Method and device for evaluating carbon footprint data of GIS equipment, electronic equipment and storage medium

Abstract

The application discloses a GIS device carbon footprint data evaluation method and device, electronic equipment and storage medium. The method comprises the following steps: acquiring secondary data, unit process emission data and carbon emission data of each stage of the whole life cycle of the GIS device; a first scoring matrix corresponding to field data in the secondary data and a second scoring matrix corresponding to background data in the secondary data are constructed respectively; the product carbon footprint data quality score is determined based on the first scoring matrix, the unit process emission data and the carbon emission data of each stage of the whole life cycle; the background database data quality score is determined based on the second scoring matrix; and the quality of the GIS device carbon footprint data is evaluated based on the product carbon footprint data quality score and the background database data quality score. The scheme can accurately and effectively evaluate the GIS device carbon footprint data, thereby enhancing the accuracy of the GIS power equipment product carbon footprint accounting.

Description

Technical Field

[0001] The present invention relates to the field of data management technology, and in particular to a carbon footprint data evaluation method, device, electronic device and storage medium for GIS equipment. Background Art

[0002] Data quality assessment involves analyzing various data attributes and dimensions through systematic techniques and methods to measure and evaluate whether the data quality meets expected requirements and standards. Its purpose is to ensure that data accuracy, completeness, consistency, timeliness, and validity meet established standards, enabling quantification and decision-making. In product and equipment manufacturing, the quality of collected carbon footprint data needs to be assessed and analyzed to enhance the accuracy of carbon footprint accounting. However, existing data quality assessment models primarily focus on data quality assessment in large data environments, establishing corresponding constraints based on business quality to conduct data assessment. However, there are no established methods or guidelines for assessing the quality of carbon footprint data for gas-insulated metal-enclosed switchgear and controlgear (GIS) production equipment. Summary of the Invention

[0003] The present invention provides a carbon footprint data evaluation method, device, electronic device and storage medium for GIS equipment, which can accurately and effectively evaluate the carbon footprint data of GIS equipment.

[0004] According to one aspect of the present invention, a method for evaluating carbon footprint data of a GIS device is provided, comprising:

[0005] Obtain secondary data of GIS equipment, unit process emission data and carbon emission data at all stages of the entire life cycle;

[0006] respectively constructing a first scoring matrix corresponding to the field data in the secondary data and a second scoring matrix corresponding to the background data in the secondary data;

[0007] Determining a product carbon footprint data quality score based on the first scoring matrix, the unit process emission data, and the carbon emission data for each stage of the life cycle;

[0008] determining a background database data quality score based on the second scoring matrix;

[0009] The quality of the carbon footprint data of the GIS device is evaluated based on the product carbon footprint data quality score and the background database data quality score.

[0010] According to another aspect of the present invention, a carbon footprint data evaluation device for a GIS device is provided, comprising:

[0011] Data acquisition module, used to obtain secondary data of GIS equipment, unit process emission data and carbon emission data at all stages of the life cycle;

[0012] a scoring matrix construction module, configured to respectively construct a first scoring matrix corresponding to the field data in the secondary data and a second scoring matrix corresponding to the background data in the secondary data;

[0013] A product carbon footprint data quality score determination module is used to determine the product carbon footprint data quality score based on the first scoring matrix, the unit process emission data, and the carbon emission data of each stage of the life cycle;

[0014] A background database data quality score determination module, configured to determine a background database data quality score based on the second scoring matrix;

[0015] The carbon footprint data quality evaluation module is used to evaluate the quality of the carbon footprint data of the GIS device based on the product carbon footprint data quality score and the background database data quality score.

[0016] According to another aspect of the present invention, an electronic device is provided, comprising:

[0017] at least one processor; and

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the carbon footprint data evaluation method for GIS equipment described in any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the carbon footprint data evaluation method for GIS equipment described in any embodiment of the present invention when executed.

