CN116127690A - Method, system, medium, equipment and terminal for predicting carbon emission of steel - Google Patents
Method, system, medium, equipment and terminal for predicting carbon emission of steel Download PDFInfo
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Abstract
The invention belongs to the technical field of carbon emission control, and discloses a steel carbon emission prediction method, a system, a medium, equipment and a terminal, which are used for analyzing energy consumption in a steel production process, establishing a substance flow balance model and a carbon substance flow model of a production route in a production process and analyzing substance flows and carbon element flows of a certain steel plant; constructing a prediction model of energy consumption-carbon emission of a certain steel plant based on LEAP and a scene analysis method, and predicting the energy consumption and the carbon emission of the certain steel plant in 2020-2050 based on the LEAP model; based on the predicted result, the LMDI factor decomposition method is used for prospective decomposition of carbon emission influencing factors in steel production, and policy suggestion of low-carbon transformation of a certain steel plant is provided. The invention has the innovation points that the carbon emission of a steel plant is predicted, a low-carbon transformation path of the steel plant is provided, and experience and direction are provided for carbon emission reduction of the steel industry through research and analysis of a typical long-flow steel enterprise such as the steel plant.
Description
Technical Field
The invention belongs to the technical field of carbon emission control, and particularly relates to a steel carbon emission prediction method, a steel carbon emission prediction system, a steel carbon emission prediction medium, steel carbon emission prediction equipment and a steel carbon emission prediction terminal.
Background
Currently, the iron and steel industry has great carbon emission reduction potential as one of the main carbon dioxide emission sources worldwide. The carbon emission amount in the steel industry accounts for about 15 percent of the total national carbon emission amount, and is the industry with the largest carbon emission amount in 31 manufacturing industry gates. The green transformation type steel industry is taken as the steel industry of the high-energy industry, is also an important industry of greenhouse gas emission, and has a long green transformation path.
The steel production has three main process routes: coke ovens, blast furnaces and converter steelmaking (BF-BOF process), electric arc furnace steelmaking with scrap (scrap-EAF process) and Direct Reduced Iron (DRI) in electric arc furnace steelmaking (DRI-EAF process) are employed. The traditional blast furnace ironmaking method belongs to a long-flow route, from iron ore to molten iron, through converter steelmaking, and then to refining and continuous casting. The main raw materials of the electric arc furnace steelmaking are scrap steel and 10% of molten iron, the electric arc furnace steelmaking belongs to short-flow steelmaking, the time is less, and the energy consumption and the carbon dioxide emission are also less.
The low-carbon metallurgical technology is blast furnace top gas circulation technology, novel direct reduction technology and novel smelting reduction technology, and is specifically as follows:
(1) Blast furnace top gas circulation technology (TGR-BF)
The blast furnace top gas cycle (TGR-BF) was chosen as the preferred option for the next step of testing on an industrial scale blast furnace, this new technology utilizing oxygen blasting and using vacuum pressure swing adsorption technology to remove carbon dioxide from the blast furnace top gas, after which the blast furnace gas is transported back to the blast furnace for secondary use. After the blast furnace top gas circulation technology is matched with the carbon dioxide capturing and storing technology, compared with the traditional technology, the emission of carbon dioxide can be reduced by 26 percent.
(2) Novel direct reduction technology (ULPORED)
The novel direct reduction process (ULPORED) replaces the traditional reducing agent coke with natural gas, and the reducing gas such as hydrogen generated by the natural gas directly reduces lump ore or pellets into solid iron, but the process has higher cost.
(3) New melt reduction technique (HIsarna)
The new smelting reduction process (HIsarna) process can be broken down into 5 parts: raw material preparation, cyclone melting, secondary combustion, molten pool reduction and waste gas treatment. The sintering and coking processes in the traditional process are avoided, the heat requirement is reduced, and the technology has poorer technical maturity than the first two technologies. Currently, two main low-carbon metallurgical technology paths in the world are mainly divided into two main categories: one is for long process, the carbon dioxide emission reduction is realized mainly by blowing hydrogen-rich reducing gas into a blast furnace to reduce carbon consumption, and the countries currently devoted to researching the path mainly include China, japan, korea, germany and the like; the other is for short flows, and the countries currently researching this path are mainly sweden, austria, germany, etc. Germany and china are rarely two countries where there is a compromise between the two low carbon metallurgical technology studies.
Based on the method, domestic scholars obtain a certain research result on the aspects of research and analysis of carbon emission influence factors, innovation of a carbon emission accounting method, carbon emission prediction in the steel industry and the like. Han Ying and the like calculate the carbon emission conditions of the iron and steel industry in 1994-2006 according to the common method of IPCC, and the analysis results show that the carbon dioxide emission of the iron and steel industry in 1994-2006 is more than 14% of the total emission in China on average. Du Tao, cai Jiuju and the like establish analysis methods of material flows, energy flows and pollutant flows of iron and steel enterprises based on a material balance theory and an input-output theory, and research and analyze changes and progress of ton steel energy consumption and environmental load of the iron and steel industry in China. Luan Tianyang based on LEAP model, different conditions are set Jing Canshu for energy consumption and carbon emission research of Jilin province steel industry, energy demand and carbon emission in 2015-2030 are predicted, and a low-carbon development path of the steel industry is provided through single factor influence analysis and energy-saving low-carbon technology evaluation. Gao Chengkang et al establish an MFAIO model based on a coupling method of logistics analysis and input-output to analyze the carbon footprint of an iron and steel enterprise, and obtain that the iron-making process is the process with the highest carbon emission in the iron and steel production process, the gas with the highest carbon content in each gas type is carbon dioxide, and the carbon dioxide emission in each energy consumption is coal, coke and blast furnace gas. The collyrium et al are based on a mass conservation method and an activity level factor method, account carbon emission of the iron and steel enterprises, only consider direct emission reduction potential, do not carry out deep research on indirect emission reduction potential, and provide a certain help for energy conservation and emission reduction of the iron and steel enterprises. Zhang Huiyi a tens of millions of ton long process steel enterprises are taken as examples, and a method for analyzing carbon emission of the steel enterprises by combining a material flow analysis method with a unit balance model is provided, so that a method and a basis are provided for enterprise carbon emission accounting and carbon emission reduction scheme formulation. Zhao Yiwei the carbon dioxide emission of ton steel of Y steel works is calculated by using a domestic recommended input-output method and an international steel association recommended life cycle method, and a set of greenhouse gas emission calculation method which accords with the national conditions of China steel enterprises based on the full life cycle method is provided from the aspects of calculating boundaries, emission factors, classification of materials and energy sources and evaluating reference lines.
