide; m is M i Expressed as the relative molecular mass of the ith carbonate; n represents n carbonates;
wherein the process emissions are carbonates, which include carbonates and bicarbonates, and the carbon dioxide-generating emissions are derived from the chemical reaction decomposition of the carbonates.
Preferably, for S4, the formula for the net purchase power data is as follows:
AD electric power = IPAD Electric power -OPAD Electric power
Wherein AD is Electric power Expressed as net outsourcing power in kilowatt-hours; IPAD (IPAD) Electric power Expressed as the amount of outsourcing power in kilowatt-hours; OPAD (optical fiber attachment) Electric power Expressed as external power transmission in kilowatt-hours;
and obtaining similar load operation characteristics according to the net outsourcing power quantity data.
Preferably, the similar load operation characteristic of the net outsourcing electricity quantity data is obtained, and the method further comprises the following steps:
acquiring an initial feature set in the net outsourcing power data according to the net outsourcing power data;
invoking key features related to the load from the acquired initial feature set and integrating the key features into a key feature subset;
acquiring time sequence feature information of a key feature subset corresponding to the power data;
extracting time sequence data of each load from the power data according to the time sequence characteristic information;
determining electricity utilization characteristic information of each load based on time sequence data of the load;
taking the time sequence data and the basic value of each load as model input samples, and simultaneously taking the electricity characteristic information of each load as model output samples to train a preset network model so as to obtain an identification model of each load;
acquiring the change condition of the target electricity utilization characteristic of each load in the electric power data, and determining the electricity utilization change rule of each load according to the change condition;
and confirming the load quantity with the similarity of the electricity change rule larger than or equal to a preset threshold value as the similar load, and marking the load quantity as the final operation characteristic.
Preferably, for data optimization of the sum of emissions of fossil fuel combustion emissions data, process emissions data, net purchase power data, and thermal consumption data in S5, comprising:
outputting and setting parameters in the calculation optimization system, and importing emission data into data;
carrying out data operation on the input parameter data and the emission data;
firstly, forward transmitting the parameter data, wherein the parameter data is transmitted from a low level to a high level;
back-propagation is performed when the data results from the propagation do not match the expectations, where back-propagation is the propagation training of errors from high levels to the underlying layers.
Further, the textile industry carbon emission check accounting method further comprises:
monitoring the time for acquiring the carbon emission value corresponding to each stage of the whole textile process in real time;
comparing the time for acquiring the carbon emission value corresponding to each stage with the excessive time corresponding to each link in the whole textile process flow, and acquiring the time difference between the time for acquiring the carbon emission value corresponding to each stage and the carbon emission time node corresponding to each link in the whole textile process flow;
judging whether the time difference between the time for acquiring the carbon emission value corresponding to each stage and the carbon emission time node corresponding to each link in the whole textile process flow exceeds a preset time difference threshold value or not; the time difference threshold is obtained through the following formula:
wherein T is y Representing a time difference threshold; n represents the number of carbon emission value acquisitions; delta T represents the data processing delay caused by data redundancy after the current N times of carbon emission values are completed; t (T) si Representing theoretical allowable delay time length of carbon emission value data acquisition corresponding to the ith process flow stage;
and when the time difference between the time for acquiring the carbon emission value corresponding to each stage and the time node for discharging carbon corresponding to each link in the whole textile process flow exceeds a preset time difference threshold value, early warning is carried out.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention provides a carbon emission check accounting method for textile industry, which is characterized in that the calculation and reporting of the activity level data of the ith fossil fuel in the year are calculated through a summation formula of carbon dioxide emission generated by burning fossil fuel, the calculation of the activity level data of the ith fossil fuel can be more accurate according to the calculation of the activity level of burning fossil fuel, the calculation of the consumption of various fossil fuels and the average low-level heating value in the year, and the calculation of carbon dioxide emission factor data in burning fossil fuel can be further optimized after the calculation is completed.
