Carbon asset data management method and system, readable storage medium and electronic equipment

Abstract

The invention provides a carbon asset data management method and system, a readable storage medium and electronic equipment. The method comprises the following steps: collecting carbon emission target data; performing data processing analysis on the carbon emission target data to obtain carbon asset data, the carbon asset data including carbon credit and trading information, transfer information and use information of carbon assets; performing compliance risk identification based on the carbon asset data in combination with a preset carbon management strategy, wherein the identification content specifically comprises whether the carbon asset data is compliant or not and the risk of the carbon asset; and carrying out visual display on an identification result obtained by identifying the compliance risk, and carrying out visual display on the identification result by utilizing an interactive display interface. According to the carbon asset data management method and system, the readable storage medium and the electronic equipment, comprehensive management and operation support of carbon assets can be provided for enterprises by combining real-time market information on the basis of comprehensive acquisition, management and optimization of the carbon asset data.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and in particular, relates to a carbon asset data management method, system, readable storage medium and electronic device. Background Art

[0002] Carbon assets refer to quota emissions, emission reduction credits and related activities that can directly or indirectly affect greenhouse gas emissions under a mandatory carbon emissions trading mechanism or a voluntary carbon emissions trading mechanism. Under the general trend of energy conservation and emission reduction, management departments can exercise macro-control over the carbon emissions of related industries by issuing carbon emission indicators.

[0003] At present, carbon emission trading has further evolved into a financial asset with investment value and liquidity. However, in the process of trading, carbon assets in existing technologies need to be traded on the premise of meeting their own carbon asset needs. In addition, during the trading process, due to errors in human operations, carbon asset operations may be affected, resulting in reduced carbon asset management efficiency. Summary of the invention

[0004] In view of the above-mentioned shortcomings of the prior art, an object of the present invention is to provide a carbon asset data management method, system, readable storage medium and electronic device to solve the above-mentioned problems.

[0005] In a first aspect, the present invention provides a carbon asset data management method, the method comprising the following steps:

[0006] Collecting carbon emission target data, wherein the carbon emission target data at least includes carbon emission basic data, energy consumption carbon emission data and transportation process carbon emission data;

[0007] Performing data processing and analysis on the carbon emission target data to obtain carbon asset data, wherein the carbon asset data includes carbon credits and carbon asset purchase and sale information, transfer information, and use information;

[0008] Based on the carbon asset data and the preset carbon management strategy, compliance risk identification is performed, including whether the carbon asset data is compliant and the risks of carbon assets;

[0009] The identification results of the compliance risks are visualized and displayed, wherein the identification results are visualized using an interactive display interface.

[0010] In a possible implementation of the present application, the carbon emission target data is collected, wherein the carbon emission target data at least includes carbon emission basic data, energy consumption carbon emission data and transportation process carbon emission data, specifically including:

[0011] Acquiring input data inputted by the user terminal on the interactive display interface;

[0012] Acquiring communication data of a sensing device and a monitoring device, wherein the communication data includes sensing data and monitoring data;

[0013] The carbon emission target data is obtained based on the input data, the sensor data and the monitoring data, wherein the carbon emission basic data is obtained based on the input data, the energy consumption carbon emission data is obtained based on the sensor data, and the transportation process carbon emission data is obtained based on the monitoring data.

[0014] In a possible implementation of the present application, the carbon emission target data is processed and analyzed to obtain carbon asset data, wherein the carbon asset data includes carbon credits and carbon asset purchase and sale information, transfer information and usage information, specifically including:

[0015] The data processing of the carbon emission data specifically includes missing value processing and outlier detection and modification, wherein the carbon emission data after data processing is accurate and consistent data;

[0016] The processed carbon emission data is subjected to data analysis to obtain the carbon asset data, wherein the data analysis is specifically performed using a network model, and the network model includes at least a statistical model and a prediction model.

[0017] In one possible implementation of the present application, a statistical model is used for data analysis, specifically including: performing a time series analysis on the carbon emission data after data processing, and using a multivariate linear regression model to analyze the correlation between various factors of carbon emissions to obtain the carbon credit corresponding to the time season and emission trend.

[0018] In one possible implementation of the present application, a prediction model is used for data analysis, specifically including: using a machine learning model to build a regression decision tree model and a random forest model using a support vector machine for analysis and prediction, and using a deep learning model to verify the prediction data of the machine learning model to obtain the purchase, sale, transfer and usage information of carbon assets corresponding to the time season and emission trends.