Foreign scholars have achieved a certain research result in the research and prediction of carbon emission reduction in the steel industry. Arens et al analyzed the energy intensity of the German iron and Steel industry between 1991 and 2007 and calculated the contribution of electric arc furnace scale increase and top gas recovery to energy consumption reduction. Johansson and Johansson
Two Swedish iron and steel enterprises are taken as researchesThe object, the potential of the comprehensive steel plant and the steel plant taking scrap steel as raw materials in reducing carbon dioxide emission is analyzed, and the technology for reducing carbon emission in the Swedish steel industry is provided. Worrell E et al calculated that the energy consumption of the United states steel production was reduced by 27% between 1958 and 1994, estimated the carbon dioxide emission reduction, investment cost and operation and maintenance costs of each energy saving measure, analyzed the carbon dioxide emission reduction potential of the United states steel industry, and constructed an economic supply curve for the United states steel production. Wei YM et al analyzed the historical energy efficiency of the steel industry in the middle of 1994-2003 using a Malmequist index decomposition analysis of MPI (Ma Erm Nyquist productivity index). Research shows that the energy efficiency of the steel industry in China is improved by 60% in 1994 to 2003, which is mainly due to technical progress. Leticia O and the like use a physical index-based decomposition method to decompose structural changes and efficiency improvements in departments, analyze the energy use and carbon dioxide emission in the Mexico steel industry in 1970-1996, and use structural/efficiency analysis to compare with international advanced values, thereby giving the best available emission reduction technology. Lin et al use multiple regression models in combination with risk analysis to evaluate the future energy intensity of the Chinese steel industry, and research and development intensity, energy saving investment, labor productivity and industry concentration are all important variables affecting energy intensity. Y Kim et al, analyzed the emission trend of the steel industry by physical index method, and analyzed the steel industry in seven countries, i.e., brazil, china, india (developing country), mexico and korea (emerging industrialized country) and united states (industrialized country). It was found in most countries that yield is a major factor affecting carbon dioxide emissions and energy efficiency is a major factor affecting the strength of emissions in steel production. The Ali Hasanbenigi and the like analyze the emission reduction potential of the steel industry of China by using a conservation supply curve model, compare the energy intensity of the steel industry of China and the steel industry of America, and simultaneously consider the industrial structure between the two countries to obtain that the energy intensity of the steel production of China is higher than that of America, the main reason is that the steel yield of the electric arc furnace of China is low in proportion, and the accumulated cost-effective fuel saving potential of 11999PJ in 2010-2030 years is calculated, so that the carbon dioxide emission 1191Mt is reduced. Seyithan based on LE The AP model builds four different scenes, and estimates the energy consumption and carbon dioxide emission reduction potential of the Turkish iron and steel industry.
The technology uses various research methods to decompose and calculate the carbon emission of the steel industry or the steel enterprises in certain countries and regions, builds a prediction model and obtains a certain research result. However, some techniques adopt inaccurate accounting methods, the research scope is a plurality of main procedures of steel production, and the given measure paths are not comprehensive.
Through the above analysis, the problems and defects existing in the prior art are as follows: the existing steel carbon emission prediction technology adopts an accounting method which is not accurate enough, has a narrow research range and gives an insufficient comprehensive measure path. The index weights of the carbon emission factors and various influencing factors in the steel production process are not clear enough, and a prediction and accounting method for the whole process carbon emission life cycle of the whole steel industrial production is lacked.
Disclosure of Invention
Aiming at the problems existing in the prior art, the invention provides a method, a system, a medium, equipment and a terminal for predicting steel carbon emission.
The invention is realized in such a way that a method for predicting the carbon emission of steel comprises the following steps:
Analyzing energy consumption in the steel production process, establishing a material flow balance model and a carbon material flow model of a production route in the production process, and analyzing material flow and carbon element flow of a certain steel plant; a predictive model of energy consumption-carbon emission of a steel plant based on LEAP and a contextual analysis method is constructed, and the model is built based on LMDI factor decomposition and LEAP model. Determining the index weight of the influence of each influencing factor on the carbon emission in the steel production process by using an LMDI method, and predicting the energy consumption and the carbon emission in 2020-2050 in an embedded LEAP model; and the policy proposal of low-carbon transformation of a certain steel factory is provided for prospective decomposition of carbon emission influencing factors in steel production in the future year.
Further, the steel carbon emission prediction method includes the steps of:
step one, constructing a LEAP model frame and establishing a level 3 index;
setting emission reduction scenes and parameters, and comparing scene simulation results;
and thirdly, analyzing the LMDI influence factors and proposing a low-carbon transformation policy suggestion of a certain steel mill.
Further, the LEAP model framework in the first step comprises a predicted total requirement of a certain steel plant, wherein the total requirement is divided into four parts of fossil fuel, industrial production, electric power and heating power and carbon fixation products; the fossil fuel comprises clean coal, anthracite, bituminous coal, natural gas, coke, diesel oil, coke oven gas, blast furnace gas, converter gas and hydrogen; the industrial production comprises limestone, dolomite, electrodes and scrap steel; the electricity and heat include net purchase electricity and net purchase heat; the carbon-fixing product comprises coarse steel, coarse benzene and tar.
Further, the level 3 index established in the LEAP model framework in the step one includes:
(1) The first level of index is the total demand;
(2) The second level of indexes are the amount of fossil fuel, industrial production, electric power and thermal power and carbon fixation products in total demand respectively;
(3) The third level of indicators are the amount of different fuel types in fossil fuels, the amount of different raw material types in industrial production, the specific amounts of electricity and heat, the amount of coarse steel, coarse benzene and tar in carbon-fixing products, respectively.
Further, the emission reduction scene in the second step includes a reference scene, an energy efficiency improvement scene and an energy structure change scene; the parameters include crude steel yield, iron to steel ratio, blast furnace ratio, electric furnace ratio, and energy intensity.
Further, the LMDI influencing factor analysis in the third step includes:
(1) Total yield of coarse steel Q;
(2) The proportions representing the various carbon emissions include: emissions from the combustion of fossil fuels, emissions from solvent consumption in industrial processes, emissions from net purchase of electricity and thermal counterparts, and emissions implicit in carbon sequestration products;
(3) Carbon emission intensity: representing the carbon dioxide emissions produced per ton of crude steel;
the total carbon emissions of the steel industry are expressed as:
Wherein, subscript i=1, 2, 3, 4 represents the carbon emission type, the emission of fossil fuel combustion, the emission generated by solvent consumption in the industrial production process, the emission corresponding to the net purchase of electric power and heat, and the emission implied by the carbon fixation product; the LMDI decomposition analysis method is utilized to obtain:
ΔC tot ＝C T -C 0 ＝ΔC pdn +ΔC int +ΔC str ；
wherein C is carbon emission; q is the yield of the coarse steel; c (C) i Representing carbon emissions of different carbon emission types; i i Is the ratio of carbon emission to crude steel yield, and represents the carbon emission intensity; s is S i Is the ratio of the carbon emission amount of different carbon emission types to the total carbon emission amount, and represents the carbon emission structure; t is the last year of the period; t=0 is the reference year of the period; ΔC tot Is the total carbon dioxide emission variation; ΔC pdn The emission reduction contribution degree for the yield of the crude steel; ΔC int The emission reduction contribution degree for the carbon emission intensity; ΔC str Contributing to the emission reduction of the carbon emission structure.
The contribution degree delta C of the coarse steel yield and the emission reduction of three scenes is obtained by using LMDI addition factor decomposition calculation pdn Emission reduction contribution degree Δc of carbon emission intensity int And the emission reduction contribution degree deltac of the carbon emission structure str 。
Another object of the present invention is to provide a steel carbon emission prediction system to which the steel carbon emission prediction method is applied, the steel carbon emission prediction system comprising:
The energy consumption analysis module is used for analyzing the production energy consumption of a certain steel plant, establishing a material flow balance model and a carbon material flow model of a production route of a production process, and analyzing the material flow and the carbon element flow of the certain steel plant;
the prediction model construction module is used for constructing a prediction model of energy consumption-carbon emission of a certain steel plant based on LEAP and a scene analysis method, and predicting the energy consumption and the carbon emission of the certain steel plant in 2020-2050 years based on the LEAP model;
and the factor decomposition module is used for prospective decomposing carbon emission influencing factors in steel production by using an LMDI factor decomposition method based on the predicted result and providing policy suggestions for low-carbon transformation of a certain steel plant.
Another object of the present invention is to provide a computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of the steel carbon emission prediction method.
Another object of the present invention is to provide a computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of the steel carbon emission prediction method.
Another object of the present invention is to provide an information data processing terminal for implementing the steel carbon emission prediction system.
