Accounting method and system based on constructed light-hydrogen-electricity integrated lamp carbon footprint database

Abstract

The invention relates to an accounting method and system based on a constructed light-hydrogen-electricity integrated lamp carbon footprint database, and is applied to the technical field of carbon footprint accounting, and the method comprises the steps: carrying out the automatic analysis of product information through employing a pre-trained S-BERT semantic analysis model, replacing a tedious manual interpretation and configuration process, remarkably shortening the cycle of carbon footprint accounting, and improving the efficiency of carbon footprint accounting. The automation degree and the accounting efficiency are improved; according to intelligent matching based on semantic analysis, errors caused by artificial experience differences or negligence are reduced, semantic matching rules and factor libraries are optimized for core components of the light-hydrogen-electricity integrated lamp, the accounting pertinence and accuracy are improved, the technical blank of new energy lamp carbon footprint accounting is filled, and the new energy lamp carbon footprint accounting efficiency is improved. The objectivity and the accuracy of accounting standard and factor selection are ensured, and the accuracy and the consistency of accounting are improved; different product characteristics, market requirements and variable accounting standards can be automatically adapted, enterprises can conveniently cope with complex international trade environments, and the adaptability and flexibility of accounting are enhanced.

Description

Technical Field

[0001] This invention relates to the field of carbon footprint accounting technology, specifically to an accounting method and system based on a constructed integrated photovoltaic-hydrogen-electric lamp carbon footprint database. Background Technology

[0002] Product carbon footprint refers to the total greenhouse gas emissions directly or indirectly generated by a product throughout its life cycle, including all stages from raw material acquisition, production, transportation, distribution, use to disposal. With increasing global attention to climate change and the implementation of relevant international trade policies (such as the EU's carbon border adjustment mechanism), accurately and efficiently calculating product carbon footprint has become an important issue that enterprises, especially export-oriented enterprises, must address.

[0003] Currently, calculating product carbon footprints faces numerous challenges. First, multiple parallel accounting standards exist globally, such as the International Organization for Standardization's ISO 14067 standard, the European Union's Product Environmental Footprint (PEF) standard, and national standards in various countries (such as China's GB / T 24067-2024). These different standards differ in accounting boundaries, data requirements, and calculation methods. Companies need to choose the appropriate standard based on their target market or customer requirements. Second, carbon emission factor data is vast and dynamically changing, requiring continuous updates to ensure the accuracy of the calculations.

[0004] To address these challenges, several configurable carbon footprint accounting systems have emerged in the existing technology. These systems typically include a dynamically updated emission factor database and allow users to build accounting models by configuring lifecycle stages and accounting elements, enabling adaptive accounting for different products. However, these existing systems still have shortcomings in terms of automation and intelligence. Specifically, when faced with new product information, such as unstructured product names, semi-structured bills of materials, or process description text, the system cannot automatically understand this information. This forces users, typically experts in carbon accounting, to perform a significant amount of manual interpretation and judgment, manually converting this unstructured information into structured input that the system can recognize, and accordingly manually selecting applicable accounting standards, determining accounting boundaries, and choosing matching emission factors. This process is not only inefficient and labor-intensive, but also highly susceptible to errors introduced by human judgment bias, affecting the accuracy and reliability of the final accounting results. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide a method and system for calculating the carbon footprint of a constructed integrated photohydrogen-electric lamp, aiming to solve the technical problems of low automation, reliance on manual interpretation and configuration, and the need to improve efficiency and accuracy in the existing carbon footprint calculation process.

[0006] According to a first aspect of the present invention, a method for calculating the carbon footprint of an integrated photohydrogen-electric lamp based on a constructed database is provided, the method comprising: Establish a carbon footprint database for integrated photoelectric, hydrogen, and electric lamp products; Obtain product information related to the photo-hydrogen-electric integrated lamp product to be accounted for, and parse the product information using a pre-trained S-BERT semantic analysis model to achieve standardized field matching of product information; Based on the standardized fields of the product information, target feature dimension data is extracted. The target feature dimension data includes: export region, core product components, production process type and compliance certification type. The similarity between the export region and compliance certification type and the description text corresponding to each accounting standard in the database is calculated, and the accounting standard with the highest semantic similarity is selected as the target accounting standard. Based on the core components of the product and the type of production process, a similarity match is performed on the data list field in the database to obtain an emission list; based on the emission list, a target emission factor list is obtained by matching the target emission factors in the factor library of the target accounting standard through similarity matching. Based on the established target accounting standards, target emission factor list, and activity data from the emission inventory, a standardized accounting model is used to calculate the carbon footprint of the product to be accounted for.

[0007] Preferably, The database includes: a carbon emission factor database, a life cycle inventory database (LCI), a life cycle impact assessment database (LCIA), and a unit process database (UPR). The carbon emission factor database includes at least the EU PEF standard, ISO 14067 standard, and GB / T 24067-2024 standard; Each emission factor is associated with a set of metadata, which is in the following format: standard number-applicable scenario-geographical scope-update time.

[0008] Preferably, it further includes: Automatic emission factor update methods include: The database connects to official data sources from multiple standards organizations, monitors emission factor updates in real time, and synchronizes updates to the Life Cycle Inventory (LCI) and Life Cycle Impact Assessment (LCIA) databases based on preset standard-factor substitution relationships.

