Electrical equipment carbon footprint double-track accounting method based on time-sharing dynamic factors and fixed factors

Abstract

The invention discloses an electrical equipment carbon footprint double-track accounting method based on a time-sharing dynamic factor and a fixed factor. The method comprises the following steps: S1, dividing a full life cycle stage; s2, constructing a physical product-digital mirror image; s3, accounting a time-sharing dynamic power carbon emission factor; s4, constructing a double-track accounting engine; s5, verifying and optimizing the model; according to the method, a product full life cycle stage mapping rule is provided, a carbon footprint accounting model fusing space-time dynamic coupling characteristics is constructed, a double-track accounting framework of time-sharing dynamic factors and fixed factors is innovatively adopted, and parallel calculation and result comparison of product carbon footprints are supported. A full-chain technical support is provided for the electrician equipment industry to cope with novel environment regulations such as European Union carbon tax, and the industrial low-carbon international competitiveness is effectively enhanced by improving the carbon accounting precision.

Description

Technical Field

[0001] This invention relates to the field of carbon accounting technology, specifically to a dual-track accounting method for the carbon footprint of electrical equipment based on time-sharing dynamic factors and fixed factors. Background Technology

[0002] As a key carrier of energy production, transmission, distribution, and use, electrical equipment faces the dual challenges of scientific rigor and international compliance in carbon footprint accounting methods. While carbon footprint accounting models for electrical equipment have begun to emerge, they have not yet systematically integrated time-based dynamic factors, resulting in limited accuracy.

[0003] Although current carbon footprint accounting for electrical equipment is based on the Life Cycle Assessment (LCA) methodology framework, significant technical shortcomings still exist in practical applications: First, static factors cannot reflect the spatiotemporal dynamics of electricity carbon emissions. In terms of time, the industry generally uses a fixed annual average electricity carbon emission factor to calculate indirect emissions from electricity consumption, ignoring the fluctuations in grid carbon emission intensity at different times of day, seasons, and years. In terms of space, regional or national average electricity carbon emission factors mask the differences in provincial and municipal grid structures, resulting in calculations that fail to reflect the true emission intensity of the equipment's location.

[0004] Secondly, there is a lack of a unified and practical dynamic accounting framework. Existing LCA standards and tools are mainly designed to process relatively static, average-based input data. The existing system cannot provide a clear and easy-to-operate architecture to efficiently, accurately, and in a standardized manner "inject" key, high-value dynamic data into the core process of carbon footprint accounting for the entire life cycle of electrical equipment, and organically integrate it with relatively fixed supply chain emission data, ultimately outputting more accurate and more spatiotemporally representative accounting results. Summary of the Invention

[0005] This invention aims to at least solve one of the technical problems existing in the prior art. To this end, one objective of this invention is to propose a dual-track accounting method for the carbon footprint of electrical equipment based on time-sharing dynamic factors and fixed factors. This method is applicable to the accurate measurement of carbon emissions throughout the entire life cycle of equipment such as transformers and power cables.