In combination with the technical scheme and the technical problems to be solved, the technical scheme to be protected has the following advantages and positive effects:
the invention predicts the energy consumption and carbon emission of a steel plant 2020-2050 based on the LEAP model. The method is characterized in that three scenes of a reference scene, an energy efficiency improvement scene and an energy structure change scene are set, parameters are set on main influencing factors such as coarse steel yield, iron-steel ratio, blast furnace ratio, electric furnace ratio, energy intensity, equipment structure, production structure, energy-saving low-carbon technology popularity rate and the like, and three scene carbon emission prediction change comparison diagrams are obtained. Based on the predicted results of energy consumption and carbon emission in the steel works 2020-2050, the influence factors in the predicted results are decomposed by using an LMDI (least squares direct injection) additive decomposition method.
The invention analyzes the energy consumption in the steel production process, establishes a mass flow balance model and a carbon mass flow model of a production route in the production process, and analyzes the mass flow and the carbon element flow of a certain steel plant; constructing a prediction model of energy consumption-carbon emission of a certain steel mill based on LEAP and a scene analysis method; based on the LEAP model, the energy consumption and carbon emission of the steel plant are predicted, based on the predicted result, the LMDI factor decomposition method is used for prospective decomposition of carbon emission influencing factors in steel production, policy suggestion of low-carbon transformation is provided, and experience is provided for the low-carbon transformation of the steel industry in China.
According to the invention, the energy consumption and the carbon substance flow in the production process are analyzed, and a prediction model of energy consumption-carbon emission of a certain steel mill based on LEAP and a scene analysis method is constructed; based on the prediction result, an LMDI factor decomposition method is adopted to decompose carbon emission influencing factors of a steel plant, a low-carbon transformation path of a certain steel plant is provided, and guidance is provided for low-carbon transformation of the steel industry in China.
In addition, the main innovation point of the method is that the carbon emission of the steel mill is predicted, meanwhile, the predicted result of the carbon emission of the steel mill is subjected to prospective analysis of influence factors, and the prospective analysis result of the influence factors is referred to find out the importance of carbon emission reduction in the future. The invention is through the research and analysis of a typical long-flow steel enterprise in a country such as a certain steel factory.
The expected benefits and commercial values after the technical scheme of the invention is converted are as follows: the method can accurately predict the carbon emission of future years in the industrial production process of the tapping iron, and can guide the key direction of carbon emission reduction, thereby saving the cost for enterprises.
The technical scheme of the invention fills the technical blank in the domestic and foreign industries: and intuitively analyzing the index weight value of the influence of various influencing factors on the carbon emission in the industrial production process of the tapping iron. Fills the technical blank in the domestic and foreign industries.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments of the present invention will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for predicting carbon emission of steel provided by an embodiment of the invention;
FIG. 2 is a diagram of a LEAP model framework provided by an embodiment of the present invention;
fig. 3 is a reference scenario carbon emission prediction map provided by an embodiment of the present invention;
fig. 4 is a graph of a reference scenario fossil fuel combustion carbon emission prediction provided by an embodiment of the present invention;
FIG. 5 is a graph of a benchmark scenario industrial process carbon emission prediction provided by an embodiment of the present invention;
FIG. 6 is an energy efficiency improvement scenario carbon emission prediction map provided by an embodiment of the present invention;
FIG. 7 is a graph of energy efficiency improvement scenario fossil fuel combustion carbon emission predictions provided by an embodiment of the present invention;
FIG. 8 is a graph of predicted carbon emissions for an energy efficiency improvement scenario industrial process provided by an embodiment of the present invention;
fig. 9 is a graph of prediction of carbon emissions for an energy structure change scenario provided by an embodiment of the present invention;
Fig. 10 is a graph showing prediction of fossil fuel combustion carbon emission in accordance with an embodiment of the present invention;
FIG. 11 is a graph showing the prediction of carbon emissions in an industrial process for energy structure change scenarios provided by embodiments of the present invention;
fig. 12 is a view showing a prediction of fossil fuel consumption in the case of energy structure change according to the embodiment of the present invention;
FIG. 13 is a graph comparing predicted changes in carbon emissions for three scenarios provided by an embodiment of the present invention;
FIG. 14 is a view of a predictive analysis of reference scenario impact factors provided by an embodiment of the present invention;
FIG. 15 is a graph of predictive analysis of energy consumption improvement scenario impact factors provided by an embodiment of the present invention;
fig. 16 is a predictive analysis chart of the influence factors of the scene of the energy structure change provided by the embodiment of the invention;
fig. 17 is a schematic view showing a process for producing hydrogen direct reduced iron according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the following examples in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Aiming at the problems existing in the prior art, the invention provides a method, a system, a medium, equipment and a terminal for predicting steel carbon emission, and the invention is described in detail below with reference to the accompanying drawings.
In order to fully understand how the invention may be embodied by those skilled in the art, this section is an illustrative embodiment in which the claims are presented for purposes of illustration.
As shown in fig. 1, the method for predicting the carbon emission of steel provided by the embodiment of the invention comprises the following steps:
s101, analyzing energy consumption in the steel production process, establishing a mass flow balance model and a carbon mass flow model of a production route in the production process, and analyzing mass flow and carbon element flow of a certain steel plant;
s102, constructing a prediction model of energy consumption-carbon emission of a certain steel plant based on LEAP and a scene analysis method, and predicting future energy consumption and carbon emission of the steel plant based on the LEAP model;
s103, based on the predicted result, utilizing an LMDI factor decomposition method to prospectively decompose carbon emission influencing factors in steel production, and providing policy suggestion of low-carbon transformation of a certain steel mill.
The LEAP model framework in the step S101 provided by the embodiment of the invention comprises a predicted total demand of a certain steel plant, wherein the total demand is divided into four parts of fossil fuel, industrial production, electric power and heating power and carbon fixation products; the fossil fuel comprises clean coal, anthracite, bituminous coal, natural gas, coke, diesel oil, coke oven gas, blast furnace gas, converter gas and hydrogen; industrial production includes limestone, dolomite, electrodes and scrap steel; electricity and heat include net purchase electricity and net purchase heat; carbon-fixing products include crude steel, crude benzene and tar.
The 3-level index established in the LEAP model framework in step S101 provided by the embodiment of the present invention includes:
(1) The first level of index is the total demand;
(2) The second level of indexes are the amount of fossil fuel, industrial production, electric power and thermal power and carbon fixation products in total demand respectively;
(3) The third level of indicators are the amount of different fuel types in fossil fuels, the amount of different raw material types in industrial production, the specific amounts of electricity and heat, the amount of coarse steel, coarse benzene and tar in carbon-fixing products, respectively.
The emission reduction scene of the step S102 provided by the embodiment of the invention comprises a reference scene, an energy efficiency improvement scene and an energy structure change scene; parameters include crude steel yield, iron to steel ratio, blast furnace ratio, electric furnace ratio, and energy intensity.
The LMDI influence factor analysis in step S103 provided by the embodiment of the present invention includes:
(1) Total yield of coarse steel Q;
(2) The proportions representing the various carbon emissions include: emissions from the combustion of fossil fuels, emissions from solvent consumption in industrial processes, emissions from net purchase of electricity and thermal counterparts, and emissions implicit in carbon sequestration products;
(3) Carbon emission intensity: representing the carbon dioxide emissions produced per ton of crude steel;
The total carbon emissions of the steel industry are expressed as:
wherein, subscript i=1, 2, 3, 4 represents the carbon emission type, the emission of fossil fuel combustion, the emission generated by solvent consumption in the industrial production process, the emission corresponding to the net purchase of electric power and heat, and the emission implied by the carbon fixation product; the LMDI decomposition analysis method is utilized to obtain:
ΔC tot ＝C T -C 0 ＝ΔC pdn +ΔC int +ΔC str ；
wherein C is carbon emission; q is the yield of the coarse steel; c (C) i Representing carbon emissions of different carbon emission types; i i Is the ratio of carbon emission to crude steel yield, and represents the carbon emission intensity; s is S i Is the ratio of the carbon emission amount of different carbon emission types to the total carbon emission amount, and represents the carbon emission structure; t is the last year of the period; t=0 is the reference year of the period; ΔC tot Is the total carbon dioxide emission variation; ΔC pdn The emission reduction contribution degree for the yield of the crude steel; ΔC int The emission reduction contribution degree for the carbon emission intensity; ΔC str Contributing to the emission reduction of the carbon emission structure.
