Multi-dimensional quantitative evaluation method for electric hydrogen-carbon comprehensive energy footprint in steel production

Abstract

The invention provides a multi-dimensional quantitative evaluation method for electric hydrogen-carbon comprehensive energy footprint in steel production, and relates to the technical field of low-carbon metallurgy and life cycle evaluation. The multi-dimensional quantitative evaluation method comprises the steps of system boundary setting, data acquisition and energy tracing, multi-dimensional quantitative index system construction, net footprint calculation, normalization and visualization, and result analysis and optimization. By means of the normalized radar map, a manager can visually recognize green electricity, green hydrogen gaps and high-carbon bottlenecks within one minute, process parameter adjustment suggestions are directly obtained, and the real-time performance and accuracy of low-carbon decision making of iron and steel enterprises are remarkably improved. According to the method, energy consumption is remarkably reduced, the method is green, low-carbon, short in process and high in efficiency, suggestions for optimizing and adjusting process parameters can be quickly and accurately obtained, and industrial large-scale popularization and application are facilitated.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of low-carbon metallurgy and life cycle assessment, and particularly refers to a multi-dimensional quantitative evaluation method for electric-hydrogen-carbon comprehensive energy footprint of steel production. BACKGROUND

[0002] In the existing steel manufacturing field, the process-based carbon footprint evaluation mainly follows the IPCC fixed emission factor method or enterprise-level material balance method, which can only give the CO2 equivalent per ton of steel and cannot simultaneously quantify the relative contributions of the three types of heterogeneous energy, i.e., electricity, hydrogen energy, and fossil carbon.

[0003] Chinese patent CN117713251B discloses a steady-state multi-energy flow calculation method for an electric-hydrogen-carbon multi-energy system, which realizes system-level energy-emission analysis of the coupling of power grids, hydrogen networks, and carbon networks by constructing a unified energy path model and a carbon flow collection and tracing model; however, this method is only applicable to the generation-transmission-distribution link and does not cover the energy quality conversion and recycled coal gas secondary utilization specific to high-temperature metallurgical processes such as sintering, blast furnaces, and converters, and thus cannot be directly applied to the steel production process.

[0004] Chinese patent CN117574684B further provides 8760-hour-level time sequence production simulation for an electric-hydrogen-carbon comprehensive energy system, which considers renewable power output fluctuations and green hydrogen penalty costs on a macro scale; however, the model granularity of this method stops at the “park-area” level, lacks fine description of process-level electric, hydrogen, and carbon input-transformation-output, and does not solve the carbon-hydrogen offset problem of secondary recycled flows such as coke oven gas, synthesis gas, and shaft furnace top gas.

[0005] Chinese patent CN113361122A discloses a steel enterprise external purchased electricity adjustable potential evaluation method that considers multi-energy coupling and process optimization, which establishes a multi-energy coupling model and energy system adjustable constraints in a steel enterprise, constructs a mapping relationship between production processes and energy systems, proposes a steel enterprise external purchased electricity adjustable potential evaluation model that considers multi-energy coupling and process optimization, and obtains the maximum adjustable potential of external purchased electricity and the corresponding energy system and production process scheduling operation strategy through optimization model solving; thus, although this method covers high-temperature metallurgical processes such as sintering, blast furnaces, and converters, its focus is on the influence of external purchased electricity as a supplementary energy on reducing production costs and improving process efficiency, and it does not consider multi-dimensional quantitative evaluation of the electric-hydrogen-carbon comprehensive energy footprint of steel production.

[0006] Chinese patent CN115563860A discloses a modeling and timing optimization method for the coupling characteristics of electricity, hydrogen, and carbon in steel industrial parks. The purpose of the modeling is to analyze the flow and consumption characteristics of various energy sources such as electricity and hydrogen in the park, as well as the timing distribution characteristics of carbon flow in each stage. However, this patent is essentially a "power scheduling optimization method for industrial parks" and does not solve the problem of "multi-dimensional quantitative evaluation of the comprehensive energy footprint of electricity, hydrogen, and carbon in steel production" proposed in this application. The two methods have completely different objectives, model structures, and evaluation dimensions. Moreover, the technical solution lacks a three-dimensional footprint system, lacks hydrogen-based process modeling, and lacks full-process comparability, which are the technical defects that this application aims to overcome.

[0007] Chinese patent CN118898501A discloses a multi-resource sharing decision-making method and device for hydrogen-based multi-energy microgrids including shared hydrogen storage stations. This patent proposes a resource sharing decision-making method for hydrogen multi-energy microgrid systems. Its task is to optimize the allocation, scheduling, sharing, and operating costs of hydrogen energy in multiple microgrids. It proposes a "hydrogen energy sharing factor" for hydrogen energy allocation between microgrids; it uses an energy router to describe energy exchange in the multi-energy microgrid, including electricity, hydrogen, heat, and gas, but does not involve industrial process energy consumption models; it constructs an optimization function with the objective of minimizing cost or maximizing benefit, combining hydrogen storage prices, electricity purchase and sale prices, hydrogen production power consumption, microgrid load, and hydrogen demand forecasts, and solves the problem using linear programming or mixed integer programming; finally, it outputs a hydrogen energy sharing strategy, energy flow paths within / between microgrids, and a scheduling scheme with optimal operating costs. However, the carbon emission data in this patent does not provide process-level carbon flow or path analysis, and it lacks process-level energy consumption models, three-dimensional electric-hydrogen-carbon footprint systems, hydrogen-based metallurgical mechanism models, and full-process comparability. Therefore, it cannot achieve the multi-dimensional quantitative assessment of the comprehensive energy footprint of electric-hydrogen-carbon in steel production as described in this application.

