Open-pit coal mine carbon emission accounting method and device, electronic equipment and storage medium

Abstract

This disclosure provides a method, apparatus, electronic device, and storage medium for carbon emission accounting in open-pit coal mines, relating to the field of carbon emission accounting technology. By receiving user-inputted time range setting instructions, it collects and integrates multi-source energy consumption data, carbon emission-related parameters, and carbon sink data from the mining area based on these instructions. It dynamically calculates energy consumption and carbon emission indicators for each production stage within the selected time period, generating visual charts representing energy consumption and carbon emission distributions. Furthermore, it constructs models showcasing the changing trends of energy consumption and carbon emissions based on different time scales. Therefore, it can solve the problems of data lag, error accumulation, single analysis dimensions, and lack of multi-time-scale trend analysis and visualization of energy consumption and carbon emission distributions caused by the use of a distributed data collection and manual statistics model, the lack of a unified data integration platform, and dynamic analysis models in existing technologies.

Description

Technical Field

[0001] This disclosure relates to the field of carbon emission accounting technology, and in particular to a method and apparatus, electronic equipment and storage medium for carbon emission accounting in open-pit coal mines. Background Technology

[0002] Against the backdrop of global climate change response, environmental protection requirements are becoming increasingly stringent. As a crucial method of coal production, open-pit coal mines' carbon emission accounting is vital for assessing regional and global carbon footprints. Currently, the industry's demand for accurate and refined management of carbon emission data continues to rise. However, existing accounting methods are primarily manual, with low levels of informatization. They employ a combination of decentralized data collection and manual statistics, lacking a unified data integration platform and dynamic analysis models, resulting in issues such as data lag, error accumulation, and limited analytical dimensions. Furthermore, existing technologies cannot track energy consumption flows across self-operated and outsourced business processes, lack standardized mechanisms for importing K-values, carbon sinks, and emission parameters, and lack interannual / monthly / day-scale trend analysis and visualization functions for process energy consumption distribution. This makes it difficult for enterprises to accurately identify high-energy-consuming / high-emission processes and make in-depth decisions, necessitating the development of a scientific and efficient accounting system. Summary of the Invention

[0003] This disclosure provides a method and apparatus for carbon emission accounting in open-pit coal mines, as well as electronic equipment and storage media. Its main objective is to at least partially address one of the technical problems in related technologies.

[0004] According to a first aspect of this disclosure, a method for carbon emission accounting in open-pit coal mines is provided, comprising:

[0005] Receive user input for setting the time range; Based on the time range setting command, collect and integrate multi-source energy consumption data, carbon emission-related parameters and carbon sink data of the mining area; Based on the multi-source energy consumption data, carbon emission-related parameters, and carbon sink data, the energy consumption and carbon emission indicators for each production stage within the selected time period are dynamically calculated. Generate and display visual charts to characterize energy consumption and carbon emission distribution; Based on different time scales, we construct and demonstrate the changing trends of energy consumption and carbon emissions.

[0006] Optionally, the collection and integration of multi-source energy consumption data, carbon emission-related parameters, and carbon sink data in the mining area includes: Receive energy consumption conversion parameter data uploaded by users, which is used to convert the consumption of electricity, diesel and explosives into standard energy consumption and carbon emissions; Receive carbon sequestration data uploaded by users, including carbon sequestration by vegetation in mining areas and carbon sequestration by ecological restoration projects.

[0007] Optionally, the dynamic calculation of energy consumption and carbon emission indicators for each production stage within the selected time period includes: Receive user instructions on whether to calculate electricity-related emissions and fugitive emissions; Based on the selection instruction, the indirect carbon emissions from electricity consumption and the fugitive emissions from equipment operation are calculated using the corresponding calculation models. Net carbon emissions are calculated based on the difference between total carbon emissions and carbon sinks.

[0008] Optionally, generating and displaying the visualization charts used to characterize energy consumption distribution and carbon emission distribution includes: In response to the user's selection of different display modes, a Sankey diagram is generated and switched to display the corresponding mode; the display modes include a self-operated mode for displaying the energy consumption or carbon emission flow of the self-operated production process in the mining area, an outsourced mode for displaying the energy consumption or carbon emission flow of the outsourced operation process, and an overview mode for displaying the overall energy consumption or carbon emission flow of the process. Based on user selection or preset rules, generate and display bar charts and pie charts to represent data in different dimensions.

