Method for accounting for carbon emissions in production of electrical equipment with multiple materials

Abstract

The application discloses a kind of multi-material iteration electrical equipment production carbon emission accounting method and system, method includes: to target electrical equipment is material disassembly and identification, establish material type list;Determine the dosage threshold range of each material;With equipment total weight and material density as input, execute iterative calculation, under total weight constraint and threshold constraint condition, each material actual dosage is deduced;Based on each material actual dosage and corresponding carbon emission factor, calculate the total carbon emission of equipment body;The application also discloses corresponding accounting system, include material classification module, threshold determination module, iterative calculation engine module and carbon emission calculation module;The application solves the technical problem that electrical equipment production stage carbon emission is difficult to accurately account due to bill of materials opacity, with high calculation precision, wide applicability, can identify carbon emission hot spot and the like advantages, can be widely applied in transformer, GIS, carbon footprint accounting of a variety of electrical equipment such as high resistance.

Description

Technical Field

[0001] This invention belongs to the technical field of carbon emission calculation and life cycle assessment of power equipment. Specifically, it relates to a method for calculating carbon emissions of substation electrical equipment based on a material usage threshold iterative algorithm. It is particularly suitable for solving the carbon emission calculation problem caused by the complexity of material types and uncertain usage during the production stage of electrical equipment. Background Technology

[0002] The life-cycle carbon emission assessment of power infrastructure is receiving increasing attention. As a core hub of the power system, substations typically encompass multiple stages of their life-cycle carbon emissions, including construction, equipment manufacturing, installation and commissioning, operation and maintenance, and decommissioning and recycling. Currently, industry research and practice largely focus on the construction, installation and commissioning, and operation and maintenance stages. However, significant technical challenges and gaps remain in the carbon emission accounting for the core components of substations—various electrical equipment (such as main transformers, GIS, HGIS, high-voltage reactors, circuit breakers, and disconnectors) during the manufacturing stage. This deficiency results in an incomplete life-cycle carbon emission assessment system for substations, making it difficult to support accurate low-carbon design and supply chain management.

[0003] The aforementioned technical challenges primarily stem from the complexity of the materials used in electrical equipment and the lack of transparency in information. A typical piece of electrical equipment often contains multiple materials, such as metals (steel, copper, aluminum), insulating materials (epoxy resin, insulating paperboard), and insulating oil. The types, proportions, and quantities of materials vary significantly between different manufacturers, models, and voltage levels, and there is a lack of publicly available and standardized bills of materials (BOMs) within the industry. This makes traditional carbon emission accounting methods (such as "activity data")... The "emission factor" is difficult to apply directly, mainly because: Multi-material composite characteristics: Traditional methods are usually applicable to single materials or simple products, but cannot handle the coupling and uncertainty of the amount of each material in multi-material composite equipment.

[0004] Lack of a systematic allocation algorithm: Existing technology lacks a systematic algorithm that can reasonably and constrainingly allocate the total weight of the equipment to each component material.

[0005] Poor adaptability of emission factor databases: Existing carbon emission factor databases are mostly general-purpose and difficult to directly adapt to the material composition of complex electrical equipment.

[0006] To address the aforementioned issues, current industry practices often employ two simplified approaches: one is to ignore the equipment manufacturing phase, resulting in a severely incomplete carbon footprint throughout the entire lifecycle; the other is to use empirical estimations or average carbon emission factors for rough calculations based on the total weight of the equipment. These methods yield inaccurate results and fail to reveal the carbon emission contributions of individual materials, thus failing to provide effective guidance for low-carbon optimization design.

[0007] Therefore, there is an urgent need for a scientific, systematic, and operable method to accurately calculate the carbon emissions during the production stage of electrical equipment when material usage information is not fully transparent, to fill the gaps in existing technologies, and to improve the carbon emission assessment system for the entire life cycle of substations. Summary of the Invention

[0008] The main objective of this invention is to provide a method for calculating carbon emissions from the production of electrical equipment using a multi-material iteration approach, aiming to solve existing technical problems.

[0009] To achieve the above objectives, this invention provides a method for carbon emission accounting in the production of electrical equipment using multi-material iteration, comprising the following steps: S1: Disassemble and identify the target electrical equipment at the material level, and establish a standardized list of constituent material types g1, g2, ..., g n , where n is the total number of material types; S2: Based on market research data, industry standards, measured data from similar equipment samples, and / or supplier technical information, for each material g n Define the minimum dosage. n With the maximum usage limit (max) n Determine the set of material usage thresholds {[min1,max1],[min2,max2],…,[min n ,max n ]}; S3: Obtain the total factory weight G of the target electrical equipment, and the density parameters ρ of each material. n ; S4: Using the material type list, the material usage threshold set, the total weight at the factory gate G, and the density parameter ρ n As input, perform iterative calculations, satisfying the total weight constraint ∑G n =G and threshold constraint min n ≤G n ≤max n Under the given conditions, reverse calculation of the actual usage G of each material. n ; S5: Based on the actual usage of each material G n and the corresponding carbon emission factor S n The total carbon emissions of the equipment during the production stage are calculated as F = ∑S. n G n It also outputs the calculation results.

[0010] Further, step S1 includes: S1.1: Collect the design drawings of the target electrical equipment; S1.2: Identify the materials of each functional component and record the name, purpose, and form of each material; S1.3: Group materials with the same chemical composition into the same material type. n Establish a standardized list of material types and assign a unique code to each material.