[0008] In summary, current technology has not yet developed an assessment tool that covers the entire steelmaking process, can be updated in real time, and can intuitively present the electricity-hydrogen-carbon footprint structure in a three-dimensional visualization. There is an urgent need for a multi-dimensional quantitative method that takes into account both process mechanisms and data-driven approaches to support steel companies in accurately identifying emission reduction bottlenecks and formulating low-carbon transformation strategies. Summary of the Invention

[0009] The main objective of this invention is to address the shortcomings of existing technologies in assessing the carbon footprint of steel production processes. These technologies suffer from limitations such as a single dimension for carbon footprint evaluation, fragmented system boundaries, poor dynamic adaptability, inability to perform three-dimensional visualization assessment of the electricity-hydrogen-carbon footprint structure within their applicable scope, and failure to address the carbon-hydrogen deduction of secondary circulating streams such as coke oven gas, syngas, and vertical shaft furnace top gas. Therefore, this invention proposes a multi-dimensional quantitative assessment method for the comprehensive energy footprint of electricity, hydrogen, and carbon in steel production, which can solve the aforementioned problems.

[0010] A multidimensional quantitative assessment method for the combined energy footprint of electricity, hydrogen, and carbon in steel production, comprising the following steps:

[0011] S1. Set system boundaries: The set system boundaries need to cover the entire process from ore / scrap steel entering the plant to steel products leaving the plant;

[0012] S2. Data Acquisition and Energy Traceability: Energy consumption, material consumption and process parameters need to be collected in real time in each process. Electricity is classified into green electricity, thermal power and process waste heat power generation according to energy source. Hydrogen energy is classified into green hydrogen, gray hydrogen and blue hydrogen. Carbon is classified into fossil carbon and recycled carbon.

[0013] S3. Construct a multi-dimensional quantitative indicator system: Establish three-dimensional quantitative indicators for electric footprint, hydrogen footprint, and carbon footprint;

[0014] S4. Net footprint calculation: Based on the hybrid method of energy balance and life cycle assessment, calculate the net footprint intensity of electricity-hydrogen-carbon for each process and the entire process under specific boundaries.

[0015] S5. Normalization and Visualization: Normalize the proportions of electricity, hydrogen, and carbon energy and plot them in an electricity-hydrogen-carbon three-dimensional coordinate system to form an interactive radar chart.

[0016] S6. Result Analysis and Optimization: Based on the spatial distance between the 3D map and the target low-carbon zone, the energy structure bias is identified based on the 3D map, and the bottleneck links for carbon reduction and the energy structure optimization path are automatically output to realize low-carbon decision support for steel enterprises.

[0017] Optionally, the entire process in S1 includes sintering, pelletizing, blast furnace, direct reduction, melt reduction, converter, electric furnace and rolling, as well as various main and auxiliary processes.

[0018] Optionally, in S2, renewable electricity is green electricity, thermal power is brown electricity; green hydrogen is produced by water electrolysis, gray hydrogen is produced by natural gas, and blue hydrogen is produced by purifying coke oven gas; fossil carbon is coke or pulverized coal, and recycled carbon is biochar or carbon obtained by injecting waste plastics.

[0019] Optionally, energy traceability in S2 adopts a dynamic factor library, which is updated in real time with changes in the external power structure, hydrogen energy source structure and carbon price.

[0020] Optionally, while tracing energy sources in S2, an energy conversion coefficient database is established, including the relationship between gas composition and quality conversion, to provide a theoretical basis for subsequent deduction accounting.

[0021] Optionally, in S3, establishing three-dimensional quantitative indicators for electrical footprint, hydrogen footprint, and carbon footprint requires defining a unified calculation caliber and unit, and introducing a cycle metabolism correction term to perform carbon-hydrogen offset accounting for secondary energy flow, thus avoiding double measurement.

[0022] Optionally, S3, for the two recyclable energy streams unique to the steelmaking process—blast furnace gas and converter gas—analyzes the gas composition to accurately calculate the hydrocarbon composition corresponding to the actual amount of gas consumed in the rolling process; and establishes a cross-process deduction mechanism: the carbon footprint of gas generated in upstream processes is included in the output item, and an equal amount is deducted when used in downstream processes, effectively avoiding double counting; among them, the carbon and hydrogen components in blast furnace gas are deducted from the total consumption respectively when used for rolling heating.

[0023] Optionally, the secondary energy stream includes coke oven gas, syngas, and top gas.

[0024] Optionally, S4 requires carbon-hydrogen deduction accounting for secondary circulating streams such as coke oven gas, syngas, vertical furnace top gas, and molten reduction tail gas to eliminate duplicate metering.

[0025] Optionally, in S4, net footprint calculation uses historical production data trained by machine learning algorithms to automatically calibrate model coefficients.

[0026] Optionally, in S4, based on the deduction accounting, the net consumption of three types of energy is calculated: electricity consumption is directly added to the amount used in each process, and because of its end-use characteristics, it does not involve deduction; hydrogen energy consumption first summarizes the initial total input (hydrogen in coke oven gas and natural gas), and then deducts the hydrogen deduction amount in the recovered gas to obtain the actual net consumption value; fossil carbon consumption is calculated by summarizing the total input of all carbon-containing fuels and subtracting the carbon deduction amount in the recovered gas.

[0027] Optionally, in S6, when the Euclidean distance between any normalized coordinate and the target green cone region exceeds a set threshold, optimization feedback is automatically triggered, providing suggestions for adjusting the green hydrogen blending ratio, renewable power procurement ratio, and process operation parameters.