[0009] Preferably, The database model supports the construction of integrated photo-hydrogen-electric lamp products according to a preset system classification, which includes: products, systems, components, parts, and raw materials; the preset system classification distinguishes different integrated photo-hydrogen-electric lamp products using a 5-digit hexadecimal code. The database model also supports nested carbon footprints, dividing the integrated photovoltaic-hydrogen-electric lamp product into a hydrogen fuel cell power generation system, a solar power generation system, a lithium battery power generation system, and a lamp holder subsystem. Data from each subsystem are referenced to participate in the calculation of the product's carbon footprint. The database contains a standard adaptation association table, which represents the mapping relationship between accounting standards, emission factors, and LCI data. When an emission factor update is triggered, the corresponding data in the database is updated in conjunction with the standard adaptation association table.

[0010] Preferably, it further includes: A system boundary for carbon footprint accounting of integrated photonics, hydrogen, and electricity lamp products is pre-defined. This system boundary is obtained by combining semantic analysis with the product's export region and compliance certification type using a pre-trained S-BERT semantic analysis model. The carbon footprint accounting of integrated photonics, hydrogen, and electricity lamp products is then performed based on this system boundary.

[0011] Preferably, The system boundary is divided into carbon emissions from raw material acquisition to product delivery, including: the raw material acquisition stage, production and processing stage, and transportation stage of the fuel cell power generation system, solar power generation system, lithium battery power generation system, and lamp holder subsystem corresponding to the integrated photovoltaic-hydrogen-electric lamp product to be calculated. The phase division of the system boundary is obtained based on the target accounting standard.

[0012] Preferably, it further includes: Methods for compensating for missing data include: For missing data in the core components or production process types of the product, a pre-trained S-BERT semantic analysis model is used to obtain similar products of the photo-hydrogen-electric integrated lamp to be verified through semantic analysis; reference data is selected from the similar products, and the reference data meets the requirement that the semantic similarity with the production process of the product to be verified is greater than a preset threshold, and the reference basis is marked; if there is obvious abnormality in the data, an early warning is triggered and manual verification is prompted.

[0013] Preferably, it further includes: The carbon footprint accounting results are displayed, including: The carbon footprint accounting results include: product information, carbon emissions, carbon emission distribution of each subsystem, carbon data quality analysis, standard adaptation instructions, and semantic matching logs.

[0014] Preferably, The standard adaptation instructions include the name of the target accounting standard used in the accounting, the version of the target accounting standard, and the version of the emission factor library. The semantic matching log includes the semantic similarity values ​​of the feature dimension parsing results and the recommendation results. If there is reference data, the source of the reference data is indicated to trace the appropriateness of the calculation process.

[0015] According to a second aspect of the present invention, an accounting system based on a constructed carbon footprint database of integrated photohydrogen-electric lamps is provided, the system comprising: Database building module: used to build a carbon footprint database for integrated photohydrogen-electric lamp products; Information parsing module: Used to obtain product information related to the photo-hydrogen-electric integrated lamp product to be calculated, and to parse the product information through a pre-trained S-BERT semantic analysis model to achieve standardized field matching of product information; Target accounting standard confirmation module: used to extract target feature dimension data based on the standardized fields of the product information. The target feature dimension data includes: export region, core product components, production process type and compliance certification type. The module calculates the similarity between the export region and compliance certification type and the description text corresponding to each accounting standard in the database, and selects the accounting standard with the highest semantic similarity as the target accounting standard. Target emission factor matching module: used to perform similarity matching based on the core components of the product and the production process type in the database according to the data list field to obtain an emission list; and to match the target emission factors in the factor library of the target accounting standard according to the emission list to obtain a target emission factor list. Carbon footprint accounting module: Used to calculate the carbon footprint of the product to be accounted for using a standardized accounting model based on the determined target accounting standards, target emission factor list and emission inventory activity data.

[0016] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects: This application utilizes a pre-trained S-BERT semantic analysis model to automatically analyze product information, replacing the tedious manual interpretation and configuration process. This significantly shortens the carbon footprint accounting cycle and improves automation and efficiency. Intelligent matching based on semantic analysis reduces errors caused by human experience differences or oversights. Semantic matching rules and factor libraries are optimized for core components of integrated photovoltaic-hydrogen-electric lamps (hydrogen-air-cooled fuel cells and solid-state hydrogen storage components), enhancing the targeting and accuracy of the accounting. This fills the technological gap in carbon footprint accounting for new energy lighting fixtures, ensuring the objectivity and accuracy of accounting standards and factor selection, and improving the accuracy and consistency of the accounting. The solution can automatically adapt to different product characteristics, market requirements, and changing accounting standards, facilitating enterprises in dealing with complex international trade environments and enhancing the adaptability and flexibility of the accounting process.

[0017] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0019] Figure 1 This is a flowchart illustrating an accounting method based on a constructed carbon footprint database of an integrated photohydrogen-electric lamp, according to an exemplary embodiment. Figure 2 This is an overall schematic diagram of the carbon footprint database and accounting system for photovoltaic hydrogen-electric products, according to another exemplary embodiment; Figure 3 This is a schematic diagram of the architecture of a pre-trained SBERT semantic analysis model according to another exemplary embodiment; Figure 4 This is a system schematic diagram illustrating an accounting system based on a constructed carbon footprint database of an integrated photohydrogen-electric lamp, according to another exemplary embodiment. In the attached diagram: 1-Database construction module, 2-Information parsing module, 3-Target accounting standard confirmation module, 4-Target emission factor matching module, 5-Carbon footprint accounting module. Detailed Implementation

[0020] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the invention as detailed in the appended claims.