[0011] Furthermore, in step S2, the lower limit of dosage min n and maximum usage limit n Determined as follows: min n =a n (1 δ), max n =b n (1+δ), where a n b is the minimum amount of this material extracted from multi-source data. n δ represents the maximum amount of material used extracted from multi-source data, and δ is the safety margin coefficient.

[0012] Further, step S4 includes: S4.1: Initialization, set the iteration number k=0, and calculate the volume coefficient of each material based on the median threshold. Initial material usage G n （0） = r n x n （0） ; S4.2: Calculate the total weight of the k-th round. and total weight error ; S4.3: Allocate the total weight error according to the current weight percentage of each material to obtain the temporary adjustment amount; S4.4: Force the temporary usage to be within the threshold range, and record the set of fixed materials C that are cut. fixed And the set of free materials C that can still be freely adjusted free ; S4.5: Calculate the total weight and remaining error after cutting. If the absolute value of the remaining error is less than or equal to the convergence accuracy ε, then convergence is determined and the current material usage is output. S4.6: If the remaining error is not zero and the free material set is not empty, then distribute the remaining error to each free material according to the weight ratio of the free materials, update the amount of free materials, and keep the value of the fixed materials unchanged after cutting. S4.7: Let k ← k+1, return to sub-step S4.2 and repeat until the convergence condition is met or the maximum number of iterations is reached.

[0013] Further, in sub-step S4.4, the temporary usage is projected onto the threshold in the following manner: when the temporary usage is less than min... n At that time, Gn (clip) =min n When the temporary usage exceeds the maximum n At that time, Gn (clip) =max n When the temporary dosage is in [min n ,max n When Gn is within the interval, (clip) =Temporary usage.

[0014] Further, step S5 includes: S5.1: According to material type g n Retrieve the corresponding carbon emission factor S from the carbon emission factor database. n ; S5.2: Calculate the carbon emission contribution F of each material n =S n G n ; S5.3: Sum the carbon emission contributions of all materials to obtain the total carbon emission of the equipment itself during the production stage, F = ∑F n It also outputs the calculation results.

[0015] Furthermore, the target electrical equipment includes a main transformer, GIS, HGIS, high-voltage reactor, circuit breaker or disconnector.

[0016] A carbon emission accounting system for the production of electrical equipment using multiple materials iterations, comprising: The electrical equipment material classification module is used to disassemble and identify target electrical equipment at the material level, and establish a standardized list of constituent material types g1, g2, ..., g n The material type list is then passed to the material usage threshold determination module and the numerical iteration calculation engine module, respectively. The material usage threshold determination module is used to determine the g of each material based on market research data, industry standards, measured data from similar equipment samples, and / or supplier technical information. n Define the minimum dosage. n With the maximum usage limit (max) n The set of material usage thresholds is determined and passed as core constraint parameters to the numerical iteration calculation engine module; The numerical iterative calculation engine module is used to calculate the material type list, the material usage threshold set, the total factory weight G of the target electrical equipment, and the density parameter ρ of each material. n As input, execute the iterative algorithm, satisfying the total weight constraint ∑G n =G and threshold constraint min n ≤G n ≤max n Under the condition of reverse calculation, the actual usage G of each material is calculated. n The actual usage of each material is then passed to the carbon emission calculation module. The carbon emission calculation module is used to calculate emissions based on the actual usage of each material (G). n and the corresponding carbon emission factor S n Perform the final carbon emission calculation F=∑S n G n It also outputs the total carbon emissions F of the equipment during the production stage.

[0017] Furthermore, the numerical iterative calculation engine module includes: The initialization unit is used to set the iteration round k=0, the maximum number of iterations Kmax, and the convergence accuracy ε, and to calculate the volume factor of each material based on the median threshold. and initial material usage G n （0） = r n x n （0） ; Error calculation unit, used to calculate the current total weight G （k） =∑G n （k） and total weight error ΔG （k） =G G （k） ; The error allocation unit is used to allocate the total weight error to each material according to the current weight ratio of each material, so as to obtain a temporary adjustment amount. The threshold projection unit is used to force the temporary usage to be constrained within the threshold range and to record the fixed material set and the free material set; The residual error redistribution unit is used to distribute the residual error to each free material according to the weight ratio of the free materials when the residual error is not zero and the free material set is not empty. The convergence judgment unit is used to determine whether the convergence condition is met or the maximum number of iterations is reached, and outputs the final material usage.

[0018] Furthermore, the carbon emission calculation module includes: Factor matching unit, used to match material type gn Retrieve the corresponding carbon emission factor S from the carbon emission factor database. n ; The sub-item calculation unit is used to calculate the carbon emission contribution Fn=S of each material. n G n ; The summation output unit is used to sum the carbon emission contributions of all materials to obtain the total carbon emission of the equipment body during the production stage, F = ∑F. n It also outputs the calculation results.

[0019] In another aspect, the present invention also discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the method described above.

[0020] In another aspect, the present invention also discloses a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method described above.

[0021] The beneficial effects of this invention are reflected in: This invention is the first to combine an iterative algorithm with a material usage threshold constraint system, breaking through the bottleneck of traditional methods that cannot break down the total weight of equipment. Even in the absence of a complete bill of materials, it can accurately back-calculate the actual usage of various materials based on parameters such as the total mass of the equipment, material density, and industry statistical thresholds, providing a brand-new technical approach for carbon emission accounting of complex electrical equipment.