[0021] The carbon footprint data evaluation scheme for GIS equipment of the embodiment of the present invention includes: obtaining the secondary data, unit process emission data and carbon emission data of each stage of the life cycle of the GIS equipment; constructing a first scoring matrix corresponding to the field data in the secondary data and a second scoring matrix corresponding to the background data in the secondary data; determining the product carbon footprint data quality score based on the first scoring matrix, the unit process emission data and the carbon emission data of each stage of the life cycle; determining the background database data quality score based on the second scoring matrix; and evaluating the quality of the carbon footprint data of the GIS equipment based on the product carbon footprint data quality score and the background database data quality score. Through the technical scheme provided by the embodiment of the present invention, the carbon footprint data of GIS equipment can be accurately and effectively evaluated, thereby enhancing the accuracy of carbon footprint accounting of GIS power equipment products and providing data support for accurate accounting of product carbon footprints.

[0022] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 A flowchart of a carbon footprint data evaluation method for GIS equipment provided in Example 1 of the present invention;

[0025] Figure 2 A flowchart of a carbon footprint data evaluation method for GIS equipment provided in Example 2 of the present invention;

[0026] Figure 3 A schematic diagram of the structure of a carbon footprint data evaluation device for GIS equipment provided in the third embodiment of the present invention;

[0027] Figure 4 A schematic diagram of the structure of an electronic device for implementing the carbon footprint data evaluation method for GIS equipment according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] Example 1

[0031] Figure 1 A flowchart of a method for evaluating carbon footprint data of a GIS device is provided for the first embodiment of the present invention. This embodiment is applicable to the case of evaluating carbon footprint data of a GIS device. The method can be executed by a carbon footprint data evaluation device of a GIS device. The carbon footprint data evaluation device of the GIS device can be implemented in the form of hardware and / or software. The carbon footprint data evaluation device of the GIS device can be configured in an electronic device. Figure 1 As shown, the method includes:

[0032] S110. Obtain secondary data of GIS equipment, unit process emission data, and carbon emission data for each stage of the entire life cycle.

[0033] In an embodiment of the present invention, carbon footprint data related to GIS equipment is obtained. This data includes primary data, secondary data, unit process emissions data, carbon emissions data for each stage of the entire life cycle, and product carbon footprint data. Primary data, also known as first-hand data, refers to the quantified value of a process or activity obtained through direct measurement or calculation based on direct measurement.

[0034] Secondary data are quantitative values ​​of unit processes or activities obtained by means other than direct measurement at the original source or calculations based on direct measurement. Secondary data may include data from databases and public literature, default emission factors in national inventories, calculated data, estimated values, or other representative data verified by the competent authorities. Secondary data may also be referred to as unit process input data. Unit process emission data can be understood as the output data of the unit process after the input data enters the unit process, where a process can be understood as a set of interrelated or interacting activities that convert inputs into outputs. A unit process can be understood as the most basic part determined in a life cycle assessment to quantify input and output data. Input data may include product, material, and energy flows entering a unit process, and output data may include product, material, and energy flows leaving a unit process.

[0035] The carbon emission data at each stage of the entire life cycle refers to the amount of carbon emissions generated at different stages of a product or process. The various stages of the entire life cycle of GIS equipment may include the raw and auxiliary material acquisition stage, the raw and auxiliary material transportation stage, the product production stage, the product transportation stage, the product use stage, the waste disposal stage, and the like. In an embodiment of the present invention, the raw and auxiliary material acquisition stage starts from the extraction of materials from nature and ends when the raw and auxiliary materials leave the upstream supplier. The process of the raw and auxiliary material acquisition stage may include: a) mining, extraction, and production of general materials; b) processing of recycled materials; c) production of components or assemblies of upstream suppliers; d) production of consumables and packaging materials; e) transportation of materials and parts between upstream suppliers; f) the impact of upstream production using electricity, heat, and fossil fuels. The raw and auxiliary material transportation stage starts from the time when the raw and auxiliary materials leave the upstream supplier and ends when the raw and auxiliary materials arrive at the production plant. The product production phase begins when raw materials enter the production plant and ends when the final product leaves the production plant. The processes in the product production phase include: a) production of major parts, components, and subassemblies; b) assembly and assembly of the product; c) inspection and packaging of the product; d) transportation and warehousing within the production plant; e) greenhouse gas emissions within the production plant; and f) waste management related to the production process. The product transportation phase begins when the final product leaves the production plant and ends when the product arrives at the place of use. The product use phase begins when the product arrives at the place of use and ends at the end of its lifespan. The processes in the product use phase include: a) operation of the product, including power loss; and b) the impact of the product's routine maintenance process. The waste disposal phase begins when the product's lifespan ends and ends when the product returns to nature or is assigned to another product. The processes in the waste disposal phase include: a) disassembly of discarded products; b) separation, screening, and waste treatment; and c) other recycling and disposal processes. A product's carbon footprint is the total carbon emissions generated throughout the product's lifecycle (from raw material acquisition to disposal / recycling), typically expressed in tons of carbon dioxide equivalent (tCO2e). Therefore, the product's carbon footprint can be determined based on the carbon emissions data for each stage of a GIS device's lifecycle. The product's carbon footprint refers to the sum of all greenhouse gas emissions and greenhouse gas removals, expressed in units of carbon dioxide equivalent, over the GIS device's entire lifecycle.