[0009] Optionally, the model for constructing and demonstrating the changing trends of energy consumption and carbon emissions includes: The annual trend is presented in a composite chart format, with a bar chart representing the total energy consumption or carbon emissions and a line chart representing the change in energy consumption or carbon emissions per unit product. Generate and display a process flow diagram containing multiple process steps, and display the real-time energy consumption data and carbon emission data of the corresponding steps in the flow diagram.

[0010] Optional, also includes: Based on the selected time range, generate structured energy consumption reports and carbon emission reports, and convert the energy consumption reports and carbon emission reports into document formats that can be stored and distributed offline.

[0011] According to a second aspect of this disclosure, an open-pit coal mine carbon emission accounting device is provided, comprising: The receiving unit is used to receive the user's input instruction for setting the time range; The data acquisition unit is used to collect and integrate multi-source energy consumption data, carbon emission-related parameters, and carbon sink data of the mining area based on the time range setting instructions. The calculation unit is used to dynamically calculate the energy consumption index and carbon emission index of each production link in the selected time period based on the multi-source energy consumption data, carbon emission related parameters and carbon sink data. The generation unit is used to generate and display visual charts that characterize the distribution of energy consumption and carbon emissions. The building blocks are used to construct and display models of changing trends in energy consumption and carbon emissions based on different time scales.

[0012] Optionally, the acquisition unit is also used for: Receive energy consumption conversion parameter data uploaded by users, which is used to convert the consumption of electricity, diesel and explosives into standard energy consumption and carbon emissions; Receive carbon sequestration data uploaded by users, including carbon sequestration by vegetation in mining areas and carbon sequestration by ecological restoration projects.

[0013] Optionally, the computing unit is also used for: Receive user instructions on whether to calculate electricity-related emissions and fugitive emissions; Based on the selection instruction, the indirect carbon emissions from electricity consumption and the fugitive emissions from equipment operation are calculated using the corresponding calculation models. Net carbon emissions are calculated based on the difference between total carbon emissions and carbon sinks.

[0014] Optionally, the generating unit is also used for: In response to the user's selection of different display modes, a Sankey diagram is generated and switched to display the corresponding mode; the display modes include a self-operated mode for displaying the energy consumption or carbon emission flow of the self-operated production process in the mining area, an outsourced mode for displaying the energy consumption or carbon emission flow of the outsourced operation process, and an overview mode for displaying the overall energy consumption or carbon emission flow of the process. Based on user selection or preset rules, generate and display bar charts and pie charts to represent data in different dimensions.

[0015] Optionally, building blocks are also used for: The annual trend is presented in a composite chart format, with a bar chart representing the total energy consumption or carbon emissions and a line chart representing the change in energy consumption or carbon emissions per unit product. Generate and display a process flow diagram containing multiple process steps, and display the real-time energy consumption data and carbon emission data of the corresponding steps in the flow diagram.

[0016] Optional, also includes: The conversion unit is used to generate structured energy consumption reports and carbon emission reports according to the selected time range, and convert the energy consumption reports and carbon emission reports into document formats that can be stored and distributed offline.

[0017] According to a third aspect of this disclosure, an electronic device is provided, comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect above.

[0018] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are configured to cause the computer to perform the method described in the first aspect above.

[0019] According to a fifth aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0020] The open-pit coal mine carbon emission accounting method, apparatus, electronic equipment, and storage medium disclosed herein receive user-input time range setting instructions, collect and integrate multi-source energy consumption data, carbon emission-related parameters, and carbon sink data of the mining area based on these instructions, dynamically calculate energy consumption and carbon emission indicators for each production stage within the selected time period, generate visual charts representing energy consumption and carbon emission distribution, and construct models to display the changing trends of energy consumption and carbon emissions based on different time scales. Therefore, it can solve the problems of data lag, error accumulation, single analysis dimensions, and lack of multi-time scale trend analysis and visualization of energy consumption and carbon emission distribution caused by the use of a distributed data collection and manual statistics mode, the lack of a unified data integration platform and dynamic analysis model in existing technologies. This achieves the technical effect of accurately integrating, dynamically calculating, intuitively presenting, and tracking multi-dimensional trends of energy consumption and carbon emission data in the mining area, helping to accurately grasp the energy consumption and carbon emission situation and support efficient management decisions.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0022] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein: Figure 1 A schematic flowchart illustrating a carbon emission accounting method for open-pit coal mines provided in this embodiment of the disclosure; Figure 2 This is a schematic diagram of the structure of an open-pit coal mine carbon emission accounting device provided in an embodiment of the present disclosure; Figure 3 A schematic block diagram of an example electronic device provided for embodiments of this disclosure. Detailed Implementation