[0022] This invention addresses the industry pain points of opaque material information, complex material types, and large fluctuations in usage for electrical equipment. By setting reasonable upper and lower limits for material usage to narrow the iteration range and combining multiple rounds of iterative solutions to obtain reliable material usage, it completely solves the problem that traditional solutions cannot carry out carbon emission accounting during the production stage, filling a technological gap in the industry.

[0023] This invention abandons outdated methods such as extensive empirical estimation and rough calculation of average factors. Instead, it integrates physical constraints (total equipment weight, material density) and statistical constraints (material usage threshold) to construct a mathematical model. The entire calculation process is logically rigorous and based on sufficient evidence, effectively improving the reliability and accuracy of carbon emission accounting results and meeting the requirements of refined carbon management.

[0024] This invention is not limited to a single equipment model or a specific manufacturer. As long as the type of equipment materials and the reasonable usage range are clearly defined, it can be applied. It can be widely adapted to various substation electrical equipment such as main transformers, GIS, HGIS, high-voltage reactors, circuit breakers, and disconnect switches. At the same time, the method and principle can be extended to the carbon emission calculation of other complex electromechanical products.

[0025] This invention can not only complete the numerical accounting of carbon emissions, but also the data on the amount of various materials used and their carbon emission contributions obtained during the iterative process can intuitively reflect the proportion of carbon emissions of different materials. This provides data support and optimization direction for lightweight equipment design, low-carbon material substitution, and low-carbon transformation of the raw material supply chain, thus helping to upgrade electrical equipment to a low-carbon level. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the carbon emission accounting method for the production of electrical equipment based on multi-material iteration according to the present invention; Figure 2 This is a schematic diagram of the carbon emission accounting system for electrical equipment production based on multi-material iteration according to the present invention. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] Please see Figure 1 This embodiment takes a 110kV oil-immersed transformer as an example to illustrate in detail the specific implementation process of the multi-material iterative carbon emission accounting method for electrical equipment production provided by the present invention: S1: Disassemble and identify the target electrical equipment at the material level, and establish a standardized list of constituent material types g1, g2, ..., g n Where n is the total number of material types; S1.1: Collect the design drawings of the target electrical equipment.

[0029] Collect complete design drawings for the target 110kV oil-immersed transformer, including general assembly drawings, core assembly drawings, winding assembly drawings, tank structure drawings, and insulation system diagrams. The design drawings should be obtained from the equipment manufacturer to ensure their accuracy and completeness. If complete design drawings are unavailable, material information can be extracted from the equipment bidding technical specifications, structural descriptions attached to the product certificate, or publicly available technical data on similar equipment.

[0030] S1.2: Material identification of each functional component. The material aspects of each functional component of the transformer are disassembled and identified one by one. Core assembly: composed of stacked silicon steel sheets, identified as silicon steel sheets (g1); Winding assembly: composed of copper conductors, identified as copper conductors (g2); Insulation system: including insulating paperboard, insulating molded parts, etc., identified as insulating paperboard (g3); Insulating medium: transformer oil, identified as insulating oil (g4); Housing assembly: including oil tank, heat sink, etc., identified as steel (g5). Record the name, purpose, and form of each material in the equipment to form a preliminary material identification record table.

[0031] S1.3: Material merging and coding.

[0032] Materials with the same chemical composition are grouped into the same material type. For example, silicon steel sheets of different specifications are all grouped into the material type "silicon steel sheets"; steel of different grades are all grouped into the material type "steel".

[0033] After consolidation, five material types were identified for the 110kV oil-immersed transformer in this embodiment. A standardized list of material types is established as follows:

[0034] Assign a unique code to each material and establish a material classification database for use by subsequent modules.

[0035] S2: Based on market research data, industry standards, measured data from similar equipment samples, and / or supplier technical information, for each material g n Define the minimum dosage. n With the maximum usage limit (max) n Determine the set of material usage thresholds; S2.1: Collect material usage data for transformers of the same type and voltage level from at least three of the following sources: Market research: Research the material data of 110kV oil-immersed transformers produced by no fewer than 5 different transformer manufacturers, including the design usage or actual weighing data of each material; Industry standards: Consult relevant industry standards for recommended ranges or typical values ​​for the weight of various transformer components; Sample measurement: Disassemble and weigh or analyze the bill of materials for no less than 3 110kV oil-immersed transformers of the same model that are in production or already in operation to obtain the actual usage data of each material.

[0036] S2.2: For each material gn, extract the minimum amount a of that material from all data sources. n and maximum value b n Taking the five materials in this embodiment as examples, the data range collected is as follows: Silicon steel sheet: a1=1900kg, b1=2600kg; Insulating oil: a2=2800kg, b2=3600kg; Copper conductor: a3=1400kg, b3=1900kg; Insulating paperboard: a4=180kg, b4=320kg; Steel: a5=750kg, b5=1050kg.

[0037] Considering engineering margins, a safety margin factor δ=0.05 is set, and the minimum usage limit (min) is calculated according to the following formula. n and maximum usage limit n min n =a n (1 δ), max n =b n (1+δ) The threshold ranges for each material were calculated: Silicon steel sheet: min1 = 1900 0.95 = 1805 kg, max1 = 2600 1.05 = 2730 kg; Insulating oil: min² = 2800 0.95 = 2660 kg, max2 = 3600 1.05 = 3780 kg; Copper conductor: min³ = 1400 0.95 = 1330 kg, max3 = 1900 1.05 = 1995 kg; Insulating cardboard: min4 = 180 0.95 = 171 kg, max4 = 320 1.05 = 336 kg; Steel: min5 = 750 0.95 = 712.5 kg, max5 = 1050 1.05 = 1102.5 kg.

