CN114611934B - Whole-process carbon emission accounting method for iron and steel enterprises based on Gaussian distribution fitting and rolling correction - Google Patents
Whole-process carbon emission accounting method for iron and steel enterprises based on Gaussian distribution fitting and rolling correction Download PDFInfo
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- 229910052799 carbon Inorganic materials 0.000 title claims abstract description 151
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 title claims abstract description 54
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- 239000000047 product Substances 0.000 claims description 14
- 230000005611 electricity Effects 0.000 claims description 13
- 239000007789 gas Substances 0.000 claims description 10
- 239000006227 byproduct Substances 0.000 claims description 9
- 239000008188 pellet Substances 0.000 claims description 8
- 238000005070 sampling Methods 0.000 claims description 7
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 4
- 239000003245 coal Substances 0.000 claims description 4
- 238000001514 detection method Methods 0.000 claims description 4
- 238000005516 engineering process Methods 0.000 claims description 4
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- 238000013480 data collection Methods 0.000 claims description 2
- 230000008569 process Effects 0.000 abstract description 9
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- 238000004939 coking Methods 0.000 abstract description 3
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- 238000005245 sintering Methods 0.000 abstract description 3
- 238000009628 steelmaking Methods 0.000 abstract 1
- UHOVQNZJYSORNB-UHFFFAOYSA-N Benzene Chemical compound C1=CC=CC=C1 UHOVQNZJYSORNB-UHFFFAOYSA-N 0.000 description 6
- 239000000203 mixture Substances 0.000 description 5
- 239000000571 coke Substances 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
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- XKRFYHLGVUSROY-UHFFFAOYSA-N Argon Chemical compound [Ar] XKRFYHLGVUSROY-UHFFFAOYSA-N 0.000 description 2
- ODINCKMPIJJUCX-UHFFFAOYSA-N Calcium oxide Chemical compound [Ca]=O ODINCKMPIJJUCX-UHFFFAOYSA-N 0.000 description 2
- 235000019738 Limestone Nutrition 0.000 description 2
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- 238000011897 real-time detection Methods 0.000 description 2
- 102100037651 AP-2 complex subunit sigma Human genes 0.000 description 1
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 1
- MYMOFIZGZYHOMD-UHFFFAOYSA-N Dioxygen Chemical compound O=O MYMOFIZGZYHOMD-UHFFFAOYSA-N 0.000 description 1
- 101000806914 Homo sapiens AP-2 complex subunit sigma Proteins 0.000 description 1
- 239000000654 additive Substances 0.000 description 1
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- 230000007547 defect Effects 0.000 description 1
- 229910001873 dinitrogen Inorganic materials 0.000 description 1
- 229910001882 dioxygen Inorganic materials 0.000 description 1
- 239000010459 dolomite Substances 0.000 description 1
- 229910000514 dolomite Inorganic materials 0.000 description 1
- 230000004907 flux Effects 0.000 description 1
- 239000002803 fossil fuel Substances 0.000 description 1
- 239000005431 greenhouse gas Substances 0.000 description 1
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- 239000004615 ingredient Substances 0.000 description 1
- 238000002955 isolation Methods 0.000 description 1
- 238000012946 outsourcing Methods 0.000 description 1
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- -1 sinter Substances 0.000 description 1
- 239000002893 slag Substances 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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Abstract
The invention discloses a total-flow carbon emission accounting method for an iron and steel enterprise based on Gaussian distribution fitting and rolling correction. The method comprises the following steps: detecting and collecting component data of raw materials and products used in main production processes (sintering, pelletizing, coking, ironmaking and steelmaking) of the steel and iron combined enterprises; carrying out Gaussian distribution fitting treatment on data in a database based on Matlab and rolling iteration to obtain the mean value and variance of the content of the material components; according to the difference of the carbon content of the materials and the content of other substances, calculating the carbon emission factors of the materials and the error range of the carbon emission factors; and calculating the carbon emission of each main process according to the using amount of the actual raw materials of the process, so as to obtain the carbon emission and the error range of the whole steel process. The method can effectively solve the problems that the carbon dioxide emission calculation is not specific, has large fluctuation and is difficult to attach to the actual situation in the production process of iron and steel enterprises, and has the capability of processing a large amount of data actual measurement data and calculating the carbon emission in real time.