[0021] Example 1 Figure 1 This is a flowchart illustrating an exemplary embodiment of a method for calculating the carbon footprint of an integrated photohydrogen-electric lamp based on a constructed database. Figure 1 As shown, the method includes: S1, construct a carbon footprint database for integrated photo-hydrogen-electric lamp products; S2, obtain product information related to the photo-hydrogen-electric integrated lamp product to be calculated, and parse the product information through the pre-trained S-BERT semantic analysis model to achieve standardized field matching of product information; S3. Extract target feature dimension data based on the standardized fields of product information. The target feature dimension data includes: export region, core components of the product, production process type and compliance certification type. Calculate the similarity between the export region and compliance certification type and the description text corresponding to each accounting standard in the database, and select the accounting standard with the highest semantic similarity as the target accounting standard. S4. Based on the core components of the product and the type of production process, perform similarity matching on the data list field in the database to obtain an emission list; based on the emission list, perform similarity matching on the target emission factors in the factor library of the target accounting standard to obtain a target emission factor list; S5. Based on the established target accounting standards, target emission factor list, and activity data of the emission inventory, the carbon footprint of the product to be accounted for is calculated using a standardized accounting model. Understandably, this application requires the prior construction of a carbon footprint database for integrated photohydrogen-electric lamp products. The database contains at least four core sub-databases, and the functions and relationships of each sub-database are as follows: Carbon emission factor library: Stores emission factors under different accounting standards, with each emission factor associated with metadata such as "standard number-applicable scenario-geographical scope-update time"; The carbon emission factor database includes emission factor databases corresponding to mainstream international and domestic carbon footprint accounting standards, covering at least: International standards: EU PEF (Product Environmental Footprint) standard, ISO 14067 standard; Domestic standard: GB / T 24067-2024 "Greenhouse gases, product carbon footprint, quantification requirements and guidelines"; Each factor is associated with complete metadata, such as "PEF 2024 version hydrogen air-cooled fuel cell stack production emission factor (2.8 kgCO2 / kW)", which indicates the applicable region (EU), update time (2024-03), and data source (EU JRC database). Automatic factor update mechanism: Data source integration: Connect to official data sources from standards organizations such as the EU JRC and the China Council for International Cooperation on Environment and Development to monitor factor updates in real time; Substitutional Relationship: Preset "standard-factor" substitutional relationship (e.g., "PEF 2024 version solid hydrogen storage alloy preparation factor substitutes 2023 version"); Linked Updates: When basic factors (such as electricity emission factors and hydrogen production factors) are updated, the system automatically triggers the synchronous update of the LCI library, LCIA library, and "Standard Adaptation Association Table" to ensure the timeliness of accounting data. LCI Library: Records the input and output data of each unit process of the photohydrogen-electric integrated lamp (such as the raw material consumption and energy consumption in the production of solid hydrogen storage components). LCIA Library: Stores data related to carbon footprint impact assessment (such as global warming potential (GWP) values). UPR library: Stores basic process data for each production unit (such as fuel cell stack assembly and hydrogen storage tank molding).

[0022] The database supports classification systems and coding, specifically including: The database model is constructed according to a five-level classification system of "product-system-component-part-raw material" and a 5-digit hexadecimal code is used for differentiation (for example, in the code 010103010C, 01 represents the integrated photovoltaic-hydrogen-electric lamp product, 01 represents the fuel cell power generation system, 03 represents the hydrogen air-cooled fuel cell component, 01 represents the proton exchange membrane, and 0C represents the precious metal catalyst), to ensure that the data classification is clear and traceable.

[0023] The database supports data nesting and association, specifically including: Supporting a nested carbon footprint system: The integrated photovoltaic-hydrogen-electric lamp product is divided into four subsystems: fuel cell power generation system (including hydrogen air-cooled fuel cell and hydrogen delivery components), solar power generation system, lithium battery power generation system, and lamp holder subsystem. Data from each subsystem can be referenced (e.g., when calculating the overall product carbon footprint, the LCI data of the hydrogen air-cooled fuel cell subsystem is automatically called). At the same time, a "standard adaptation association table" is established to record the mapping relationship between "calculation standard - emission factor - LCI data" to provide data support for the calculation.

[0024] After the database is built, when it is necessary to perform accounting for the integrated photohydrogen-electric lamp product, as shown in the attached document... Figure 2 As shown, it specifically includes: Data Acquisition and Analysis: Supports multiple data access methods: manually creating data lists, batch importing BOM tables (Excel or PDF format files), and creating data lists based on existing database data lists; after access, it automatically parses the data format and extracts core information such as product name, model, life cycle unit process, materials (such as hydrogen air-cooled fuel cells, solid hydrogen storage components), activity level (such as component production energy consumption), and emission factors. Semantic analysis preprocessing: The BOM (Bill of Materials) text information is automatically parsed based on a pre-trained S-BERT semantic analysis model. The architecture of the S-BERT semantic analysis model is shown in the attached figure. Figure 3 As shown, Recommended standardized fields: such as identifying the text "hydrogen air-cooled fuel cell stack" and matching standard fields such as "material name: hydrogen air-cooled fuel cell stack; specification: XXkW; life cycle stage: production and processing"; Field validation: If the parsed value is "solid hydrogen storage tank material 304 stainless steel", it will automatically check whether it conforms to the database's preset "hydrogen storage component material" field specification. If it does not conform, it will prompt for correction.