The contribution degree delta C of the coarse steel yield and the emission reduction of three scenes is obtained by using LMDI addition factor decomposition calculation pdn Emission reduction contribution degree Δc of carbon emission intensity int And the emission reduction contribution degree deltac of the carbon emission structure str 。
The steel carbon emission prediction system provided by the embodiment of the invention comprises:
The energy consumption analysis module is used for analyzing the production energy consumption of a certain steel plant, establishing a material flow balance model and a carbon material flow model of a production route of a production process, and analyzing the material flow and the carbon element flow of the certain steel plant;
the prediction model construction module is used for constructing a prediction model of energy consumption-carbon emission of a certain steel plant based on LEAP and a scene analysis method, and predicting the energy consumption and the carbon emission of the certain steel plant in 2020-2050 years based on the LEAP model;
and the factor decomposition module is used for prospective decomposing carbon emission influencing factors in steel production by using an LMDI factor decomposition method based on the predicted result and providing policy suggestions for low-carbon transformation of a certain steel plant.
The embodiment of the invention has a great advantage in the research and development or use process, and has the following description in combination with data, charts and the like of the test process.
Examples: prediction of carbon emissions from steelworks
1. LEAP model framework
The embodiment of the invention predicts the energy consumption and carbon emission data of a certain steel plant in 2019-2050, selects the LEAP model as an analysis tool, and focuses on analyzing the energy supply and consumption change trend and the corresponding energy consumption and carbon emission peak situation of the certain steel plant under different policy plans, thereby contributing to the future green low-carbon transformation building of the certain steel plant. Wherein parameters such as carbon emission factor are entered in the main hypothesis. Establishing 3-level indexes in the framework, wherein the contents of each index are as follows:
(1) The first level of index is the total demand.
(2) The second level of indicators are the amount of fossil fuel, industrial production, electrical and thermal, and carbon sequestration products, respectively, in total demand.
(3) The third level of indicators are the amount of different fuel types in fossil fuels, the amount of different raw material types in industrial production, the specific amounts of electricity and heat, the amount of coarse steel, coarse benzene and tar in carbon-fixing products, respectively.
A specific frame is shown in fig. 2. In the LEAP model, the total demand is divided into four parts, fossil fuels, industrial production, electricity and heat, and carbon sequestration products. Fossil fuels comprise clean coal, anthracite, bituminous coal, natural gas, coke, diesel oil, coke oven gas, blast furnace gas, converter gas and hydrogen; industrial production comprises limestone, dolomite, electrodes and scrap steel; electricity and heat include net purchase electricity and net purchase heat; the carbon-fixing product comprises coarse steel, coarse benzene and tar. The existing fuel types of a certain steel plant and the fuel types possibly introduced in future development processes, such as hydrogen and the like, are fully considered in the construction of the model.
2. Scenario setting and parameter setting
2.1 scenario set-up
The factors influencing the energy consumption and the carbon emission of the invention are based on the analysis results of the energy consumption and the carbon emission of the third chapter, and are also drawn up by referring to the literature and industry association data. The invention designs three different emission reduction scenes, the 2019 is taken as a reference year, the time span is set to 2019-2050, and reasonable emission reduction measures are explored from the three different emission reduction scenes, so that the invention provides the basis of policy planning for the Wuhan city government and the steel industry. The specific scenario is described as follows:
(1) Reference scene
The reference scene takes the related parameters of steel production in 2019 of a certain steel mill as the reference parameters, and the energy efficiency improvement scene and the energy structure change scene are larger than the reference scene in energy conservation and emission reduction. And estimating the change condition of the carbon emission of the 2050 steel plant according to the reference parameters. The situation is set in such a way that the energy structure of a certain steel mill is not changed; the energy saving and emission reduction strength is kept unchanged, and the energy consumption of unit products is reduced slowly; the yield of the crude steel in a certain steel factory keeps the original descending trend, but the descending speed of the yield of the crude steel is slower; the electric furnace steel ratio of a certain steel plant is not improved and is still zero; the iron-steel ratio has a larger gap with the advanced level in China, and the popularity of non-blast furnace ironmaking technology is slowly increased; the utilization rate of the scrap steel is slowly improved; energy saving and emission reduction technologies represented by dry quenching, sintering desulfurization and blast furnace residual pressure recovery are widely applied, and other key technologies are relatively slow to popularize.
(2) Energy efficiency improvement scenario
Under the situation of energy efficiency improvement, the capacity elimination speed after elimination is faster than that of the reference situation, the steel capacity is not increased again, and the crude steel yield of a certain steel factory gradually drops after reaching a peak value in 2018; the energy saving and emission reduction force is greater than that of the reference situation, and the comprehensive energy consumption level of ton steel is reduced faster than that of the reference situation; the electric furnace steel ratio is improved, but the lifting is slow; the iron-steel ratio starts to decline slowly, but a larger gap still exists between the iron-steel ratio and the advanced level in China, and the non-blast furnace ironmaking technology is not popularized yet; the utilization rate of the scrap steel is greatly improved; under the condition that the technologies of fan variable frequency speed regulation, dry quenching technology, sintering desulfurization, regenerative heating furnace technology, blast furnace residual pressure recovery, sintering waste heat recovery power generation technology and the like are adopted, a certain steel plant further implements and promotes the energy saving and emission reduction technology.
(3) Energy structure change scenario
The energy structure reform of the iron and steel industry is completed, and the transformation and the upgrading are successful. The energy structure change scene is based on an energy efficiency improvement scene, and under the scene, key energy saving and emission reduction technologies are comprehensively popularized, and advanced energy saving and emission reduction technologies are comprehensively popularized; the productivity of the crude steel is steadily reduced; the product structure is optimized; long-process steelmaking is gradually replaced by short-process steelmaking; the energy consumption of unit products of a certain steel mill is greatly reduced, and the international advanced level is reached; setting the electric furnace steelmaking proportion in the steel industry of Wuhan in 2019-2050 to continuously increase, and popularizing non-blast furnace ironmaking technology; the utilization rate of the scrap steel is greatly improved, and the iron-steel ratio is continuously reduced; the consumption of fossil energy is greatly reduced.
The invention takes the difference value among three different scenes as the potential of carbon emission reduction of a certain steel plant. The energy efficiency improvement scene is to increase the implementation and popularization of the energy saving technology on the basis of the reference scene, and the energy structure change scene is to increase the change of the energy structure on the basis of the energy efficiency improvement scene.
2.2 parameter settings
The research influence factors mainly comprise coarse steel yield, iron-steel ratio, blast furnace ratio, electric furnace ratio, energy intensity, equipment structure, production structure and energy-saving low-carbon technology popularity rate. The invention sets the scene parameters as shown in table 1, wherein the high, medium and low represent the activity level of each influence factor, the high in the positive index represents the maximum increase amplitude, and the low in the negative index represents the maximum increase amplitude. The specific setting of the parameters takes five time nodes of 2020, 2025, 2030, 2035 and 2050.
