Method and device for identifying carbon emission of energy equipment

Abstract

The invention provides an energy equipment carbon emission identification method and device, and relates to the technical field of carbon emission, and the method comprises the steps: obtaining energy equipment attribute information and carbon emission source data through a code scanning identification mode; the method comprises the following steps: measuring and identifying material components of energy equipment through a material analysis method to obtain element composition and mass fraction according to an identification result; according to the element composition, the mass fraction and the energy equipment attribute information, obtaining mass data of energy equipment composition elements; and calculating carbon emission data of the energy equipment based on the quality data and the carbon emission factors corresponding to the corresponding elements. By adopting the scheme, the accuracy and credibility of the carbon emission data of the key equipment of the energy station can be ensured, and corresponding technical and data support is provided for the energy station to actively participate in green carbon footprint accounting, carbon transaction and carbon quota.

Description

Technical Field

[0001] The present application relates to the field of carbon emission technology, and in particular to a method and device for identifying carbon emissions from energy equipment. Background Art

[0002] Low-carbonization, zero-carbonization and even negative carbonization emissions are goals that need to be gradually achieved in the new energy field. In the process of energy development, it is necessary to monitor and manage the carbon emissions of energy equipment in real time. The carbon emissions of energy equipment involve the consumption of carbon dioxide in various links of the industrial chain, such as material preparation, production and manufacturing, transportation, construction, service and use, and decommissioning. Therefore, the carbon emissions of energy equipment throughout its life cycle must be considered.

[0003] At present, most of the research on carbon emissions of energy equipment at home and abroad focuses on the carbon dioxide consumption in a certain link of the entire life cycle. At the same time, for carbon emission data in different links, many manufacturers have not formed complete, comprehensive and traceable carbon emission measurement methods and related carbon emission data, resulting in carbon emission data values ​​in different links of the industrial chain being different from the actual values. Summary of the invention

[0004] The present application aims to solve one of the technical problems in the related art at least to some extent.

[0005] To this end, the first purpose of this application is to propose a method for identifying carbon emissions from energy equipment, which solves the technical problem that existing methods cannot guarantee the accuracy and completeness of the acquired carbon emission data, and realizes the acquisition and accurate calculation of carbon emission data.

[0006] The second objective of the present application is to provide a carbon emission identification device for energy equipment.

[0007] To achieve the above-mentioned purpose, the first aspect of the present application proposes a method for identifying carbon emissions from energy equipment, including: obtaining energy equipment attribute information and carbon emission source data by scanning code identification; measuring and identifying the material composition of the energy equipment by a material analysis method to obtain the elemental composition and mass fraction based on the identification results; obtaining the mass data of the constituent elements of the energy equipment based on the elemental composition and mass fraction and the energy equipment attribute information; and calculating the carbon emission data of the energy equipment based on the mass data and the carbon emission factors corresponding to the corresponding elements.

[0008] The energy equipment carbon emission identification method of the embodiment of the present application directly collects carbon emission related data of on-site energy equipment to achieve accurate accounting of equipment carbon emission data. At the same time, it actively obtains the existing carbon emission data of energy equipment by scanning codes (KKS or material codes) for identification, and based on the results of direct accounting, realizes the verification and certification of the existing carbon emission data of energy equipment, ensures the accuracy and reliability of carbon emission data of key equipment in energy stations, and provides corresponding technical and data support for energy stations to actively participate in green carbon footprint recognition, carbon trading and carbon quotas.

[0009] Optionally, in one embodiment of the present application, the method further includes scanning and identifying the KKS code, material code and RFID code by means of the code scanning and identification method.

[0010] Optionally, in one embodiment of the present application, the carbon emission data is calculated by the following formula:

[0011] E=∑ i Q i *C i

[0012] Among them, E is the carbon emission data of the equipment, Q is the mass data of the equipment's constituent elements, and C is the carbon emission factor of the equipment's constituent elements.

[0013] Optionally, in one embodiment of the present application, after obtaining the carbon emission data, the method further includes:

[0014] Comparing and analyzing the carbon emission data with the carbon emission source data to obtain a data comparison result;

[0015] The data comparison result based on the error is to collect and calculate the carbon emission data of energy equipment multiple times through material analysis method to obtain the total carbon emission data;

[0016] The average data of the total carbon emission data is compared and analyzed with the carbon emission source data to obtain the final carbon emission data.