[0025] The parsable product-related text information includes: product name, model, export region, production process description, bill of materials text and compliance certification requirements, and can extract four major feature dimensions: "export region, core product components, production process type, and compliance certification type". The multi-dimensional data quality assessment algorithm can dynamically assign weights to each dimension (30% for export region, 25% for core product components, 20% for production process type, and 25% for compliance certification type); a customizable semantic similarity threshold (default 80%) can be set; based on the feature dimension matching results and the similarity threshold, an appropriate accounting standard, emission factor, and system boundary recommendation list are output, specifically including: If the parsing results in "Export Region = EU" and "Compliance Certification Requirement = EPD (Environmental Product Declaration)", with a semantic similarity ≥ 90%, the EU PEF standard, the corresponding emission factor library for PEF, and the "cradle to gate" (raw material acquisition to product delivery) system boundary are prioritized. If the target market is the EU and EPD certification is required, the PEF standard will be automatically loaded, using the GWP value specified by PEF, and "cross-border hydrogen transportation" will be included in the system boundary. If the target is domestic compliance, the GB / T 24067-2024 standard will be automatically loaded, and the system boundary will include the "domestic transportation after product delivery" stage. The factors will use domestically regionalized data (such as "electricity emission factors in North China"), specifically including: Semantic analysis: Extract information such as "export region = EU" and "certification requirement = EPD". When the semantic similarity is ≥90%, the "cradle to gate" boundary (covering the stages of raw material acquisition → product delivery, including the production and transportation of hydrogen-containing air-cooled fuel cells and solid hydrogen storage components) is recommended. Standard Adaptation: Based on the recommended boundaries, load the boundary rules of the corresponding standards (such as "exclude carbon emissions during product use" under the PEF standard) to ensure that the boundary settings are compliant.

[0026] If the core component of the product is identified as "hydrogen air-cooled fuel cell" and the production process description includes "stack assembly - air-cooling system integration - performance testing", and the semantic similarity is ≥85%, then the relevant emission factors (including sub-factors such as stack catalyst preparation and air-cooling fan processing) under the target standard for "hydrogen air-cooled fuel cell production" are recommended. If the core component of the product is identified as "solid-state hydrogen storage" and the production process description includes "hydrogen storage material synthesis - hydrogen storage tank molding - sealing test," and the semantic similarity is ≥80%, then the following emission factors related to "solid-state hydrogen storage component production" under the target standard (including sub-factors such as hydrogen storage alloy preparation and metal tank processing) are recommended: When selecting a data list in the database, it automatically recommends suitable data (e.g., if the database parses "product containing hydrogen air-cooled fuel cell" → recommends "hydrogen air-cooled fuel cell production unit process data list"). Emission factor matching: Load the target accounting standard factor library, and use semantic algorithms to verify factor suitability (e.g., "PEF2024 version hydrogen air-cooled fuel cell catalyst factor" has a semantic similarity of ≥85% with the product process) to ensure accurate factor selection; It should be noted that if the data entering the database is missing or abnormal, the pre-trained S-BERT semantic analysis model can be used to find data from other batches or companies producing similar integrated photohydrogen-electric lamps with similar manufacturing processes as a reference. The reference data must meet a semantic similarity of ≥80%, and the reference basis must be indicated, specifically including: For missing or abnormal data (such as "emission factor of solid hydrogen storage component is missing"), the system automatically searches for data from other batches or companies with similar photovoltaic-hydrogen-electric integrated lamp products and similar production processes as a reference. The reference data must meet the requirement of semantic similarity ≥80% (the threshold can be customized) and be marked with the reference basis (such as "reference to the emission factor of solid hydrogen storage component of model GH-2023-S, similarity 85%)". If there is obvious abnormality in the data (such as "energy consumption of hydrogen air-cooled fuel cell production far exceeds the industry average"), an alert is triggered and manual verification is prompted.

[0027] Carbon footprint accounting: The life cycle assessment method is adopted, and the calculation is based on a standardized accounting model. The core formula is:

[0028] In the formula, PCF Carbon footprint of integrated photohydrogen-electric lamp products (unit: kgCO2 / set). AD i For the first product system i Activity data for each emission inventory (such as energy consumption in hydrogen air-cooled fuel cell production and raw material consumption for solid hydrogen storage components). EF i For the first product system i Emission factor data for each emission inventory (from the recommended target accounting standard factor library, with adaptability verified by semantic algorithms); Results Analysis and Presentation: Output multi-dimensional accounting results, including: Basic information: Product name, model, accounting standard, factor library version; Carbon emissions: Total carbon footprint and the carbon emission share of each subsystem (fuel cell power generation system, solar power generation system, etc.) (e.g., "the carbon emission share of the hydrogen air-cooled fuel cell subsystem is 42%"). Data quality analysis: data integrity (e.g., "95% of the data comes from real-world enterprise data, and 5% is semantic recommendation reference data"), factor fit (e.g., "average semantic matching degree of factors is 88%)); Standard Adaptation Description and Semantic Log: Mark the standards that the calculation conforms to (e.g., "Complies with PEF 2024 standard, can be used for EU EPD certification"), record the semantic parsing results and recommendation basis, so as to facilitate traceability and compliance verification; Among them, the adaptation description includes the standard name, standard version and factor library version used in the calculation; the semantic matching log includes feature dimension parsing results, semantic similarity values ​​of recommendation results and reference data sources (if any), which are used to trace the rationality of the adaptation in the calculation process.

