Carbon footprint data evaluation method and device of GIS equipment, electronic equipment and storage medium
By acquiring and building a scoring matrix, the gap in the quality evaluation of carbon footprint data of GIS equipment is solved, and the accurate evaluation of carbon footprint data of GIS equipment is achieved, which improves the accuracy of carbon footprint accounting.
Patent Information
- Application Number
- CN202411658374.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-20
- Publication Date
- 2024-12-20
- Estimated Expiration
- 2044-11-20
AI Technical Summary
The existing data quality evaluation model fails to effectively evaluate the quality of carbon footprint data of gas insulated metal closed switch process production equipment (GIS), and lacks evaluation methods and guidelines for this field.
By obtaining the secondary data of GIS equipment, unit process emission data and carbon emission data at each stage of the entire life cycle, a scoring matrix of on-site data and background data is constructed, the product carbon footprint data quality score and background database data quality score are determined, and GIS is comprehensively evaluated. Carbon footprint data quality of the equipment.
It realizes accurate and effective evaluation of the carbon footprint data of GIS equipment, enhances the accuracy of carbon footprint accounting, and provides data support for accurate accounting of the carbon footprint of products.
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Figure CN119166627A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of data management, and in particular to a carbon footprint data evaluation method, device, electronic device and storage medium for GIS equipment. Background Art
[0002] Data quality evaluation refers to the analysis of various attributes and dimensions of data through systematic techniques and methods, so as to measure and evaluate whether the quality of data meets the expected requirements and standards. Its purpose is to ensure that the accuracy, completeness, consistency, timeliness, effectiveness and other aspects of the data meet the established standards, so as to enable the process of quantification and decision-making. In the production of product equipment and process, it is necessary to evaluate and analyze the quality of the collected carbon footprint data to enhance the accuracy of carbon footprint accounting. However, most of the existing data quality evaluation models are aimed at data quality evaluation in big data situations, and corresponding constraint rules are established through business quality to conduct data evaluation. However, there is no evaluation method and criteria for the quality of carbon footprint data of gas insulated metal enclosed switchgear and controlgear (GIS) process 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 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] 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;
[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, used 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, 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 whole 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, there is provided an electronic device, the electronic device 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 secondary data, unit process emission data and carbon emission data of each stage of the whole life cycle of 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 whole 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 footprint.
[0022] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily 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 Embodiment 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 Embodiment 3 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 scheme of the present invention, the technical scheme 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 described embodiments 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 creative work should fall within the scope of protection of the present invention.
[0029] It should be noted that the terms "first", "second", etc. in the specification 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 data 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 that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.
[0030] Embodiment 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 at all stages of the life cycle.
[0033] In an embodiment of the present invention, relevant carbon footprint data of GIS equipment is obtained, wherein the relevant carbon footprint data of GIS equipment includes primary data, secondary data, unit process emission data, carbon emission data of each stage of the whole life cycle and product carbon footprint data. Among them, primary data is the quantitative value of a process or activity obtained by direct measurement or calculation based on direct measurement, also known as first-hand data.
[0034] Secondary data are quantitative values of unit processes or activities obtained by means other than direct measurement at the original source or calculation based on direct measurement. Secondary data may include data in 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 can also be called 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 the process can be understood as a set of interrelated or interacting activities that convert inputs into outputs. The unit process can be understood as the most basic part determined in the life cycle assessment to quantify input and output data. Input data may include products, materials, and energy flows entering a unit process, and output data may include products, materials, and energy flows leaving a unit process.
[0035] The carbon emission data at each stage of the whole life cycle refers to the carbon emissions generated at different stages of the product or process. The stages of the whole life cycle of GIS equipment may include the raw and auxiliary materials acquisition stage, the raw and auxiliary materials transportation stage, the product production stage, the product transportation stage, the product use stage, the waste disposal stage and other stages. In an embodiment of the present invention, the raw and auxiliary materials 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 materials 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 materials 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 starts from the time when the raw and auxiliary materials enter the production plant and ends when the final product leaves the production plant. The process of the product production phase includes: a) production of major parts, components, and assemblies; b) assembly and assembly of products; c) inspection and packaging of products; d) transportation and warehousing within the production plant; e) greenhouse gas emissions within the production plant; f) waste management related to the production process. The product transportation phase starts from the time when the final product leaves the production plant and ends when the product arrives at the place of use. The product use phase starts from the time when the product arrives at the place of use and ends at the end of the product's service life. The process of the product use phase includes: a) operation of the product, including power loss; b) the impact of the product's daily maintenance process. The waste disposal phase starts from the end of the product's service life and ends when the product returns to nature or is assigned to another product's life cycle. The process of the waste disposal phase includes: a) disassembly of waste products; b) disassembly, screening and waste treatment; c) other recycling and disposal processes. The product carbon footprint data is the total carbon emissions generated during the entire product life cycle (from raw material acquisition to disposal / recycling), usually expressed in tons of carbon dioxide equivalent (tCO2e). Therefore, the product carbon footprint data can be determined based on the carbon emission data of each stage of the GIS equipment's life cycle. The product carbon footprint refers to the sum of all greenhouse gas emissions and greenhouse gas removals of GIS equipment expressed in units of carbon dioxide equivalent throughout its life cycle.