2. The invention provides a textile enterprise industry carbon emission verification accounting method, which is characterized in that electric data is further subjected to data analysis according to the obtained net outsourcing electric power quantity data, sub-data in the electric data can be rapidly subjected to characteristic normalization processing through obtaining an initial characteristic set of the electric data, so that data characteristics of each dimension can be counted, conditions are laid for subsequent load operation characteristic judgment, target electricity utilization characteristics corresponding to target time sequence series data of each key characteristic in a key characteristic subset can be rapidly obtained through constructing an identification model of each load, and further, the operation characteristics of the load can be accurately determined, and data acquisition efficiency and accuracy are improved.
3. The invention provides a checking and accounting method for carbon emission in textile industry, which is characterized in that the total carbon emission is summarized and calculated through formulas of the sum of fossil fuel combustion emission, process emission and electric power and thermal consumption purchased by the industry, the calculation mode enables the obtained data to be more accurate, parameters in a calculation optimization system in a controller are set according to specific textile conditions, the obtained total carbon emission summary data are imported after setting is completed, the imported total carbon emission summary data and the set parameter data are subjected to data operation, wherein the parameter data can be subjected to forward propagation training to obtain final lost data when passing through each hidden layer, and the parameter data is subjected to backward propagation to form a backward propagation mechanism according to a gradient decreasing formula by layer.
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FIG. 1 is a schematic diagram of an overall carbon emission check flow of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to solve the problem that in the prior art, in the whole textile process, the carbon emission of fossil fuel in the material energy emission is not effectively calculated and optimized, so that the material energy emission data is inaccurate, referring to fig. 1, the embodiment provides the following technical scheme:
a checking and accounting method for carbon emission of textile industry comprises the following steps:
s1: emission source identification: acquiring data of a carbon emission link and a carbon emission type in the whole spinning process flow;
s2, activity level data acquisition: according to the obtained carbon emission data of each link, calculating the activity level of fossil fuel combustion in the carbon emission data, reporting the consumption of various fossil fuels and the average low-level heating value in the annual period, and obtaining calculated data, and marking the calculated data as horizontal data;
s3, emission factor data acquisition: according to the acquired level data, carrying out data calculation on carbon dioxide emission factor data of fossil fuel combustion in the level data, and marking the acquired data as factor data;
s4, data calculation and analysis: according to the acquired factor data, respectively carrying out data calculation on the fuel combustion emission data, the process emission data, the net purchase power data and the emission of the thermal consumption data in the factor data, carrying out specific data analysis on the net purchase power data, and finally marking the calculated fuel combustion emission data, the process emission data, the net purchase power data and the emission data of the thermal consumption data as integral data;
s5, summarized data optimization: and according to the obtained overall data, carrying out data calculation on the sum of the total carbon dioxide emission amount in the overall data and the emission amount of fossil fuel combustion emission amount data, process emission amount data, net purchase power data and heat consumption data in the overall textile process flow, and optimizing data parameters through calculation optimization.
For the identification of the carbon emission link in S1, the method includes: the process energy emission identification and the material energy emission identification, wherein the process energy emission identification comprises electric energy, water energy, steam energy and coal energy consumed in the whole link; converting according to carbon dioxide values generated by electric energy, water energy and steam energy in a production unit, and discharging carbon emission values of the electric energy, the water energy and the steam energy, wherein the coal energy converts the carbon emission values of the coal energy according to carbon dioxide generated by a consumption unit; the material energy source emission identification comprises fuel emission, auxiliary agent emission and auxiliary material emission, carbon emission values are respectively converted according to carbon dioxide generated in the fuel emission, the auxiliary agent emission and the auxiliary material emission of production consumption, and aiming at the type of the carbon emission in S1, the material energy source emission identification comprises the following steps: direct and indirect discharge; wherein direct emissions include fuel combustion, carbonate consumption, refrigerant consumption, and pollutant disposal; indirect emissions include electrical consumption, thermal consumption and consumption of dyeing auxiliaries other than carbonates; the type of carbon dioxide emissions is determined by the link of the carbon dioxide emissions.