[0028] The above technical solution has at least the following advantages compared with the existing technology:

[0029] The above-mentioned solution proposes a multi-dimensional quantitative assessment method for the comprehensive energy footprint of electricity, hydrogen, and carbon in steel production. This method can solve the problems existing in the steel process carbon footprint assessment, such as the single dimension of assessment, fragmented system boundaries, poor dynamic adaptability, inability to perform three-dimensional visualization assessment of the electricity-hydrogen-carbon footprint structure within the applicable scope, and failure to solve the technical problems of carbon-hydrogen deduction for secondary circulating flows such as coke oven gas, syngas, and vertical furnace top gas.

[0030] This method divides the entire steel production process into several process-level nodes and, for the first time, places three heterogeneous energy sources—electricity, hydrogen, and carbon—in a unified three-dimensional coordinate system for synchronous quantification, breaking through the limitations of traditional single-dimensional carbon emission factors.

[0031] This invention solves the problem of repeated metering of recycled energy sources such as coke oven gas and syngas in the upstream and downstream through a carbon-hydrogen offset mechanism of secondary circulation.

[0032] This invention utilizes normalized radar charts, enabling managers to intuitively identify green electricity and green hydrogen gaps and high-carbon bottlenecks within one minute, and directly obtain process parameter adjustment suggestions, significantly improving the real-time nature and accuracy of low-carbon decision-making in steel enterprises.

[0033] In summary, compared with traditional ironmaking methods, the present invention creatively solves the technical problems existing in the prior art by setting system boundaries, data acquisition and energy traceability, constructing a multi-dimensional quantitative indicator system, calculating net footprint, normalization and visualization, and collaboratively analyzing and optimizing results. This method significantly reduces energy consumption, is green and low-carbon, has a short process and high efficiency, and can quickly and accurately obtain suggestions for optimizing and adjusting process parameters, which is conducive to large-scale industrial application. Attached Figure Description

[0034] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 This is a flowchart illustrating a multi-dimensional quantitative assessment method for the integrated energy footprint of electro-hydrogen-carbon production in steel production according to the present invention.

[0036] Figure 2 This invention provides a three-dimensional visualization radar image of the electric-hydrogen-carbon footprint. Detailed Implementation

[0037] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0038] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0039] In the embodiments of the present invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that when the distinction is not emphasized, their intended meanings are consistent.

[0040] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0041] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0042] A multidimensional quantitative assessment method for the comprehensive energy footprint of steel production involving electricity, hydrogen, and carbon, wherein the multidimensional quantitative assessment method for the comprehensive energy footprint of steel production involving electricity, hydrogen, and carbon combines Figure 1 Includes the following steps:

[0043] S1. Set system boundaries: The set system boundaries need to cover the entire process from ore / scrap steel entering the plant to steel products leaving the plant;

[0044] S2. Data Acquisition and Energy Traceability: Energy consumption, material consumption and process parameters need to be collected in real time in each process. Electricity is classified into green electricity, thermal power and process waste heat power generation according to energy source. Hydrogen energy is classified into green hydrogen, gray hydrogen and blue hydrogen. Carbon is classified into fossil carbon and recycled carbon.

[0045] S3. Construct a multi-dimensional quantitative indicator system: Establish three-dimensional quantitative indicators for electric footprint, hydrogen footprint, and carbon footprint;

[0046] S4. Net footprint calculation: Based on the hybrid method of energy balance and life cycle assessment, calculate the net footprint intensity of electricity-hydrogen-carbon for each process and the entire process under specific boundaries.

[0047] S5. Normalization and Visualization: The proportions of electricity, hydrogen, and carbon energy are normalized and plotted in a three-dimensional coordinate system of electricity-hydrogen-carbon, forming an interactive radar chart; for example... Figure 2 As shown;

[0048] S6. Result Analysis and Optimization: Based on the spatial distance between the 3D map and the target low-carbon zone, the energy structure bias is identified based on the 3D map, and the bottleneck links for carbon reduction and the energy structure optimization path are automatically output to realize low-carbon decision support for steel enterprises.

[0049] Specifically, the entire process in S1 includes sintering, pelletizing, blast furnace, direct reduction, melt reduction, converter, electric furnace and rolling, as well as various main and auxiliary processes.

[0050] Specifically, in S2, renewable electricity is green electricity, thermal power is brown electricity; green hydrogen is produced by electrolysis of water, gray hydrogen is produced by natural gas, and blue hydrogen is produced by purification of coke oven gas; fossil carbon is coke or pulverized coal, and recycled carbon is biochar or carbon obtained by blowing waste plastics.

[0051] In particular, S2 uses a dynamic factor library for energy traceability, which is updated in real time with changes in the external power structure, hydrogen energy source structure, and carbon price.

[0052] In particular, while tracing energy sources in S2, an energy conversion coefficient database is established, including the relationship between gas composition and quality conversion, to provide a theoretical basis for subsequent deduction and accounting.

[0053] In particular, establishing three-dimensional quantitative indicators for electricity footprint, hydrogen footprint, and carbon footprint in S3 requires defining a unified calculation caliber and unit, and introducing a cycle metabolism correction term to perform carbon-hydrogen offset accounting for secondary energy flow, thus avoiding double measurement.

[0054] Specifically, S3 addresses the two recyclable energy streams unique to the steelmaking process: blast furnace gas and converter gas. By analyzing the gas composition, it accurately calculates the hydrocarbon composition corresponding to the actual amount of gas consumed in the rolling process. A cross-process deduction mechanism is established: the carbon footprint of gas generated in upstream processes is included in the output item, and an equal amount is deducted when used in downstream processes, effectively avoiding double counting. Among them, the carbon and hydrogen components in blast furnace gas are deducted from the total consumption when used for rolling heating.

[0055] In particular, secondary energy flows include coke oven gas, syngas, and top gas.

[0056] In particular, S4 requires carbon-hydrogen deduction accounting for secondary circulating streams such as coke oven gas, syngas, vertical shaft furnace top gas, and molten reduction tail gas to eliminate duplicate metering.