[0038] S2.3: The reasonableness of the above threshold ranges is assessed, and obviously erroneous data is excluded. For example, check whether the threshold ranges for each material are reasonable, whether the sum of the amounts of each material covers the total weight of the equipment, and whether there are any values ​​that significantly deviate from common sense physics. After review, the threshold ranges for each material in this embodiment are all reasonable, and the output threshold set is: {[1805,2730], [2660,3780], [1330,1995], [171,336], [712.5,1102.5]}.

[0039] To facilitate subsequent calculations, this embodiment uses the following set of thresholds after rounding:

[0040] S3: Obtain the total factory weight G = 8000 kg for the target 110kV oil-immersed transformer from the equipment nameplate or certificate of conformity. Obtain the density parameter ρ of each material from the material property database. n Silicon steel sheet: ρ1=7.65 10³ kg / m³; Insulating oil: ρ² = 0.895 10³ kg / m³; Copper conductor: ρ³ = 8.93 10³ kg / m³; Insulating cardboard: ρ₄ = 1.05 10³ kg / m³; Steel: ρ5 = 7.85 10³kg / m³.

[0041] S4: Using the material type list, the material usage threshold set, the total weight at the factory gate G, and the density parameter ρ n As input, perform iterative calculations, satisfying the total weight constraint ∑G n =G and threshold constraint min n ≤G n ≤max n Under the given conditions, reverse calculation of the actual usage G of each material. n ; S4.1: Assume the iteration round k=0, the maximum number of iterations K_max=200, and the convergence accuracy ε=0.1kg. Calculate the volumetric coefficient χ for each material based on the median threshold. n Initial value: The calculation yielded: χ1 （0） =(1800+2750) / (2 7650)=4550 / 15300≈0.2974m³; χ2 （0） =(2650+3800) / (2 895) = 6450 / 1790 ≈ 3.6034 m³; χ3 （0） =(1300+2000) / (2 8930)=3300 / 17860≈0.1848m³; χ4 （0） =(170+340) / (2 1050) = 510 / 2100 ≈ 0.2429 m³; χ5 （0） =(700+1110) / (2 7850)=1810 / 15700≈0.1153m³.

[0042] Initial material usage Gn （0） =ρ n χ n （0） G1 （0） =7650 0.2974≈2275kg; G2 （0） =895 3.6034≈3225kg; G3 （0） =8930 0.1848≈1650kg; G4 （0） =1050 0.2429≈255kg; G5 （0） =7850 0.1153≈905kg.

[0043] Initial total weight G （0） =2275+3225+1650+255+905=8310kg.

[0044] S4.2: Total weight of round k: G （k） =∑G n （k） Total weight error: ΔG （k） =G G （k） Round 0: G （0） =8310kg, ΔG （0） =8000 8310= 310kg.

[0045] S4.3: Calculate the current weight percentage of each material: w n （k） =G n （k） / G （k） The weight percentages of each material in round 0 are as follows: w1 = 2275 / 8310 ≈ 0.2738; w2 = 3225 / 8310 ≈ 0.3881; w3 = 1650 / 8310 ≈ 0.1986; w4 = 255 / 8310 ≈ 0.0307; w5 = 905 / 8310 ≈ 0.1089.

[0046] The temporary adjustment amount is obtained by proportionally allocating the total weight error: G n （temp） =G n （k） +ΔG （k） w n （k） G1 （temp）=2275+( 310) 0.2738≈2275 84.9 = 2190.1 kg; G2 （temp） =3225+( 310) 0.3881≈3225 120.3 = 3104.7 kg; G3 （temp） =1650+( 310) 0.1986≈1650 61.6 = 1588.4 kg; G4 （temp） =255+( 310) 0.0307≈255 9.5 = 245.5 kg; G5 （temp） =905+( 310) 0.1089≈905 33.8 = 871.2 kg.

[0047] S4.4: Force temporary usage to be constrained within a threshold range: when G n （temp） <min n At that time, Gn (clip) =min n When G n （temp） max n At that time, Gn (clip) =max n ; when min n ≤G n （temp） ≤max n At that time, Gn (clip) =G n （temp） .

[0048] After projecting each material in round 0: G1 (clip) =2190.1kg (within [1800, 2750], free); G2 (clip) =3104.7kg (within [2650, 3800], free); G3 (clip) =1588.4kg (within [1300, 2000], free); G4 (clip) =245.5kg (within [170, 340], free); G5 (clip) =871.2kg (within [700, 1110], free).

[0049] In this embodiment, none of the materials touched the boundary. fixed =Φ,C free ={1,2,3,4,5}.

[0050] S4.5: Total weight after cutting: G (clip) =∑Gn (clip) G (clip) =2190.1+3104.7+1588.4+245.5+871.2=7999.9kg Residual error: ΔG rem =G G (clip) =8000 7999.9 = 0.1 kg due to |ΔG rem |=0.1kg≤ε=0.1kg, which satisfies the convergence condition.

[0051] S4.6: Actual usage of each material after convergence: G1=2190.1kg (silicon steel sheet); G2=3104.7kg (insulating oil); G3=1588.4kg (copper conductor); G4=245.5kg (insulating paperboard); G5=871.2kg (steel).

[0052] The total weight is verified to be 2190.1 + 3104.7 + 1588.4 + 245.5 + 871.2 = 7999.9 kg ≈ 8000 kg, which meets the total weight constraint.