[0017] Optionally, in one embodiment of the present application, after obtaining the final carbon emission data, the method further includes:

[0018] Upload the final carbon emission data to a preset database, and dynamically transmit it to the site digital display platform to update the corresponding carbon emission data information in the equipment coding system; and,

[0019] The relevant information of the energy equipment is visualized through a digital display platform to obtain a visualization result.

[0020] Optionally, in one embodiment of the present application, after obtaining the carbon emission data of the energy equipment, the method further includes calculating the carbon emission data of the first type of energy equipment to obtain measured carbon emission data, and calculating the measured average carbon emission data of the energy equipment:

[0021] E1n=∑ i Q i *C is

[0022] E1a=(E1+E2+.....En) / N

[0023] Among them, E1n is the nth measured carbon emission data of the first energy equipment, Q i is the mass data of the measured equipment components, C is is the standard carbon emission factor of the equipment components, N is the number of material analyses, and E1a is the measured average carbon emission data of the first energy equipment.

[0024] Optionally, in one embodiment of the present application, the method further includes:

[0025] Obtaining standard carbon emission data of energy equipment based on the energy equipment attribute information obtained by scanning code identification;

[0026] Calculating an actual carbon emission data correction coefficient based on the standard carbon emission data and the measured average carbon emission data;

[0027] The carbon emission data of the system including various energy devices is calculated according to the carbon emission data correction coefficient.

[0028] Optionally, in one embodiment of the present application, the carbon emission data correction coefficient and the system carbon emission data are calculated by the following formulas respectively:

[0029] K1=E1a / E1s

[0030] E=∑ i E ia =∑ i E is *K i

[0031] Among them, K1 is the carbon emission data correction coefficient of the first type of energy equipment, E1s is the standard carbon emission data of the energy equipment, E is the overall carbon emission data of the system, and E ia is the measured average carbon emission data of the i-th energy equipment, E is is the standard carbon emission data of the i-th energy equipment, K i is the carbon emission data correction coefficient of the i-th energy equipment.

[0032] The second object of the present application is to provide a carbon emission identification device for energy equipment, comprising:

[0033] The data acquisition module is used to obtain energy equipment attribute information and carbon emission source data by scanning code recognition;

[0034] The component determination module is used to measure and identify the material composition of energy equipment through material analysis methods, so as to obtain the element composition and mass fraction based on the identification results;

[0035] A mass calculation module, used to obtain mass data of the constituent elements of the energy device according to the element composition and mass fraction and the energy device attribute information;

[0036] The carbon emission data calculation module is used to calculate the carbon emission data of the energy equipment based on the mass data and the carbon emission factors corresponding to the corresponding elements.

[0037] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0039] Figure 1 A schematic diagram of a process for identifying carbon emissions from energy equipment provided in Example 1 of the present application;

[0040] Figure 2 This is an architecture diagram of the energy equipment carbon emission identification platform according to an embodiment of the present application;

[0041] Figure 3 This is a general structural diagram of a digital testing device according to an embodiment of the present application;

[0042] Figure 4 Function diagrams of other components of the embodiments of the present application;

[0043] Figure 5 This is an example diagram of an Ethernet communication interface according to an embodiment of the present application;

[0044] Figure 6 This is an example diagram of interface interconnection in GPIF mode of an embodiment of the present application;

[0045] Figure 7 This is an example diagram of a gun-style shape according to an embodiment of the present application;

[0046] Figure 8 This is an example diagram of performance parameters of key measurement test digital equipment in an embodiment of the present application;

[0047] Fig. 9 This is an example diagram of the material recognition scene workflow of an embodiment of the present application;

[0048] Fig.10 This is an example diagram of the coding recognition scenario workflow of an embodiment of the present application;

[0049] Fig.11 This is an example diagram of system function modules of the carbon footprint testing digital equipment according to an embodiment of the present application;

[0050] Fig.12 This is an example diagram of the code recognition process of an embodiment of the present application;

[0051] Fig.13 This is an example diagram of the hydropower plant identification system hierarchy of an embodiment of the present application;

[0052] Fig.14 This is an example diagram of the wind power plant identification system hierarchy in an embodiment of the present application;

[0053] Fig.15 This is an example diagram of the photovoltaic power station identification system hierarchy according to an embodiment of the present application;

[0054] Fig.16 This is an example diagram of the material identification process of an embodiment of the present application;

[0055] Fig.17 This is an example diagram of the first encoding scanning process of an embodiment of the present application;

[0056] Fig.18 This is an example diagram of the second encoding scanning process of an embodiment of the present application;

[0057] Fig.19 A schematic diagram of the structure of a carbon emission identification device for energy equipment provided in an embodiment of the present application. DETAILED DESCRIPTION

[0058] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0059] The following describes the energy equipment carbon emission identification method and device according to the embodiment of the present application with reference to the accompanying drawings.