[0036] In the embodiment of the present invention, the secondary data, unit process emission data and carbon emission data at each stage of the whole life cycle all include two types of data: field data and background data.
[0037] S120: 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 respectively.
[0038] In an embodiment of the present invention, the field data in the secondary data is scored based on the 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 the 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 the first scoring matrix corresponding to the field data.
[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, year, etc. 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 the first data quality attribute information. Exemplarily, 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. Exemplarily, a field data quality scoring table is obtained. Table 1 is the field data quality scoring table 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 of all field data.
[0043] In an embodiment of the present invention, the background data in the secondary data is scored based on the 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 the second data quality attribute information of the background data; wherein the second data quality attribute information includes time representativeness, regional representativeness and technical representativeness; based on the second data quality attribute information and the background data quality scoring table, constructing the second scoring matrix corresponding to the background data.
[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 report date is better within the validity period of the data set than 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 is 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 in an embodiment of the present invention:
[0045] Table 2 Background data quality rating table
[0046]
[0047] Based on the second data quality attribute information and the background data quality score table, the scores of the background data of the secondary data in terms of time representativeness (TiR), geographical representativeness (GeR), and technical representativeness (TeR) are determined, and the second scoring matrix corresponding to the background data is constructed based on the scores of the background field data of the secondary data in terms of time representativeness (TiR), geographical representativeness (GeR), and technical representativeness (TeR). As shown in Table 2, if the release date of the environmental carbon footprint report of the background data is within the validity period of the data set, the score of the background data in terms of the attribute of time representativeness (TiR) is 1 point; if the simulated process in the environmental carbon footprint study of the background data is applied in some areas where the data set is valid, the score of the background data in terms of the attribute of geographical representativeness (GeR) is 2 points. 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 the second scoring matrix corresponding to the background data is constructed 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.
[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, the product carbon footprint data quality score is calculated based on the first scoring matrix, unit process emission data and carbon emission data at each stage of the whole life cycle corresponding to the field data of the secondary data (i.e., unit process input data). Optionally, 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 at each stage of the whole life cycle, including: 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 corresponding life cycle stage carbon emission data quality score based on the unit process emission data quality score and the carbon emission data at each stage of the whole life cycle; calculating the product carbon footprint data quality score according to the carbon emission data quality score of each life cycle stage.
[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 is Indicates the first The score corresponding to the attribute of regionality of the field data. 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 the attribute of energy consumption type, Indicates the first The score of the field data corresponding to the attribute of production process and equipment indicates the score of the secondary data. The corresponding score of the field data in terms of the attribute of year.
[0051] The unit process emission data quality score is calculated based on the field data quality scores corresponding to all the 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 unit process emission data quality score corresponding to the unit process emission data, n represents the number of inputs contained in the unit process, For unit process The carbon emissions generated by each input. According to 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 the life cycle stage corresponding to the carbon emission data of each stage of the life cycle can be calculated according to the following formula: ,in, Indicates the phase number of the entire life cycle, Indicates the number of unit processes included in the life cycle stage, Indicates 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 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, the background database data quality score corresponding to the background data is calculated according to the second scoring matrix corresponding to the background data in the secondary data. Exemplarily, the second scoring matrix is a scoring matrix constructed by analyzing the attributes of the three dimensions of time representativeness, geographical representativeness and technical representativeness of the background data, and the background database data quality score can be calculated according to the following formula: , represents the background database data quality score, represents 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. Among them, 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, based on the product carbon footprint data quality score and the background database data quality score, the GIS carbon footprint data score is determined, 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 preset 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] Find the target score range of the GIS carbon footprint data score in the GIS data quality level table, and use the quality level corresponding to the target score range in the GIS data quality level table as the quality level of the carbon footprint data of the GIS device. For example, if the GIS carbon footprint data score is 1.8, the quality level of the carbon footprint data of the GIS device is level three, which means that the quality of the carbon footprint data of the GIS device is average.
[0063] Optionally, the evaluation results of the carbon footprint data of the GIS device can also be displayed through a display module, wherein the display module can include an electronic digital large screen. Exemplarily, the quality calculation results, quality levels and corresponding quality evaluation results of the GIS carbon footprint data at different stages and backgrounds can be visualized and analyzed.