[0023] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0024] The following description, with reference to the accompanying drawings, outlines an embodiment of the carbon emission accounting method and apparatus for open-pit coal mines, as well as electronic equipment and storage media.

[0025] Figure 1 This is a schematic flowchart illustrating a carbon emission accounting method for open-pit coal mines provided in an embodiment of this disclosure.

[0026] like Figure 1 As shown, the method includes the following steps: Step 101: Receive the user's input instruction for setting the time range.

[0027] In the embodiments of this disclosure, to achieve targeted accounting and analysis of energy consumption and carbon emissions in mining areas, this technical solution first configures a time period setting and receiving function. This function is used to receive user-inputted time range setting instructions (i.e., the target time period instructions for calculating and analyzing energy consumption and carbon emission indicators specified by the user based on accounting needs). The time range can be flexibly defined by the user based on actual management, statistical, or decision-making needs, and its time scale is not specifically limited, adapting to accounting requirements in different scenarios. As one implementation method, the user can input the setting instruction through the time selection interaction component configured in the system, realizing the autonomous setting of the start and end times of the target accounting period, including supporting the specification of ranges across continuous or non-continuous time periods.

[0028] Existing technologies suffer from fixed accounting periods and lack of flexibility. The embodiments disclosed in this disclosure can achieve precise adaptation of accounting periods to actual user needs, providing a precise range basis for subsequent data collection, indicator calculation and trend analysis based on specific time periods, thereby improving the pertinence and flexibility of energy consumption and carbon emission accounting.

[0029] Step 102: Based on the time range setting instruction, collect and integrate multi-source energy consumption data, carbon emission-related parameters, and carbon sink data of the mining area.

[0030] In the embodiments of this disclosure, after receiving a user-defined time range instruction, this technical solution initiates a targeted data collection and integration mechanism. Based on the time period specified by the instruction, it selectively collects multi-source energy consumption data (i.e., data related to various energy consumption generated in each production and operation phase of the mine), carbon emission-related parameters (i.e., various benchmark parameters and calculation parameters supporting carbon emission accounting), and carbon sink data (i.e., carbon absorption-related data used to calculate net carbon emissions). The collected data is then uniformly aggregated, standardized, and integrated to eliminate the impact of data format differences and source dispersion, forming a data foundation suitable for subsequent accounting and analysis. As one implementation method, data collection can be achieved through interaction between the system and various data collection nodes in the mine or through user-initiated import. During the integration process, the integrity and validity of the data can be verified to ensure the reliability of the integrated data.

[0031] Existing technologies suffer from problems such as scattered data collection, lack of targeted matching and unified integration with the target time period. The embodiments disclosed in this disclosure can achieve precise time-based collection and standardized integration of multi-source data, providing comprehensive, reliable and target-time-appropriate data support for subsequent dynamic calculation of energy consumption and carbon emission indicators, thereby improving data utilization efficiency.

[0032] Step 103: Based on the multi-source energy consumption data, carbon emission-related parameters, and carbon sink data, dynamically calculate the energy consumption and carbon emission indicators for each production stage within the selected time period.

[0033] In the embodiments of this disclosure, based on the aforementioned integrated multi-source energy consumption data, carbon emission-related parameters, and carbon sink data, this technical solution employs a dynamic calculation mechanism adapted to data characteristics. Using the selected time period as the calculation dimension, it performs systematic indicator calculations for each production stage in the mining area, ultimately dynamically generating energy consumption indicators (i.e., various quantitative parameters characterizing the energy consumption level of each stage) and carbon emission indicators (i.e., various quantitative parameters reflecting the scale, intensity, and net emissions of carbon emissions in each stage) corresponding to each production stage within that time period. During the calculation process, by establishing a corresponding correlation logic between data and indicators, the consistency of the indicator calculation results with the selected time period, each production stage, and the basic data is ensured. As one implementation method, the calculation process can combine the matching relationship between energy consumption data and carbon emission-related parameters, incorporating the correction logic of carbon sink data for carbon emission indicators, to achieve accurate calculation of the two types of indicators for each stage.