[0060] Figure 1 A flowchart of a method for identifying carbon emissions from energy equipment provided in Example 1 of the present application.

[0061] like Figure 1As shown, the energy equipment carbon emission identification method includes the following steps:

[0062] Step 101, obtaining energy equipment attribute information and carbon emission source data by scanning code recognition;

[0063] Step 102, measuring and identifying the material components of the energy device by a material analysis method, so as to obtain the element composition and mass fraction according to the identification result;

[0064] Step 103, obtaining mass data of the constituent elements of the energy device according to the element composition and mass fraction and the attribute information of the energy device;

[0065] Step 104: Calculate the carbon emission data of the energy equipment based on the mass data and the carbon emission factors corresponding to the corresponding elements.

[0066] The energy equipment carbon emission identification method of the embodiment of the present application directly collects carbon emission related data of on-site energy equipment to achieve accurate accounting of equipment carbon emission data. At the same time, it actively obtains the existing carbon emission data of energy equipment by scanning codes (KKS or material codes) for identification, and based on the results of direct accounting, realizes the verification and certification of the existing carbon emission data of energy equipment, ensures the accuracy and reliability of carbon emission data of key equipment in energy stations, and provides corresponding technical and data support for energy stations to actively participate in green carbon footprint recognition, carbon trading and carbon quotas.

[0067] Optionally, in one embodiment of the present application, the method further includes scanning and identifying the KKS code, material code and RFID code by scanning code identification.

[0068] Optionally, in one embodiment of the present application, the carbon emission data is calculated by the following formula:

[0069] E=∑ i Q i *C i

[0070] Among them, E is the carbon emission data of the equipment, Q is the mass data of the equipment's constituent elements, and C is the carbon emission factor of the equipment's constituent elements.

[0071] Optionally, in one embodiment of the present application, after obtaining the carbon emission data, the method further includes:

[0072] Compare and analyze the carbon emission data with the carbon emission source data to obtain data comparison results;

[0073] Based on the data comparison results of the errors, the carbon emission data of energy equipment is collected and calculated multiple times through material analysis methods to obtain the total carbon emission data;

[0074] The average data of the total carbon emission data is compared and analyzed with the carbon emission source data to obtain the final carbon emission data.

[0075] Optionally, in one embodiment of the present application, after obtaining the final carbon emission data, the method further includes:

[0076] Upload the final carbon emission data to the preset database and dynamically transmit it to the site digital display platform to update the corresponding carbon emission data information in the equipment coding system; and,

[0077] The relevant information of energy equipment is visualized through a digital display platform to obtain visualization results.

[0078] Optionally, in one embodiment of the present application, the carbon emission data of the first type of equipment is calculated by the following formula:

[0079] E1n=∑ i Q i *C is

[0080] Among them, E1n is the nth measured carbon emission data of the first type of equipment, Q i is the mass data of the constituent elements of the measured equipment, and Cis is the standard carbon emission factor of the constituent elements of the energy equipment.

[0081] Measured average carbon emissions data for energy equipment:

[0082] E1a=(E1+E2+.....En) / N

[0083] Where N is the number of material analyses; E1a is the measured average carbon emission data of the first type of equipment.

[0084] Optionally, in one embodiment of the present application, the property information of the device is obtained after scanning the code for identification, and the standard carbon emission data E1s of the device is further obtained. According to the standard carbon emission data and the measured average carbon emission data, the existing carbon emission data correction coefficient k can be obtained:

[0085] K1=E1a / E1s

[0086] Among them, K1 is the carbon emission data correction coefficient of the equipment. If K1=1, the carbon emission data of the equipment is considered to be correct. If 0<K1<1, it can be preliminarily determined that the standard carbon emission data corresponding to the equipment is deviated. It is recommended to use the measured average carbon emission data of the device as the standard. If K1>1, the measured average carbon emission data should be verified. E1s is the standard carbon emission data of the equipment; E1a is the measured average carbon emission data of the equipment.