For S2, data calculation is performed on the consumption amount and the average low-grade heating value of various fossil fuels in the accounting and reporting years of the activity level of fossil fuel combustion, including the following formulas:
AD i =NCV i ×FC i
wherein AD is i Expressed as activity level of the ith fossil fuel in Megajoules (MJ) during the accounting and reporting years; NCV (NCV) i The average low heat generation in megajoules per ton (MJ/t) for solid or liquid fuels, expressed as the ith fuel during the accounting and reporting years; for gaseous fuels, the unit is megajoules/ten thousand cubic meters (MJ/ten thousand Nm 3), FC i Expressed as net fuel consumption in the ith fuel in accounting and reporting years, in tons (t) for solid or liquid fuel and tens of thousands of cubic meters (tens of thousands of Nm 3) for gaseous fuel using enterprise metering data;
the activity level data of the ith fossil fuel in the last calculated accounting and reporting year is marked as level data.
For the data calculation of carbon dioxide emission factor data of the combustion of fossil fuel in S3, the following formula is included:
EF i =CC i ×44/12×10 -6
wherein EF is i Carbon dioxide emission factor expressed as the ith fossil fuel in grams carbon dioxide per megajoule (g-CO 2 /MJ);CC i Expressed as carbon content per unit heating value of the ith fuel in grams of carbon per megajoule (g-C/MJ), and 44/12 as carbon dioxide (CO 2 ) And carbon (C);
the carbon dioxide emission factor data from the fossil fuel calculated last is labeled as factor data. Specifically, the sum formula of the carbon dioxide emission amount generated by burning fossil fuel is as follows:
E combustion process Expressed as accounting and reporting of CO produced by fossil fuel combustion over the year 2 Emissions in tons of carbon dioxide (t-CO) 2 );AD i Expressed as activity level of the ith fossil fuel in Megajoules (MJ) during the accounting and reporting years; EF (electric F) i Carbon dioxide emission factor expressed as the ith fossil fuel in grams carbon dioxide per megajoule (g-CO 2 /MJ); i is expressed as a fossil fuel type code, the activity level data of the ith fossil fuel in the accounting and reporting years is calculated through a summation formula of carbon dioxide emission generated by fossil fuel combustion, the calculation of the data is carried out according to the accounting of the activity level of fossil fuel combustion and the consumption and average low-level heating value of various fossil fuels in the reporting years, so that the calculation of the activity level data of the ith fossil fuel is more accurate, and the calculation of the carbon dioxide emission factor data in fossil fuel combustion can be carried out after the calculation is completed, so that the emission data can be further optimized.
In order to solve the problems of imperfect calculation of emission data and no further improvement of accuracy of electric power data in the prior art, referring to fig. 1, the present embodiment provides the following technical scheme:
for S4, the formula for the process emission data is as follows:
wherein E is Procedure Expressed as process emissions in tons of carbon dioxide over the accounting and reporting years; f (F) i The elimination of the ith carbonate, expressed as accounting and reporting yearsConsumption in tons; f (f) i Purity expressed as i-th carbonate, expressed in%, 100% was taken when the business did not make actual measurements; ρ i The utilization rate of the ith carbonate is expressed in percent, 100 percent is taken when the enterprises do not make practical measurement, and 44 is expressed as the relative molecular mass of carbon dioxide; m is M i Expressed as the relative molecular mass of the ith carbonate; n represents n carbonates;
wherein the process emissions are carbonates, which include carbonates and bicarbonates, and the carbon dioxide-generating emissions are derived from the chemical reaction decomposition of the carbonates.