[0034] Step 104: Generate and display a visualization chart to characterize the distribution of energy consumption and carbon emissions.

[0035] In the embodiments of this disclosure, based on the energy consumption and carbon emission indicators of each production stage obtained through the aforementioned dynamic calculation, this technical solution adopts a visualization presentation mechanism adapted to the needs of distribution characteristic representation, generating a visual chart that can intuitively reflect the distribution of energy consumption and carbon emissions in the mining area. This chart is presented to the user through a preset display interface. The chart can specifically reflect the core distribution characteristics of each production stage in terms of energy consumption and carbon emissions, such as their proportion and flow direction. Its presentation format is not specifically limited, adapting to the distribution cognition and analysis needs in different scenarios. As one implementation method, the visualization chart may include pie charts, Sankey diagrams, etc., respectively used to clearly display the composition proportion and flow relationship of energy consumption and carbon emissions in each stage.

[0036] The existing technologies address the problem that energy consumption and carbon emission distribution information is difficult to perceive intuitively and that the core distribution characteristics are unclear. By visualizing and clearly presenting the distribution information, users can quickly and accurately grasp the distribution patterns of energy consumption and carbon emissions, providing intuitive data support for identifying key links and formulating optimization strategies.

[0037] Step 105: Construct and display models of changing trends in energy consumption and carbon emissions based on different time scales.

[0038] In the embodiments of this disclosure, based on the aforementioned dynamically calculated energy consumption and carbon emission indicators, this technical solution constructs a trend model that characterizes the evolution of energy consumption and carbon emissions in mining areas, using different time scales as analytical dimensions. This model is presented to users through an appropriate display method. The time scale can be flexibly selected according to actual analytical needs. The model can systematically reflect the core change characteristics of energy consumption and carbon emissions at different scales, such as fluctuations and increases / decreases, providing intuitive model support for trend analysis. As one implementation method, the time scale may include common dimensions such as year, month, and day. The trend model can be constructed using a combination of bar charts and line charts to clearly present the changing trends of energy consumption and carbon emissions at each time scale.

[0039] Existing technologies lack multi-timescale trend analysis and struggle to systematically grasp the patterns of energy consumption and carbon emission changes. Visual modeling and presentation of energy consumption and carbon emission change trends at different time scales help users fully understand the dynamics of change and provide a reliable basis for comparing historical data and predicting future trends.

[0040] The open-pit coal mine carbon emission accounting method disclosed herein receives user-input time range setting instructions, collects and integrates multi-source energy consumption data, carbon emission-related parameters, and carbon sink data of the mining area based on these instructions, dynamically calculates energy consumption and carbon emission indicators for each production stage within the selected time period, generates visual charts representing energy consumption and carbon emission distribution, and constructs models to display the changing trends of energy consumption and carbon emissions based on different time scales. Therefore, it can solve the problems of data lag, error accumulation, single analysis dimensions, and lack of multi-time scale trend analysis and visualization of energy consumption and carbon emission distribution caused by the use of a combination of decentralized data collection and manual statistics, the lack of a unified data integration platform and dynamic analysis model in existing technologies. This achieves the technical effect of accurately integrating, dynamically calculating, intuitively presenting, and tracking multi-dimensional trends of energy consumption and carbon emission data in the mining area, helping to accurately grasp the energy consumption and carbon emission situation and support efficient management decisions.

[0041] As a specific implementation of this disclosure, based on the basic scheme, the collection and integration of multi-source energy consumption data, carbon emission-related parameters, and carbon sink data in the mining area are further defined as follows: receiving energy consumption conversion parameter data uploaded by users, wherein the energy consumption conversion parameter data is used to convert the consumption of electricity, diesel, and explosives into standard energy consumption and carbon emissions; and receiving carbon sink data uploaded by users, wherein the carbon sink data includes the carbon sequestration amount of vegetation in the mining area and the carbon sequestration amount of ecological restoration projects.