[0087] Through the above steps, the actual carbon emission data and variation coefficient of the equipment can be confirmed and revised to achieve more accurate calculation of carbon emission data.

[0088] Furthermore, the embodiment of the present application can complete the calculation of carbon emission data of a system including multiple devices, and the calculation formula is:

[0089] E=∑ i E ia =∑ i E iS *K i

[0090] Where: E is the overall carbon emission data of the system; E ia is the measured average carbon emission data of the i-th equipment; E is is the standard carbon emission data of the i-th equipment; K i is the carbon emission data correction coefficient of the ith equipment.

[0091] Figure 2 This is the architecture diagram of the energy equipment carbon emission identification platform of this embodiment. Figure 2 As shown, this embodiment develops on-site monitoring and collection technologies and systems for the carbon emissions of equipment in the production, transportation, use and disposal stages, forms a set of key measurement and testing digital equipment, obtains more accurate carbon emission data through on-site collection, data transmission and precise calculation, and constructs a digital evaluation management system and management platform for the carbon footprint of green energy devices throughout their life cycle. The management platform stores data from key measurement and testing digital equipment, and the management system verifies and authenticates carbon emission data based on the data from the management platform. An energy equipment carbon emission identification platform is constructed based on key measurement and testing digital equipment, the management platform and the management system, providing certain support for achieving the goals of low-carbonization, zero-carbonization and even negative carbonization emissions in the energy field.

[0092] (1) Key measurement and testing digital equipment

[0093] Figure 3 This is the overall structural diagram of the test digital device of this embodiment, including green equipment element collection points and power collection terminal. The power collection terminal includes a touch screen interaction unit, a storage unit, an uplink communication unit, an electrical parameter signal conditioning unit, a downlink communication interface and a central processing unit.

[0094] The material analysis component is the core component of the key measurement and testing digital equipment of this embodiment, which is used for material analysis and carbon emission accounting based on LIBS technology. This component includes an excitation source, a detector, a camera, etc.

[0095] This embodiment includes all components other than the core LIBS component such as Figure 4As shown, it is used for functions such as scanning, calculation, storage, transmission, interaction, and power supply.

[0096] The communication interface and transmission of key measurement and test digital equipment include Ethernet communication interface and USB communication interface.

[0097] The Ethernet communication interface consists of a terminal, a control terminal, and a router. The terminal provides two ways of installation: wireless networking with wireless access to the network and wireless networking with wired access to the network. Wireless networking is flexible and free, and is not affected by geographical location. Figure 5 shown.

[0098] Considering the frequency of task switching, a hot switch function is designed to facilitate the switching of wireless networks; considering the security and simplicity of data, WEP, WPA / WPA2 security authentication and TKIP, AES and other encryption modes are adopted, and users only need to configure the user name and password; considering the system power consumption and system stability, low-power functions such as deep sleep and standby mode are added, and the system is developed to automatically reconnect when offline. This design can meet the application of testing digital equipment in different environments.

[0099] The USB communication interface in this embodiment uses the GPIF interface mode of the USB controller CY7C68013A.

[0100] The EZ-USB FX2 series chip CY7C68013A is the first intelligent USB protocol microcontroller that supports USB2.0 protocol and is backward compatible. It supports standard transmission (12Mbps) and high-speed transmission (480Mbps). FX2 integrates the enhanced 8051 microcontroller core, USB transceiver, serial interface engine SIE and GPIF and other functional units. USB data transmission can be completed in 3 different working modes, namely Slave FIFO mode, Ports mode and GPIF mode.

[0101] When the GPIF interface mode is in normal port mode, all I / O pins can be used as general I / O ports of the microcontroller core. Figure 6 This is a schematic diagram of interface interconnection in GPIF mode. Figure 6As shown, when in "slave FIFO" mode, the FX2 endpoint FIFO is directly connected to the external processor or external programmable logic unit. In this mode, GPIF is not activated, and the master control end can use synchronous or asynchronous methods, and can provide an independent clock for the FX2 interface. The GPIF mode is called the general programmable interface mode. The GPIF master control mode means that in the high-speed data transmission mode, the microcontroller kernel does not participate in the data transmission channel control, and the parallel data reading and data packaging are completed by hardware. The FX2 FIFO is controlled by the internal integrated GPIF, and the software programming method is used to output the read and write control waveform and read the FIFO status flag, control the FIFO selection, and provide a special user interface to the external control end, which can access multiple universal bus interfaces. This embodiment uses the GPIF of FX2 to construct a USB data transmission channel.