For S4, the formula for the net purchase power data is as follows:
AD electric power = IPAD Electric power - OPAD Electric power
Wherein AD is Electric power Expressed as net outsourcing power in kilowatt-hours (kilowatt-hours/h); IPAD (IPAD) Electric power Expressed as the amount of outsourcing power in kilowatt-hours (kilowatt-hours/h); OPAD (optical fiber attachment) Electric power Expressed as external transmission power in kilowatt-hours (kilo kW/h);
obtaining similar load operation characteristics according to the net outsourcing power quantity data, wherein the similar load operation characteristics of the net outsourcing power quantity data are obtained, and the method further comprises the following steps: acquiring an initial feature set in the net outsourcing power data according to the net outsourcing power data; invoking key features related to the load from the acquired initial feature set and integrating the key features into a key feature subset; acquiring time sequence feature information of a key feature subset corresponding to the power data; extracting time sequence data of each load from the power data according to the time sequence characteristic information; determining electricity utilization characteristic information of each load based on time sequence data of the load; taking the time sequence data and the basic value of each load as model input samples, and simultaneously taking the electricity characteristic information of each load as model output samples to train a preset network model so as to obtain an identification model of each load; acquiring the change condition of the target electricity utilization characteristic of each load in the electric power data, and determining the electricity utilization change rule of each load according to the change condition; and confirming the load quantity with the similarity of the electricity change rule larger than or equal to a preset threshold value as the similar load, and marking the load quantity as the final operation characteristic.
Specifically, the formula of carbon dioxide emission in the thermodynamic production link corresponding to the thermodynamic consumption data is as follows:
E heat of the body =AD Heat of the body ×EF Heat of the body
E Heat of the body Expressed as the emission of carbon dioxide in ton of carbon dioxide (t-CO) in the thermodynamic production process corresponding to the net purchase thermodynamic quantity 2 );AD Heat of the body Expressed as net outsourcing heat in millions of kilojoules (GJ) over the accounting and reporting years; EF (electric F) Heat of the body Expressed as annual average heat supply emission factor in tons of carbon dioxide per million kilojoules (t-CO) 2 /GJ);
The usage formula of the thermal consumption data is as follows:
AD heat of the body = IPAD Heat of the body -OPAD Heat of the body
AD Heat of the body Expressed as activity data, i.e., net outsourcing heat force in million kilojoules (GJ); IPAD (IPAD) Heat of the body Expressed as activity data, i.e., the amount of outsourcing heat in million kilojoules (GJ); the outsourcing heat quantity refers to the heat quantity from outside the organization boundary of the enterprise (unit), and does not comprise the heat quantity from renewable energy sources and complementary energy heating facilities entrusted to operation of the enterprise (unit) in the factory boundary area; OPAD (optical fiber attachment) Heat of the body Expressed as activity data, i.e., the amount of external heat transfer in millions of kilojoules (GJ); the external heat transmission force comprises heat quantity which is transmitted to the non-industrial production activities of the enterprises (units) and is outside the tissue boundary of the enterprises (units), and does not comprise heat quantity which is provided by renewable energy resources and complementary energy heat supply facilities which are entrusted to be operated by the enterprises (units) in the factory boundary area of the enterprises (units), if the enterprises (units) operate or entrusted to be operated (such as contract energy management and the like) in the factory boundary area of the enterprises (units), the enterprises (units) use the part of heat to be regarded as not generating indirect emission, but the carbon dioxide emission generated by the combustion of fossil fuel used by the heat supply facilities is required to be counted into the integral emission of the enterprises (units);
meanwhile, the electric data is further analyzed according to the obtained net outsourcing electric power quantity data, the sub-data in the electric power data can be rapidly subjected to characteristic normalization processing through obtaining an initial characteristic set of the electric power data, so that the data characteristic of each dimension can be counted, conditions are laid for subsequent load quantity operation characteristic judgment, the target electricity utilization characteristic corresponding to the target time sequence data of each key characteristic in the key characteristic subset can be rapidly obtained through constructing an identification model of each load quantity, and further the load quantity operation characteristic can be accurately determined, and the data acquisition efficiency and accuracy are improved.