[0029] To better understand the technical solutions described above in this application, the following implementation examples are provided, including: Case 1: A new energy company is exporting integrated photovoltaic-hydrogen-electric lamps to the EU market. It needs to complete carbon footprint accounting and obtain EPD certification according to the EU PEF standard. The core configuration of the product is a "1.0 kW hydrogen air-cooled fuel cell (including platinum-based catalyst and proton exchange membrane) + 100 W monocrystalline silicon photovoltaic module + aluminum alloy lamp holder." The production process covers "hydrogen air-cooled fuel cell stack assembly → air-cooling system integration → performance testing → photovoltaic module packaging → complete unit assembly." The company needs to achieve compliant accounting through this application to meet the EU CBAM carbon tariff requirements. (See attached...) Figure 2 As shown, the specific implementation process is as follows: Carbon footprint data list for integrated photoelectric, hydrogen, and electric lamp products has been entered into the database: Data Import: Enterprises import data in batches using an Excel-formatted BOM table. Key text information includes: "Product Name: Hydrogen-Air-Cooled Fuel Cell Photovoltaic-Hydrogen-Electric Integrated Lamp; Export Region: EU, France; Certification Requirements: EPD; Core Components: 1.0 kW Hydrogen-Air-Cooled Fuel Cell (Proton Exchange Membrane Material: Perfluorosulfonic Acid Resin, Catalyst: Platinum-Based), 100 W Monocrystalline Silicon Photovoltaic Module; Activity Level Data: Stack Assembly Energy Consumption 7.8 kWh / unit, Photovoltaic Module Encapsulation Energy Consumption 4.2 kWh / unit."

[0030] Semantic intelligent preprocessing: The S-BERT semantic analysis model is used to parse the BOM table text and automatically recommend standardized fields. Component fields: "Material name: Hydrogen air-cooled fuel cell; Specification: 1.0 kW; Life cycle stage: Production and processing (including fuel cell stack catalyst preparation and air-cooled fan processing)" and "Material name: Monocrystalline silicon photovoltaic module; Specification: 100W; Life cycle stage: Production and processing (including monocrystalline silicon cutting and module packaging)". Process field: "Unit process: Integration of air-cooled system for hydrogen air-cooled fuel cell; Activity level data: Quantity of air-cooled fan assembly: 1 unit / unit, assembly time: 0.25 h / unit".

[0031] Data governance: Identify the missing "emission factor of platinum-based catalyst for hydrogen air-cooled fuel cells" and match data of similar products through semantic analysis algorithms: It is recommended to refer to the catalyst factor of the same enterprise and process model (semantic similarity 87%), and the reference basis is "production batch in February 2024, process consistency reaches 90%".

[0032] Carbon footprint database of integrated photoelectric lamps: Database access and standard adaptation: Based on the semantic parsing results ("Export to EU + EPD certification", semantic similarity 92%), automatically load the PEF 2024 factor library and synchronously update the LCI library data. Carbon emission factor library: calls up the "preparation factor of platinum-based catalyst for hydrogen air-cooled fuel cells (3.5 kg CO2 / g)", "processing factor of air-cooled fan (0.75 kg CO2 / unit)" and "encapsulation factor of monocrystalline silicon photovoltaic module (0.72 kg CO2 / W)" under the PEF standard; LCI Library: Updated "Input Data for Hydrogen Air-Cooled Fuel Cell Production Unit" - Platinum-based catalyst consumption 0.4 g / unit, air-cooled fan 1 unit / unit, monocrystalline silicon photovoltaic module raw material consumption 1.2 kg / unit; Data classification and coding: Coding is carried out according to a five-level system of "product-system-component-part-raw material". For example: Product code: 01 (photovoltaic-hydrogen-electric integrated lamp); System code: 01 (fuel cell power generation system); Component code: 03 (hydrogen air-cooled fuel cell component); Part code: 01 (proton exchange membrane); Raw material code: 0C (perfluorosulfonic acid resin) to achieve full-chain data traceability.

[0033] Carbon footprint calculation and results display of integrated photoelectric, hydrogen, and electric lamp products: System boundary setting: The semantic algorithm recommends a "cradle to gate" boundary (semantic similarity 92%), and the adaptive accounting engine module loads PEF standard rules to clearly define the boundary coverage of "hydrogen air-cooled fuel cell raw material acquisition (platinum ore mining, resin synthesis) → stack production → air-cooled system integration → photovoltaic module production → complete unit assembly → export sea freight (Shanghai Port, China to Le Havre Port, France, 9800 km)", excluding the product use and disposal stages.

[0034] Carbon footprint accounting: using the core formula: The calculations, key parameters, and results are shown in Table 1: Table 1 Key parameters and calculation results of carbon footprint of photohydrogen-electric products in Case 1

[0035] Results Display: Output multi-dimensional results: Basic information: Product: Photovoltaic-hydrogen-electric integrated lamp; calculation standard: PEF 2024; factor library version: 2024.03. Carbon emission distribution: Monocrystalline silicon photovoltaic modules account for 77.4%, sea freight exports account for 19.0%, hydrogen air-cooled fuel cells account for 2.3%, and assembly energy consumption accounts for 1.3%. Compliance statement: "The accounting results comply with EU PEF standards and can be used for EPD certification and CBAM carbon tariff declarations"; Semantic log: "Export region - standard matching degree 92%, hydrogen air-cooled fuel cell factor matching degree 87%, data integrity 94%".

[0036] Case 2: A company is purchasing integrated photovoltaic-hydrogen-electric lights for lighting in its domestic industrial park. The company needs to complete carbon footprint accounting according to the national standard GB / T 24067-2024 and meet the dual-carbon project acceptance requirements. The core configuration of this product is "4L solid-state hydrogen storage module (LaNi5 hydrogen storage alloy) + 1.0 kW hydrogen air-cooled fuel cell (including platinum-based catalyst proton exchange membrane) + 160W polycrystalline photovoltaic module + steel structure lamp holder". The manufacturing process includes "hydrogen storage alloy synthesis → hydrogen storage tank molding → sealing test → photovoltaic module welding → complete unit assembly", as shown in the attached document. Figure 2 As shown, the specific implementation process is as follows: Carbon footprint data list for integrated photoelectric, hydrogen, and electric lamp products has been entered into the database: Data import: Enterprises manually input information, key information includes "Product Name: Hydrogen-Air-Cooled Fuel Cell Photovoltaic-Hydrogen-Electric Integrated Lamp; Certification Requirements: Compliant with GB / T 24067-2024 standard; Core Components: 4L solid-state hydrogen storage tank (LaNi5 hydrogen storage alloy), 1.0 kW hydrogen-air-cooled fuel cell (including platinum-based catalyst proton exchange membrane), 100 W monocrystalline silicon photovoltaic module; Activity Level Data: Tank welding energy consumption: 3.5 kWh / unit, stack assembly energy consumption: 7.8 kWh / unit, photovoltaic module encapsulation energy consumption: 4.2 kWh / unit".