[0102] The appearance design of key measurement and testing digital equipment adopts gun-style design, such as Figure 7 As shown, it can not only be operated with one hand, but also has complete functions and can be used in a variety of occasions. The gun-style design not only meets the functional needs, but is also very user-friendly. It also has a major breakthrough in styling, making it cool and atmospheric. Figure 8 This is an example diagram of performance parameters of key measurement test digital equipment in this embodiment.

[0103] (2) Backend management

[0104] The carbon footprint measurement and testing digital equipment of this embodiment mainly copes with two working scenarios, including identifying the main material to calculate the carbon footprint and identifying the code to calculate the carbon footprint.

[0105] Among them, calculating the carbon footprint of any object is applicable to all inorganic objects. Identify the main material of the object and calculate the carbon footprint of the object in combination with the manually added relevant parameters. Fig. 9 Example diagram of scene workflow for material identification, such as Fig. 9 As shown, in this scenario, the workflow of the device is to collect the material composition and content data of the object through the material detection transmitter, manually input the weight, volume parameters of the object, etc., obtain the carbon emission factor of the corresponding material in the carbon emission factor database in the background, and calculate its carbon footprint, and display it in the UI interface.

[0106] Identification code carbon footprint calculation refers to the calculation of the carbon footprint of green energy equipment through identification code and index. It is applicable to green energy equipment with KKS code or material code. Specifically,

[0107] For equipment that has been calculated by the green energy equipment carbon footprint assessment system, scan the KKS code or material code configured on the green energy equipment, link the green energy equipment carbon footprint assessment system, obtain and display its carbon footprint information on the UI interface. The workflow is to scan the code through the image recognition port, obtain the carbon footprint data in the background, and display it on the UI interface.

[0108] For equipment that has not been calculated by the Green Energy Equipment Carbon Footprint Assessment System, the activity level data in the associated information management system (such as the ERP system) is obtained through the KKS code or material code, and the relevant carbon emission factors are matched in combination with the manually entered supplementary parameters.

[0109] Calculate its carbon footprint and display it on the UI interface. Fig.10 An example diagram of the workflow for encoding recognition scenarios is shown below. Fig.10 As shown, the workflow is to scan the code through the image recognition port, obtain the relevant data from other systems in the background, display it on the UI interface, manually enter the missing data, obtain the carbon emission factor of the corresponding material in the carbon emission factor database in the background, calculate its carbon footprint, and display it on the UI interface.

[0110] (3) Management system

[0111] After demand analysis and use case design, the system functional modules of the carbon footprint test digital equipment are as follows: Fig.11 As shown, it is mainly divided into the following: material identification, code scanning, carbon footprint accounting, and information interaction.

[0112] The material identification function is mainly to realize data collection of the material composition of the object. The carbon footprint measurement test digital equipment uses LIBS technology to identify, classify, qualitatively and quantitatively analyze the material of objects composed of materials such as alloys / carbon steel. It is suitable for the detection of light elements such as C, Li and Si. The system applies high-energy laser to the sample, forming a laser spot (plasma) on the surface of the sample to excite the sample to emit light. The light is then analyzed by the spectral system and the monitoring system to obtain the elemental composition and content of the sample.

[0113] The coding recognition function is mainly used to realize data collection and recognition of KKS codes and material codes carried by green energy equipment and link other related information management systems. Fig.12 This is an example diagram of the coding recognition process, such as Fig.12 As shown, the coding recognition function mainly includes barcode scanning configuration definition, handheld barcode collection application, collection log query and other functional services. The system administrator defines and allocates barcode scanning configuration in the system. System business users scan and collect barcodes on the handheld terminal and handle daily business. They can also query the collection log.

[0114] KKS coding and material coding have corresponding coding rules, and the corresponding decoding methods need to be configured in advance. The barcode scanning configuration definition function mainly configures the two business scenarios of barcode scanning KKS coding and material coding, including setting configuration type, target type of order generation, source order type, handheld application name, handheld function name, scanning and parsing order, scan and parsing post-action, scanning interface display information, business type mapping and other information, so as to complete the configuration of specific barcode scanning scenarios.