[0036] In the embodiment of the present invention, the secondary data, unit process emission data and carbon emission data at each stage of the entire life cycle all include two types of data: field data and background data.

[0037] S120: Constructing a first scoring matrix corresponding to the field data in the secondary data and a second scoring matrix corresponding to the background data in the secondary data.

[0038] In an embodiment of the present invention, field data in the secondary data is scored based on a pedigree matrix method to construct a first scoring matrix corresponding to the field data in the secondary data. Optionally, constructing the first scoring matrix corresponding to the field data in the secondary data includes: analyzing the field data in the secondary data to determine first data quality attribute information of the field data; wherein the first data quality attribute information includes regionality, raw material type, energy consumption type, production process and equipment, and year; and constructing the first scoring matrix corresponding to the field data based on the first data quality attribute information and a field data quality scoring table.

[0039] In an embodiment of the present invention, the field data in the secondary data is analyzed to determine the data quality attribute information such as regionality, raw material type, energy consumption type, production process and equipment, and year of the field data. For the convenience of description, each data quality attribute information of the field data in the secondary data is referred to as first data quality attribute information. For example, in terms of the attribute of regionality of the field data in the secondary data, the data in the area where the GIS product is located is better than the average data source in China, and the average data source in China is better than the data sources in other countries; in terms of the attribute of raw material type, data produced using the same raw materials is better than data produced using different raw materials but with similar products; in terms of the attribute of energy consumption type, the higher the corresponding data quality is when the energy consumption type and proportion are the same or similar; in terms of the attribute of year, the closer the year is to the current year, the higher the corresponding data quality is. For example, a field data quality score sheet is obtained. Table 1 is the field data quality score sheet provided in an embodiment of the present invention:

[0040] Table 1 Field data quality scoring table

[0041]

[0042] Based on the first data quality attribute information and the field data quality scoring table, the scores of the field data of the secondary data in the above five attributes are determined, and the first scoring matrix corresponding to the field data is constructed based on the scores of the field data of the secondary data in the above five attributes. As shown in Table 1, if the energy consumption type of the field data is the same and the energy consumption ratio is similar, the score of the field data in the attribute of energy consumption type is 2 points; if the field data is data produced with the same raw materials, the score of the field data in the attribute of raw material type is 1 point. It should be noted that the field data in the secondary data may be one or more, and the attribute scores corresponding to each field data in the five attributes of regionality, raw material type, energy consumption type, production process and equipment, and year are determined, and the first scoring matrix corresponding to the field data is constructed based on the attribute scores corresponding to the five attributes of regionality, raw material type, energy consumption type, production process and equipment, and year for all field data.

[0043] In an embodiment of the present invention, background data in the secondary data is scored based on a pedigree matrix method to construct a second scoring matrix corresponding to the background data in the secondary data. Optionally, constructing the second scoring matrix corresponding to the background data in the secondary data includes: analyzing the background data in the secondary data to determine second data quality attribute information of the background data; wherein the second data quality attribute information includes temporal representativeness, regional representativeness, and technical representativeness; and constructing the second scoring matrix corresponding to the background data based on the second data quality attribute information and a background data quality scoring table.