TABLE 1 selection of parameters under different scenarios
(1) Yield of crude steel
To predict and analyze the total carbon emissions of a steel mill 2020-2050, it is necessary to estimate the future trend of the crude steel yield of a steel mill. In combination with the actual situation of a certain steel mill, the coarse steel yield of the certain steel mill in 2019-2050 is set to show a slow descending trend according to the policy opinion. The specific time nodes are set in tables 3, 4 and 5 after parameter adjustment, and the yield reduction speeds of the coarse steel in three different scenes are different. As the yield of the crude steel decreases, the consumption of various fossil energy sources is driven to decrease, and the specific parameter table of the various fossil energy sources is shown.
(2) Energy intensity
In 2020, the comprehensive energy consumption of ton steel of a certain steel factory is 569 kg of standard coal per ton steel, and the comprehensive energy consumption set value of ton steel of a certain steel factory is 540 kg of standard coal per ton steel in the situation of energy efficiency improvement and is lowered at different speeds under different situations in consideration of the fact that the electric furnace ratio of foreign steel to a certain steel factory and the waste steel utilization rate are too large.
(3) Equipment structure
At present, a steel mill normally runs a 5-seat blast furnace, an electric furnace is not used, scrap steel is directly put into a converter, and the iron-steel ratio is reduced in this way. The iron to steel ratio was decreased at different rates in different scenarios and the electric furnace ratio was increased at different rates in different scenarios, wherein the reference scenario and the energy efficiency improvement scenario were still without changing the energy structure by introducing electric furnaces, the electric furnace ratio remained zero, in the energy structure change scenario, the electric furnace ratio parameter setting was increased by about 30% in the developed state of electric furnace ratio, the world electric furnace steel ratio was about 30%, and the united states was 60%, as shown by the arc furnace ratio in the united states ferrous metallurgical industry of table 2, the united states electric furnace ratio increase period was 1960 to 1985, and the long-term trend was to gradually increase the electric furnace steel ratio. With reference to the data and the actual conditions in China, setting the specific parameters of the electric furnace of a certain steel mill to continuously rise.
Table 2 arc furnace in the united states ferrous metallurgy industry
(4) Emission factor
For fossil fuels, the emission factor is basically unchanged with time, and is set to be a constant value, and a statistical monitoring value of a certain steel plant or a default value in a greenhouse gas emission accounting method and report guidelines (trial) of China steel manufacturing enterprises are used, and an IPCC default value in a TED template of a LEAP model is adopted for the emission factor which is not provided by the certain steel plant.
(5) Scrap ratio
The steel is generally changed into scrap steel after 8-30 years of use, the scrap steel resources are rapidly increased, and the scrap steel consumption is increased year by year. Referring to the prediction result of the total amount of Chinese scrap steel resources, the parameters are set as follows:
table 3 parameter settings under reference scenario
Table 4 energy efficiency improvement scenario parameter settings
Table 5 parameter settings in energy structure change scenarios
3. Comparison of simulation results of three scenes of certain steel mill
3.1 reference scenarios
Fig. 3 is a graph showing a comparison of predicted changes in carbon emissions in a reference scenario, in which the fossil fuel-fired carbon emissions of a steel mill are carbon emissions having the largest proportion, the fossil fuel-fired carbon emissions are slowly reduced substantially as the yield of the raw steel is reduced, the amount of carbon dioxide emissions generated by the net purchased electricity and heat is inferior to the amount of carbon emissions generated by the fossil fuel-fired carbon emissions, in which the amount of net purchased electricity is not greatly changed, the proportion of outsourced green electricity is not increased or decreased, and the amount of carbon emissions is substantially maintained. The carbon dioxide emission amount implied by the carbon-fixing product of a certain steel mill is very small in proportion to the carbon dioxide emission amount of the certain steel mill, and the variation is hardly displayed on the carbon emission diagram of the whole certain steel mill, so that the carbon-fixing product is not the key point of emission reduction of the certain steel mill.
Under the implementation of the existing energy-saving and emission-reducing technology and according to the trend of the decrease of the coarse steel yield in 2011-2019, the carbon dioxide emission generated by the combustion activity of the net consumption fossil fuel is slowly decreased. Fig. 4 is a graph showing the prediction of the carbon emissions from the combustion of reference fossil fuels, and it can be seen that the consumption of clean coal is decreasing, because the outsourcing amount of coke is increasing in recent years for a steel mill to reduce the carbon emissions. In the baseline scenario, this trend will continue to hold, with the consumption of coke increasing. The consumption of bituminous coal is reduced at a certain rate because, in the sintering process, a certain steel mill has replaced general bituminous coal with anthracite in order to reduce environmental pollution, but both anthracite and bituminous coal are used in the iron-making process. Although anthracite replaces bituminous coal, the consumption of anthracite is reduced due to the reduction of the yield of coarse steel, and the consumption of anthracite in a certain steel plant has a tendency of slowly increasing in combination with the actual situation of energy consumption analysis of the certain steel plant, so that the consumption of anthracite still has a tendency of slowly increasing. The natural gas consumption and blast furnace gas consumption fluctuation are small. The yield of byproducts such as tar, crude benzene and the like is relatively small, the fluctuation is small, and the influence on the whole carbon emission is small.
The carbon dioxide emissions generated in the industrial process are mainly due to the fact that dolomite and limestone are used as the carbon dioxide emissions generated by the solvent consumption in the ironmaking process, the dolomite and limestone consumption does not change much without a change in technology, fig. 5 is a graph of a reference scene industrial process carbon emissions prediction, the dolomite and limestone consumption and the generated carbon dioxide emissions decrease due to a change in the yield of coarse steel, the electrode is small and the consumption does not change, and although the consumption of scrap is increasing in the reference scene, the carbon dioxide emissions of the electrode and the scrap are small and substantially unchanged due to a too small emission factor of the scrap. The carbon dioxide emissions produced by the industrial process decrease with the production of the crude steel.
3.2 energy efficiency improvement scenarios
Fig. 6 is a graph showing a comparison of predicted changes in carbon emissions for an energy efficiency improvement scenario where fossil fuel-fired carbon emissions from a steel mill remain the largest carbon emissions, the fossil fuel-fired carbon emissions slowly decrease with decreasing levels of coarse steel production, and the net purchased power and thermal generated carbon dioxide emissions are inferior to the fossil fuel-fired carbon emissions, and the net purchased power and thermal carbon emissions slowly decrease as well. The hidden carbon dioxide emission of the carbon-fixing product of a certain steel mill is very small in proportion to the carbon dioxide emission of the certain steel mill, and the variation is hardly displayed on the carbon emission diagram of the whole certain steel mill, so that the carbon-fixing product is not the key point of emission reduction.
As shown in fig. 7, when the energy saving and emission reduction technology is further applied, the carbon dioxide emission amount generated by the combustion activity of the net consumed fossil fuel continuously decreases in the year 2020 to 2050 according to the trend of decreasing the coarse steel yield in 2011 to 2019. As the outsourcing amount of coke is increased in a certain steel mill, the consumption amount of clean coal is rapidly reduced. The consumption of bituminous coal decreases at a certain rate, and anthracite coal replaces general bituminous coal, resulting in an increase in the consumption of anthracite coal. The reduction of the coarse steel yield also reduces the consumption of anthracite coal, the consumption of the anthracite coal of a certain steel plant is kept at a constant level in recent years, and the consumption of the anthracite coal in the future has a basically constant trend under the condition of energy efficiency improvement. The natural gas consumption and blast furnace gas consumption fluctuation are small. The yield of byproducts such as tar, crude benzene and the like is relatively small, the fluctuation is small, and the influence on the whole carbon emission is small.