[0057] In particular, the net footprint calculation in S4 uses machine learning algorithms to train historical production data and automatically calibrates the model coefficients.

[0058] Specifically, in S4, based on the deduction accounting, the net consumption of three types of energy is calculated: electricity consumption is directly added to the amount used in each process, and because of its end-use characteristics, it does not involve deduction; hydrogen energy consumption first summarizes the initial total input (hydrogen in coke oven gas and natural gas), and then deducts the hydrogen deduction amount in the recovered gas to obtain the actual net consumption value; fossil carbon consumption is calculated by summarizing the total input of all carbon-containing fuels and subtracting the carbon deduction amount in the recovered gas.

[0059] Specifically, in S6, when the Euclidean distance between any normalized coordinate and the target green cone region exceeds a set threshold, optimization feedback is automatically triggered, providing suggestions for adjusting the green hydrogen blending ratio, renewable electricity procurement ratio, and process operation parameters.

[0060] Example 1

[0061] A multidimensional quantitative assessment method for the combined energy footprint of electricity, hydrogen, and carbon in steel production, comprising the following steps:

[0062] S1. Define system boundaries: The defined system boundaries need to cover the entire process from ore / scrap steel entering the plant to steel leaving the plant; clearly define the system boundaries to cover the entire process from raw material entering the plant to steel leaving the plant, including sintering, pelletizing (assuming it accounts for 30% of the total raw materials), blast furnace, converter and rolling processes; see Table 1 for details.

[0063] Table 1. Raw Material / Energy Input Boundary Settings for Each Process

[0064]

[0065] S2. Data Acquisition and Energy Traceability: Energy consumption, material consumption and process parameters need to be collected in real time in each process, as shown in Table 2.

[0066] After completing the basic data collection, various energy sources were finely classified and traced: electricity consumption was categorized into clean green electricity and traditional thermal power based on its source; hydrogen energy input was labeled according to its preparation method, with hydrogen purified from coke oven gas classified as blue hydrogen and hydrogen components in natural gas considered as gray hydrogen; carbon input was strictly distinguished between fossil carbon sources (such as coke and pulverized coal) and recycled carbon sources (such as carbon components in recovered coal gas). Simultaneously, an energy conversion coefficient database was established (as shown in Table 3), including the relationship between coal gas composition and mass conversion (e.g., a CO content of 22% in blast furnace gas corresponds to a carbon mass of 0.536 kg / m³ per unit volume), providing a theoretical basis for subsequent deduction calculations.

[0067] Table 2 Energy and Material Data Collection Table for Each Process (Based on Ton of Steel)

[0068]

[0069]

[0070] S3. Construct a multi-dimensional quantitative indicator system: Establish three-dimensional quantitative indicators for electricity footprint, hydrogen footprint, and carbon footprint; targeting the unique secondary energy cycles in the steelmaking process, such as the two recyclable energy flows of blast furnace gas and converter gas. By analyzing the gas composition (as shown in Table 3), accurately calculate the hydrocarbon composition corresponding to the actual amount of gas consumed in the rolling process. Establish a cross-process deduction mechanism: the carbon footprint of gas generated in upstream processes is included in the output item, and an equal amount is deducted when used in downstream processes, effectively avoiding double counting. In particular, the carbon and hydrogen components in blast furnace gas are deducted from the total consumption when used for rolling heating.

[0071] Table 3 Gas Composition

[0072]

[0073] BFG carbon credit = 300m 3 ×0.22×0.536kg / m 3=35.42kg,

[0074] BFG hydrogen discount = 300m 3 ×0.025×0.0899kg / m 3 =0.67kg,

[0075] LDG carbon credit = 50m 3 ×0.60×1.607kg / m 3 =48.21kg,

[0076] LDG hydrogen deduction = 50m 3 ×0.015×0.0899kg / m 3 =0.07kg,

[0077] Total carbon credit = 35.42 + 48.21 = 83.63 kg

[0078] Total hydrogen deduction = 0.67 + 0.07 = 0.74 kg;

[0079] S4. Net footprint calculation: Based on the hybrid method of energy balance and life cycle assessment, calculate the net footprint intensity of electricity-hydrogen-carbon for each process and the entire process under specific boundaries.

[0080] Based on the deduction accounting, the net consumption of three types of energy is calculated: electricity consumption is directly accumulated by adding the amount used in each process, and because of its end-use characteristics, it is not subject to deduction; hydrogen consumption is first summarized by total initial input (hydrogen in coke oven gas and natural gas), and then the hydrogen deduction amount in recovered gas is deducted to obtain the actual net consumption value; fossil carbon consumption is calculated by total input of all carbon-containing fuels and then subtracting the carbon deduction amount in recovered gas. This step, through the "one-time input - cyclical deduction" accounting mechanism, truly reflects the net energy demand of the process;

[0081] Net electricity consumption: 35 + 18 + 85 + 28 + 42 = 208 kWh;

[0082] Net hydrogen consumption:

[0083] Coke oven gas hydrogen = 80m 3 ×0.55×0.0899kg / m 3 =3.96kg,

[0084] Natural gas hydrogen = 15m 3 ×0.80×0.0899kg / m 3 =1.08kg,

[0085] Total hydrogen input = 3.96 + 1.08 = 5.04 kg;

[0086] Net fossil carbon consumption:

[0087] Sintered weight = 48 + 12 = 60 kg

[0088] pellets = 25kg

[0089] Blast furnace = 340 + 120 = 460 kg

[0090] Rolling = 15m 3 ×0.80×0.536kg / m 3 =6.43kg,

[0091] Total carbon input = 60 + 25 + 460 + 6.43 = 551.43 kg

[0092] Net carbon consumption = 551.43 - 83.63 = 467.80 kg;

[0093] S5. Normalization and Visualization: Normalize the calculated net electricity consumption, net hydrogen consumption, and net fossil carbon consumption. First, unify the units of measurement (e.g., convert all to GJ equivalent, electricity: 1kWh=0.0036GJ, hydrogen: 1kg H2=0.12GJ, fossil carbon: 1kg C=0.0333GJ), and sum them to obtain the total energy consumption.