[0053] Verify the threshold constraints for each material: 1800≤2190.1≤2750; 2650≤3104.7≤3800; 1300≤1588.4≤2000; 170≤245.5≤340; 700≤871.2≤1110.

[0054] Additional explanation: How to handle boundary conditions during iteration. Taking this embodiment as an example, assuming the temporary usage of each material after a certain iteration is: G1=1780kg, G2=3150kg, G3=1600kg, G4=250kg, G5=900kg, then: (1) G1 is cut to min1 = 1800 kg, and C is recorded. fixed ={1},C free ={2,3,4,5};(2)Calculate the total weight after cutting and the remaining error;(3)If the remaining error is not zero and C free If not empty, the remaining error is allocated to the free material according to the weight ratio of the free material; (4) update the amount of free material and fix the material to keep the value after cutting unchanged; (5) enter the next iteration.

[0055] If ΔG in a certain iteration rem ≠0 and C free If empty, it means there is no feasible solution under the current threshold constraint, triggering an alarm and outputting the least squares solution—the combination that satisfies the threshold constraint but has the smallest total weight error among the last projection results.

[0056] S4.7: After each iteration, let k←k+1, return to S303 and repeat until any of the following conditions are met: (1) |ΔG rem |≤ε (convergence accuracy), determine convergence, output the current material usage; (2) all G in two consecutive iterations n If the change is less than ε / 10 and the total error no longer decreases, convergence is determined; (3) k>K max If the solution still fails to converge, output the least squares feasible solution.

[0057] In this embodiment, convergence is achieved in just one iteration. In practical applications, since the total weight G of the equipment is necessarily equal to the sum of the actual amounts of each material used, and the threshold range is derived from statistics of actual equipment, convergence is usually achieved within 10 to 50 iterations.

[0058] S5: Based on the actual usage of each material G n and the corresponding carbon emission factor S n The total carbon emissions of the equipment during the production stage are calculated as F = ∑S. n G n and output the calculation results; S5.1: Match carbon emission factors. Based on material type g n Retrieve the corresponding carbon emission factor S from authoritative databases n This embodiment uses the Ecoinvent 3.8 database and the China Product Life Cycle Greenhouse Gas Emission Coefficient Database (2022) as data sources. The carbon emission factors of each material are as follows:

[0059] If a material is a composite material (such as oil-impregnated cardboard), its carbon emission factor is calculated by weighted average of the mass fractions of each component. In this embodiment, all materials are single materials, and the corresponding carbon emission factor is used directly.

[0060] S5.2: Carbon emission contribution of each material: F n =S n G n F1=2.5 2190.1 = 5475.25 kg CO2e; F2 = 1.8 3104.7 = 5588.46 kg CO2e; F3 = 5.2 1588.4 = 8259.68 kg CO2e; F4 = 3.0 245.5 = 736.50 kg CO2e; F5 = 2.2 871.2 = 1916.64 kg CO2e.

[0061] S5.3: Total carbon emissions of the equipment itself during the production phase: F = ∑F n =5475.25+5588.46+8259.68+736.50+1916.64=21976.53kgCO2e Output format: F rounded to the nearest integer, F≈21977kgCO2e. Optional output: detailed carbon emission table for each material.

[0062] As shown in the above detailed table, although copper conductors account for only 19.9% ​​of the total weight, their carbon emission contribution is as high as 37.6%, making them the main source of carbon emissions during transformer production. Insulating oil accounts for the largest share (38.8% of the total weight), but due to its lower carbon emission factor, its contribution is only 25.4%. This detailed data can provide reference and optimization direction for the low-carbon design of equipment.

[0063] Example 2 This example uses a 252kV GIS (Gas Insulated Switchgear) circuit breaker bay as an example to illustrate the application of the method of the present invention on GIS equipment.

[0064] S1: Collect the design drawings of the 252kV GIS circuit breaker bay for electrical equipment material classification, and identify and group the materials of each functional component: (1) Shell assembly: aluminum alloy shell, identified material is aluminum alloy (g1); (2) Conductor assembly: copper conductive rod and contact, identified material is copper conductor (g2); (3) Insulation assembly: epoxy resin cast insulation, identified material is epoxy resin (g3); (4) Operating mechanism: steel operating linkage and spring, identified material is steel (g4); (5) Sulfur hexafluoride gas: insulation and arc extinguishing medium, identified material is SF6 gas (g5). Establish a material type list: {aluminum alloy, copper conductor, epoxy resin, steel, SF6 gas}.

[0065] S2: Determine the usage threshold range for each material. Through market research, industry standards, and sample testing, data on the usage of each material was collected. Statistical analysis was then used to determine the threshold range for each material.

[0066] S3-4: The actual usage of each material was determined through iterative calculation. The total factory weight G = 2200 kg was obtained from the equipment nameplate. The density of each material was obtained from the material property database: aluminum alloy ρ1 = 2.70. 10³ kg / m³, copper conductor ρ² = 8.93 10³ kg / m³, epoxy resin ρ3 = 1.20 10³ kg / m³, steel ρ₄ = 7.85 10³ kg / m³, SF6 gas ρ5 = 6.17 kg / m³.

[0067] The convergence accuracy was set to ε = 0.1 kg, and the maximum number of iterations K_max = 200. After iterative calculation (the iteration process is the same as in Example 1, and will not be repeated here), the actual usage of each material after convergence is as follows: G1 = 1050 kg (aluminum alloy); G2 = 380 kg (copper conductor); G3 = 190 kg (epoxy resin); G4 = 265 kg (steel); G5 = 38 kg (SF6 gas).