As shown in fig. 8, the carbon dioxide emissions generated in the industrial process are mainly due to the fact that dolomite and limestone serve as carbon dioxide generated by solvent consumption in the ironmaking process, and in the case of energy efficiency improvement, only energy saving and emission reduction technology is added, and no change of energy structures and ironmaking and steelmaking technology is involved, so that the dolomite and the limestone still serve as solvents in the ironmaking process, and the consumption of the dolomite and the limestone and the generated carbon dioxide are reduced due to the change of the coarse steel yield. Meanwhile, under the condition of energy efficiency improvement, the scrap steel ratio is further improved relative to the reference scene, and the figure shows that the carbon dioxide amount generated by the scrap steel is increased, but the total carbon dioxide emission generated in the industrial production process is influenced little due to the fact that the emission factor is too small, so that the carbon dioxide emission generated in the industrial production process basically shows a declining trend.
Under the circumstance of energy efficiency improvement, under the promotion of technologies such as top pressure recovery power generation (dry TRT), converter gas dry recovery and the like, the amount of electricity and heat generated by net purchase can be slowly reduced, the proportion of outsourcing green electricity is increased, and the amount of carbon emission generated by the net purchase amount of electricity and heat can be reduced.
3.3 energy Structure Change scenario
As shown in fig. 9, it can be seen that a certain steel plant is developed according to the energy structure change scenario.
As shown in fig. 10, when the energy saving and emission reduction technology is further popularized, a new iron making and steel making technology is introduced into a certain steel plant, the traditional long-process steel making is gradually replaced by the short-process steel making, the carbon emission of fossil fuel combustion is greatly reduced, bituminous coal is completely abandoned by the certain steel plant after 2035 years, and the consumption of clean coal, coke and smokeless coal is also reduced year by year. As shown in fig. 11, the carbon emissions in the industrial process decreased year by year, and the carbon emissions decrease rate increased after 2035.
As can be seen from the energy structure change scenario fossil fuel consumption prediction fig. 12, hydrogen has been used as an energy source in 2025, 2035 is an important time node, the hydrogen smelting iron and steel technology is mature, the hydrogen usage amount has been greatly increased, and under the energy structure change scenario, it is assumed that the experimental hydrogen metallurgy technology is started in 2025, and the technology is mature and put into use in large quantities in 2035. Therefore, fossil energy sources such as clean coal, anthracite and the like can exit the stage of iron and steel smelting at a faster speed after 2035 years. The carbon dioxide emissions from the net consumption fossil fuel combustion activities in 2020-2050 continue to drop substantially, and by 2050, the carbon dioxide emissions from the fossil fuel combustion activities have been controlled below 50 ten thousand tons.
The carbon dioxide emission generated in the industrial production process is mainly due to the fact that dolomite and limestone are used as carbon dioxide generated by solvent consumption in an iron-making process, under the condition of energy structure change, an energy-saving and emission-reducing technology is added, and under the change of the iron-making and steel-making technology, the consumption of the dolomite and the limestone is reduced along with the yield of steel before 2035 years; after 2035, the consumption of dolomite and limestone is greatly reduced, and the hydrogen energy steelmaking replaces the traditional long-flow steelmaking due to the generation of a new steelmaking technology, and the dolomite and the limestone do not serve as solvents in the sintering and ironmaking processes any more, so the carbon dioxide emission generated in the industrial production process is approaching zero in 2050.
Under the condition of energy structure change, the consumption of electric power and heat is reduced under the popularization of technologies such as top pressure recovery power generation (dry TRT), converter gas dry recovery and the like, but the proportion of electric furnace steelmaking is increased, the proportion of outsourced green electric power is greatly increased, and under the comprehensive influence of the factors, the simulation result shows that the amount of the electric power purchased in a net way and the carbon emission generated by heat are reduced.
The carbon dioxide emission amount implied by the carbon-fixing product of a certain steel mill is small because the carbon dioxide emission amount accounts for a small proportion of the carbon dioxide emission amount of the certain steel mill, and the change amount is also small under the condition of energy structure change, and is not the key point of carbon emission reduction work of the certain steel mill.
3.4 three scene contrast analysis
Fig. 13 is a graph showing the predicted change in carbon emissions for three scenarios.
4. LMDI influence factor analysis
4.1LMDI decomposition
In the present invention, only a certain steelworks is subjected to decomposition analysis, not the entire manufacturing department. Thus, the decomposition formula and the factors to be considered are corrected. Based on the availability of data and important factors affecting the use of energy sources in steel production, the invention modifies the LMDI decomposition formula as follows: several main factors affecting the energy consumption of steel production are considered, and a decomposition formula is proposed according to the factors. These factors are:
1. total yield of crude steel Q.
2. Representing the ratio of various carbon emissions, four types are available: emissions from the combustion of fossil fuels, emissions from solvent consumption in industrial processes, emissions from net purchase of electricity and thermal counterparts, and emissions implicit in carbon sequestration products.
3. Carbon emission intensity: representing the carbon dioxide emissions produced per ton of crude steel.
The total carbon emissions of the steel industry are expressed as:
wherein, subscript i=1, 2, 3, 4 indicates the carbon emission type, the emissions of fossil fuel combustion, the emissions generated by solvent consumption in industrial production, the emissions corresponding to net purchase of electricity and heat, and the emissions implied by carbon fixation products. By using the LMDI decomposition analysis method, the invention can obtain:
ΔC tot ＝C T -C 0 ＝ΔC pdn +ΔC int +ΔC str (5)
in the formula (2), C is carbon emission; q is the yield of the coarse steel; c (C) i Representing carbon emissions of different carbon emission types; i i Is the ratio of carbon emission to crude steel yield, and represents the carbon emission intensity; s is S i Is the ratio of the carbon emission amount of different carbon emission types to the total carbon emission amountRepresenting the carbon emission structure. In formula (5), T is the last year of the period; t=0 is the baseline year for this period; ΔC tot Is the total carbon dioxide emission variation; ΔC pdn The emission reduction contribution degree for the yield of the crude steel; ΔC int The emission reduction contribution degree for the carbon emission intensity; ΔC str Contributing to the emission reduction of the carbon emission structure.
4.2 influence factor analysis
The contribution degree delta C of the coarse steel yield and emission reduction of three scenes in the table 6 is obtained by decomposing and calculating by using LMDI addition factors pdn Emission reduction contribution degree Δc of carbon emission intensity int And the emission reduction contribution degree deltac of the carbon emission structure str 。
Fig. 14, 15 and 16 are drawn from table 6 as follows. It can be seen that in three situations, the contribution of the coarse steel yield to the reduction of the carbon emission is the largest, the contribution degree of the carbon emission intensity is slightly smaller, the contribution degree of the carbon emission structure is almost negligible, and in the energy structure change situation, the emission reduction contribution degree of the carbon emission structure reaches-36.2 ten thousand tons of carbon dioxide only because the hydrogen energy steelmaking is set to be used in a large amount within the time span of 2045-2050.
TABLE 6 selection of parameters under different scenarios
From the predictive analysis of the baseline scenario impact factors, it can be seen that the emission reduction contribution of the coarse steel yield is as high as-124.6 ten thousand tons of carbon dioxide in the time span 2020-2025. Within 2025-2030, 2030-2035, 2035-2040, 2040-2045, 2045-2050, the contribution degree of the coarse steel yield to carbon emission reduction is reduced, but the contribution degree to carbon emission reduction is still the largest. The energy consumption structure and the energy technical level are not basically changed due to slow structure adjustment, green development and autonomous innovation process, so that the emission reduction contribution degree of the carbon emission intensity is-53 ten thousand tons of carbon dioxide. Within 2025-2030, 2030-2035, 2035-2040, 2040-2045, 2045-2050, the contribution degree of carbon emission intensity to carbon emission reduction is in a decreasing trend due to the gradual application of the energy saving and emission reduction technology. Since the proportions of fossil fuel combustion emissions, solvent consumption emissions during industrial production, net purchase of electricity and thermal counterparts, and implied emissions of carbon sequestration products have not been altered, the emission reduction contribution of carbon emission structures has been negligible within 2020-2050.