[0037] Semantic intelligent preprocessing: The S-BERT semantic analysis model is used to parse the BOM table text and automatically recommend standardized fields. Component field: "Material name: Solid hydrogen storage tank; Specification: 4 L (LaNi5 hydrogen storage alloy); Life cycle stage: Production and processing (including hydrogen storage alloy synthesis and metal tank processing)"; Process field: "Unit process: hydrogen storage tank forming; Activity level data: tank welding energy consumption: 3.5 kWh / unit".

[0038] Data governance: An anomaly was identified in the "Polycrystalline photovoltaic module welding emission factor" (the enterprise reported a value of 0.08 kgCO2 / W, far exceeding the industry average of 0.05 kgCO2 / W). An alert was triggered, and data from enterprises using the same process were matched using a semantic algorithm (semantic similarity of 83%). A corrected factor of 0.051 kgCO2 / W was recommended. After verification by the enterprise, it was confirmed that the original data was an input error ("welding energy consumption" was mistakenly entered as "emission factor"). After correction, the data was entered into the database.

[0039] Carbon footprint database of integrated photoelectric lamps: Database access and standard adaptation: Based on semantic parsing results ("domestic park lighting + GB / T 24067-2024 standard", semantic similarity 83%), the domestic factor library is automatically loaded, and the LCI library data is updated synchronously. Carbon emission factor library: calls "LaNi5 hydrogen storage alloy synthesis factor (8.3kgCO2 / g)", "metal tank processing factor (1.1 kgCO2 / unit)" and "polycrystalline silicon photovoltaic module welding factor (0.051 kgCO2 / W)" under GB / T 24067-2024 standard; LCI Library: Updated "Input Data for Solid Hydrogen Storage Tank Production Unit" - LaNi5 hydrogen storage alloy consumption: 1.5 kg / unit, metal tank: 3.2 units / unit, welding energy consumption: 3.5 kWh / unit.

[0040] Data classification and coding: Coding is carried out according to a five-level system of "product-system-component-part-raw material". For example: Product code: 01 (photovoltaic-hydrogen-electric integrated lamp); System code: 01 (fuel cell power generation system); Component code: 04 (solid-state hydrogen storage component); Part code: 02 (hydrogen storage tank); Raw material code: 0D (LaNi5 hydrogen storage alloy) to achieve full-chain data traceability.

[0041] Carbon footprint calculation and results display of integrated photoelectric, hydrogen, and electric lamp products: System boundary setting: The semantic algorithm recommends a "cradle to gate" boundary (compliant with GB / T 24067-2024 standard), and the adaptive accounting engine module loads the GB / T 24067-2024 standard rules to clearly define the boundary coverage of "solid hydrogen storage alloy mining → hydrogen storage tank production → hydrogen fuel cell production → photovoltaic module production → complete machine assembly → domestic road transportation (320 km from factory to park)", excluding the product use and disposal stages; Carbon footprint accounting: using the core formula: The calculations, key parameters, and results are shown in Table 2. Table 2 Key parameters and calculation results of carbon footprint of photohydrogen-electric products in Case 2

[0042] Results Display: The system outputs multi-dimensional results: Basic information: Product: Photovoltaic-hydrogen-electric integrated lamp; accounting standard: GB / T 24067-2024; factor library version: 2024.01. Carbon emission distribution: Solid-state hydrogen storage modules account for 35.4%, hydrogen fuel cells account for 28.2%, polycrystalline silicon photovoltaic modules account for 19.0%, and domestic transportation accounts for 4.1%; Compliance statement: "The calculation results comply with GB / T 24067-2024 standard and can be used for acceptance of domestic park lighting projects"; Semantic log: "Qualified match rate 91%, solid hydrogen storage factor match rate 93%, hydrogen air-cooled fuel cell factor match rate 87%, data integrity 94%".