[0006] To address the aforementioned problems, this invention provides a dual-track accounting method for the carbon footprint of electrical equipment based on time-sharing dynamic factors and fixed factors, comprising the following steps: S1. Divide the entire life cycle into six stages: raw material acquisition, raw material transportation, manufacturing, product transportation, product use, and decommissioning and recycling. S2. Constructing a physical product-digital mirror: First, collect real-time data throughout the entire lifecycle through sensors and API interfaces; then, unify the spatiotemporal reference and generate a spatiotemporal label of "power grid area code + standard date" using the power grid area code (GB / T31464-2015); S3. Calculate the time-of-use dynamic electricity carbon emission factor. The calculation formula is as follows: Time-of-use electricity carbon emission factor = (carbon emissions from power generation within the grid + total carbon emissions from grid facilities and SF6 + net carbon emissions from inter-regional power input) / (electricity supplied to the grid within the region + net electricity input from outside the region - line loss). S4. Construct a dual-track accounting engine: The carbon footprint accounting of electrical equipment consists of the cumulative carbon emissions from six key processes, and its general expression is as follows: Where k corresponds to the lifecycle stage number: k=1: Raw material acquisition; k=2: Raw material transportation; k=3: Production and manufacturing; k=4: Product transportation; k=5: Product use; k=6: Retirement and recycling; When using dynamic and fixed factors to accurately calculate carbon footprints, the differences lie in the calculation of electricity carbon emissions. The calculation formulas for the two approaches are as follows: in: : The power consumption of component k during time period t, in kWh, typically obtained through terminal data collection. Dynamic electricity carbon emission factor for this period, unit: kgCO2 / kWh in: Total power consumption of stage k, unit: kWh You can choose the latest factors released by the provincial ecological and environmental departments. Or the national power grid average Unit: kgCO2 / kWh; S5. Compare the results of the dual-track accounting through actual cases and use sensitivity analysis to correct the deviation.

[0007] Preferably, when S2 constructs spatiotemporal tags, the following conditions must be met: A. The time granularity is daily, which matches the resolution of the time-division dynamic factor; B. Spatial mapping to standard power grid area codes.

[0008] Preferably, the time-sharing dynamic factor is calculated using a three-level grid system including national, provincial, and municipal levels, relying on data from the synchronous line loss platform and the online power grid platform.

[0009] Preferably, S4's dual-track accounting engine supports parallel output of dynamic factor path and fixed factor path results, and comparative analysis of the differences.

[0010] The advantages of this invention compared to the prior art are: This invention presents a dual-track accounting method for the carbon footprint of electrical equipment based on time-sharing dynamic factors and fixed factors. It proposes a product lifecycle stage mapping rule, constructs a carbon footprint accounting model integrating spatiotemporal dynamic coupling characteristics, and innovatively adopts a dual-track accounting framework of time-sharing dynamic factors and fixed factors, supporting parallel calculation and result comparison of product carbon footprints. This provides full-chain technical support for the electrical equipment industry to cope with new environmental regulations such as EU carbon tariffs, and effectively enhances the industry's low-carbon international competitiveness by improving carbon accounting accuracy.

[0011] 1. This method uses a dynamic factor path (based on spatiotemporal composite coding) and a fixed factor path (provincial / national annual average factor) for parallel calculation. It can provide a stable accounting benchmark based on fixed factors, and capture dynamic changes with time-sharing dynamic factors, which is convenient to adapt to the rapidly changing production and operation environment and policy requirements.

[0012] 2. This method integrates the physical operation characteristics of the power grid, the technological characteristics of equipment manufacturing, and the geographical distribution of the supply chain to construct a multi-source data fusion governance system covering six major links in electrical equipment. It creates a factor library that is progressively refined from national to provincial to municipal levels, eliminating the "spatiotemporal averaging" defects of traditional accounting methods. This accurately captures carbon intensity differences across power dispatch zones, achieving "emissions occurring at any time and place, calculated according to the factors of that time and place." 3. The dual-track carbon footprint accounting method for electrical equipment constructed in this paper has universality and can be extended to multiple types of equipment fields to assist in the output of carbon footprint reports. It has broad application value in promoting the low-carbon transformation of the electrical equipment manufacturing industry and helping to achieve dual carbon goals. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a flowchart of the product carbon footprint calculation based on LCA in this invention; Figure 2This is a diagram of the dual-track architecture for carbon footprint accounting in this invention. Detailed Implementation

[0015] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0016] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "joining" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0017] The present invention will now be described in further detail with reference to the accompanying drawings.

[0018] Combination Figures 1-2 The present invention discloses a dual-track accounting method for the carbon footprint of electrical equipment based on time-sharing dynamic factors and fixed factors. The method is divided into four parts: full life cycle stage division, construction of "physical product-digital mirror", time-sharing dynamic electricity carbon emission factor accounting, and construction of dual-track accounting engine.