[0068] The verified total weight is 1050 + 380 + 190 + 265 + 38 = 1923 kg, which differs from the factory total weight of 2200 kg. This is because the GIS equipment also includes materials for other components that are not included in the bill of materials for this embodiment. In practical applications, the completeness of the bill of materials should be ensured, and all component materials should be included in the classification system. This embodiment is only used to illustrate the method flow.

[0069] S5: Calculate the total carbon emissions of the ontology based on carbon emission factors. Retrieve the carbon emission factors of each material from the Ecoinvent 3.8 database: Aluminum alloy: S1=8.5kgCO2e / kg; Copper conductor: S2=5.2kgCO2e / kg; Epoxy resin: S3=4.5kgCO2e / kg; Steel: S4=2.2kgCO2e / kg; SF6 gas: S5=23500kgCO2e / kg.

[0070] Calculate the individual carbon emissions: F1 = 8.5 1050 = 8925 kg CO2e; F2 = 5.2 380 = 1976 kg CO2e; F3 = 4.5 190 = 855 kg CO2e; F4 = 2.2 265 = 583 kg CO2e; F5 = 23500 38 = 893000 kg CO2e.

[0071] Total carbon emissions during equipment production: F = 8925 + 1976 + 855 + 583 + 893000 = 905339 kg CO2e The calculation results above show that although the amount of SF6 gas used is extremely small, its carbon emission contribution is as high as 893,000 kg CO2e, accounting for 98.6% of the total emissions. This fully demonstrates the value of the method of the present invention—through refined material usage calculation and itemized carbon emission calculation, it can accurately identify carbon emission hotspots and provide a clear direction for the low-carbon design of equipment.

[0072] Example 3: This example uses a 500kV high-voltage shunt reactor to illustrate the application of the method of the present invention on large electrical equipment.

[0073] S1: Collect the design drawings of the target 500kV high-voltage parallel reactor for electrical equipment materials classification, and identify and group the materials of each functional component: (1) Core assembly: made of stacked silicon steel sheets, identified material is silicon steel sheet (g1); (2) Winding assembly: made of copper conductor, identified material is copper conductor (g2); (3) Insulation system: including insulating paper, insulating molded parts, etc., identified material is insulating material (g3); (4) Insulating medium: reactor oil, identified material is insulating oil (g4); (5) Shell assembly: steel plate welded oil tank, identified material is steel (g5); (6) Cooling device: radiator and pipeline, identified material is steel (grouped with g5). Establish a material type list: {silicon steel sheet, copper conductor, insulating material, insulating oil, steel}.

[0074] S2: Determine the usage threshold range for each material. Through market research, industry standards, and sample testing, data on the usage of each material was collected. Statistical analysis was then used to determine the threshold range for each material.

[0075] S3-4: Determine the actual usage of each material through iterative calculation. Obtain the total factory weight G = 55000 kg from the equipment nameplate. Obtain the density of each material from the material property database. Set the convergence accuracy ε = 0.1 kg and the maximum number of iterations K_max = 200. After iterative calculation, the actual usage of each material after convergence is: G1 = 21500 kg (silicon steel sheet); G2 = 7800 kg (copper conductor); G3 = 1950 kg (insulating material); G4 = 14800 kg (insulating oil); G5 = 12450 kg (steel).

[0076] The verified total weight is 21500 + 7800 + 1950 + 14800 + 12450 = 58500 kg, which does not match the factory total weight of 55000 kg. This is because the actual equipment may include other auxiliary materials not included in the list, or the threshold range settings for some materials may not be precise enough. In this case, the completeness of the material classification should be rechecked, or the threshold range should be adjusted and the process restarted.

[0077] Assuming that a sixth material, "auxiliary material" (g6), was added after verification, with a threshold range of [500, 1500] kg, the following results were obtained after re-iteration: G1 = 20500 kg; G2 = 7500 kg; G3 = 1800 kg; G4 = 14000 kg; G5 = 10500 kg; G6 = 700 kg. The total weight verified is: 20500 + 7500 + 1800 + 14000 + 10500 + 700 = 55000 kg.

[0078] S5: Calculate the total carbon emissions of the equipment based on carbon emission factors. Retrieve the carbon emission factors of each material from the Ecoinvent 3.8 database, calculate the individual carbon emissions, and sum them to obtain the total carbon emissions of the equipment during the production stage. Due to the large amount of materials used and the high total carbon emissions of large reactors, the calculation results are of great significance for the carbon emission assessment of the entire life cycle of substations.

[0079] Please see Figure 2 The present invention also provides a carbon emission accounting system for the production of electrical equipment based on multi-material iteration, comprising the following four modules.

[0080] (I) Electrical Equipment Material Classification Module This module is used to disassemble and identify the target electrical equipment at the material level, establishing a standardized list of constituent material types. Input: Design drawings, technical specifications, or tender technical parameters of the target electrical equipment. Processing Logic: The module has a built-in material identification engine that can automatically match typical material composition templates according to the equipment type, and allows users to manually add, delete, or modify material types. For complex equipment, the module supports step-by-step disassembly—first identifying functional components, and then performing material analysis on each component. Output: A standardized list of material types {g1, g2, ..., g...} n The module outputs a list of material types as fixed parameters, along with a unique code for each material. Data transfer: This module's output list of material types is passed to both the material usage threshold determination module and the numerical iteration calculation engine module.