[0044] The background data in the secondary data is analyzed to determine the data quality attribute information of the background data in three dimensions: time representativeness (TiR), geographical representativeness (GeR), and technical representativeness (TeR). For the convenience of description, each data quality attribute information of the background data in the secondary data is referred to as the second data quality attribute information. Among them, in terms of the attribute of time representativeness of the background data in the secondary data, the environmental carbon footprint reporting date is better if it is within the validity period of the data set than if it is outside the validity period of the data set; in terms of the attribute of geographical representativeness, the process required in the environmental carbon footprint study has corresponding applications in the country where the data set is valid, which is better than the required process not being applied in the country where the data set is valid; in terms of the attribute of technical representativeness, the technology used in the carbon footprint study is the same as the technology within the scope of the data set, which is better than the technology used in the carbon footprint study being different from the technology within the scope of the data set. Exemplarily, a background data quality score table is obtained. Table 2 is the background data quality score table provided by an embodiment of the present invention:

[0045] Table 2 Background data quality rating table

[0046]

[0047] Based on the secondary data quality attribute information and the background data quality scoring table, the scores for the secondary data's background data in terms of temporal representativeness (TiR), geographical representativeness (GeR), and technological representativeness (TeR) were determined. A second scoring matrix corresponding to the background data was constructed based on the scores for these three attributes. As shown in Table 2, if the release date of the environmental carbon footprint report for the background data falls within the dataset's validity period, the background data's score for the temporal representativeness (TiR) attribute is 1. If the simulated processes in the background data's environmental carbon footprint study are applied in some regions where the dataset is valid, the background data's score for the geographical representativeness (GeR) attribute is 2. It should be noted that there may be one or more background data in the secondary data. The attribute scores corresponding to each background data in terms of the three attributes of time representativeness (TiR), geographical representativeness (GeR), and technical representativeness (TeR) are determined, and based on the attribute scores corresponding to the three attributes of time representativeness (TiR), geographical representativeness (GeR), and technical representativeness (TeR) of all background data, a second scoring matrix corresponding to the background data is constructed.

[0048] S130. Determine a product carbon footprint data quality score based on the first scoring matrix, the unit process emission data, and the carbon emission data for each stage of the entire life cycle.

[0049] In an embodiment of the present invention, a product carbon footprint data quality score is calculated based on a first scoring matrix corresponding to the field data of the secondary data (i.e., the unit process input data), the unit process emission data, and the carbon emission data for each stage of the life cycle. Optionally, determining the product carbon footprint data quality score based on the first scoring matrix, the unit process emission data, and the carbon emission data for each stage of the life cycle includes: calculating the field data quality score of the secondary data based on the first scoring matrix; calculating the unit process emission data quality score based on the field data quality score and the unit process emission data; calculating the carbon emission data quality score for the corresponding life cycle stage based on the unit process emission data quality score and the carbon emission data for each stage of the life cycle; and calculating the product carbon footprint data quality score based on the carbon emission data quality score for each of the life cycle stages.

[0050] Exemplarily, the field data quality score corresponding to each field data in the secondary data is calculated according to the first scoring matrix. For example, the field data quality score corresponding to each field data can be calculated according to the following formula: ,in, Indicates the number of field data in the unit process input data (secondary data). Indicates the first The field data quality score corresponding to the field data, Indicates the first The score of the field data in terms of regionality, Indicates the first The score corresponding to the raw material type attribute of the field data, Indicates the first The corresponding score of the field data in terms of energy consumption type, Indicates the first The score of the field data corresponding to the attribute of production process and equipment indicates the The corresponding score of the field data in terms of the year attribute.

[0051] The unit process emission data quality score is calculated based on the field data quality scores corresponding to all field data in the secondary data and the unit process emission data. For example, the unit process emission data quality score corresponding to each unit process emission data can be calculated according to the following formula: ,in, Indicates the unit process number, Indicates the The unit process emission data quality score corresponding to the unit process emission data, n represents the number of inputs included in the unit process, For unit process The carbon emissions generated by each input. Based on the unit process emission data quality score and the carbon emission data of each stage of the life cycle, the carbon emission data quality score of the corresponding life cycle stage is calculated. For example, the carbon emission data quality score of each stage of the life cycle corresponding to the carbon emission data of each stage of the life cycle can be calculated according to the following formula: ,in, Indicates the stage number of the entire life cycle, Indicates the number of unit processes included in the life cycle stage, Indicates the The carbon emissions of each unit process. The product carbon footprint data quality score is calculated based on the carbon emission data quality scores of all life cycle stages. For example, the product carbon footprint data quality score can be calculated according to the following formula: ,in, Indicates the product carbon footprint data quality score, Indicates the number of life cycle stages included in the product’s carbon footprint, Indicates the Carbon emissions at each life cycle stage.