[0019] S1. Lifecycle Stages Based on the manufacturing boundaries of electrical equipment, supply chain characteristics, and the spatiotemporal coupling principle, the entire product lifecycle is divided into six stages: raw material acquisition, raw material transportation, manufacturing, product transportation, product use, and decommissioning and recycling. The spatiotemporal characteristics of each stage are key factors affecting the accuracy of electricity carbon factor selection and the scientific validity of the calculation results. The division criteria follow a dual-dimensional principle: the time dimension focuses on the impact of the heterogeneity of the duration of each stage on the timing of electricity consumption, and the spatial dimension focuses on the effect of the differences in the geographical distribution of the supply chain on the regional power structure.

[0020] 1. Raw material acquisition stage: This stage covers the mining, smelting, and processing of metal materials such as silicon steel, copper, and aluminum, as well as insulating and structural materials.

[0021] 2. Raw material transportation stage: This involves the entire process of multimodal logistics transportation from suppliers to the production site, including key parameters such as transportation mode, vehicle type, load factor and transportation distance.

[0022] 3. Manufacturing stage: In-depth workshop-level processes, including component assembly processes, equipment operation energy consumption, waste disposal, etc., such as silicon steel sheet cutting and coating, copper and aluminum wire stretching and insulation treatment, iron core coil assembly, etc.

[0023] 4. Product transportation stage: Integrate multi-dimensional data such as product weight, transportation distance, transportation mode and energy efficiency parameters of transportation vehicles to accurately calculate the carbon footprint of the transportation process.

[0024] 5. Product usage phase: Focusing on operating energy consumption, collect spatial characteristic parameters of the equipment's operating environment (such as installation location attributes, ambient temperature and humidity, cooling system energy consumption) and dynamic operating characteristic parameters (such as real-time load rate, hourly time-series load curve).

[0025] 6. Retirement and recycling phase: Accurately collect data on the entire process of dismantling, transportation, processing and reuse, including energy consumption of dismantling equipment, transportation logistics data, waste disposal methods and resource reuse pathways.

[0026] Raw material acquisition occurs primarily in the early stages of equipment manufacturing, involving upstream links such as basic material smelting and chemical material production. The distribution of raw material suppliers exhibits regional clustering. Logistics and transportation are characterized by intermittent energy consumption, with transportation cycles strongly coupled to modes of transport. The production and manufacturing stage spans a considerable period. The location of the production base determines the regional power structure parameters. Electrical equipment products have long service lifespans, and the power grid structure varies depending on the operating location. The spatial distribution of decommissioning and recycling is influenced by the recycling process; physical recycling methods are concentrated near raw material production areas, while chemical recycling methods tend to be located in technology-intensive regions. S2. Construct a "physical product-digital mirror". The premise of product carbon footprint accounting is to create a digital model for electrical equipment products that is synchronized with and dynamically updated throughout their life cycle. By integrating real-time / near real-time data, spatiotemporal coding, process models, and factor accounting logic, a digital mapping model covering multiple levels such as product physical state, activity data, and spatiotemporal attributes is constructed, providing structured input data for a dual-track accounting model of time-sharing dynamic factors and fixed factors.

[0027] First, deploy sensors supporting remote data transmission at key stages throughout the product lifecycle. For example, deploy sensors in the workshop to monitor process-level energy consumption and equipment operating status during the manufacturing phase; integrate smart meters into electrical equipment or key components to monitor operating power consumption, load rate, ambient temperature, etc.; and install GPS positioning on transportation vehicles or packaging. For stages with information systems, use standardized API interfaces to collect key data such as raw material purchase orders, supplier information, and batch information. Based on ubiquitous sensing and interface integration, build a data collection network for the entire product lifecycle.