[0043] Case 3: A company exports integrated photovoltaic-hydrogen-electric lamps to the Southeast Asian market and needs to complete carbon footprint accounting according to ISO 14067 standards. The core configuration of this product is a "0.6kW hydrogen air-cooled fuel cell (including platinum-based catalyst proton exchange membrane) + 2L solid hydrogen storage (Mg2NiH4) + 80W thin-film photovoltaic module." The manufacturing process covers "hydrogen air-cooled fuel cell stack assembly → air-cooling system integration → performance testing → photovoltaic module packaging → complete unit assembly." The target market includes Southeast Asian countries such as Thailand and Malaysia. (See attached image.) Figure 2 As shown, the specific implementation process is as follows: Carbon footprint data list for integrated photoelectric, hydrogen, and electric lamp products has been entered into the database: Data Import: Enterprises import data in batches using PDF format BOM tables. Key text information includes: "Product Name: Hydrogen-Air-Cooled Fuel Cell Photovoltaic-Hydrogen-Electric Integrated Lamp; Export Region: Southeast Asia; Compliance Standard: ISO 14067; Core Components: 0.6 kW Hydrogen-Air-Cooled Fuel Cell, 2L Mg2NiH4 Solid Hydrogen Storage Module, 80 W Thin-Film Photovoltaic Module; " Semantic intelligent preprocessing: The S-BERT semantic analysis model is used to parse the BOM table text and automatically recommend standardized fields. Component fields: "Material name: Hydrogen air-cooled fuel cell; Specification: 0.6 kW; Life cycle stage: Production and processing (including stack catalyst preparation and air-cooled fan processing)"; "Material name: Solid hydrogen storage tank; Specification: 2 L (Mg2NiH4 hydrogen storage alloy); Life cycle stage: Production and processing (including hydrogen storage alloy synthesis and metal tank processing)"; "Material name: Thin-film photovoltaic module; Specification: 80 W; Life cycle stage: Production and processing (coating)"; Process field: "Unit process: Integration of air-cooled system for hydrogen air-cooled fuel cell; Activity level data: Quantity of air-cooled fan assembly: 1 unit / unit, assembly time: 0.25 h / unit".

[0044] Data governance: Identify the missing "emission factor of platinum-based catalyst for hydrogen air-cooled fuel cells" and match data of similar products through semantic analysis algorithms: It is recommended to refer to the catalyst factor of the same enterprise and process model (semantic similarity 87%), and the reference basis is "production batch in February 2024, process consistency reaches 90%".

[0045] Carbon footprint database of integrated photoelectric lamps: Database access and standard adaptation: Based on the semantic parsing results ("Export to Southeast Asia + ISO 14067 certification", semantic similarity 90%), the ISO 14067 factor library is automatically loaded, and the LCI library data is updated synchronously. Carbon emission factor library: calls up the following from ISO 14067 standards: “Fuel cell stack production factor (2.2 kgCO2 / kW)”, “Air-cooled fan processing factor (0.65 kgCO2 / unit)”, “Mg2NiH4 hydrogen storage alloy synthesis factor (8.6 kgCO2 / kg)”, and “Thin-film photovoltaic module production factor (0.68 kgCO2 / W)”. Data classification and coding: Coding is carried out according to a five-level system of "product-system-component-part-raw material". For example: Product code: 01 (photovoltaic-hydrogen-electric integrated lamp); System code: 01 (fuel cell power generation system); Component code: 03 (photovoltaic module); Part code: 02 (perovskite thin film); Raw material code: 0B (perovskite raw material), realizing full-chain data traceability.

[0046] Carbon footprint calculation and results display of integrated photoelectric, hydrogen, and electric lamp products: System boundary setting: The semantic algorithm recommends a "cradle to gate" boundary (semantic similarity 92%), and the adaptive accounting engine module loads the IAO 14067 standard rules to clearly cover the boundary covering "raw material acquisition for hydrogen air-cooled fuel cells (platinum ore mining, resin synthesis) → stack production → air-cooled system integration → photovoltaic module production → complete unit assembly → export air freight (range 1200km)", excluding the product use and disposal stages.

[0047] Carbon footprint accounting: using the core formula: The calculations, key parameters, and results are shown in Table 3. Table 3 Key parameters and calculation results of carbon footprint of photovoltaic-hydrogen-electric products in Case 3

[0048] Results Display: The system outputs multi-dimensional results: Basic information: Product: Photovoltaic-hydrogen-electric integrated lamp; accounting standard: ISO 14067; factor library version: 2024.02. Carbon emission distribution: thin-film photovoltaic modules account for 79.6%, hydrogen-air-cooled batteries 1.9%, solid-state hydrogen storage modules 14.8%, and air freight exports account for 2.7%; Compliance statement: "The accounting results comply with the EU ISO14067 standard and can be used for carbon information disclosure in the Southeast Asian market." Semantic log: "Export region - standard matching degree 89%, hydrogen air-cooled fuel cell factor matching degree 85%, data integrity 92%".

[0049] Example 2 Figure 4 This is a system schematic diagram illustrating an accounting system based on a constructed integrated photohydrogen-electric lamp carbon footprint database, according to another exemplary embodiment. The system includes: Database Construction Module 1: Used to build a carbon footprint database for integrated photohydrogen-electric lamp products; Information parsing module 2: Used to obtain product information related to the photo-hydrogen-electric integrated lamp product to be calculated, and to parse the product information through a pre-trained S-BERT semantic analysis model to achieve standardized field matching of product information; Target accounting standard confirmation module 3: is used to extract target feature dimension data based on the standardized fields of the product information. The target feature dimension data includes: export region, core components of the product, production process type and compliance certification type. The similarity of the export region and compliance certification type with the description text corresponding to each accounting standard in the database is calculated, and the accounting standard with the highest semantic similarity is selected as the target accounting standard. Target emission factor matching module 4: is used to perform similarity matching based on the core components of the product and the production process type in the database according to the data list field to obtain an emission list; and to obtain a target emission factor list by matching the target emission factors in the factor library of the target accounting standard according to the emission list. Carbon Footprint Calculation Module 5: This module is used to calculate the carbon footprint of the product to be accounted for using a standardized accounting model, based on the established target accounting standards, target emission factor list, and activity data from the emission inventory.

[0050] It is understood that the same or similar parts in the above embodiments can be referred to each other, and the contents not described in detail in some embodiments can be referred to the same or similar contents in other embodiments.

[0051] It should be noted that in the description of this invention, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, in the description of this invention, unless otherwise stated, "a plurality of" means at least two.

[0052] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

[0053] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0054] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0055] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0056] The storage media mentioned above can be read-only memory, disk, or optical disk, etc.