[0115] The hydropower plant identification system (KKS) is divided into 5 levels to identify the equipment installation location. The first level is the plant code level; the second level is the unit / workshop / area level, the third level is the system level, the fourth level is the equipment level, and the fifth level is the component level. It is composed of 21 fixed-length numbers or letters, including: plant code (4 digits), unit (2 digits), power generation system (5 digits), equipment (5 digits), component (5 digits). The specific format is as follows: Fig.13 shown.

[0116] The wind farm identification system (KKS) is divided into four levels to identify wind farm equipment and structures. The first level is the site code level; the second level is the plant code level; the third level is the system code level; and the fourth level is the equipment code level. The specific format is as follows: Fig.14 shown.

[0117] The photovoltaic power station identification system (KKS) is divided into 4 levels to identify the equipment installation location, a total of 19 digits, including the site code, the whole plant code, the system layer code, and the equipment layer code. The specific format is as follows: Fig.15 shown.

[0118] The barcode collection function is operated by business operators holding carbon footprint measurement and testing digital equipment. Users scan the code through the scanning port. If the code can be self-parsed, the system automatically matches the source document type and the target type. If the barcode self-parse fails, the user manually specifies the target type and the source document type. Then the system parses and generates the target document and the reference relationship information of the document according to the user settings, and automatically records the scan log. The code parsing service provides the code collection management module with code data parsing services. When receiving a code parsing request, the code parsing service first parses the code structure, and then combines the data in the code file to obtain the code parsing result, and returns it to the caller to complete the code parsing operation.

[0119] The carbon footprint accounting function is mainly to calculate the product carbon footprint of the target item. The calculation of the product carbon footprint is to sum the activity level data of materials, energy and waste involved in all activities in the entire product life cycle within the system boundary, multiplied by their emission factors. Decompose the product life cycle, analyze the source of carbon emissions in each segment, merge the same sources in different stages, and obtain a quantitative model of the product carbon footprint. Since there are two ways to collect data and the collected data sources are different, this embodiment defines this function separately in the two scenarios of material analysis and code scanning.

[0120] Based on material recognition

[0121] Based on the material recognition function mentioned above, the composition data of the object can be obtained. Since the data source is relatively single, the carbon footprint calculated in this scenario only considers the carbon emissions contained in the production and manufacturing stage of the target object, and does not consider its transportation, energy consumption and waste.

[0122] The calculation of carbon footprint needs to be clear about the raw materials. The chemical elements and their contents contained in the target object can be obtained by using LIBs technology. In order to confirm the raw materials, the carbon footprint measurement and testing digital equipment will embed a database containing the raw materials and element ratios of common green energy equipment, and map them with the main elements of the collected objects. The specific process is as follows: Fig.16 shown.

[0123] However, due to errors in the results of material analysis in the data source, the manually entered attribute values ​​may be derived from estimates, and there are also large errors in the raw material list and corresponding content through element matching, which makes it difficult to guarantee the accuracy of the carbon footprint results calculated by this method.

[0124] Based on code recognition

[0125] Green energy equipment in the electric field will have a unique identifier that symbolizes its identity: KKS code, material code. In the green energy equipment carbon footprint assessment system, each carbon footprint data also has its corresponding code ID. By mapping the KKS code and material code with the carbon footprint ID, the carbon footprint information of the green energy equipment in the green energy equipment carbon footprint assessment system can be obtained by scanning the KKS code and material code index. The specific process is as follows: Fig.17 shown.

[0126] Considering that the implementation of the green energy equipment carbon footprint assessment system may have incomplete coverage within a certain period, there will be equipment in the power field that has not been calculated by the green energy equipment carbon footprint assessment system. However, based on the material coding, linked to the ERP system, relevant material information can be obtained, such as Fig.18As shown. Combined with the manually entered attribute values, the raw material list of the accounting target and its corresponding mass can be obtained. Then matching the embedded emission factor database, the carbon footprint of the green energy equipment can be obtained through the accounting model. Similar to the material analysis scenario, the carbon footprint calculated in this scenario only considers the carbon emissions contained in the production and manufacturing stage of the target object, without considering its transportation, energy consumption and waste.

[0127] The accuracy of the carbon footprint obtained by this method depends on the completeness and accuracy of the BOM in the ERP system.

[0128] The information interaction function includes information display and information input, where information display includes:

[0129] After the carbon footprint measurement and testing digital equipment is turned on, the interface will display two function entrances: material identification and code scanning.

[0130] After completing the material identification, the interface will display the analysis results.