[0064] The carbon footprint data evaluation method of the 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 whole 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 whole 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 the GIS equipment can be accurately and effectively evaluated, thereby enhancing the accuracy of the carbon footprint accounting of the GIS power equipment products and providing data support for the accurate accounting of the product carbon footprint.
[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 score variable Scoring GIS Carbon Footprint Data The degree of influence (i.e. sensitivity) express right When a relative change occurs in the input scoring variable, the GIS carbon footprint data score A relative change will occur, measuring the impact of the input scoring variables on the GIS carbon footprint data score.
[0066] Embodiment 2
[0067] Figure 2 A flowchart of a carbon footprint data evaluation method for GIS equipment provided in the second embodiment of the present invention is shown in FIG. Figure 2 As shown, the method includes:
[0068] S210. Obtain secondary data of GIS equipment, unit process emission data and carbon emission data at each stage of the 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, geographical 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 the 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. Based on the unit process emission data quality score and the carbon emission data of each stage of the entire life cycle, calculate the carbon emission data quality score of the corresponding life cycle stage.
[0076] S290. Calculate the product carbon footprint data quality score according to 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 of 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 footprint.
[0080] Embodiment 3
[0081] Figure 3 This is 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. Figure 3 As shown, the device comprises:
[0082] The data acquisition module 310 is used to acquire the secondary data of the GIS equipment, the unit process emission data and the carbon emission data of each stage of the whole life cycle;
[0083] A scoring matrix construction module 320, used 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;
[0084] A product carbon footprint data quality score determination module 330 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 whole life cycle;
[0085] A background database data quality score determination module 340, 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] 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;
[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 to:
[0091] 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, geographical representativeness and technical representativeness;
[0092] Based on the second data quality attribute information and the background data quality score table, a second score 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] Based on the unit process emission data quality score and the carbon emission data of each stage of the whole life cycle, calculate the carbon emission data quality score of the corresponding life cycle stage;
[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 grade determination unit is used to determine 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.
[0101] Optional, GIS carbon footprint data score determination unit for:
[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 the 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 the corresponding functional modules and beneficial effects of the execution method.
[0108] Embodiment 4
[0109] Figure 4A schematic diagram of the structure 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 processing, cellular phones, smart phones, 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 required herein.
[0110] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.
[0111] A number of 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 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 through a computer network such as the Internet and / or various telecommunication networks.
[0112] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the carbon footprint data evaluation method of the GIS device.
[0113] In some embodiments, the carbon footprint data evaluation method for GIS equipment may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the carbon footprint data evaluation method for GIS equipment described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the carbon footprint data evaluation method for GIS equipment in any other appropriate manner (e.g., by means of firmware).
[0114] Various implementations of the systems and techniques described above herein 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), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including 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, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, 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 equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, 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 may be implemented on an electronic device having: 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 a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).
[0118] The systems and techniques described herein may be implemented in a computing system that includes backend 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 frontend components (e.g., a user computer with a graphical user interface or a 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 backend components, middleware components, or frontend components. The components of the system may 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 a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.
[0120] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.
[0121] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims
1. A method for evaluating carbon footprint data of GIS equipment, It is characterized in that include: Obtain secondary data of GIS equipment, unit process emission data and carbon emission data at all stages of the 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; 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; Determining a background database data quality score based on the second scoring matrix; 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.
2. The method according to claim 1, It is characterized in that Constructing a first scoring matrix corresponding to the field data in the secondary data, including: 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; 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.
3. The method according to claim 1, It is characterized in that Constructing a second scoring matrix corresponding to the background data in the secondary data, including: 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, geographical representativeness and technical representativeness; Based on the second data quality attribute information and the background data quality score table, a second score matrix corresponding to the background data is constructed.
4. The method according to claim 1, It is characterized in that Based on the first scoring matrix, the unit process emission data and the carbon emission data at each stage of the life cycle, the product carbon footprint data quality score is determined, 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; Based on the unit process emission data quality score and the carbon emission data of each stage of the whole life cycle, calculate the carbon emission data quality score of the corresponding life cycle stage; The product carbon footprint data quality score is calculated based on the carbon emission data quality scores of each life cycle stage.
5. The method according to claim 1, It is 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.
6. The method according to claim 5, It is characterized in that Based on the product carbon footprint data quality score and the background database data quality score, a GIS carbon footprint data score is determined, 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.
7. The method according to claim 5, It is 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 a preset level, the influence of each input scoring variable on the GIS carbon footprint data score is determined respectively.
8. A carbon footprint data evaluation device for GIS equipment, It is 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, used 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, 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 whole 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; 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.
9. An electronic device, It is 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 executable 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 one of claims 1-7.
10. A computer-readable storage medium, It is 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 7 when executed.
Citation Information
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