[0042] Specifically, in the data collection and integration process of the basic solution, the system is configured with a dedicated data receiving module. This module has the data interaction capability to adapt to user upload operations and is used to accurately receive energy consumption conversion parameter data uploaded by users (i.e., quantitative coefficient data used to establish the correspondence between energy consumption and standard energy consumption and carbon emissions). This data is set separately for the three core energy consumption types of electricity, diesel, and explosives. Each type of energy corresponds to a unique standardized conversion coefficient, which can be directly used to convert the actual consumption into the standard energy consumption value of a unified measurement standard, and further derive the corresponding carbon emissions. At the same time, the data receiving module synchronously receives carbon sink data uploaded by users. The carbon sink data specifically includes the carbon sequestration data of vegetation formed by natural vegetation in the mining area through photosynthesis, and the carbon sequestration data of engineering projects (such as greening reconstruction, soil improvement and supporting vegetation planting) implemented in the mining area. Both types of carbon sequestration data are accompanied by collection timestamps and regional identification information to ensure accurate correlation with the target accounting period and mining area.

[0043] By clarifying the core data types and sources of energy consumption conversion and carbon sink accounting, the consistency and accuracy of the basis for calculating standard energy consumption, carbon emissions, and net carbon emissions are ensured, effectively avoiding accounting deviations caused by unclear or missing data types, and further improving the reliability of energy consumption and carbon emission index accounting results.

[0044] As a specific implementation of this disclosure, based on the basic scheme, the dynamic calculation of energy consumption indicators and carbon emission indicators of each production link within the selected time period is further defined, including: receiving a user's selection instruction on whether to calculate electricity-related emissions and fugitive emissions; calculating the indirect carbon emissions generated by electricity consumption and the fugitive emissions generated by equipment operation using the corresponding calculation model according to the selection instruction; and calculating the net carbon emissions based on the difference between the total carbon emissions and the carbon sink.

[0045] Specifically, in the dynamic calculation process of the basic solution, the system has a preset instruction receiving unit. This unit is used to accurately receive the user's binary selection instruction regarding whether to calculate electricity-related emissions (i.e., indirect carbon emissions from electricity consumption) and fugitive emissions (i.e., emissions from fugitive leaks during equipment operation). The instruction is transmitted to the calculation module in a standardized signal form. The calculation module has two built-in specialized calculation models. When it receives the instruction to calculate electricity-related emissions, it calls the electricity indirect carbon emission calculation model, combines the integrated electricity consumption data and energy conversion parameters, and derives the indirect carbon emission calculation result through a quantitative conversion formula. Emissions; When a command to calculate fugitive emissions is received, the fugitive emission calculation model is started. Based on the equipment running time, operating parameters, and preset fugitive emission factors, the corresponding fugitive carbon emissions are calculated. Subsequently, the system first summarizes the direct carbon emissions of each production link in the selected time period, the calculated indirect carbon emissions (if any), and the fugitive carbon emissions (if any) to obtain the total carbon emissions. Then, the difference calculation logic is called to subtract the total carbon sequestration corresponding to the integrated carbon sink data from the total carbon emissions. Finally, the net carbon emissions of each production link in the selected time period are obtained, which together with energy consumption indicators and other carbon emission indicators constitute a complete accounting result.

[0046] By providing flexible emission calculation options and specialized calculation models, it adapts to the emission statistics needs under different accounting scenarios, ensuring the comprehensiveness and flexibility of carbon emission index calculation. At the same time, through a clear net carbon emission calculation logic, it accurately reflects the actual carbon income and expenditure of the mining area, further enhancing the practicality and reference value of the accounting results.

[0047] As a specific implementation of this disclosure, based on the basic scheme, the generation and display of visualization charts for characterizing energy consumption distribution and carbon emission distribution are further defined, including: generating and switching Sankey diagrams in the corresponding display modes in response to the user's selection of different display modes; the display modes include a self-operated mode for displaying the energy consumption or carbon emission flow of the mining area's self-operated production process, an outsourced mode for displaying the energy consumption or carbon emission flow of the outsourced operation process, and an overview mode for displaying the overall energy consumption or carbon emission flow of the process; and generating and displaying bar charts and pie charts for characterizing data of different dimensions according to user selection or preset rules.