[0094] Net electricity consumption = 208 kWh × 0.0036 = 0.7488 GJ

[0095] Net hydrogen consumption = 4.30 kg H2 × 0.12 = 0.516 GJ

[0096] Net carbon consumption = 467.80 kgC × 0.0333 = 15.5777 GJ

[0097] Total energy consumption = 0.7488 + 0.516 + 15.5777 = 16.8425 GJ;

[0098] Then calculate the relative proportions of the three types of energy:

[0099] E re1 =0.7488 / 16.8425=0.0445,

[0100] H re1 =0.516 / 16.8425=0.0306,

[0101] C re1 =15.5777 / 16.8425=0.9249;

[0102] 3D coordinates: (0.0445, 0.0306, 0.9249);

[0103] It is plotted in a three-dimensional coordinate system of electricity, hydrogen, and carbon to form an interactive radar chart;

[0104] S6. Result Analysis and Optimization: Based on the spatial distance between the 3D map and the target low-carbon zone, the energy structure bias is identified based on the 3D map, and the bottleneck links for carbon reduction and the energy structure optimization path are automatically output to realize low-carbon decision support for steel enterprises.

[0105] Example 2 (Complete Steel Production Process Based on Hydrogen-Based Shaft Furnace)

[0106] This embodiment provides a multi-dimensional quantitative assessment example of the comprehensive energy footprint of electricity, hydrogen, and carbon in the entire steel production process based on a hydrogen-based vertical shaft furnace (Hy-DRI). The process route includes "pelletizing – hydrogen-based vertical shaft furnace (DRI) – electric arc furnace (EAF) – refining – rolling". The energy structure is mainly based on green electricity and green hydrogen, while also considering the recycling of top gas from the vertical shaft furnace. It has an electricity footprint, hydrogen footprint, and carbon footprint structure that is significantly different from that of Embodiment 1, which can support further coverage of the claims.

[0107] S1. System Boundary Setting (Hydrogen-Based Shaft Furnace Full Process): The system boundary covers the entire process from pellet input to hot-rolled steel output, including pelleting (100% purchased pellets), hydrogen-based shaft furnace Hy-DRI (all-hydrogen or hydrogen-natural gas mixed reduction), electric arc furnace (EAF), secondary refining (LF / VD), continuous casting, and rolling (heating furnace uses green electricity or recovered furnace top gas). The boundary includes all primary and secondary energy inputs and shaft furnace top gas circulation (including desorption, dry dust removal, and re-hydrogenation conditioning before return to the shaft furnace).

[0108] S2. Data Acquisition and Energy Traceability: Table 4 sets the material and energy input boundaries for each process (based on ton steel), and Table 5 provides detailed data for each process (based on ton steel). Energy sources are categorized as follows: Electricity: Green electricity (photovoltaic + wind power ratio ≥ 80%), thermal power (supplement); Hydrogen: Green hydrogen (electrolysis), gray hydrogen (natural gas), blue hydrogen (coke oven gas purification); Carbon sources: Natural gas (fossil fuels), recycled CO from furnace top gas (recycled carbon).

[0109] Table 4 Energy / material input boundaries for the entire process of a hydrogen-based shaft furnace (tons of steel)

[0110]

[0111] Table 5 Detailed data for each process (by ton of steel)

[0112]

[0113] S3. Construct three-dimensional quantitative indicators (electric footprint, hydrogen footprint, carbon footprint): Calculate the carbon-hydrogen offset of the furnace top gas cycle based on the furnace top gas composition.

[0114] CO content 6%, carbon density 1.25 kg / m³ 3

[0115] H2 content 45%, hydrogen density 0.0899 kg / m³ 3

[0116] Rolling uses 120 m 3 Top Gas, the discount amount is:

[0117] Carbon deduction:

[0118] 120 m 3 ×0.06 ×1.25 = 9.0 kg

[0119] Hydrogen deduction:

[0120] 120 m 3 ×0.45×0.0899=4.86 kg H2

[0121] Since the Top Gas comes from the Hy-DRI process, its carbon and hydrogen are both circulating and should be deducted from the total input.

[0122] S4. Net footprint calculation (including revolving deductions)

[0123] (1) Net electricity consumption

[0124] Total electricity: 22 + 95 + 420 + 55 + 28 + 48 = 668 kWh (not deductible)

[0125] (2) Net hydrogen consumption

[0126] Total input:

[0127] 55 kg of green hydrogen

[0128] 5 kg of gray hydrogen

[0129] Hydrogen conversion in natural gas: 8 m 3 ×0.89×0.0899=0.64 kg

[0130] Total: 60 + 0.64 = 60.64 kg

[0131] Top Gas Discount:

[0132] Hydrogen deduction of 4.86 kg

[0133] Net hydrogen consumption: 55.78 kg

[0134] (3) Net carbon consumption

[0135] Fossil carbon:

[0136] Natural gas reduction stage: 20 m 3 ×0.75×0.536=8.04 kg

[0137] Rolled natural gas: 8 m 3 ×0.75×0.536=3.23 kg

[0138] Total carbon input = 11.27 kg

[0139] 9.0 kg of carbon can be deducted.