[0028] Secondly, the spatiotemporal benchmarks were unified and data fusion was implemented. Regarding time benchmark anchoring, the daily granularity was used as the smallest unit, unifying the activity times of each stage of the product's entire lifecycle to a calendar date coordinate system. This avoids invalid, finely detailed time recordings and ensures strict matching with the time resolution of time-of-use dynamic power factors. For spatial location mapping, traditional administrative divisions were abandoned, and the power grid zoning coding system of the "China Power Grid Regional Division Standard" (GB / T 31464-2015) was adopted. Production plants, raw material origins, logistics hubs, and equipment installation locations are all mapped to standard power grid regional codes (such as the A03 area of ​​the East China Power Grid), eliminating spatial errors between administrative boundaries and power dispatch areas at the source. By establishing precise spatiotemporal correspondences between effective activity data at each stage, a spatiotemporally coupled composite label of "power grid regional code + standard date" was generated. This coding system allows each unit of carbon emission to be traced back to a specific power grid region and date, providing structured input for dynamic factor matching.

[0029] S3. Time-of-use dynamic electricity carbon emission factor accounting The product's total lifecycle carbon footprint encompasses two areas. Area one includes direct emissions from fossil fuel combustion. Area two includes indirect emissions from purchased electricity, heat, etc. The carbon emissions implied by net purchased electricity are calculated using the emission factor method, supporting the calculation of the product's total lifecycle carbon footprint. The formula is as follows: Traditional electricity carbon emission factors are divided into national average CO2 emission factors and provincial average CO2 emission factors. The national average CO2 emission factor is calculated at a macro level, showing the national average power supply structure; the provincial average CO2 emission factor shows inter-provincial differences, masking intra-provincial differences and time-period fluctuations. These crudely calculated factor values ​​cannot reflect the changes in electricity carbon emission intensity over different time periods and in different regions.

[0030] To overcome the spatiotemporal limitations of traditional electricity carbon emission factors, the calculation scale needs to be shortened in the time dimension, refined to the day, to capture typical load characteristics of different months. In the spatial dimension, scientific zoning is implemented, constructing a three-tiered grid system of "national → provincial → municipal" to reflect regional power structure differences. Based on the power generation data at the critical point of the same line loss platform and the full-time generation data of power sources from the grid platform, a time-sharing dynamic electricity carbon emission factor collaborative calculation framework is constructed, as shown in the following formula: S4 Dual-Track Computing Engine Construction The carbon footprint accounting of electrical equipment consists of the cumulative carbon emissions from six key processes, and its general expression is as follows: Where k corresponds to the lifecycle stage number: k=1: Raw material acquisition; k=2: Raw material transportation; k=3: Manufacturing; k=4: Product transportation; k=5: Product usage; k=6: Retirement and recycling.

[0031] When using dynamic and fixed factors to accurately calculate carbon footprints, the differences lie in the calculation of electricity carbon emissions. The calculation formulas for the two approaches are as follows: in, The power consumption (kWh) of component k during time period t is generally obtained through terminal data collection. Dynamic electricity carbon emission factor (kgCO2 / kWh) for this period in, Total power consumption of stage k (kWh) You can choose the latest factors released by the provincial ecological and environmental departments. Or the national power grid average (kgCO2 / kWh) S5. Model Validation and Optimization The dual-track accounting model is applied to actual electrical equipment product cases, and compared and verified with actual enterprise monitoring data or existing authoritative carbon footprint data to analyze the deviation between the model's calculation results and the actual situation. If there is a significant deviation between the calculation results and the actual situation, sensitivity analysis is used to identify key factors and sensitive links that have a significant impact on the carbon footprint of electrical equipment, check for problems in parameter settings, calculation methods, and data quality in the model, and make targeted corrections.

[0032] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings: like Figure 1 As shown, the method of this invention constructs a complete process for a carbon footprint accounting model based on Life Cycle Assessment (LCA), including three core parts: input, processing, and output. Input data includes a data list (containing data on power grid dispatch, meteorology, and grid losses) and a three-level grid factor library (containing national, provincial, and time-based dynamic factors). The model calculates carbon emissions for each stage using carbon emission formulas for each stage and performs carbon conversion for the same batch of functional units. Output data consists of carbon emission data for each stage, helping enterprises understand carbon emission distribution and formulate emission reduction strategies.