[0081] (ii) Material Usage Threshold Determination Module: This module is used to define reasonable lower and upper limits for the usage of each material. Input: A list of material types from the classification module; external data sources include market research data, industry standards, measured data from similar equipment samples, supplier technical information, etc.

[0082] Processing logic: (1) Data acquisition submodule: Automatically or semi-automatically collects usage data of each material from multiple data sources; (2) Statistical analysis submodule: Performs statistical analysis on the collected data and extracts the minimum usage value a of each material. n and maximum value b n (3) Threshold calculation submodule: according to min n =a n (1 δ), max n =b n (1+δ) Calculate the lower and upper limits of the dosage, where δ is the safety margin coefficient (default 0.05, which can be adjusted by the user); (4) Review submodule: make a reasonable judgment on the threshold range, exclude obvious erroneous data, and give review opinions.

[0083] Output: A set of material usage thresholds {[min1,max1],[min2,max2],…,[min n ,max n Data transfer: The threshold set output by this module is used as the core constraint parameters and passed to the numerical iterative calculation engine module.

[0084] (III) Numerical Iterative Calculation Engine Module This module is the core solver of the system, used to execute iterative algorithms and reverse-engineer the actual usage of each material. Input: Material type list from the classification module, threshold set from the threshold module, total factory weight G of the equipment, and density parameter ρ of each material. n .

[0085] Processing logic: (1) Initialization unit: Set the iteration round k=0, the maximum number of iterations K_max=200, and the convergence accuracy ε=0.1kg. Calculate the volume coefficient of each material based on the median threshold. and initial material usage G n （0） = r n x n （0） (2) Error calculation unit: calculates the current total weight G. （k） =∑G n （k） and total weight error ΔG （k） =G G （k） (3) Error allocation unit: based on the current weight percentage of each material w n （k） =G n （k） / G （k） The total weight error is allocated to each material to obtain the temporary adjustment amount G. n （temp） =G n （k） +ΔG （k） w n （k）(4) Threshold projection unit: The temporary usage is forcibly constrained to the threshold range, and the set of fixed materials C_fixed that is cut off and the set of free materials C that can still be freely adjusted are recorded. free (5) Residual error redistribution unit: When the residual error is not zero and the free material set is not empty, the residual error is distributed to each free material according to the weight ratio of the free material; (6) Convergence judgment unit: Determine whether the convergence condition is met or the maximum number of iterations is reached, and output the final material usage.

[0086] Output: Actual usage of each material {G1, G2, ..., G...} n Data transmission: The actual usage set of each material output by this module is used as the core input and transmitted to the carbon emission calculation module. Exception handling: If k > K max If convergence is still not achieved, the least squares feasible solution is output—the combination that satisfies the threshold constraint but has the smallest total weight error among the last projection results, and a warning message is issued to prompt the user to check the rationality of the input data.

[0087] (iv) Carbon Emission Calculation Module This module is used to perform the final carbon emission calculation. Input: Actual material usage G from the iterative engine module. n Carbon emission factor S of each material n ( ).

[0088] Processing logic: (1) Factor matching unit: based on material type g n Retrieve the corresponding carbon emission factor S from authoritative databases n If a material is a composite material, it is calculated by weighted average of components; (2) Itemized calculation unit: calculate the carbon emission contribution F of each material. n =S n G n (3) Summation output unit: Summing the carbon emission contributions of all materials to obtain the total carbon emission of the equipment body during the production stage F=∑F n .

[0089] Output: Total carbon emissions F of the equipment during the production phase; optional output includes a detailed list of carbon emissions for each material. Data Transfer: The output of this module is the final calculation result, which can be sent to a display interface, reporting system, or life-cycle assessment platform.

[0090] In another aspect, the present invention also discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the method described above.

[0091] In another aspect, the present invention also discloses a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method described above.

[0092] It is understood that the systems, devices, and storage media provided in the embodiments of the present invention correspond to the methods provided in the embodiments of the present invention, and the explanations, examples, and beneficial effects of the relevant content can be referred to the corresponding parts of the above methods.

[0093] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state disk (SSD)).

[0094] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0095] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0096] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for carbon emission accounting in the production of electrical equipment using multi-material iteration, characterized in that, Includes the following steps: S1: Disassemble and identify the target electrical equipment at the material level, and establish a standardized list of constituent material types g1, g2, ..., g n , where n is the total number of material types; S2: Based on market research data, industry standards, measured data from similar equipment samples, and / or supplier technical information, for each material g n Define the minimum dosage. n With the maximum usage limit (max) n Determine the set of material usage thresholds {[min1,max1],[min2,max2],…,[min n ,max n ]}; S3: Obtain the total factory weight G of the target electrical equipment, and the density parameters ρ of each material. n ; S4: Using the material type list, the material usage threshold set, the total weight at the factory gate G, and the density parameter ρ n As input, perform iterative calculations, while satisfying the total weight constraint ∑G n =G and threshold constraint min n ≤G n ≤max n Under the given conditions, reverse calculation of the actual usage G of each material. n ; S5: Based on the actual usage of each material G n and the corresponding carbon emission factor S n The total carbon emissions of the equipment during the production stage are calculated as F = ∑S. n G n It also outputs the calculation results.

2. The method for carbon emission accounting in the production of electrical equipment based on multi-material iteration as described in claim 1, characterized in that, Step S1 includes: S1.1: Collect the design drawings of the target electrical equipment; S1.2: Identify the materials of each functional component and record the name, purpose, and form of each material; S1.3: Group materials with the same chemical composition into the same material type. n Establish a standardized list of material types and assign a unique code to each material.