Description
Technical Field
The invention belongs to the field of soft measurement, and particularly relates to a total-flow carbon emission accounting method for an iron and steel enterprise based on Gaussian distribution fitting and rolling correction.
Background
At present, the main calculation modes of carbon dioxide in the steel production process at home and abroad mainly comprise a WSA method, an IPCC method and a greenhouse gas emission accounting method and report guidelines of China steel production enterprises, wherein the calculation modes of the three methods are different in size, are all carbon emission calculation based on carbon emission factors and material quantity, and follow the basic principle based on some improvement methods provided by the methods. Therefore, in the actual carbon emission measurement process, the measurement accuracy of the carbon emission factor is extremely important.
The material carbon emission factor adopted by enterprises in calculating the carbon dioxide emission amount in the production process is provided for a third party or is obtained through component detection of actual materials, the former has the advantages of low acquisition cost, convenient calculation and the like, but the actual carbon emission amount is difficult to reflect for different production processes of the enterprises; the latter is gradually adopted by enterprises along with the popularization of various real-time detection technologies, but the isolation among the current multiple carbon emission factor measurement and calculation is not improved. Although the real-time detection can obtain a large amount of material composition data, a plurality of carbon emission factors calculated by a group of data cannot be considered, the carbon emission factors are relatively independent after the measurement and the determination of numerical values, and the past measurement results are not inherited, and the follow-up measurement is not corrected, so that the actual carbon emission factors in the steel production process are difficult to reflect.
The method can effectively solve the problems that the carbon dioxide emission calculation is not specific, has large fluctuation and is difficult to attach to the actual situation in the production process of iron and steel enterprises, has the capability of processing a large amount of data actual measurement data and calculating the carbon emission in real time, and has excellent adaptability to real-time carbon emission calculation based on the large data.
Disclosure of Invention
The invention aims to: in order to overcome the defects in the prior art, the invention provides a full-flow carbon emission accounting method for an iron and steel enterprise based on Gaussian distribution fitting and rolling correction, which can effectively solve the problems of no pertinence, large fluctuation and difficult fitting reality in the production process of the iron and steel enterprise, has the capability of processing a large amount of data actual measurement data and calculating the carbon emission in real time, and has excellent adaptability to real-time carbon emission measurement and calculation based on the large data.
The technical scheme is as follows: in order to achieve the above purpose, the invention adopts the following technical scheme:
A full-flow carbon emission accounting method for an iron and steel enterprise based on Gaussian distribution fitting and rolling correction comprises the following steps:
Step 1, establishing a targeted raw material and product database of each procedure aiming at different raw material proportions and products in different production enterprise flows, and collecting component measurement data;
The period of collecting different materials may be different, and part of the materials adopt the PGNAA technology to carry out real-time component measurement, including iron ore, pellet, sinter and coal dust, can carry out online component detection, effectively reduce errors, and simultaneously can rapidly obtain a large amount of component information; other materials adopt a traditional laboratory component analysis mode, and have longer period and certain hysteresis;
In order to ensure the accuracy of calculation, materials occupying large carbon emission in the whole production flow are definitely required to be used, and the sampling period is shortened as much as possible; the sampling period of the material with small carbon emission factor and small influence on the whole carbon emission can be properly prolonged, and errors caused by measurement are reduced;
Step 2, constructing various raw material Gaussian distribution fitting models in different procedures according to the acquired data and iterating;
based on a Matlab platform, acquiring a mean value and a variance through Gaussian distribution fitting of acquired data, wherein the mean value is used as a material component proportion calculated by a carbon emission factor, and the variance is used for estimating an error of carbon emission calculation;