In order to solve the problem that in the prior art, after data is summarized for carbon displacement data in the whole textile process flow, further calculation optimization is not performed for summarized data, so that the relevance between data is reduced, and adjustment cannot be performed according to actual conditions, please refer to fig. 1, the embodiment provides the following technical scheme:
data optimization for the sum of emissions of fossil fuel combustion emissions data, process emissions data, net purchase power data, and thermal consumption data in S5, comprising: outputting and setting parameters in the calculation optimization system, and importing emission data into data; carrying out data operation on the input parameter data and the emission data; firstly, forward transmitting the parameter data, wherein the parameter data is transmitted from a low level to a high level; back-propagation is performed when the data results from the propagation do not match the expectations, where back-propagation is the propagation training of errors from high levels to the underlying layers.
Specifically, the formula of the sum of the fossil fuel combustion emission, the process emission and the emission of electric power and thermal consumption purchased by enterprises is as follows:
E= E combustion process +E Process+E Electric power + E Heat of the body
E is expressed as total carbon dioxide emissions in tons of carbon dioxide equivalent (tCO 2 );E Combustion process Expressed as fossil fuel combustion emissions in tons of carbon dioxide (tCO) 2 ) The method comprises the steps of carrying out a first treatment on the surface of the E is too muchThe process is expressed as process emissions in tons of carbon dioxide (tCO 2 );E Electric power Emissions expressed as net purchased electricity consumption in tons of carbon dioxide (tCO 2 );E Heat of the body Emissions expressed as net purchased thermodynamic consumption in tons of carbon dioxide (tCO 2 );
The total carbon emission amount is summarized and calculated through the formula, the obtained data is more accurate in calculation mode, parameters in a calculation optimization system in a controller are set according to specific textile conditions, the obtained total carbon emission amount summarizing data are imported after the setting is completed, the imported total carbon emission amount summarizing data and the set parameter data are subjected to data operation, wherein the data can be transmitted through each hidden layer when the parameter data are trained through forward transmission, finally lost data are obtained when the parameter data are transmitted through the hidden layers, a backward transmission mechanism is formed according to a gradient decreasing formula when the parameter data are transmitted in a backward direction, parameters can be optimized, the total carbon emission amount summarizing data can be optimized after forward transmission training and backward transmission training, and data quality is improved.
In one embodiment of the present invention, the method for checking and accounting carbon emissions in textile industry further comprises:
monitoring the time for acquiring the carbon emission value corresponding to each stage of the whole textile process in real time;
comparing the time for acquiring the carbon emission value corresponding to each stage with the excessive time corresponding to each link in the whole textile process flow, and acquiring the time difference between the time for acquiring the carbon emission value corresponding to each stage and the carbon emission time node corresponding to each link in the whole textile process flow;
judging whether the time difference between the time for acquiring the carbon emission value corresponding to each stage and the carbon emission time node corresponding to each link in the whole textile process flow exceeds a preset time difference threshold value or not; the time difference threshold is obtained through the following formula:
wherein T is y Representing a time difference threshold; n represents the number of carbon emission value acquisitions; delta T represents the data processing delay caused by data redundancy after the current N times of carbon emission values are completed; t (T) si Representing theoretical allowable delay time length of carbon emission value data acquisition corresponding to the ith process flow stage;
and when the time difference between the time for acquiring the carbon emission value corresponding to each stage and the time node for discharging carbon corresponding to each link in the whole textile process flow exceeds a preset time difference threshold value, early warning is carried out.