[0131] After scanning the material code, the interface displays the BOM information confirmation result information. After clicking to jump to carbon footprint calculation, the interface will display the calculation result.

[0132] Information input includes:

[0133] In the workflow of the carbon footprint measurement and testing digital equipment, the main information input is the supplementary entry of the data source required for carbon footprint calculation. This is mainly reflected in the material analysis scenario. After completing the material identification, the operator needs to manually enter the name, weight, and volume of the target object. Therefore, the carbon footprint measurement and testing digital equipment can meet the character input of numbers, English, Chinese, and common symbols.

[0134] The equipment in the energy equipment carbon emission identification platform of this embodiment is a key measurement and testing digital equipment for the power generation cycle of hydropower and new energy equipment based on smart Internet of Things technology. This test digital equipment can flexibly cut in from any node in the entire life cycle, detect the material of green equipment from the source, and calculate the carbon emissions generated by its component raw materials according to the standards and their calculation methods. And it can link the green energy equipment carbon footprint evaluation system by identifying KKS codes or material codes, accurately target the carbon dioxide emissions in the fixed assets of various green energy industries and enterprises throughout the life cycle, and quickly and dynamically monitor and calculate their carbon emissions throughout the life cycle in real time.

[0135] This device is used to conduct qualitative and quantitative analysis of the material composition elements of green energy equipment, and combined with the embedded key raw material database, the carbon emissions contained in the raw material production and manufacturing process of its components are obtained. It breaks through the limitations of space and network environment and realizes real-time carbon footprint measurement outdoors or even out of the network environment. In addition, the collected information and calculation results can be compared with the carbon footprint of the production and manufacturing stage in the green energy equipment carbon footprint evaluation system, providing supplementary data basis for the evaluation system.

[0136] KKS coding and material coding serve as the information foundation of the green energy industry. Using test digital equipment as a medium, linking existing coding with carbon footprint ID, it is possible to monitor the carbon footprint of green equipment at any time on site throughout its life cycle. And the device only needs to identify the existing coding to obtain data information in the carbon footprint evaluation system of green energy equipment, eliminating the huge workload of additional coding.

[0137] In order to implement the above-mentioned embodiment, the present application also proposes a carbon emission identification device for energy equipment.

[0138] Fig.19 A schematic diagram of the structure of a carbon emission identification device for energy equipment provided in an embodiment of the present application.

[0139] like Fig.19 As shown, the energy equipment carbon emission identification device includes:

[0140] The data acquisition module is used to obtain energy equipment attribute information and carbon emission source data by scanning code recognition;

[0141] The component determination module is used to measure and identify the material composition of energy equipment through material analysis methods, so as to obtain the element composition and mass fraction based on the identification results;

[0142] A mass calculation module, used to obtain mass data of the constituent elements of the energy device according to the element composition and mass fraction and the energy device attribute information;

[0143] The carbon emission data calculation module is used to calculate the carbon emission data of energy equipment based on the mass data and the carbon emission factors corresponding to the corresponding elements.

[0144] Optionally, in one embodiment of the present application, the data acquisition module is also used to scan and identify the KKS code, material code and RFID code by scanning and identifying the code.

[0145] Optionally, in one embodiment of the present application, the carbon emission data calculation module is further used to calculate the carbon emission data using the following formula:

[0146] E=∑ i Q i *Ci

[0147] Among them, E is the carbon emission data of the equipment, Q is the mass data of the equipment's constituent elements, and C is the carbon emission factor of the equipment's constituent elements.

[0148] Optionally, in one embodiment of the present application, after the carbon emission data calculation module, a data comparison and analysis module is further included, which is used to:

[0149] Compare and analyze the carbon emission data with the carbon emission source data to obtain data comparison results;

[0150] Based on the data comparison results of the errors, the carbon emission data of energy equipment is collected and calculated multiple times through material analysis methods to obtain the total carbon emission data;

[0151] The average data of the total carbon emission data is compared and analyzed with the carbon emission source data to obtain the final carbon emission data.

[0152] Optionally, in one embodiment of the present application, after the data comparison and analysis module, a data update visualization module is further included, which is used to:

[0153] Upload the final carbon emission data to the preset database and dynamically transmit it to the site digital display platform to update the corresponding carbon emission data information in the equipment coding system; and,

[0154] The relevant information of energy equipment is visualized through a digital display platform to obtain visualization results.