[0019] In a possible implementation of the present application, the compliance risk identification is performed based on the carbon asset data in combination with a preset carbon management strategy, and the identification content specifically includes whether the carbon asset data is compliant and the risks of the carbon assets, specifically including:

[0020] Obtaining a carbon management strategy, wherein the carbon management strategy includes policies and regulations related to the determined corporate carbon emissions;

[0021] Compliance risk identification is performed based on the carbon asset data and the carbon management strategy combined with different time seasons and emission trends, where:

[0022] Based on the comparison between the carbon asset data and the corresponding relevant laws and regulations, data extraction and keyword recognition are used to determine whether the carbon asset data is compliant;

[0023] The carbon asset data is compared with corresponding relevant strategies, wherein data matching is performed on the purchase and sale information, transfer information and use information of the carbon assets to determine the risks existing in the current carbon asset data.

[0024] In a possible implementation of the present application, the identification result of the compliance risk is visually displayed, wherein the identification result is visually displayed using an interactive display interface, specifically including:

[0025] Extracting the identification results obtained from the compliance risk identification judgment;

[0026] The recognition result is output to the interactive display interface for visual display, wherein the interactive display interface includes an interactive interface and a display interface.

[0027] In a second aspect, the present invention provides a carbon asset data management system, the system comprising:

[0028] A collection module, used to collect carbon emission target data, wherein the carbon emission target data at least includes production process carbon emission data, energy consumption carbon emission data and transportation process carbon emission data;

[0029] An analysis module, used for performing data processing and analysis on the carbon emission target data to obtain carbon asset data, wherein the carbon asset data includes carbon credits and carbon asset purchase and sale information, transfer information and use information;

[0030] An identification module is used to identify compliance risks based on the carbon asset data in combination with a preset carbon management strategy, and the identification content specifically includes whether the carbon asset data is compliant and the risks of carbon assets;

[0031] The display module is used to visualize the identification results of compliance risks, wherein the identification results are visualized using an interactive display interface.

[0032] In a third aspect, the present invention provides an electronic device, the electronic device comprising: a processor and a memory;

[0033] The memory is used to store computer programs;

[0034] The processor is used to execute the computer program stored in the memory so that the electronic device executes the above-mentioned carbon asset data management method.

[0035] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the above-mentioned carbon asset data management method when executed by an electronic device.

[0036] As described above, the carbon asset data management method, system, readable storage medium and electronic device described in the present invention have the following beneficial effects: based on the comprehensive collection, management and optimization of carbon asset data, combined with real-time market information, it can provide enterprises with all-round management and operational support for carbon assets, which can help enterprises maintain competitiveness in complex carbon markets, fulfill environmental and social responsibilities, and improve economic benefits. Moreover, by managing carbon emissions and carbon credits, it can optimize purchase, sales and use strategies, realize rapid trading of carbon emission rights, thereby reducing the investment costs of enterprises and increasing profits. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 Shown is a schematic diagram of a scene of an electronic device in an embodiment of the present invention;

[0038] Figure 2 Shown is a schematic diagram of the steps of the carbon asset data management method in one embodiment of the present invention;

[0039] Figure 3 Shown is a schematic diagram of the steps of the carbon asset data management method in one embodiment of the present invention;

[0040] Figure 4 Shown is a schematic diagram of the steps of the carbon asset data management method in one embodiment of the present invention;

[0041] Figure 5 Shown is a schematic diagram of the steps of the carbon asset data management method in one embodiment of the present invention;

[0042] Figure 6 Shown is a schematic diagram of the structure of a carbon asset data management system in one embodiment of the present invention;

[0043] Figure 7 It is a schematic structural diagram of an electronic device of the present invention in one embodiment. DETAILED DESCRIPTION

[0044] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0045] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0046] The following embodiments of the present invention provide a carbon asset data management method, which can be applied to Figure 1 The electronic device shown. The electronic device described in the present invention may include a mobile phone 11 with a wireless charging function, a tablet computer 12, a laptop computer 13, a wearable device, a vehicle-mounted device, an augmented reality (AR) / virtual reality (VR) device, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), etc. The embodiment of the present invention does not impose any restrictions on the specific type of the electronic device.

[0047] For example, the electronic device may be a station (STAION, ST) in a WLAN with a wireless charging function, a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA) device, a handheld device with a wireless charging function, a computing device or other processing device, a computer, a laptop computer, a handheld communication device, a handheld computing device, and / or other devices for communicating on a wireless system and a next generation communication system, such as a mobile terminal in a 5G network, a mobile terminal in a future evolved Public Land Mobile Network (PLMN), or a mobile terminal in a future evolved Non-terrestrial Network (NTN).