The technical scheme has the effects that: through the mode, the data processing efficiency monitoring strength of carbon emission can be effectively improved. Meanwhile, the time difference threshold obtained through the formula can effectively improve the rationality of time difference threshold setting and the setting of the time difference threshold and the actual data processing condition and the data redundancy condition of the whole textile process flow, and can further improve the matching property between the time difference threshold and the actual data processing condition of the whole textile process flow. And further, the monitoring efficiency and the monitoring accuracy of the data processing efficiency of the carbon emission are improved.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims (10)

1. The checking and accounting method for the carbon emission of the textile enterprise industry is characterized by comprising the following steps:
s1: emission source identification: acquiring data of a carbon emission link and a carbon emission type in the whole spinning process flow;
s2, activity level data acquisition: according to the obtained carbon emission data of each link, calculating the activity level of fossil fuel combustion in the carbon emission data, reporting the consumption of various fossil fuels and the average low-level heating value in the annual period, and obtaining calculated data, and marking the calculated data as horizontal data;
s3, emission factor data acquisition: according to the acquired level data, carrying out data calculation on carbon dioxide emission factor data of fossil fuel combustion in the level data, and marking the acquired data as factor data;
s4, data calculation and analysis: according to the acquired factor data, respectively carrying out data calculation on the fuel combustion emission data, the process emission data, the net purchase power data and the emission of the thermal consumption data in the factor data, carrying out specific data analysis on the net purchase power data, and finally marking the calculated fuel combustion emission data, the process emission data, the net purchase power data and the emission data of the thermal consumption data as integral data;
s5, summarized data optimization: and according to the obtained overall data, carrying out data calculation on the sum of the total carbon dioxide emission amount in the overall data and the emission amount of fossil fuel combustion emission amount data, process emission amount data, net purchase power data and heat consumption data in the overall textile process flow, and optimizing data parameters through calculation optimization.
2. The textile industry carbon emission check accounting method according to claim 1, wherein: for the identification of the carbon emission link in S1, the method includes:
the process energy emission identification and the material energy emission identification, wherein the process energy emission identification comprises electric energy, water energy, steam energy and coal energy consumed in the whole link;
converting according to carbon dioxide values generated by electric energy, water energy and steam energy in a production unit, and discharging carbon emission values of the electric energy, the water energy and the steam energy, wherein the coal energy converts the carbon emission values of the coal energy according to carbon dioxide generated by a consumption unit;
the material energy source emission identification comprises fuel emission, auxiliary agent emission and auxiliary material emission, and carbon emission values are respectively converted according to carbon dioxide generated in the fuel emission, the auxiliary agent emission and the auxiliary material emission of production consumption.
3. The textile industry carbon emission check accounting method according to claim 1, wherein: for the type of carbon emissions in S1, including:
direct and indirect discharge;
wherein direct emissions include fuel combustion, carbonate consumption, refrigerant consumption, and pollutant disposal;
indirect emissions include electrical consumption, thermal consumption and consumption of dyeing auxiliaries other than carbonates;
the type of carbon dioxide emissions is determined by the link of the carbon dioxide emissions.
4. The textile industry carbon emission check accounting method according to claim 1, wherein: for S2, data calculation is performed on the consumption amount and the average low-grade heating value of various fossil fuels in the accounting and reporting years of the activity level of fossil fuel combustion, including the following formulas:
AD i =NCV i ×FC i
wherein AD is i Expressed as activity level of the ith fossil fuel in megajoules during the accounting and reporting years; NCV (NCV) i Expressed as the average low heat generation of the ith fuel over the accounting and reporting years, for solids orLiquid fuel in megajoules/ton; for gaseous fuels, the unit is megajoules/ten thousand cubic meters, FC i Expressed as net consumption of the ith fuel in accounting and reporting years, in tons for solid or liquid fuel and tens of thousands of cubic meters for gaseous fuel using enterprise metering data;
the activity level data of the ith fossil fuel in the last calculated accounting and reporting year is marked as level data.
5. The textile industry carbon emission check accounting method according to claim 1, wherein: for the data calculation of carbon dioxide emission factor data of the combustion of fossil fuel in S3, the following formula is included:
EF i =CC i ×44/12×10 -6
wherein EF is i Carbon dioxide emissions factor expressed as the ith fossil fuel in grams of carbon dioxide per megajoule; CC (CC) i Carbon content in grams of carbon per megajoule, expressed as the unit heating value of the ith fuel, and 44/12 expressed as the molecular weight ratio between carbon dioxide and carbon;
the carbon dioxide emission factor data from the fossil fuel calculated last is labeled as factor data.