Setting capacity for a data set of various material components, inputting new data completely before the acquisition quantity does not reach an upper limit, and carrying out normal distribution fitting according to the existing data after each acquisition to obtain a mean value and a variance; after the collection quantity reaches the upper limit, carrying out iterative updating after each time of data collection, and banning the oldest data, and carrying out normal distribution fitting on the existing data after each time of input, so as to realize iterative updating of the raw material components;
Step 3, referring to a carbon emission calculation frame of a WSA method, adopting a carbon mass balance method, and calculating carbon emission factors aiming at actual material components in different production processes so as to obtain more accurate carbon emission;
the calculation method comprises the following steps:
Step 3.1: calculating a direct carbon emission factor;
direct carbon emissions include carbon emissions of carbonaceous matter and carbonaceous energy sources, the carbon emission factor of which is determined by the following equation:
Wherein EF i is the carbon emission factor of item i, the unit is tCO 2/t;(C)i is the carbon content of item i, and the unit is;
step 3.2: calculating an indirect carbon emission factor;
The indirect carbon emission comprises power consumption and carbon emission of partial auxiliary materials, including carbon emission caused by electric power and oxygen production, but the carbon emission place is not in the iron and steel combined enterprises, thus the indirect carbon emission is included; since the gas manufacturing process is mostly produced by consuming electricity, it can be calculated by the electricity carbon emission factor;
according to the region of the actual electricity utilization place, the indirect carbon emission factor of the rest materials can be obtained by combining the electric carbon emission factors, and the following formula is shown:
EFi＝EFe·Qei
Wherein EF i is the carbon emission factor of the i th item, the unit is tCO 2/t;EFe is the carbon emission factor of the local power grid, the unit is tCO 2/MWh;Qei is the electricity consumption of the i th item, and the unit is MWh/t;
step 3.3: calculating a deduction carbon emission factor;
In the carbon flow model, carbon substances entering the steel combined enterprise are partially discharged into the environment in the form of carbon dioxide, and the other part leaves the steel combined enterprise in the form of products and byproducts of various working procedures or is recycled, wherein the carbon substances comprise sintered ores and pellets of products or various coal gases of byproducts; the specific calculation mode is similar to that of the direct carbon emission factor;
Step 4, carrying the carbon emission factors into each procedure to calculate the carbon emission;
The carbon emission amount calculation formula is as follows:
CE＝∑EFi direct×Mi direct+∑EFi e×Mi e-∑EFi p×Mi p
Wherein EF i direct and M i direct respectively represent a direct carbon emission factor and a corresponding mass thereof, EF i e and M i e respectively represent an indirect carbon emission factor and a corresponding mass thereof, and EF i p and M i p respectively represent a deduction carbon emission factor and a corresponding mass thereof.
The beneficial effects are that: compared with the prior art, the invention has the following effective effects:
(1) The problems that carbon dioxide emission calculation is not targeted, fluctuation is large and the actual carbon dioxide emission calculation is difficult to attach in the production process of iron and steel enterprises are effectively solved;
(2) The method has the capability of processing a large amount of data and measuring data and calculating the carbon emission in real time, and has excellent adaptability to real-time carbon emission measurement and calculation based on the large data.
Drawings
FIG. 1 is a flow chart of the calculation of the present invention.
Detailed Description
The present application is further illustrated in the accompanying drawings and detailed description which are to be understood as being merely illustrative of the application and not limiting of its scope, and various equivalent modifications to the application will fall within the scope of the application as defined in the appended claims after reading the application.
A full-flow carbon emission accounting method for an iron and steel enterprise based on Gaussian distribution fitting and rolling correction comprises the following steps:
step I, constructing a corresponding material database based on the actual steel production flow
The whole production process of the combined iron and steel enterprise mainly comprises five working procedures of sintering, pelletizing, coking, blast furnaces and converters, wherein the working procedures correspond to different main raw materials.