[0052] S140: Determine a background database data quality score based on the second scoring matrix.

[0053] In an embodiment of the present invention, a background database data quality score corresponding to the background data is calculated based on a second scoring matrix corresponding to the background data in the secondary data. For example, the second scoring matrix is ​​a scoring matrix constructed by analyzing the three attributes of the background data: temporal representativeness, regional representativeness, and technical representativeness. The background database data quality score can be calculated according to the following formula: , represents the background database data quality score, Indicates the score corresponding to the attribute of temporal representativeness, Indicates the score corresponding to the attribute of regional representation, Indicates the score corresponding to the attribute of technical representativeness.

[0054] S150: Evaluate the quality of the carbon footprint data of the GIS device based on the product carbon footprint data quality score and the background database data quality score.

[0055] Exemplarily, the sum of the product carbon footprint data quality score and the background database data quality score is calculated, and the sum is used as the GIS carbon footprint data score, and the quality of the carbon footprint data of the GIS device is evaluated based on the GIS carbon footprint data score. The higher the GIS carbon footprint data score, the higher the quality of the carbon footprint data of the GIS device, that is, the higher the accuracy, completeness, consistency and validity of the carbon footprint data of the GIS device. Optionally, based on the product carbon footprint data quality score and the background database data quality score, the quality of the carbon footprint data of the GIS device is evaluated, including: determining the GIS carbon footprint data score based on the product carbon footprint data quality score and the background database data quality score; determining the quality grade of the carbon footprint data of the GIS device based on the GIS carbon footprint data score and a pre-set GIS data quality grade table.

[0056] Exemplarily, the average of the product carbon footprint data quality score and the background database data quality score is calculated, and the average is used as the GIS carbon footprint data score. Optionally, the GIS carbon footprint data score is determined based on the product carbon footprint data quality score and the background database data quality score, including: calculating the GIS carbon footprint data score according to the following formula:

[0057] ;

[0058] in, represents the GIS carbon footprint data score, Indicates the carbon footprint data quality score of the product, represents the background database data quality score, Represents the weighting coefficient.

[0059] Obtain a pre-set GIS data quality level table. For example, Table 3 is a GIS data quality level table provided in an embodiment of the present invention:

[0060] Table 3 GIS data quality level table

[0061]

[0062] The GIS data quality grade table is used to find the target score range for the GIS carbon footprint data score. The quality grade corresponding to the target score range in the GIS data quality grade table is used as the quality grade of the GIS device's carbon footprint data. For example, if the GIS carbon footprint data score is 1.8, the quality grade of the GIS device's carbon footprint data is level 3, indicating that the quality of the GIS device's carbon footprint data is average.

[0063] Optionally, the evaluation results of the carbon footprint data of the GIS device can be displayed via a display module, wherein the display module can include a large electronic digital screen. For example, the quality calculation results, quality grades, and corresponding quality evaluation results of the GIS carbon footprint data at different stages and under different backgrounds can be visually displayed and analyzed.

[0064] The carbon footprint data evaluation method for GIS equipment according to an embodiment of the present invention includes: obtaining secondary data, unit process emission data, and carbon emission data for each stage of the life cycle of the GIS equipment; constructing a first scoring matrix corresponding to the field data in the secondary data and a second scoring matrix corresponding to the background data in the secondary data; determining the product carbon footprint data quality score based on the first scoring matrix, the unit process emission data, and the carbon emission data for each stage of the life cycle; determining the background database data quality score based on the second scoring matrix; and evaluating the quality of the carbon footprint data of the GIS equipment based on the product carbon footprint data quality score and the background database data quality score. Through the technical solution provided by the embodiment of the present invention, the carbon footprint data of GIS equipment can be accurately and effectively evaluated, thereby enhancing the accuracy of carbon footprint accounting of GIS power equipment products and providing data support for accurate carbon footprint accounting of products.