[0048] The technical solutions in the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0049] Specifically, see Figure 2 In one embodiment of the invention, the carbon asset data management method of the present invention comprises the following steps:

[0050] Step S202, collecting carbon emission target data, wherein the carbon emission target data at least includes carbon emission basic data, energy consumption carbon emission data and transportation process carbon emission data;

[0051] Step S204, performing data processing and analysis on the carbon emission target data to obtain carbon asset data, wherein the carbon asset data includes carbon credits and carbon asset purchase and sale information, transfer information, and use information;

[0052] Step S206, performing compliance risk identification based on the carbon asset data in combination with a preset carbon management strategy, wherein the identification content specifically includes whether the carbon asset data is compliant and the risks existing in the carbon assets;

[0053] Step S208: Visually display the identification results of the compliance risk, wherein the identification results are visualized using an interactive display interface.

[0054] It should be noted that, in this embodiment, when managing carbon asset data, it is necessary to first clarify what the carbon asset data is, wherein the carbon asset data includes carbon credits and carbon asset purchase and sale information, transfer information and usage information, and the carbon asset data is obtained by processing and analyzing carbon emission target data, which includes first collecting carbon emission target data and then processing and analyzing it. Specifically, carbon emission target data is collected, wherein the carbon emission target data at least includes carbon emission basic data, energy consumption carbon emission data and transportation process carbon emission data. After analyzing the carbon asset data, compliance risk identification is performed based on the carbon asset data in combination with the preset carbon management strategy. The identification content specifically includes whether the carbon asset data is compliant and the risks of carbon assets. Finally, the identification results of the compliance risk identification are visualized, wherein the identification results are visualized using an interactive display interface.

[0055] Furthermore, in one embodiment of the invention, the carbon emission target data is collected, wherein the carbon emission target data at least includes carbon emission basic data, energy consumption carbon emission data and transportation process carbon emission data, such as Figure 3 As shown, the specific steps include:

[0056] Step S302, obtaining input data input by the user terminal on the interactive display interface;

[0057] Step S304, acquiring communication data of the sensing device and the monitoring device, wherein the communication data includes sensing data and monitoring data;

[0058] Step S306, obtaining the carbon emission target data based on the input data, the sensor data and the monitoring data, wherein the carbon emission basic data is obtained based on the input data, the energy consumption carbon emission data is obtained based on the sensor data, and the transportation process carbon emission data is obtained based on the monitoring data.

[0059] It should be noted that, in this embodiment, the collected carbon emission target data includes carbon emission basic data, energy consumption carbon emission data and transportation process carbon emission data, wherein the carbon emission basic data is obtained based on the input data, the energy consumption carbon emission data is obtained based on the sensor data, and the transportation process carbon emission data is obtained based on the monitoring data. Therefore, it is necessary to obtain the input data input by the user terminal in the interactive display interface; and to obtain the communication data of the sensor device and the monitoring equipment, wherein the communication data includes sensor data and monitoring data.

[0060] Furthermore, in one embodiment of the invention, the carbon emission target data is processed and analyzed to obtain carbon asset data, wherein the carbon asset data includes carbon credits and carbon asset purchase and sale information, transfer information and usage information, such as Figure 4 As shown, the specific steps include:

[0061] Step S402, performing data processing on the carbon emission data, specifically including missing value processing and outlier detection and modification, wherein the carbon emission data after data processing is accurate and consistent data;

[0062] Step S404, performing data analysis on the processed carbon emission data to obtain the carbon asset data, wherein the data analysis is specifically performed using a network model, and the network model at least includes a statistical model and a prediction model.

[0063] It should be noted that, in this embodiment, data processing and analysis of carbon emission target data include data processing and data analysis, wherein the data processing of the carbon emission data specifically includes missing value processing and outlier detection and modification, wherein the carbon emission data after data processing is accurate and consistent data, further, when data analysis is performed on the carbon emission data after data processing to obtain the carbon asset data, a network model is specifically used for analysis, and the network model at least includes a statistical model and a predictive model.

[0064] Specifically, missing value processing can use multiple interpolation methods to handle missing values ​​in the data set to ensure data integrity; and outlier detection and correction: by using statistical methods based on box plots and Z-scores to identify and process outliers to ensure data quality.