[0033] like Figure 2 As shown, the method of this invention is based on a "cradle-to-grave" methodology, comprehensively covering the entire lifecycle of a product from raw material acquisition to decommissioning and recycling. First, it collects activity data across six key stages of the entire lifecycle, laying the foundation for accurate carbon footprint calculation. Differentiated calculation methods are adopted for non-electricity carbon emissions and electricity carbon emissions. Non-electricity emissions are calculated directly based on a unified calculation logic. The electricity sector is innovatively divided into two paths: one is a dynamic factor path with time-based accumulation, capturing real-time changes in carbon emission intensity at different times; the other is a fixed factor path with a single total calculation, providing a relatively stable baseline emission level. By comparing the results of the two paths, accurate carbon footprint difference analysis can be conducted, helping enterprises gain a deeper understanding of the carbon emission patterns in the electricity sector and providing strong data support for optimizing energy use strategies and achieving precise emission reduction.

[0034] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.

Claims

1. A dual-track accounting method for the carbon footprint of electrical equipment based on time-sharing dynamic factors and fixed factors, characterized in that, Includes the following steps: S1. Divide the entire life cycle into six stages: raw material acquisition, raw material transportation, manufacturing, product transportation, product use, and decommissioning and recycling. S2. Constructing a physical product-digital mirror: First, collect real-time data throughout the entire lifecycle through sensors and API interfaces; then, unify the spatiotemporal reference and generate a spatiotemporal label of "power grid area code + standard date" using the power grid area code (GB / T31464-2015); S3. Calculate the time-of-use dynamic electricity carbon emission factor. The calculation formula is as follows: Time-of-use electricity carbon emission factor = (carbon emissions from power generation within the grid + total carbon emissions from grid facilities and SF6 + net carbon emissions from inter-regional power input) / (electricity supplied to the grid within the region + net electricity input from outside the region - line loss). S4. Construct a dual-track accounting engine: The carbon footprint accounting of electrical equipment consists of the cumulative carbon emissions from six key processes, and its general expression is as follows: Where k corresponds to the lifecycle stage number: k=1: Raw material acquisition; k=2: Raw material transportation; k=3: Production and manufacturing; k=4: Product transportation; k=5: Product use; k=6: Retirement and recycling; When using dynamic and fixed factors to accurately calculate carbon footprints, the differences lie in the calculation of electricity carbon emissions. The calculation formulas for the two approaches are as follows: in: : The power consumption of component k during time period t, in kWh, typically obtained through terminal data collection. Dynamic electricity carbon emission factor for this period, unit: kgCO2 / kWh in: Total power consumption of stage k, unit: kWh You can choose the latest factors released by the provincial ecological and environmental departments. Or the national power grid average Unit: kgCO2 / kWh; S5. Compare the results of the dual-track accounting through actual cases and use sensitivity analysis to correct the deviation.

2. The dual-track accounting method for carbon footprint of electrical equipment based on time-sharing dynamic factors and fixed factors as described in claim 1, characterized in that: When constructing the spatiotemporal label in S2, the following conditions must be met: A. The time granularity is daily, which matches the resolution of the time-division dynamic factor; B. Spatial mapping to standard power grid area codes.

3. The dual-track accounting method for carbon footprint of electrical equipment based on time-sharing dynamic factors and fixed factors as described in claim 1, characterized in that: The time-sharing dynamic factor is calculated using a three-tiered grid system: national, provincial, and municipal, relying on data from the synchronous line loss platform and the online power grid platform.

4. The dual-track accounting method for carbon footprint of electrical equipment based on time-sharing dynamic factors and fixed factors as described in claim 1, characterized in that: The S4 dual-track calculation engine supports parallel output of dynamic factor path and fixed factor path results, and compares and analyzes the differences.

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