[0057] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0058] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. The accounting method based on the constructed carbon footprint database of the photo-hydroelectric integrated lamp, characterized in that, The method comprises: constructing a carbon footprint database of the light-hydrogen-electric integrated lamp product; obtaining product information related to the light-hydrogen-electric integrated lamp product to be calculated, analyzing the product information through a pre-trained S-BERT semantic analysis model, and realizing product information standardized field matching; extracting target feature dimension data from the product information standardized field, the target feature dimension data including an export region, a product core component, a production process type, and a compliance certification type, calculating the similarity of the export region and the compliance certification type with the description text corresponding to each calculation standard in the database, and selecting the calculation standard with the highest semantic similarity as the target calculation standard; according to the product core component and the production process type, performing similarity matching according to the data list field in the database to obtain an emission list; and according to the emission list, matching a target emission factor in a factor library of the target calculation standard through similarity matching to obtain a target emission factor list; according to the determined target calculation standard, target emission factor list, and activity data of the emission list, calculating the carbon footprint of the product to be calculated by using a standardized calculation model.

2. The method of claim 1, wherein the database comprises a carbon emission factor library, a life cycle inventory library LCI, a life cycle impact assessment library LCIA, and a unit process database UPR; the carbon emission factor library at least includes the EU PEF standard, the ISO 14067 standard, and the GB / T 24067-2024 standard; each emission factor is associated with a set of metadata, and the metadata format is: standard number-applicable scenario-geographical scope-update time.

3. The method of claim 2, wherein, Further comprising: an emission factor automatic updating method, comprising: the database accesses multiple standard organization official data sources, monitors emission factor update data in real time, and synchronously updates the life cycle inventory library LCI and the life cycle impact assessment library LCIA based on a pre-set standard-factor substitution association relationship.

4. The method of claim 3, wherein the database model supports the construction of light-hydrogen-electric integrated lamp products according to a pre-set system classification, and the pre-set system classification includes products, systems, components, parts, and raw materials; and the pre-set system classification distinguishes different light-hydrogen-electric integrated lamp products in the form of 5-bit 16 hexadecimal coding; the database model also supports system carbon footprint nesting, divides the light-hydrogen-electric integrated lamp product into a hydrogen fuel cell power generation system, a solar power generation system, a lithium battery power generation system, and a lamp frame subsystem, and each subsystem data is mutually referenced to participate in product carbon footprint calculation; the database contains a standard adaptation association table, which is used to represent the mapping relationship of the calculation standard-emission factor-LCI data, and when the emission factor is updated, the corresponding data in the database is updated through the standard adaptation association table.

5. The method of claim 4, wherein, Further comprising: The system boundary of the carbon footprint accounting of the light-hydrogen-electric integrated lamp product is pre-set, the system boundary is obtained by semantic analysis through a pre-trained S-BERT semantic analysis model in combination with a product export area and a compliance certification type, and subsequent carbon footprint accounting of the light-hydrogen-electric integrated lamp product is performed based on the system boundary.

6. The method of claim 5, wherein, the system boundary is divided into carbon emissions from raw material acquisition to product delivery, including raw material acquisition, production processing, and transportation of fuel cell electronic systems, solar electronic systems, lithium battery electronic systems, and lamp sub-systems of the light-hydrogen-electric integrated lamp product to be accounted for; the stage division of the system boundary is obtained according to the target accounting standard.

7. The method of claim 6, wherein, Further comprising: a missing data compensation method, including: for missing data in the product core components or production process types, a pre-trained S-BERT semantic analysis model is used to obtain similar products of the light-hydrogen-electric integrated lamp to be accounted for through semantic analysis; reference data is selected from the similar products, the reference data satisfies a semantic similarity greater than a preset threshold with the production process of the product to be accounted for, and a reference basis is labeled; if there is obvious abnormal data, a warning is triggered and manual verification is prompted.

8. The method of claim 7, wherein, Further comprising: a carbon footprint accounting result display, including: the carbon footprint accounting result display content includes: product information, carbon emissions, carbon emissions distribution of each sub-system, carbon data quality analysis, standard adaptation description, and semantic matching log.

9. The method of claim 8, wherein, the standard adaptation description includes the target accounting standard name, the target accounting standard version, and the emission factor library version used in the accounting; the semantic matching log includes characteristic dimension analysis results, semantic similarity values of recommended results, reference data sources if there is reference data, and is used to trace the adaptation rationality of the accounting process.

10. The accounting system based on the constructed carbon footprint database of the photo-hydroelectric integrated lamp, characterized in that, The system comprises: a database construction module for constructing a carbon footprint database of light-hydrogen-electric integrated lamp products; an information analysis module for obtaining product information related to the light-hydrogen-electric integrated lamp product to be accounted for, and analyzing the product information through a pre-trained S-BERT semantic analysis model to realize product information standardized field matching; a target accounting standard confirmation module for extracting target characteristic dimension data from the product information standardized field, the target characteristic dimension data including an export area, product core components, production process types, and compliance certification types, performing similarity calculation on the export area and the compliance certification types and description texts corresponding to each accounting standard in the database, and selecting the accounting standard with the highest semantic similarity as the target accounting standard; a target emission factor matching module for performing similarity matching according to data list fields in the database based on the product core components and the production process types to obtain an emission list, and obtaining a target emission factor list by performing similarity matching on target emission factors in the factor library of the target accounting standard according to the emission list. Carbon footprint accounting module: for calculating the carbon footprint of the product to be accounted according to the determined target accounting standard, the target emission factor list and the activity data of the emission inventory, using a standardized accounting model.

Images