According to the prediction analysis of the energy consumption improvement scene influence factors, under the situation that the obsolete productivity is increased and the newly increased steel productivity is strictly forbidden, the emission reduction contribution degree of the coarse steel output in the time span of 2020-2025 is up to-355.8 ten thousand tons of carbon dioxide. Within 2025-2030, 2030-2035, 2035-2040, 2040-2045, 2045-2050, the contribution degree of the coarse steel yield to carbon emission reduction is reduced, but the contribution degree to carbon emission reduction is still the largest. Under the background of deepening energy consumption adjustment, transformation and upgrading in the steel industry and promoting and reforming the comprehensive promotion energy-saving technology, the emission reduction contribution degree of the carbon emission intensity in 2020-2025 years is-156.4 ten thousand tons of carbon dioxide. However, the carbon emission intensity is obviously reduced in the time periods of 2025 to 2030, 2030 to 2035, 2035 to 2040, 2040 to 2045 and 2045 to 2050 years. Since the iron and steel industry production technology does not change fundamentally, the emission of fossil fuel combustion, the emission generated by solvent consumption in the industrial production process, the emission corresponding to the net purchase power and heat and the hidden emission proportion of the carbon-fixing products are not changed, and the emission reduction contribution degree of the carbon emission structure is negligible.
From the predictive analysis of the influence factors of the scene of the energy structure change, the emission reduction contribution degree of the coarse steel yield in the time span of 2020-2025 is up to-500.9 ten thousand tons of carbon dioxide. Within 2025-2030, 2030-2035, 2035-2040, 2040-2045 and 2045-2050, the contribution degree of the coarse steel yield to carbon emission reduction reaches-225.9-169.3-105-81.4-27.1-ten thousand, respectively, and the contribution degree of the carbon emission strength to carbon emission reduction exceeds the coarse steel yield within the time period 2035-2040. This means that there is no need to reduce carbon emissions by greatly reducing the capacity in the context of energy structure changes. The rapid decrease in the contribution of steel yield to carbon reduction corresponds to a rapid increase in the contribution of carbon emission intensity to carbon reduction.
Under the background that the energy consumption adjustment, transformation and upgrading of the steel industry are deepened, the energy saving technology is comprehensively advanced, the energy structure is reformed, and the transformation and upgrading are successful, the emission reduction contribution degree of the carbon emission intensity in 2020-2025 years is-51.5 ten thousand tons of carbon dioxide. However, in the time periods of 2025-2030, 2030-2035, 2035-2040, 2040-2045 and 2045-2050 years, the carbon emission intensity is obviously and rapidly improved, and the contribution degree of the carbon emission intensity to carbon emission reduction reaches-84.1 ten thousand tons, -74.9 ten thousand tons, -333.8 ten thousand tons, -356.8 ten thousand tons and-375.5 ten thousand tons respectively. Particularly, in the period of 2035 to 2040 years, the carbon emission intensity is greatly reduced along with the popularization of non-blast furnace ironmaking technology and the great improvement of the utilization rate of scrap steel.
The proportions of the emissions generated by the combustion of fossil fuels, the emissions generated by the consumption of solvents in the industrial production process, the emissions corresponding to the net purchase of electric power and heat and the hidden emissions of the carbon-fixing products are not changed in the time periods of 2020-2025, 2025-2030, 2030-2035, 2035-2040 and 2040-2045 years, and the emission reduction contribution degree of the carbon emission structure is negligible. However, in the period of 2045-2050 years, the production technology of the iron and steel industry has changed fundamentally, the hydrogen energy steelmaking technology is put into use in a large amount, and the emission reduction contribution degree of the carbon emission structure reaches-36.2 ten thousand tons of carbon dioxide.
5. Policy advice
In combination with the above conclusions, the following policy suggestions are proposed:
(1) The steel yield is strictly controlled. The control of steel yield is a main means for realizing carbon emission reduction in the steel industry. The crude steel yield in the energy structure change scene in the model calculation result is used as a basis, the specific crude steel yield is shown in table 7, the crude steel yield in the simulation prediction does not comprise the scrap steel-electric arc furnace steelmaking process, and the crude steel yield of the non-scrap steel-electric furnace steel route is strictly controlled and continuously reduced. In the predicted result, the crude steel yield of a certain steel factory is reduced year by year from 2020 to 2025 to 950 ten thousand tons, and the annual reduction is about 3.0%; by 2050, the production cost is reduced to 700 ten thousand tons, and the annual average is reduced by 2.0 percent. The yield of the crude steel is continuously reduced, the consumption of the scrap steel is continuously increased, and the total yield of the final steel is increased to be reduced, but the total yield of the steel is reduced by 0.67% in the year before 2035, and then the total yield is increased to 1.43%.
TABLE 7 Steel yield control planning
(2) An electric furnace is introduced, and the proportion of electric furnace steel is improved. Compared with the traditional blast furnace molten iron-converter steelmaking process, the large scrap steel has obvious advantages in reducing carbon emission, and the urban scrap steel is used as a raw material to replace iron ore and coke, so that the carbon emission of high energy consumption or high carbon emission processes such as sintering, coking, blast furnaces and the like is reduced. In China, the world's largest steel production country, electric arc furnace steelmaking is currently limited due to limited supply of electricity and low cost DRI and scrap. The fourteen period in China gradually enters the high yield period of the waste steel, the waste steel resource amount in 2025 is estimated to reach 3 hundred million tons to 3.2 hundred million tons, and the waste steel resource amount in 2030 exceeds 3.5 hundred million tons. The supply of the Chinese scrap steel is sufficient in the future, and the increase of the domestic scrap steel demand can be met. On the basis of the increase of the accumulated quantity of steel per capita in China, the price of steel scraps in the future can be reduced.
(3) Ensures the resource supply of the scrap steel and realizes the large-scale and high-efficiency utilization of the scrap steel. The use proportion of the scrap steel is improved, and the carbon emission intensity is reduced by about 0.8 percent when the iron-steel ratio is reduced by 1 percent. Ensures that the iron-steel ratio in 2021 is reduced to below 0.85 (striving to be reduced to below 0.78 in 2024), reduces 0.086 in 2020, reduces the carbon emission intensity by 6.9% and reduces the total carbon emission by 150 ten thousand tons. Compared with the production of 1 ton of steel by using iron ore, the production of 1 ton of steel by using waste steel can save about 1.65 ton of iron ore, reduce energy consumption by 350 kg of standard coal, reduce nearly two thirds of carbon dioxide emission, nearly 80% of waste gas emission and 3 tons of solid waste emission. With the increase of accumulated steel in China, the domestic price of scrap steel is reduced, and the cost of electric arc furnace steelmaking by using the scrap steel is gradually reduced. Before 2025, the method of pouring the scrap steel into a converter is still mainly adopted to reduce carbon emission due to the cost of electric arc furnace steelmaking, the scrap steel is firstly used in the electric arc furnace for steelmaking in 2025, the use amount of the scrap steel is increased year by year, the use amount of the scrap steel reaches 30% by year 2035, and the use amount of the scrap steel reaches 36.5% by year 2050. Under the condition that a plurality of scrap steel is added in the converter moderately, the development and the flow design of the electric furnace smelting process of the clean green novel full scrap steel are enhanced.
(4) Introducing hydrogen to directly reduce iron. Fig. 17 is a process for producing hydrogen direct reduced iron. In terms of reducing the carbon emission, the total carbon dioxide emission of each ton of hot rolled steel coil in the converter steelmaking route is 2.05 tons; the carbon dioxide emission of each ton of hot rolled steel coil in the direct reduction iron steelmaking route is 0.96 ton in total, and is higher than the carbon emission generated by scrap steel-electric arc furnace steelmaking, but compared with the existing long-flow steelmaking process of a certain steel factory, the carbon emission is reduced by about 53 percent.