[0065] In some embodiments, after determining the quality level of the carbon footprint data of the GIS device, it also includes: when it is determined that the quality level is greater than the preset level, respectively determining the degree of influence of each input scoring variable on the GIS carbon footprint data score. In an embodiment of the present invention, when the quality level of the carbon footprint data of the GIS device is greater than the preset level, such as the quality level of the carbon footprint data of the GIS device is level five, it means that the quality of the carbon footprint data of the GIS device is very poor. At this time, the degree of influence of each input scoring variable on the GIS carbon footprint data score can be determined, which can also be understood as determining the sensitivity of each input scoring variable to the GIS carbon footprint data score. Among them, the input scoring variables may include attribute information such as regionality, raw material type, energy consumption type, production process and equipment, year corresponding to the field data of the secondary data, and attribute information such as time representativeness, regional representativeness and technical representativeness corresponding to the background data of the secondary data. Exemplarily, the degree of influence of the input scoring variables on the GIS carbon footprint data score can be calculated according to the following formula: ,in, Represents the input scoring variable Scoring GIS Carbon Footprint Data The degree of influence (i.e. sensitivity) express right When the input scoring variable undergoes a relative change, the GIS carbon footprint data score A relative change will occur, thereby measuring the impact of the input scoring variables on the GIS carbon footprint data score.

[0066] Example 2

[0067] Figure 2 This is a flow chart of a carbon footprint data evaluation method for GIS equipment provided in the second embodiment of the present invention, such as Figure 2 As shown, the method includes:

[0068] S210. Obtain secondary data of GIS equipment, unit process emission data, and carbon emission data for each stage of the entire life cycle.

[0069] S220. Analyze the field data in the secondary data to determine first data quality attribute information of the field data; wherein the first data quality attribute information includes regionality, raw material type, energy consumption type, production process and equipment, and year.

[0070] S230: Construct a first scoring matrix corresponding to the field data based on the first data quality attribute information and the field data quality scoring table.

[0071] S240. Analyze the background data in the secondary data to determine second data quality attribute information of the background data; wherein the second data quality attribute information includes time representativeness, regional representativeness, and technical representativeness.

[0072] S250: Construct a second scoring matrix corresponding to the background data based on the second data quality attribute information and the background data quality scoring table, and determine a background database data quality score based on the second scoring matrix.

[0073] S260: Calculate the field data quality score of the secondary data based on the first scoring matrix.

[0074] S270. Calculate a unit process emission data quality score based on the field data quality score and the unit process emission data.

[0075] S280. Calculate the carbon emission data quality score for the corresponding life cycle stage based on the unit process emission data quality score and the carbon emission data for each stage of the entire life cycle.

[0076] S290. Calculate the product carbon footprint data quality score based on the carbon emission data quality scores of each life cycle stage.

[0077] S2100. Determine a GIS carbon footprint data score based on the product carbon footprint data quality score and the background database data quality score.

[0078] S2110. Determine the quality level of the carbon footprint data of the GIS device based on the GIS carbon footprint data score and a pre-set GIS data quality level table.

[0079] The carbon footprint data evaluation method for GIS equipment in the embodiment of the present invention can accurately and effectively evaluate the carbon footprint data of GIS equipment, thereby enhancing the accuracy of carbon footprint accounting of GIS power equipment products and providing data support for accurate calculation of product carbon footprints.

[0080] Example 3

[0081] Figure 3 This is a structural diagram of a carbon footprint data evaluation device for GIS equipment provided in the third embodiment of the present invention. Figure 3 As shown, the device includes:

[0082] The data acquisition module 310 is used to obtain secondary data of GIS equipment, unit process emission data and carbon emission data at each stage of the entire life cycle;

[0083] A scoring matrix construction module 320 is used to construct a first scoring matrix corresponding to the field data in the secondary data and a second scoring matrix corresponding to the background data in the secondary data;

[0084] A product carbon footprint data quality score determination module 330 is configured to determine a product carbon footprint data quality score based on the first scoring matrix, the unit process emission data, and the carbon emission data for each stage of the life cycle;

[0085] A background database data quality score determination module 340 is configured to determine a background database data quality score based on the second scoring matrix;

[0086] The carbon footprint data quality evaluation module 350 is used to evaluate the quality of the carbon footprint data of the GIS device based on the product carbon footprint data quality score and the background database data quality score.

[0087] Optionally, the scoring matrix construction module is used to:

[0088] Analyzing the field data in the secondary data to determine first data quality attribute information of the field data; wherein the first data quality attribute information includes regionality, raw material type, energy consumption type, production process and equipment, and year;

[0089] Based on the first data quality attribute information and the field data quality scoring table, a first scoring matrix corresponding to the field data is constructed.