The main raw materials of the sintering process comprise dolomite, quicklime, iron ore, coke and the like, and the final product is sinter and byproducts thereof; the main raw materials of the pelletizing process comprise fine iron ore powder, a binder, additives, moisture and the like, and the final product is pellet ore and byproducts thereof; the main raw materials of the coking process comprise various coals and gases, and the products comprise coke, crude benzene, tar and the like; the blast furnace procedure raw materials mainly comprise pellets, sinter, coke, iron ore and various gases, and the products mainly comprise molten iron and blast furnace gases; the main raw materials of the converter process are molten iron, limestone and various ingredients, and the final products are molten steel, converter gas and the like.
Aiming at different raw material ratios and products in different production enterprise flows, a targeted raw material and product database of each procedure is established, and component measurement data are collected.
The period of collecting different materials may be different, and part of the materials adopt the PGNAA technology to carry out real-time component measurement, including iron ore, pellet, sinter and coal dust, can carry out online component detection, effectively reduce errors, and simultaneously can rapidly obtain a large amount of component information; other materials adopt the traditional laboratory component analysis mode, have longer period and have certain hysteresis.
In order to ensure the accuracy of calculation, materials occupying larger carbon emission in the whole production flow, including various pulverized coal and ores, have larger carbon emission factors and larger carbon emission compared with limestone, oxygen, blast air and the like, and for the materials, the sampling period should be shortened as much as possible, while the materials with smaller carbon emission factors and small influence on the whole carbon emission can be properly prolonged, so that the error caused by measurement is reduced.
In general, different sampling periods can make the period of subsequent calculation have a choice, and a shorter calculation period can quickly reflect the change of raw materials, but correspondingly, the burden of calculation can also be increased, and the sampling period should be properly selected according to the actual situation.
Step II, constructing various raw material Gaussian distribution fitting models in different working procedures according to the acquired data and iterating
In the historical production data of the steel combined enterprise, certain data fluctuation exists on the basis of the component proportion of each batch of materials obtained through measurement, and in the calculation of the carbon emission factor, the component proportion of each material is required to be a fixed value, so that the historical production data is subjected to data fitting to obtain the statistical component proportion of each material available for use. In the actual case, the uncertainty of the composition ratio of each material with a fixed source is mainly composed of various uncorrelated random factors, although fluctuation exists, so that the gaussian distribution can be applied to the situation.
Gaussian distribution, also known as normal distribution, is of great importance in many fields of mathematics, physics and engineering, and of great application in statistics. The probability density functions of the one-dimensional gaussian distribution and the multidimensional gaussian distribution are shown below.
Wherein X and X respectively represent one-dimensional variables and multidimensional variables, mu respectively represent one-dimensional means and vector means, and sigma 2 and sigma represent variances.
Based on a Matlab platform, a mean value and a variance are obtained through Gaussian distribution fitting of acquired data, wherein the mean value is used as a material component proportion calculated by a carbon emission factor, and the variance is used for estimating an error of carbon emission calculation.
Setting capacity for a data set of various material components, inputting new data completely before the acquisition quantity does not reach an upper limit, and carrying out normal distribution fitting according to the existing data after each acquisition to obtain a mean value and a variance; after the collection quantity reaches the upper limit, iterative updating is carried out after data are collected each time, oldest data are banned, normal distribution fitting is carried out on the existing data after each input, and iterative updating of raw material components is realized. The flow chart of which is shown in figure 1.
The size of the database is determined according to the actual running condition, a smaller database can adapt to the rapid change of the material composition, and a larger database can stabilize the fluctuation of the material composition, so that the error of composition measurement caused by measurement contingency is reduced.
Step III, determining corresponding carbon emission factors based on various material components
With reference to the carbon emission calculation framework of the WSA method, a carbon mass balance method is adopted to calculate carbon emission factors for actual material components in different production processes so as to obtain more accurate carbon emission.
(1) Direct carbon emission factor determination
Direct carbon emissions include carbon emissions of carbonaceous matter and carbonaceous energy sources, the carbon emission factor of which is determined by the following equation:
wherein EF i is the carbon emission factor of item i, the unit is tCO 2/t;(C)i is the carbon content of item i, and the unit is%.