[0140] Net carbon consumption: 2.27 kg

[0141] S5, 3D Normalization and Visualization

[0142] Unified conversion to GJ:

[0143] Electricity: 668 × 0.0036 = 2.4048 GJ

[0144] Hydrogen: 55.78 × 0.12 = 6.6936 GJ

[0145] Carbon: 2.27 × 0.0333 = 0.0756 GJ

[0146] Total energy = 9.174 GJ

[0147] Calculate the normalized percentage:

[0148] Electric footprint: 0.262

[0149] Hydrogen footprint: 0.729

[0150] Carbon footprint: 0.009

[0151] The three-dimensional coordinates are: (0.262, 0.729, 0.009)

[0152] S6. Results Analysis and Optimization Suggestions: The hydrogen content is extremely high, and the process structure meets the requirements for near-zero carbon railway lines; the carbon content is almost negligible, making it a low-carbon target area.

[0153] The main optimization directions are:

[0154] 1) Increase the proportion of top gas recirculation to 85% to reduce hydrogen consumption;

[0155] 2) Further increase the proportion of green electricity to 90% and reduce the electricity footprint;

[0156] 3) Increase the proportion of scrap steel in EAF to 30% to reduce overall energy consumption.

[0157] Example 3 (EAF All-Scrap Route (High Green Electricity Ratio))

[0158] This embodiment presents a multi-dimensional quantitative assessment method for the integrated energy footprint of an all-scrap-electric furnace (EAF) route, encompassing electricity, hydrogen, and carbon. This route differs from Embodiments 1 and 2 in that it eliminates solid-state reduction processes such as pelletizing, blast furnaces, and vertical shaft furnaces; its primary energy source is a high proportion of green electricity; hydrogen energy is used only for heating, refining, and furnace gas control; and carbon consumption is extremely low, making it a typical "near-zero carbon route." This embodiment comprehensively covers the entire process, from system boundary setting, data acquisition and traceability, three-dimensional index construction, net footprint calculation, and visualization output.

[0159] S1. System Boundary Setting: The system boundary covers the entire process from scrap steel entry to hot-rolled steel output, including: scrap steel pretreatment, electric arc furnace (EAF) smelting, LF refining (or VD vacuum refining), continuous casting, and rolling (the heating furnace uses green electricity or green hydrogen as the main energy source). This process does not include any solid-state reduction process, therefore it does not involve blast furnace gas, converter gas, or shaft furnace top gas; however, it still involves EAF furnace gas (CO+CO2) as a secondary energy flow.

[0160] S2. Data Acquisition and Energy Traceability: Table 6 summarizes the energy and raw material input data (by ton of steel) for each process.

[0161] Table 6. Energy consumption and material input at the process level (tons of steel) for the all-scrap steel-EAF route.

[0162]

[0163] S3. Construction of Three-Dimensional Quantitative Indicators (Electricity Footprint, Hydrogen Footprint, Carbon Footprint): Since this route does not use fossil carbon such as coke or pulverized coal; all hydrogen comes from electrolytic green hydrogen; and there is no recoverable coal gas (BFG / LDG / Top Gas), the secondary energy cycle deduction is very simple, only deducting carbon from EAF furnace gas (no deduction is made if the furnace gas is not recovered and reused).

[0164] EAF furnace gas composition:

[0165] CO: 55%, carbon density 1.25 kg / m³ 3

[0166] CO2: 20%, carbon density 1.98 kg / m³ 3

[0167] Total furnace gas volume: 90 m³ 3

[0168] However, this route assumes 100% emissions and no recycling, therefore no recycling deduction is made, which satisfies the "no secondary recycling flow" requirement allowed by claim 8.

[0169] S4, Net Footprint Calculation

[0170] (1) Net electricity consumption

[0171] Total power:

[0172] 18 + 420 + 55 + 28 + 52 = 573 kWh

[0173] (2) Net hydrogen consumption

[0174] All the hydrogen comes from green hydrogen:

[0175] EAF 4 kg

[0176] Refined 2 kg

[0177] Rolling 5 kg

[0178] Total green hydrogen input: 11 kg H2. No deduction (no recovered hydrogen stream).

[0179] (3) Net carbon consumption

[0180] This route has extremely low carbon sources, coming only from:

[0181] Carbon in paint / coating mixed with scrap steel: approximately 3 kg

[0182] A very small amount of natural gas is used for ignition in the process (optional): if all green hydrogen is used, then it is 0.

[0183] Here, we use 3 kg of carbon (in line with industry data). There is no secondary carbon credit.

[0184] S5, 3D Normalization and Visualization

[0185] Unified conversion to GJ:

[0186] Electricity: 573 × 0.0036 = 2.0628 GJ

[0187] Hydrogen energy: 11 × 0.12 = 1.320 GJ

[0188] Carbon: 3 × 0.0333 = 0.0999 GJ

[0189] Total energy: 3.4827 GJ

[0190] Normalization:

[0191] Electric footprint = 2.0628 / 3.4827 = 0.592

[0192] Hydrogen footprint = 1.320 / 3.4827 = 0.379

[0193] Carbon footprint = 0.0999 / 3.4827 = 0.029

[0194] 3D coordinates: (0.592, 0.379, 0.029)

[0195] The result falls within the "medium-electricity-medium-hydrogen-extremely low-carbon region," which is significantly different from Example 1 (high-carbon region) and Example 2 (high-hydrogen region), thus fully supporting the scope of the claims.

[0196] S6. Results Analysis and Optimization Path: The carbon footprint is almost negligible, making it a near-zero carbon route; the electricity share is high, and it is recommended to further increase the green electricity ratio to 95%; hydrogen energy is used for heating and refining, and can be dynamically optimized in the range of 5-20 kg based on price conditions; if scrap steel grading pretreatment (decarburization / recoating) is introduced, EAF energy consumption can be further reduced by 20-40%.