[0090] Optional, scoring matrix building module for:

[0091] Analyzing the background data in the secondary data to determine second data quality attribute information of the background data; wherein the second data quality attribute information includes time representativeness, geographical representativeness, and technical representativeness;

[0092] Based on the second data quality attribute information and the background data quality score table, a second scoring matrix corresponding to the background data is constructed.

[0093] Optional product carbon footprint data quality score determination module, used to:

[0094] Calculating a field data quality score of the secondary data based on the first scoring matrix;

[0095] Calculating a unit process emission data quality score based on the field data quality score and the unit process emission data;

[0096] Calculate the carbon emission data quality score for the corresponding life cycle stage based on the unit process emission data quality score and the carbon emission data for each stage of the life cycle;

[0097] The product carbon footprint data quality score is calculated based on the carbon emission data quality scores of each life cycle stage.

[0098] Optional carbon footprint data quality assessment module, including:

[0099] a GIS carbon footprint data score determination unit, configured to determine a GIS carbon footprint data score based on the product carbon footprint data quality score and the background database data quality score;

[0100] The quality level determination unit is used to determine the quality level of the carbon footprint data of the GIS device based on the GIS carbon footprint data score and a pre-set GIS data quality level table.

[0101] Optional, GIS carbon footprint data score determination unit, used to:

[0102] The GIS carbon footprint data score is calculated according to the following formula:

[0103] ;

[0104] in, represents the GIS carbon footprint data score, Indicates the carbon footprint data quality score of the product, represents the background database data quality score, Represents the weighting coefficient.

[0105] Optionally, also include:

[0106] The impact degree determination module is used to determine the impact degree of each input scoring variable on the GIS carbon footprint data score after determining the quality level of the carbon footprint data of the GIS device, when it is determined that the quality level is greater than a preset level.

[0107] The carbon footprint data evaluation device for GIS equipment provided in an embodiment of the present invention can execute the carbon footprint data evaluation method for GIS equipment provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0108] Example 4

[0109] Figure 4A schematic diagram of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0110] like Figure 4 As shown, electronic device 10 includes at least one processor 11 and memory, such as read-only memory (ROM) 12 and random access memory (RAM) 13, communicatively connected to at least one processor 11. The memory stores computer programs executable by the at least one processor. Processor 11 can perform various appropriate actions and processes based on the computer programs stored in ROM 12 or loaded from storage unit 18 into RAM 13. RAM 13 can also store various programs and data required for the operation of electronic device 10. Processor 11, ROM 12, and RAM 13 are interconnected via bus 14. An input / output (I / O) interface 15 is also connected to bus 14.

[0111] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0112] Processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Examples of processor 11 include, but are not limited to, central processing units (CPUs), graphics processing units (GPUs), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any other suitable processors, controllers, microcontrollers, and the like. Processor 11 executes the various methods and processes described above, such as the carbon footprint data evaluation method for GIS devices.

[0113] In some embodiments, the carbon footprint data evaluation method for a GIS device may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the carbon footprint data evaluation method for a GIS device described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to execute the carbon footprint data evaluation method for a GIS device in any other appropriate manner (e.g., by means of firmware).

[0114] Various embodiments of the systems and techniques described above can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0115] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0116] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or apparatus. A computer-readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0117] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device that has: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0118] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0119] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0120] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0121] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for evaluating carbon footprint data of GIS equipment, characterized in that: include: Obtain secondary data of GIS equipment, unit process emission data and carbon emission data at all stages of the entire life cycle; respectively constructing a first scoring matrix corresponding to the field data in the secondary data and a second scoring matrix corresponding to the background data in the secondary data; Determining a product carbon footprint data quality score based on the first scoring matrix, the unit process emission data, and the carbon emission data for each stage of the life cycle; determining a background database data quality score based on the second scoring matrix; Evaluating the quality of the carbon footprint data of the GIS device based on the product carbon footprint data quality score and the background database data quality score; The product carbon footprint data quality score is determined based on the first scoring matrix, the unit process emission data, and the carbon emission data for each stage of the life cycle, including: Calculating a field data quality score of the secondary data based on the first scoring matrix; Calculating a unit process emission data quality score based on the field data quality score and the unit process emission data; Calculate the carbon emission data quality score for the corresponding life cycle stage based on the unit process emission data quality score and the carbon emission data for each stage of the life cycle; Calculate the product carbon footprint data quality score based on the carbon emission data quality scores of each life cycle stage; The step of constructing a first scoring matrix corresponding to the field data in the secondary data includes: Analyzing the field data in the secondary data to determine first data quality attribute information of the field data; wherein the first data quality attribute information includes regionality, raw material type, energy consumption type, production process and equipment, and year; Based on the first data quality attribute information and the field data quality scoring table, constructing a first scoring matrix corresponding to the field data; wherein the first scoring matrix is ​​used to represent the attribute scores corresponding to each of the first data quality attribute information; The step of constructing a second scoring matrix corresponding to the background data in the secondary data includes: Analyzing the background data in the secondary data to determine second data quality attribute information of the background data; wherein the second data quality attribute information includes time representativeness, geographical representativeness, and technical representativeness; Based on the second data quality attribute information and the background data quality score table, a second scoring matrix corresponding to the background data is constructed; wherein the second scoring matrix is ​​used to represent the attribute scores corresponding to each piece of the second data quality attribute information.