[0065] Furthermore, in one embodiment of the invention, a statistical model is used for data analysis, specifically including: performing a time series analysis on the carbon emission data after data processing, and using a multivariate linear regression model to analyze the correlation between various factors of carbon emissions to obtain the carbon credit corresponding to the time season and emission trend.

[0066] It should be noted that, in this embodiment, statistical models are used for data analysis, including time series analysis and multivariate linear regression. Specifically, the time series analysis adopts time series analysis models such as autoregressive integrated moving average model (ARIMA), seasonal decomposition and exponential smoothing to perform trend analysis and seasonal decomposition on historical carbon emission data; while the multivariate linear regression is to construct a multivariate linear regression model to analyze the relationship between various factors affecting carbon emissions, identify the main driving factors, and thus obtain the correlation between various factors of carbon emissions to obtain the carbon credits corresponding to the time season and emission trends.

[0067] Furthermore, in one embodiment of the invention, a prediction model is used for data analysis, specifically including: using a machine learning model to construct a regression decision tree model and a random forest model using a support vector machine for analysis and prediction, and using a deep learning model to verify the prediction data of the machine learning model to obtain the purchase and sale information, transfer information and usage information of carbon assets corresponding to the time season and emission trend.

[0068] It should be noted that, in this embodiment, a prediction model is used for data analysis, and the prediction model specifically includes a machine learning model and a deep learning model. Specifically, the machine learning model includes: decision tree regression, which specifically constructs a regression decision tree model to capture nonlinear and interaction effects to predict carbon emissions, and uses a random forest model to integrate multiple decision trees to improve the accuracy and robustness of the prediction. Finally, the regression form of a support vector machine is used to handle the prediction problem of high-dimensional and nonlinear carbon emission data.

[0069] Furthermore, the deep learning model includes: a long short-term memory network (LSTM) and a convolutional neural network (CNN), wherein, based on the LSTM neural network, long-term dependency modeling is performed on time series carbon emission data to provide high-precision trend prediction, while the convolutional neural network (CNN) performs feature extraction and pattern recognition on large-scale carbon emission data to improve prediction performance, thereby obtaining the purchase, sale, transfer and usage information of carbon assets corresponding to the time season and emission trend.

[0070] Furthermore, in one embodiment of the invention, the compliance risk identification is performed based on the carbon asset data combined with the preset carbon management strategy, and the identification content specifically includes whether the carbon asset data is compliant and the risks of the carbon assets, such as Figure 5 As shown, the specific steps include:

[0071] Step S502, obtaining a carbon management strategy, wherein the carbon management strategy includes strategies and regulations related to the determined corporate carbon emissions;

[0072] Step S504, identifying compliance risks based on the carbon asset data and the carbon management strategy in combination with different time seasons and emission trends;

[0073] Step S506, comparing the carbon asset data with corresponding relevant laws and regulations, and using data extraction and keyword recognition to determine whether the carbon asset data is compliant;

[0074] Step S508, comparing the carbon asset data with corresponding relevant strategies, wherein data matching is performed on the purchase and sale information, transfer information and use information of the carbon assets to determine the risks existing in the current carbon asset data.

[0075] It should be noted that in this embodiment, after obtaining the carbon asset data, risk identification can be performed in combination with relevant strategies and regulations, wherein first, a carbon management strategy is obtained, wherein the carbon management strategy includes strategies and regulations related to the determined corporate carbon emissions, and then compliance risk identification is performed based on the carbon asset data and the carbon management strategy in combination with different time seasons and emission trends, wherein the carbon asset data is compared with the corresponding relevant regulations, and data extraction and keyword recognition are used to determine whether the carbon asset data is compliant, and the carbon asset data is compared with the corresponding relevant strategies, wherein data matching is performed on the purchase and sale information, transfer information and usage information of carbon assets to determine the risks existing in the current carbon asset data.

[0076] Furthermore, in one embodiment of the invention, the identification result of the compliance risk is visualized and displayed, wherein the identification result is visualized using an interactive display interface, specifically including:

[0077] Extracting the identification results obtained from the compliance risk identification judgment;

[0078] The recognition result is output to the interactive display interface for visual display, wherein the interactive display interface includes an interactive interface and a display interface.

[0079] It should be noted that, in this embodiment, in order to facilitate users to input data, view reports and perform management tasks, users can operate through the interactive display interface, and accordingly, the identification results obtained by the compliance risk identification judgment are extracted, so that the identification results can be output to the interactive display interface for visual display, wherein the interactive display interface includes an interactive interface and a display interface, the interactive interface is the interface for users to input data and perform operations, and the display interface allows users to view reports.