3. The method for carbon emission accounting in the production of electrical equipment based on multi-material iteration as described in claim 1, characterized in that, In step S2, the dosage lower limit min n and maximum usage limit n Determined as follows: min n =a n (1 δ), max n =b n (1+δ), where a n b is the minimum amount of this material extracted from multi-source data. n δ represents the maximum amount of material used extracted from multi-source data, and δ is the safety margin coefficient.

4. The method for carbon emission accounting in the production of electrical equipment based on multi-material iteration as described in claim 1, characterized in that, Step S4 includes: S4.1: Initialization, set the iteration number k=0, and calculate the volume coefficient of each material based on the median threshold. Initial material usage G n （0） = ρ n χ n （0） ; S4.2: Calculate the total weight of the k-th round. and total weight error ; S4.3: Allocate the total weight error according to the current weight percentage of each material to obtain the temporary adjustment amount; S4.4: Force the temporary usage to be within a threshold range, and record the set of fixed materials C that are cut. fixed And the set of free materials C that can still be freely adjusted free ; S4.5: Calculate the total weight and remaining error after cutting. If the absolute value of the remaining error is less than or equal to the convergence accuracy ε, then convergence is determined and the current material usage is output. S4.6: If the remaining error is not zero and the free material set is not empty, then distribute the remaining error to each free material according to the weight ratio of the free materials, update the amount of free materials, and keep the value of the fixed materials unchanged after cutting. S4.7: Let k ← k+1, return to sub-step S4.2 and repeat until the convergence condition is met or the maximum number of iterations is reached.

5. The method for carbon emission accounting in the production of electrical equipment using multi-material iteration as described in claim 4, characterized in that, In sub-step S4.4, the temporary usage is projected onto the threshold in the following manner: when the temporary usage is less than min... n At that time, Gn (clip) =min n When the temporary usage exceeds the maximum n At that time, Gn (clip) =max n When the temporary dosage is in [min n ,max n When Gn is within the interval, (clip) =Temporary usage.

6. The carbon emission accounting method for the production stage of electrical equipment based on iterative multi-material usage as described in claim 1, characterized in that, Step S5 includes: S5.1: According to material type g n Retrieve the corresponding carbon emission factor S from the carbon emission factor database. n ; S5.2: Calculate the carbon emission contribution F of each material n =S n G n ; S5.3: Sum the carbon emission contributions of all materials to obtain the total carbon emission of the equipment itself during the production stage, F = ∑F n It also outputs the calculation results.

7. The method for carbon emission accounting in the production of electrical equipment based on multi-material iteration as described in claim 1, characterized in that, The target electrical equipment includes main transformers, GIS, HGIS, high-voltage reactors, circuit breakers or disconnect switches.

8. A carbon emission accounting system for the production of electrical equipment using multiple materials iterative processes, characterized in that, include: The electrical equipment material classification module is used to disassemble and identify target electrical equipment at the material level, and establish a standardized list of constituent material types g1, g2, ..., g n The material type list is then passed to the material usage threshold determination module and the numerical iteration calculation engine module, respectively. The material usage threshold determination module is used to determine the g of each material based on market research data, industry standards, measured data from similar equipment samples, and / or supplier technical information. n Define the minimum dosage. n With the maximum usage limit (max) n The set of material usage thresholds is determined and passed as core constraint parameters to the numerical iteration calculation engine module; The numerical iterative calculation engine module is used to calculate the material type list, the material usage threshold set, the total factory weight G of the target electrical equipment, and the density parameter ρ of each material. n As input, execute the iterative algorithm, satisfying the total weight constraint ∑G n =G and threshold constraint min n ≤G n ≤max n Under the condition of reverse calculation, the actual usage G of each material is calculated. n The actual usage of each material is then passed to the carbon emission calculation module. The carbon emission calculation module is used to calculate emissions based on the actual usage of each material (G). n and the corresponding carbon emission factor S n Perform the final carbon emission calculation F=∑S n G n It also outputs the total carbon emissions F of the equipment during the production stage.

9. The carbon emission accounting system for electrical equipment production based on multi-material iteration as described in claim 8, characterized in that, The numerical iterative calculation engine module includes: The initialization unit is used to set the iteration round k=0, the maximum number of iterations Kmax, and the convergence accuracy ε, and to calculate the volume factor of each material based on the median threshold. and initial material usage G n （0） = ρ n χ n （0） ; Error calculation unit, used to calculate the current total weight G （k） =∑G n （k） and total weight error ΔG （k） =G G （k） ; The error allocation unit is used to allocate the total weight error to each material according to the current weight ratio of each material, so as to obtain a temporary adjustment amount. The threshold projection unit is used to force the temporary usage to be constrained within the threshold range and to record the fixed material set and the free material set; The residual error redistribution unit is used to distribute the residual error to each free material according to the weight ratio of the free materials when the residual error is not zero and the free material set is not empty. The convergence judgment unit is used to determine whether the convergence condition is met or the maximum number of iterations is reached, and outputs the final material usage.

10. The carbon emission accounting system for electrical equipment production based on multi-material iteration as described in claim 8, characterized in that, The carbon emission calculation module includes: Factor matching unit, used to match material type g n Retrieve the corresponding carbon emission factor S from the carbon emission factor database. n ; The sub-item calculation unit is used to calculate the carbon emission contribution Fn=S of each material. n G n ; The summation output unit is used to sum the carbon emission contributions of all materials to obtain the total carbon emission of the equipment body during the production stage, F = ∑F. n It also outputs the calculation results.

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