For example, a certain coal has a carbon content of 63% and a corresponding carbon emission factor of 2.31tCO 2/t.
(2) Indirect carbon emission factor determination
The indirect carbon emission includes power consumption and carbon emission of part of auxiliary materials, including carbon emission caused by electric power and oxygen production, but the carbon emission site is not in the iron and steel united enterprises, and therefore belongs to the indirect carbon emission. Since the gas manufacturing process is mostly produced by consuming electricity, it can be calculated by the electricity carbon emission factor. Table 1 shows the carbon emission factors for the current large grid OM calculation conditions.
TABLE 1 electric carbon emission factor
| Grid name | EFgrid(tCO2/MWh) |
| North China electric network | 0.9437 |
| Northeast electric network | 1.0886 |
| Huadong power grid | 0.7888 |
| Huazhong electric network | 0.8444 |
| Northwest electric network | 0.8990 |
| Southern electric network | 0.8139 |
According to the region of the actual electricity utilization place, the indirect carbon emission factor of the rest materials can be obtained by combining the electric carbon emission factors, and the following formula is shown:
EFi＝EFe·Qei (4)
Wherein EF i is the carbon emission factor of the i th item, the unit is tCO 2/t;EFe is the carbon emission factor of the local power grid, the unit is tCO 2/MWh;Qei is the electricity consumption of the i th item, and the unit is MWh/t.
Table 2 shows the reference carbon emission factors calculated on the basis of the eastern grid for a part of the materials, and the specific results should be combined with the actual results.
TABLE 2 partial Material Indirect carbon emission factor Meter
| Name of the name | Unit (unit) | EF(tCO2/unit) |
| Self-generating power | MWh | 0.389 |
| Blowing air | Km 3 (standard condition) | 0.095 |
| Compressed air | Km 3 (standard condition) | 0.127 |
| Oxygen gas | Km 3 (standard condition) | 1.267 |
| Nitrogen gas | Km 3 (standard condition) | 1.267 |
| Argon gas | Km 3 (standard condition) | 2.122 |
| Steam generation | t | 0.407 |
| New water | t | 0.000243 |
(3) Bucking carbon emission factor determination
In the carbon flow model, carbon substances entering the steel-iron combined enterprise are partially discharged into the environment in the form of carbon dioxide, and the other part leaves the steel-iron combined enterprise in the form of products and byproducts of various procedures or is recycled, wherein the carbon substances comprise sintered ores, pellets or various kinds of coal gas as byproducts. The specific calculation is similar to that of the direct carbon emission factor, and thus will not be described here.
Step IV, carrying the carbon emission factors into each process to calculate the carbon emission
The basic principle of carbon dioxide emission is shown in the following formula according to the principle of the WSA method.
E CO2 = direct emission + indirect emission-offset emission (5) where direct emission refers to CO 2 emitted during production with emission sources owned or controlled by reporting entities. I.e., the CO 2 emissions from the consumption of fossil fuels, fluxes, etc. by the enterprise itself. Indirect emissions are those used by reporting entity activities, but emissions occur from sources of emissions controlled by other entities. The emission of the electric power is generated by the electric power production department, and the emission of CO 2 of the electric power is calculated when the iron and steel enterprises use outsourcing electricity, namely the indirect emission. The offset emissions refer to the offset of CO 2 emissions caused by the sale of byproducts (including tar, crude benzene) or the use of metallurgical slag as cement, etc.
Carbon emission calculation:
CE＝∑EFi direct×Mi direct+∑EFi e×Mi e-∑EFi p×Mi p (6)
Wherein EF i direct and M i direct respectively represent a direct carbon emission factor and a corresponding mass thereof, EF i e and M i e respectively represent an indirect carbon emission factor and a corresponding mass thereof, and EF i p and M i p respectively represent a deduction carbon emission factor and a corresponding mass thereof.
The foregoing is only a preferred embodiment of the invention, it being noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the invention.