[0080] The embodiment of the present application also provides a carbon asset data management system, which can implement the carbon asset data management method described in the present application, but the implementation device of the carbon asset data management method described in the present application includes but is not limited to the structure of the carbon asset data management system listed in this embodiment. All structural deformations and replacements of the prior art made according to the principles of the present application are included in the protection scope of the present application.

[0081] See also Figure 6 In one embodiment, this embodiment provides a carbon asset data management system 60, the system comprising:

[0082] A collection module 61 is used to collect carbon emission target data, wherein the carbon emission target data at least includes production process carbon emission data, energy consumption carbon emission data and transportation process carbon emission data;

[0083] An analysis module 62, for performing data processing and analysis on the carbon emission target data to obtain carbon asset data, wherein the carbon asset data includes carbon credits and carbon asset purchase and sale information, transfer information and use information;

[0084] An identification module 63 is used to identify compliance risks based on the carbon asset data in combination with a preset carbon management strategy, and the identification content specifically includes whether the carbon asset data is compliant and the risks of the carbon assets;

[0085] The display module 64 is used to visualize the identification results of the compliance risks, wherein the identification results are visualized using an interactive display interface.

[0086] Since the specific implementation of this embodiment corresponds to the aforementioned method embodiment, the same details will not be repeated here, and those skilled in the art should also understand that Figure 6 The division of the modules in the embodiment is merely a division of logical functions, and in actual implementation, all or part of them can be integrated into one or more physical entities, and these modules can be implemented entirely in the form of software called by processing elements, or entirely in the form of hardware, or some modules can be implemented in the form of software called by processing elements, and some modules can be implemented in the form of hardware.

[0087] In the several embodiments provided by the present invention, it should be understood that the disclosed system, device or method can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules / units is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules or units can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules or units, which can be electrical, mechanical or other forms.

[0088] The modules / units described as separate components may or may not be physically separated, and the components displayed as modules / units may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules / units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention. For example, the functional modules / units in the various embodiments of the present invention may be integrated into one processing module, or each module / unit may exist physically separately, or two or more modules / units may be integrated into one module / unit.

[0089] Those of ordinary skill in the art should further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0090] The embodiment of the present invention also provides a computer-readable storage medium. A person of ordinary skill in the art can understand that all or part of the steps in the method for implementing the above embodiment can be completed by instructing the processor through a program, and the program can be stored in a computer-readable storage medium, and the storage medium is a non-transitory medium, such as a random access memory, a read-only memory, a flash memory, a hard disk, a solid-state hard disk, a magnetic tape, a floppy disk, an optical disc, and any combination thereof. The above storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a digital video disc (DVD)), or a semiconductor medium (e.g., a solid-state disk (SSD)), etc.

[0091] An embodiment of the present invention further provides an electronic device, which includes a processor and a memory.

[0092] The memory is used to store computer programs.

[0093] The memory includes: ROM, RAM, disk, USB flash drive, memory card or CD and other media that can store program codes.

[0094] The processor is connected to the memory and is used to execute the computer program stored in the memory so that the electronic device executes the above-mentioned carbon asset data management method.

[0095] Preferably, the processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0096] like Figure 7 As shown, the electronic device of the present invention is in the form of a general computing device. The components of the electronic device may include but are not limited to: one or more processors or processing units 71, a memory 72, and a bus 73 connecting different system components (including the memory 72 and the processing unit 71).

[0097] Bus 73 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0098] Electronic devices typically include a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device, including volatile and non-volatile media, removable and non-removable media.

[0099] The memory 72 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 721 and / or cache memory 722. The electronic device may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 723 may be used to read and write non-removable, non-volatile magnetic media ( Figure 7 not shown, usually called a "hard drive"). Although Figure 7Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 73 via one or more data medium interfaces. The memory 72 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0100] A program / utility 724 having a set (at least one) of program modules 7241 may be stored, for example, in the memory 72, such program modules 7241 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 7241 generally perform the functions and / or methods of the embodiments described herein.