[0197] Optimization suggestions include:

[0198] 1) The proportion of green electricity procurement will be increased to 90-95%;

[0199] 2) Hydrogen injection can be dynamically adjusted between 5-12 kg to optimize electrode consumption;

[0200] 3) The use of hydrogen-based heating furnaces to replace natural gas heating further reduces carbon emissions.

[0201] Example 4: Electrolytic Ironmaking (MOE / SIDERWIN route)

[0202] This embodiment presents a multi-dimensional quantitative assessment of the integrated energy footprint of an electrolysis ironmaking-based steel production route, encompassing electricity, hydrogen, and carbon. This route is based on liquid oxide electrolysis (MOE) or aqueous electrolytic deposition (SIDERWIN), and its characteristics include: no use of coke, pulverized coal, or natural gas throughout the entire process; no use of hydrogen-based solid reduction (distinct from Example 2); the primary energy source is ultra-high proportion green electricity (≥90%); carbon emissions mainly originate from carbon-containing impurities in pellet or iron concentrate pretreatment; the process generates high-purity O2, providing additional value to the system; and there are no secondary circulation flows such as coke oven gas, blast furnace gas, or vertical shaft furnace top gas. This route represents a typical ultra-low carbon / near-zero carbon metallurgical pathway, exhibiting significant technical differences from the previous three embodiments.

[0203] S1. System Boundary Setting (Entire Electrolytic Ironmaking Process): The system boundary covers the entire process from iron concentrate intake to hot-rolled steel output, including: iron concentrate pretreatment (desulfurization, dephosphorization, grinding), pelletizing / slurry oxide preparation (based on MOE or SIDERWIN routes), electrolytic ironmaking (main process), electric furnace or induction furnace (IF) melting and temperature control, refining (LF / VD), continuous casting, and rolling. This route eliminates coking, sintering, pellet roasting, blast furnace, vertical shaft furnace, and converter steps, thus reducing the carbon input of the entire process.

[0204] S2. Data Acquisition and Energy Traceability: Table 7 summarizes the material and energy inputs (by ton of steel) for the key processes in this route. Energy source classification: Electricity: Primarily green electricity, with thermal power used only as a backup (approximately 8-20%). Hydrogen: No hydrogen is used in the main processes; only a small amount of green hydrogen can be used for rolling heating. Carbon source: Mainly from carbonaceous impurities (1-2%) carried in iron concentrate, and CO2 decomposition in slagging agents.

[0205] S3. Construction of three-dimensional quantitative indicators (electric footprint, hydrogen footprint, carbon footprint): Since there is no coke oven gas, converter gas, blast furnace gas, or vertical furnace top gas; and no secondary energy recovery flow; therefore, there is no secondary energy deduction mechanism involved (in accordance with the claims: only "includes secondary energy flow", not that each embodiment must exist and deduct).

[0206] Table 7 Summary of Process-Level Data for the Entire Electrolytic Ironmaking (MOE / SIDERWIN) Process

[0207]

[0208] Carbon footprint mainly comes from:

[0209] Carbon impurities in iron concentrate (1.7 t × 1.5% ≈ 25.5 kg C)

[0210] Limestone decarbonization (CaCO3 → CaO + CO2)

[0211] Assuming 35 kg of limestone contains 12% carbon:

[0212] 35 kg × 0.12 = 4.2 kg C

[0213] Total carbon input: approximately 30 kg C / t steel

[0214] S4 Net Footprint Calculation

[0215] (1) Net electricity consumption

[0216] Total electricity: 65 + 40 + 3800 + 160 + 55 + 25 + 48 = 4193 kWh

[0217] (2) Net hydrogen consumption

[0218] Green hydrogen used only in rolling: 2 kg H2

[0219] If electric heating is used instead, the hydrogen content will be 0. This embodiment adopts the "low hydrogen scenario".

[0220] (3) Net carbon consumption

[0221] Iron concentrate carbon impurities: 25.5 kg

[0222] Limestone decarbonization: 4.2 kg

[0223] Total: 29.7 kg C ≈ 30 kg C. No secondary energy deduction.

[0224] S5 3D Normalization and Visualization

[0225] Unified conversion to GJ:

[0226] Electricity: 4193 × 0.0036 = 15.0948 GJ

[0227] Hydrogen energy: 2 × 0.12 = 0.24 GJ

[0228] Carbon energy: 30 × 0.0333 = 0.999 GJ

[0229] Total energy = 16.3338 GJ

[0230] Normalization:

[0231] Electric footprint = 15.0948 / 16.3338 = 0.924

[0232] Hydrogen footprint = 0.24 / 16.3338 = 0.015

[0233] Carbon footprint = 0.999 / 16.3338 = 0.061

[0234] 3D coordinates: (0.924, 0.015, 0.061)

[0235] Conclusion: Extremely high electricity share; minimal hydrogen energy participation; extremely low carbon emissions.

[0236] S6 Result Analysis and Optimization Path: Electricity footprint is the dominant factor (>90%), and carbon footprint is extremely low; electrolytic ironmaking is suitable for locations with abundant green electricity (desert photovoltaic, coastal wind power, etc.).

[0237] Optimization directions:

[0238] 1) Increase the proportion of green electricity to ≥95% and reduce the carbon footprint of thermal power;

[0239] 2) Replacing part of the EAF with an induction furnace can reduce power consumption;

[0240] 3) Limestone decarbonization can further reduce carbon consumption through carbon capture and storage (CCUS);

[0241] 4) Oxygen byproducts (>99%) can be used as negative carbon economic benefits for energy deduction (if policy allows).

[0242] The above-mentioned solution proposes a multi-dimensional quantitative assessment method for the comprehensive energy footprint of electricity, hydrogen, and carbon in steel production. This method can solve the problems existing in the steel process carbon footprint assessment, such as the single dimension of assessment, fragmented system boundaries, poor dynamic adaptability, inability to perform three-dimensional visualization assessment of the electricity-hydrogen-carbon footprint structure within the applicable scope, and failure to solve the technical problems of carbon-hydrogen deduction for secondary circulating flows such as coke oven gas, syngas, and vertical furnace top gas.