6. Summary
The invention predicts the energy consumption and carbon emission of a steel plant 2020-2050 based on the LEAP model. The method is characterized in that three scenes of a reference scene, an energy efficiency improvement scene and an energy structure change scene are set, parameters are set on main influencing factors such as coarse steel yield, iron-steel ratio, blast furnace ratio, electric furnace ratio, energy intensity, equipment structure, production structure, energy-saving low-carbon technology popularity rate and the like, and three scene carbon emission prediction change comparison diagrams are obtained. Based on the predicted results of energy consumption and carbon emission of a certain steel plant 2020-2050, an LMDI (least squares direct injection) additive decomposition method is applied to decompose influencing factors in the predicted results, and policy suggestions are given based on the predicted analysis results.
The prediction result shows that the target of reducing 35% of carbon in 2035 can be completed only under the situation of energy structure change; the "carbon neutralization" objective was essentially accomplished by 2050. The influence factor decomposition result shows that the emission reduction contribution degree of the coarse steel yield is maximum in the time spans of 2020-2025, 2025-2030 and 2030-2035. The emission reduction contribution degree of the carbon emission intensity is maximum in the time span of 2030-2035, 2035-2040 and 2040-2045 years. In the period of 2045-2050 years, the hydrogen energy steelmaking technology is put into use in a large quantity, and the emission reduction contribution degree of the carbon emission structure reaches-36.2 ten thousand tons of carbon dioxide.
It should be noted that the embodiments of the present invention can be realized in hardware, software, or a combination of software and hardware. The hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or special purpose design hardware. Those of ordinary skill in the art will appreciate that the apparatus and methods described above may be implemented using computer executable instructions and/or embodied in processor control code, such as provided on a carrier medium such as a magnetic disk, CD or DVD-ROM, a programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The device of the present invention and its modules may be implemented by hardware circuitry, such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., as well as software executed by various types of processors, or by a combination of the above hardware circuitry and software, such as firmware.
The foregoing is merely illustrative of specific embodiments of the present invention, and the scope of the invention is not limited thereto, but any modifications, equivalents, improvements and alternatives falling within the spirit and principles of the present invention will be apparent to those skilled in the art within the scope of the present invention.
Claims (10)
1. A steel carbon emission prediction method, characterized by comprising:
analyzing energy consumption in the steel production process, establishing a material flow balance model and a carbon material flow model of a production route in the production process, and analyzing material flow and carbon element flow of a certain steel plant; constructing a prediction model of energy consumption-carbon emission of a certain steel plant based on LEAP and a scene analysis method, and predicting future energy consumption and carbon emission of the certain steel plant based on the LEAP model; based on the predicted result, the LMDI factor decomposition method is used for prospective decomposition of carbon emission influencing factors in steel production, and policy suggestion of low-carbon transformation of a certain steel plant is provided.
2. The steel carbon emission prediction method according to claim 1, characterized in that the steel carbon emission prediction method comprises the steps of:
Step one, constructing a LEAP model frame and establishing a level 3 index;
setting emission reduction scenes and parameters, and comparing scene simulation results;
and thirdly, analyzing the LMDI influence factors and proposing a low-carbon transformation policy suggestion of a certain steel mill.
3. The method of predicting carbon emissions in steel as claimed in claim 2, wherein the LEAP model framework in step one includes predicting total demand of a steel plant, the total demand being divided into fossil fuel, industrial production, electric power and thermal power, and carbon-fixing products; the fossil fuel comprises clean coal, anthracite, bituminous coal, natural gas, coke, diesel oil, coke oven gas, blast furnace gas, converter gas and hydrogen; the industrial production comprises limestone, dolomite, electrodes and scrap steel; the electricity and heat include net purchase electricity and net purchase heat; the carbon-fixing product comprises coarse steel, coarse benzene and tar.
4. The method for predicting carbon steel emissions of claim 2, wherein the level 3 index established in the LEAP model framework in the step one comprises:
(1) The first level of index is the total demand;
(2) The second level of indexes are the amount of fossil fuel, industrial production, electric power and thermal power and carbon fixation products in total demand respectively;
(3) The third level of indicators are the amount of different fuel types in fossil fuels, the amount of different raw material types in industrial production, the specific amounts of electricity and heat, the amount of coarse steel, coarse benzene and tar in carbon-fixing products, respectively.
5. The steel carbon emission prediction method according to claim 2, wherein the emission reduction scene in the second step includes a reference scene, an energy efficiency improvement scene, and an energy structure change scene; the parameters include crude steel yield, iron to steel ratio, blast furnace ratio, electric furnace ratio, and energy intensity.
6. The method for predicting carbon steel emissions of claim 2, wherein the LMDI influencing factor analysis in step three comprises:
(1) Total yield of coarse steel Q;
(2) The proportions representing the various carbon emissions include: emissions from the combustion of fossil fuels, emissions from solvent consumption in industrial processes, emissions from net purchase of electricity and thermal counterparts, and emissions implicit in carbon sequestration products;
(3) Carbon emission intensity: representing the carbon dioxide emissions produced per ton of crude steel;
the total carbon emissions of the steel industry are expressed as:
wherein, subscript i=1, 2, 3, 4 represents the carbon emission type, the emission of fossil fuel combustion, the emission generated by solvent consumption in the industrial production process, the emission corresponding to the net purchase of electric power and heat, and the emission implied by the carbon fixation product; the LMDI decomposition analysis method is utilized to obtain:
ΔC tot ＝C T -C 0 ＝ΔC pdn +ΔC int +ΔC str ；
Wherein C is carbon emission; q is the yield of the coarse steel; c (C) i Representing carbon emissions of different carbon emission types; i i Is the ratio of carbon emission to crude steel yield, and represents the carbon emission intensity; s is S i Is the ratio of the carbon emission amount of different carbon emission types to the total carbon emission amount, and represents the carbon emission structure; t is the last year of the period; t=0 is the reference year of the period; ΔC tot Is the total carbon dioxide emission variation; ΔC pdn The emission reduction contribution degree for the yield of the crude steel; ΔC int The emission reduction contribution degree for the carbon emission intensity; ΔC str The emission reduction contribution degree of the carbon emission structure;
the contribution degree delta C of the coarse steel yield and the emission reduction of three scenes is obtained by using LMDI addition factor decomposition calculation pdn Emission reduction contribution degree Δc of carbon emission intensity int And the emission reduction contribution degree deltac of the carbon emission structure str 。
7. A steel carbon emission prediction system applying the steel carbon emission prediction method according to any one of claims 1 to 6, characterized in that the steel carbon emission prediction system comprises:
the energy consumption analysis module is used for analyzing the production energy consumption of a certain steel plant, establishing a material flow balance model and a carbon material flow model of a production route of a production process, and analyzing the material flow and the carbon element flow of the certain steel plant;
The prediction model construction module is used for constructing a prediction model of energy consumption-carbon emission of a certain steel plant based on LEAP and a scene analysis method, and predicting the energy consumption and the carbon emission of the certain steel plant in 2020-2050 years based on the LEAP model;
and the factor decomposition module is used for prospective decomposing carbon emission influencing factors in steel production by using an LMDI factor decomposition method based on the predicted result and providing policy suggestions for low-carbon transformation of a certain steel plant.
8. A computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of the steel carbon emission prediction method according to any one of claims 1 to 6.
9. A computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of the steel carbon emission prediction method according to any one of claims 1 to 6.
10. An information data processing terminal for implementing the steel carbon emission prediction system according to claim 7.
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