6. The textile industry carbon emission check accounting method according to claim 1, wherein: for S4, the formula for the process emission data is as follows:
wherein E is Procedure Expressed as process emissions in tons of carbon dioxide over the accounting and reporting years; f (F) i Expressed as the consumption of the ith carbonate in tons during the accounting and reporting years; f (f) i Purity expressed as i-th carbonate, expressed in%, 100% was taken when the business did not make actual measurements; ρ i Expressed as the utilization of the ith carbonate,expressed in%, 100% when the business does not make actual measurements, 44 is expressed as the relative molecular mass of carbon dioxide; m is M i Expressed as the relative molecular mass of the ith carbonate; n represents n carbonates;
wherein the process emissions are carbonates, which include carbonates and bicarbonates, and the carbon dioxide-generating emissions are derived from the chemical reaction decomposition of the carbonates.
7. The textile industry carbon emission check accounting method according to claim 1, wherein: for S4, the formula for the net purchase power data is as follows:
AD electric power = IPAD Electric power -OPAD Electric power
Wherein AD is Electric power Expressed as net outsourcing power in kilowatt-hours; IPAD (IPAD) Electric power Expressed as the amount of outsourcing power in kilowatt-hours; OPAD (optical fiber attachment) Electric power Expressed as external power transmission in kilowatt-hours;
and obtaining similar load operation characteristics according to the net outsourcing power quantity data.
8. The textile industry carbon emission check accounting method of claim 7, wherein: the similar load operation characteristic acquisition of the net outsourcing electricity quantity data further comprises the following steps:
acquiring an initial feature set in the net outsourcing power data according to the net outsourcing power data;
invoking key features related to the load from the acquired initial feature set and integrating the key features into a key feature subset;
acquiring time sequence feature information of a key feature subset corresponding to the power data;
extracting time sequence data of each load from the power data according to the time sequence characteristic information;
determining electricity utilization characteristic information of each load based on time sequence data of the load;
taking the time sequence data and the basic value of each load as model input samples, and simultaneously taking the electricity characteristic information of each load as model output samples to train a preset network model so as to obtain an identification model of each load;
acquiring the change condition of the target electricity utilization characteristic of each load in the electric power data, and determining the electricity utilization change rule of each load according to the change condition;
and confirming the load quantity with the similarity of the electricity change rule larger than or equal to a preset threshold value as the similar load, and marking the load quantity as the final operation characteristic.
9. The textile industry carbon emission check accounting method according to claim 1, wherein: data optimization for the sum of emissions of fossil fuel combustion emissions data, process emissions data, net purchase power data, and thermal consumption data in S5, comprising:
outputting and setting parameters in the calculation optimization system, and importing emission data into data;
carrying out data operation on the input parameter data and the emission data;
firstly, forward transmitting the parameter data, wherein the parameter data is transmitted from a low level to a high level;
back-propagation is performed when the data results from the propagation do not match the expectations, where back-propagation is the propagation training of errors from high levels to the underlying layers.
10. The textile industry carbon emission check accounting method according to claim 1, wherein: further comprises:
monitoring the time for acquiring the carbon emission value corresponding to each stage of the whole textile process in real time;
comparing the time for acquiring the carbon emission value corresponding to each stage with the excessive time corresponding to each link in the whole textile process flow, and acquiring the time difference between the time for acquiring the carbon emission value corresponding to each stage and the carbon emission time node corresponding to each link in the whole textile process flow;
judging whether the time difference between the time for acquiring the carbon emission value corresponding to each stage and the carbon emission time node corresponding to each link in the whole textile process flow exceeds a preset time difference threshold value or not; the time difference threshold is obtained through the following formula:
wherein T is y Representing a time difference threshold; n represents the number of carbon emission value acquisitions; delta T represents the data processing delay caused by data redundancy after the current N times of carbon emission values are completed; t (T) si Representing theoretical allowable delay time length of carbon emission value data acquisition corresponding to the ith process flow stage;
and when the time difference between the time for acquiring the carbon emission value corresponding to each stage and the time node for discharging carbon corresponding to each link in the whole textile process flow exceeds a preset time difference threshold value, early warning is carried out.
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