Claims (1)
1. The whole-flow carbon emission accounting method for the iron and steel enterprises based on Gaussian distribution fitting and rolling correction is characterized by comprising the following steps of;
Step 1, establishing a targeted raw material and product database of each procedure aiming at different raw material proportions and products in different production enterprise flows, and collecting component measurement data;
The period of collecting different materials may be different, and part of the materials adopt the PGNAA technology to carry out real-time component measurement, including iron ore, pellet, sinter and coal dust, can carry out online component detection, effectively reduce errors, and simultaneously can rapidly obtain a large amount of component information; other materials adopt a traditional laboratory component analysis mode, and have longer period and certain hysteresis;
In order to ensure the accuracy of calculation, materials occupying large carbon emission in the whole production flow are definitely required to be used, and the sampling period is shortened as much as possible; the sampling period of the material with small carbon emission factor and small influence on the whole carbon emission can be properly prolonged, and errors caused by measurement are reduced;
Step 2, constructing various raw material Gaussian distribution fitting models in different procedures according to the acquired data and iterating;
based on a Matlab platform, acquiring a mean value and a variance through Gaussian distribution fitting of acquired data, wherein the mean value is used as a material component proportion calculated by a carbon emission factor, and the variance is used for estimating an error of carbon emission calculation;
Setting capacity for a data set of various material components, inputting new data completely before the acquisition quantity does not reach an upper limit, and carrying out normal distribution fitting according to the existing data after each acquisition to obtain a mean value and a variance; after the collection quantity reaches the upper limit, carrying out iterative updating after each time of data collection, and banning the oldest data, and carrying out normal distribution fitting on the existing data after each time of input, so as to realize iterative updating of the raw material components;
Step 3, referring to a carbon emission calculation frame of a WSA method, adopting a carbon mass balance method, and calculating carbon emission factors aiming at actual material components in different production processes so as to obtain more accurate carbon emission;
the calculation method comprises the following steps:
Step 3.1: calculating a direct carbon emission factor;
direct carbon emissions include carbon emissions of carbonaceous matter and carbonaceous energy sources, the carbon emission factor of which is determined by the following equation:
Wherein EF i is the carbon emission factor of item i, the unit is tCO 2/t;(C)i is the carbon content of item i, and the unit is;
step 3.2: calculating an indirect carbon emission factor;
The indirect carbon emission comprises power consumption and carbon emission of partial auxiliary materials, including carbon emission caused by electric power and oxygen production, but the carbon emission place is not in the iron and steel combined enterprises, thus the indirect carbon emission is included; since the gas manufacturing process is mostly produced by consuming electricity, it can be calculated by the electricity carbon emission factor;
according to the region of the actual electricity utilization place, the indirect carbon emission factor of the rest materials can be obtained by combining the electric carbon emission factors, and the following formula is shown:
EFi＝EFe·Qei
Wherein EF i is the carbon emission factor of the i th item, the unit is tCO 2/t;EFe is the carbon emission factor of the local power grid, the unit is tCO 2/MWh;Qei is the electricity consumption of the i th item, and the unit is MWh/t;
step 3.3: calculating a deduction carbon emission factor;
In the carbon flow model, carbon substances entering the steel combined enterprise are partially discharged into the environment in the form of carbon dioxide, and the other part leaves the steel combined enterprise in the form of products and byproducts of various working procedures or is recycled, wherein the carbon substances comprise sintered ores and pellets of products or various coal gases of byproducts; the specific calculation mode is similar to that of the direct carbon emission factor;
Step 4, carrying the carbon emission factors into each procedure to calculate the carbon emission;
The carbon emission amount calculation formula is as follows:
CE＝∑EFi direct×Mi direct+∑EFi e×Mi e-∑EFi p×Mi p
Wherein EF i direct and M i direct respectively represent a direct carbon emission factor and a corresponding mass thereof, EF i e and M i e respectively represent an indirect carbon emission factor and a corresponding mass thereof, and EF i p and M i p respectively represent a deduction carbon emission factor and a corresponding mass thereof.
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