2. The method according to claim 1, characterized in that Based on the product carbon footprint data quality score and the background database data quality score, the quality of the carbon footprint data of the GIS device is evaluated, including: Determining a GIS carbon footprint data score based on the product carbon footprint data quality score and the background database data quality score; The quality level of the carbon footprint data of the GIS device is determined based on the GIS carbon footprint data score and a pre-set GIS data quality level table.

3. The method according to claim 2, characterized in that Determine the GIS carbon footprint data score based on the product carbon footprint data quality score and the background database data quality score, including: The GIS carbon footprint data score is calculated according to the following formula: ； in, represents the GIS carbon footprint data score, Indicates the carbon footprint data quality score of the product, represents the background database data quality score, Represents the weighting coefficient.

4. The method according to claim 2, characterized in that After determining the quality level of the carbon footprint data of the GIS device, it also includes: When it is determined that the quality level is greater than the preset level, the degree of influence of each input scoring variable on the GIS carbon footprint data score is determined respectively.

5. A carbon footprint data evaluation device for GIS equipment, characterized in that: include: Data acquisition module, used to obtain secondary data of GIS equipment, unit process emission data and carbon emission data at all stages of the life cycle; a scoring matrix construction module, configured to respectively construct a first scoring matrix corresponding to the field data in the secondary data and a second scoring matrix corresponding to the background data in the secondary data; A product carbon footprint data quality score determination module is used to determine the product carbon footprint data quality score based on the first scoring matrix, the unit process emission data, and the carbon emission data of each stage of the life cycle; A background database data quality score determination module, configured to determine a background database data quality score based on the second scoring matrix; a carbon footprint data quality evaluation module, configured to evaluate the quality of the carbon footprint data of the GIS device based on the product carbon footprint data quality score and the background database data quality score; Among them, the product carbon footprint data quality score determination module is used to: Calculating a field data quality score of the secondary data based on the first scoring matrix; Calculating a unit process emission data quality score based on the field data quality score and the unit process emission data; Calculate the carbon emission data quality score for the corresponding life cycle stage based on the unit process emission data quality score and the carbon emission data for each stage of the life cycle; Calculate the product carbon footprint data quality score based on the carbon emission data quality scores of each life cycle stage; The scoring matrix construction module is used to: Analyzing the field data in the secondary data to determine first data quality attribute information of the field data; wherein the first data quality attribute information includes regionality, raw material type, energy consumption type, production process and equipment, and year; Based on the first data quality attribute information and the field data quality scoring table, constructing a first scoring matrix corresponding to the field data; wherein the first scoring matrix is ​​used to represent the attribute scores corresponding to each of the first data quality attribute information; Among them, the scoring matrix building module is used to: Analyzing the background data in the secondary data to determine second data quality attribute information of the background data; wherein the second data quality attribute information includes time representativeness, geographical representativeness, and technical representativeness; Based on the second data quality attribute information and the background data quality score table, a second scoring matrix corresponding to the background data is constructed; wherein the second scoring matrix is ​​used to represent the attribute scores corresponding to each piece of the second data quality attribute information.

6. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the carbon footprint data evaluation method for GIS equipment according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the carbon footprint data evaluation method for GIS equipment according to any one of claims 1 to 4 when executed.

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