[0101] The electronic device may also communicate with one or more external devices (e.g., keyboards, pointing devices, displays, etc.), one or more devices that enable a user to interact with the electronic device, and / or any device that enables the electronic device to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via input / output (I / O) interface 74. Furthermore, the electronic device may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via network adapter 75. Figure 7 As shown, the network adapter 75 communicates with other modules of the electronic device via the bus 73. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0102] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by a person of ordinary skill in the art without departing from the spirit and technical concept disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A carbon asset data management method, characterized in that: include: Collecting carbon emission target data, wherein the carbon emission target data at least includes carbon emission basic data, energy consumption carbon emission data and transportation process carbon emission data; Performing data processing and analysis on the carbon emission target data to obtain carbon asset data, wherein the carbon asset data includes carbon credits and carbon asset purchase and sale information, transfer information, and use information; Based on the carbon asset data and the preset carbon management strategy, compliance risk identification is performed, including whether the carbon asset data is compliant and the risks of carbon assets; The identification results of the compliance risks are visualized and displayed, wherein the identification results are visualized using an interactive display interface.

2. The carbon asset data management method according to claim 1, characterized in that: The carbon emission target data is collected, wherein the carbon emission target data at least includes carbon emission basic data, energy consumption carbon emission data and transportation process carbon emission data, specifically including: Acquiring input data inputted by the user terminal on the interactive display interface; Acquiring communication data of a sensing device and a monitoring device, wherein the communication data includes sensing data and monitoring data; The carbon emission target data is obtained based on the input data, the sensor data and the monitoring data, wherein the carbon emission basic data is obtained based on the input data, the energy consumption carbon emission data is obtained based on the sensor data, and the transportation process carbon emission data is obtained based on the monitoring data.

3. The carbon asset data management method according to claim 2, characterized in that: The carbon emission target data is processed and analyzed to obtain carbon asset data, wherein the carbon asset data includes carbon credits and carbon asset purchase and sale information, transfer information and use information, specifically including: The data processing of the carbon emission data specifically includes missing value processing and outlier detection and modification, wherein the carbon emission data after data processing is accurate and consistent data; The processed carbon emission data is subjected to data analysis to obtain the carbon asset data, wherein the data analysis is specifically performed using a network model, and the network model includes at least a statistical model and a prediction model.

4. The carbon asset data management method according to claim 3, characterized in that: The statistical model is used for data analysis, specifically including: performing time series analysis on the carbon emission data after data processing, and using a multivariate linear regression model to analyze the correlation between various factors of carbon emissions to obtain the carbon credit corresponding to the time season and emission trend.

5. The carbon asset data management method according to claim 4, characterized in that: Use prediction models to analyze data, including: using machine learning models to build regression decision tree models and random forest models, using support vector machines for analysis and prediction, and using deep learning models to verify the prediction data of machine learning models, in order to obtain the purchase, sale, transfer and use information of carbon assets corresponding to time, season and emission trends.

6. The carbon asset data management method according to claim 5, characterized in that: The compliance risk identification is performed based on the carbon asset data combined with the preset carbon management strategy, and the identification content specifically includes whether the carbon asset data is compliant and the risks of carbon assets, specifically including: Obtaining a carbon management strategy, wherein the carbon management strategy includes policies and regulations related to the determined corporate carbon emissions; Compliance risk identification is performed based on the carbon asset data and the carbon management strategy combined with different time seasons and emission trends, where: Based on the comparison between the carbon asset data and the corresponding relevant laws and regulations, data extraction and keyword recognition are used to determine whether the carbon asset data is compliant; The carbon asset data is compared with corresponding relevant strategies, wherein data matching is performed on the purchase and sale information, transfer information and use information of the carbon assets to determine the risks existing in the current carbon asset data.

7. The carbon asset data management method according to claim 6, characterized in that: The visual display of the identification results of the compliance risk, wherein the visual display of the identification results using an interactive display interface, specifically includes: Extracting the identification results obtained from the compliance risk identification judgment; The recognition result is output to the interactive display interface for visual display, wherein the interactive display interface includes an interactive interface and a display interface.

8. A carbon asset data management system, characterized in that: include: A collection module, used to collect carbon emission target data, wherein the carbon emission target data at least includes production process carbon emission data, energy consumption carbon emission data and transportation process carbon emission data; An analysis module, used for performing data processing and analysis on the carbon emission target data to obtain carbon asset data, wherein the carbon asset data includes carbon credits and carbon asset purchase and sale information, transfer information and use information; An identification module is used to identify compliance risks based on the carbon asset data in combination with a preset carbon management strategy, and the identification content specifically includes whether the carbon asset data is compliant and the risks of carbon assets; The display module is used to visualize the identification results of compliance risks, wherein the identification results are visualized using an interactive display interface.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the carbon asset data management method described in any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: The electronic device comprises: a processor and a memory; wherein the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the carbon asset data management method as described in any one of claims 1 to 7.

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