[0155] It should be noted that the above explanations of the embodiment of the method for identifying carbon emissions from energy equipment are also applicable to the device for identifying carbon emissions from energy equipment of this embodiment, and will not be repeated here.

[0156] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0157] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0158] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0159] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0160] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0161] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0162] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0163] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for identifying carbon emissions from energy equipment, characterized in that: The method comprises: Obtain energy equipment attribute information and carbon emission source data by scanning code identification; The material composition of energy equipment is measured and identified through material analysis methods to obtain element composition and mass fraction based on the identification results; Obtaining mass data of the constituent elements of the energy device according to the element composition and mass fraction and the attribute information of the energy device; The carbon emission data of the energy equipment is calculated based on the mass data and the carbon emission factors corresponding to the corresponding elements.

2. The method according to claim 1, characterized in that The method further includes scanning and identifying the KKS code, material code and RFID code by means of the code scanning and identification method.

3. The method according to claim 1, characterized in that The carbon emission data is calculated by the following formula: E=Σ i Q i *C i Among them, E is the carbon emission data of the equipment, Q is the mass data of the equipment's constituent elements, and C is the carbon emission factor of the equipment's constituent elements.

4. The method according to claim 3, characterized in that: After obtaining the carbon emission data, the method further includes: Comparing and analyzing the carbon emission data with the carbon emission source data to obtain a data comparison result; The data comparison result based on the error is to collect and calculate the carbon emission data of energy equipment multiple times through material analysis method to obtain the total carbon emission data; The average data of the total carbon emission data is compared and analyzed with the carbon emission source data to obtain the final carbon emission data.

5. The method according to claim 4, characterized in that After obtaining the final carbon emission data, the method further includes: Upload the final carbon emission data to a preset database, and dynamically transmit it to the site digital display platform to update the corresponding carbon emission data information in the equipment coding system; and, The relevant information of the energy equipment is visualized through a digital display platform to obtain a visualization result.

6. The method according to claim 3, characterized in that After obtaining the carbon emission data of the energy equipment, the method further includes calculating the carbon emission data of the first type of energy equipment to obtain measured carbon emission data, and calculating the measured average carbon emission data of the energy equipment: E1n=∑ i Q i *C is E1a=(E1+E2+…En) / N Among them, E1n is the nth measured carbon emission data of the first energy equipment, Q i is the mass data of the measured equipment components, C is is the standard carbon emission factor of the equipment components, N is the number of material analyses, and E1a is the measured average carbon emission data of the first energy equipment.

7. The method according to claim 6, characterized in that The method further comprises: Obtaining standard carbon emission data of energy equipment based on the energy equipment attribute information obtained by scanning code identification; Calculating an actual carbon emission data correction coefficient based on the standard carbon emission data and the measured average carbon emission data; The carbon emission data of the system including various energy devices is calculated according to the carbon emission data correction coefficient.

8. The method according to claim 7, characterized in that The carbon emission data correction coefficient and the system carbon emission data are calculated by the following formulas: K1=E1a / E1s And=Σ i AND ia =Σ i AND iS *K i Among them, K1 is the carbon emission data correction coefficient of the first type of energy equipment, E1s is the standard carbon emission data of the energy equipment, E is the overall carbon emission data of the system, and E ia is the measured average carbon emission data of the i-th energy equipment, E is is the standard carbon emission data of the i-th energy equipment, K i is the carbon emission data correction coefficient of the i-th energy equipment.

9. A carbon emission identification device for energy equipment, characterized in that: include: The data acquisition module is used to obtain energy equipment attribute information and carbon emission source data by scanning code recognition; The component determination module is used to measure and identify the material composition of energy equipment through material analysis methods, so as to obtain the element composition and mass fraction based on the identification results; A mass calculation module, used to obtain mass data of the constituent elements of the energy device according to the element composition and mass fraction and the energy device attribute information; The carbon emission data calculation module is used to calculate the carbon emission data of the energy equipment based on the mass data and the carbon emission factors corresponding to the corresponding elements.

10. The device according to claim 9, characterized in that After the carbon emission data calculation module, a data comparison and analysis module is also included, which is used to: Comparing and analyzing the carbon emission data with the carbon emission source data to obtain a data comparison result; The data comparison result based on the error is to collect and calculate the carbon emission data of energy equipment multiple times through material analysis method to obtain the total carbon emission data; The average data of the total carbon emission data is compared and analyzed with the carbon emission source data to obtain the final carbon emission data.

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