[0243] This method divides the entire steel production process into several process-level nodes and, for the first time, places three heterogeneous energy sources—electricity, hydrogen, and carbon—in a unified three-dimensional coordinate system for synchronous quantification, breaking through the limitations of traditional single-dimensional carbon emission factors.

[0244] This invention solves the problem of repeated metering of recycled energy sources such as coke oven gas and syngas in the upstream and downstream through a carbon-hydrogen offset mechanism of secondary circulation.

[0245] This invention utilizes normalized radar charts, enabling managers to intuitively identify green electricity and green hydrogen gaps and high-carbon bottlenecks within one minute, and directly obtain process parameter adjustment suggestions, significantly improving the real-time nature and accuracy of low-carbon decision-making in steel enterprises.

[0246] In summary, compared with traditional ironmaking methods, the present invention creatively solves the technical problems existing in the prior art by setting system boundaries, data acquisition and energy traceability, constructing a multi-dimensional quantitative indicator system, calculating net footprint, normalization and visualization, and collaboratively analyzing and optimizing results. This method significantly reduces energy consumption, is green and low-carbon, has a short process and high efficiency, and can quickly and accurately obtain suggestions for optimizing and adjusting process parameters, which is conducive to large-scale industrial application.

[0247] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0248] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0249] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0250] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A multi-dimensional quantitative evaluation method of the energy footprint of an integrated steel plant, characterized in that, The method comprises the following steps: S1, setting system boundary: the set system boundary needs to meet the whole process from the ore / scrap steel into the factory to the steel out of the factory; S2, data collection and energy tracing: real-time collection of energy consumption, material consumption and process parameters is needed in each process, and electricity is divided into green electricity and thermal power according to energy sources, hydrogen energy is divided into green hydrogen, gray hydrogen and blue hydrogen, and carbon is divided into fossil carbon and recycled carbon; S3, constructing a multi-dimensional quantitative index system: establishing three-dimensional quantitative indexes of electricity footprint, hydrogen footprint and carbon footprint; S4, net footprint calculation: based on the mixed method of energy quality balance and life cycle assessment, the net electricity-hydrogen-carbon footprint intensity of each process and the whole process under the specific boundary is calculated; S5, normalization and visualization: normalize the proportion of electricity, hydrogen and carbon, and draw it in the three-dimensional coordinate system of electricity-hydrogen-carbon to form an interactive radar chart; S6, result analysis and optimization: according to the spatial distance of three-dimensional graph and target low-carbon area, based on three-dimensional graph to identify energy structure bias, automatically output carbon reduction bottleneck link and energy structure optimization path, realize low-carbon decision support of steel enterprises.

2. The method for multi-dimensional quantitative evaluation of the energy footprint of steel production for integrated electric hydrogen and carbon according to claim 1, characterized in that, The whole process in S1 includes sintering, pelletizing, blast furnace, direct reduction, smelting reduction, converter, electric furnace and rolling main and auxiliary processes.

3. The method of claim 1, wherein the method is characterized by, In S2, renewable electricity is green electricity, thermal power is brown electricity; green hydrogen is hydrogen produced by electrolysis of water, gray hydrogen is hydrogen produced by natural gas, and blue hydrogen is hydrogen produced by purification of coke oven gas; fossil carbon is coke or coal powder, and recycled carbon is carbon produced by biomass or waste plastic injection.

4. The method of claim 1, wherein the method is characterized by, In S2, dynamic factor library is used for energy tracing, and is updated in real time with changes in external power structure, hydrogen energy source structure and carbon price.

5. The method for multi-dimensional quantitative evaluation of the energy footprint of steel production for integrated power-to-hydrogen-to-carbon according to claim 1, characterized in that, In S2, while tracing energy, an energy conversion coefficient library is established, including the composition and mass conversion relationship of coal gas, to provide a theoretical basis for subsequent deduction accounting.

6. The method for multi-dimensional quantitative evaluation of the energy footprint of steel production for integrated power-to-hydrogen-to-carbon according to claim 1, characterized in that, In S3, the three-dimensional quantitative indexes of electricity footprint, hydrogen footprint and carbon footprint need to define unified calculation caliber and unit, and introduce a cyclic metabolism correction term to conduct carbon-hydrogen deduction accounting for secondary energy flow to avoid repeated measurement.

7. The method for multi-dimensional quantitative evaluation of the energy footprint of steel production for integrated power-to-hydrogen-to-carbon according to claim 1, characterized in that, Secondary energy flow includes coke oven gas, synthesis gas and furnace top gas.

8. The method for multi-dimensional quantitative evaluation of the energy footprint of steel production for integrated power-to-hydrogen-to-carbon according to claim 1, characterized in that, In S4, carbon-hydrogen deduction accounting is needed for secondary recycling flows such as coke oven gas, synthesis gas, shaft furnace top gas and smelting reduction tail gas to eliminate repeated measurement.

9. The method for multi-dimensional quantitative evaluation of the energy footprint of steel production for integrated power-to-hydrogen-to-carbon according to claim 1, characterized in that, In S4, the net footprint calculation trains historical production data through machine learning algorithm to automatically calibrate model coefficients.

10. The method for multi-dimensional quantitative evaluation of the energy footprint of steel production for integrated power-to-hydrogen-to-carbon according to claim 1, characterized in that, In S6, when the Euclidean distance between any normalized coordinate and the target green cone region exceeds the set threshold, the optimization feedback is automatically triggered, and the green hydrogen blending ratio, renewable power purchase ratio and process operation parameter adjustment suggestions are given.

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