[0048] Specifically, the system is configured with a display mode selection response unit and a multi-type chart generation module. The display mode selection response unit monitors and receives the user's input display mode selection command in real time. This command triggers the chart generation module to start the Sankey diagram generation and switching logic: When the user selects the self-operated mode, the module extracts the energy consumption or carbon emission flow data corresponding to the self-operated production links in the mining area and generates a Sankey diagram that only represents the flow relationship and proportion of such links; when the user switches to the outsourced mode, the energy consumption or carbon emission flow data of the outsourced operation links are retrieved simultaneously, a Sankey diagram adapted to this mode is generated, and the current display content is replaced; when the user selects the overview mode, the energy consumption or carbon emission flow data of all production and operation links in the mining area are integrated to generate a Sankey diagram that reflects the overall flow distribution. Meanwhile, the chart generation module has built-in logic for generating bar charts and pie charts. It can extract energy consumption or carbon emission data of the corresponding dimensions based on the chart type selection command initiated by the user or the data analysis dimension rules preset by the system (such as automatically matching pie charts by the proportion of each link and automatically matching bar charts by the total amount of each time period), generate bar charts or pie charts that can represent the characteristics of data proportion, total amount, etc., and present them to the user through the preset display interface.

[0049] By flexibly switching between multiple modes of Sankey diagrams, the system meets users' differentiated analysis needs for self-operated, outsourced, and overall process flow. Combined with the targeted generation of bar charts and pie charts, it achieves an intuitive presentation of data distribution across different dimensions. This not only improves the efficiency of interpreting energy consumption and carbon emission distribution information but also provides diversified data visualization support for accurately locating key distribution links.

[0050] As a specific implementation of this disclosure, based on the basic scheme, the construction and display of the energy consumption and carbon emission change trend model is further defined as follows: displaying the interannual change trend in the form of a composite chart, wherein a bar chart is used to represent the total energy consumption or carbon emission, and a line chart is used to represent the change in energy consumption or carbon emission per unit product; generating and displaying a process flow chart containing multiple process steps, and displaying the real-time energy consumption data and carbon emission data of the corresponding steps in the flow chart.

[0051] Specifically, the system is configured with a trend model building module. This module has built-in composite chart generation logic and a process flow diagram generation unit. To meet the needs of displaying interannual trends, it first extracts the total energy consumption or carbon emissions data and the unit product energy consumption or unit product carbon emissions data for each year within the selected time range. The composite chart generation logic then merges these two types of data: a bar chart accurately represents the quantitative value of the total energy consumption or carbon emissions for each year based on its height dimension, while a line chart intuitively reflects the interannual fluctuations in unit product energy consumption or unit product carbon emissions. Both types of charts share a time axis coordinate, forming a synchronously related interannual trend composite chart. Simultaneously, the process flow diagram generation unit pre-stores the logical relationships between various production processes in the mining area. Based on these relationships, it generates a standardized process flow diagram including multiple processes such as coal mining and stripping. This unit establishes a communication connection with the real-time data interaction module, continuously retrieving real-time energy consumption and carbon emission data for each process process and displaying them as numerical labels at preset positions in the corresponding process flow diagram, achieving dynamic synchronization between the chart and real-time data.

[0052] The composite charts enable the synchronous visualization of the annual changes in total quantity and unit indicators, facilitating the rapid clarification of the correlation between the two. Combined with the process flow diagram with real-time data, the dynamics of energy consumption and carbon emissions in each process step are presented intuitively, which not only enhances the depth of trend analysis but also provides a clear basis for real-time monitoring of process steps.

[0053] As a specific implementation of this disclosure, based on the basic solution, the embodiments of this disclosure further include: generating structured energy consumption reports and carbon emission reports according to the selected time range, and converting the energy consumption reports and carbon emission reports into document formats that can be stored and distributed offline.

[0054] Specifically, the system adds a report generation module and a format conversion unit. The report generation module is pre-configured with structured report templates, which contain core data fields related to energy consumption and carbon emissions (such as total energy consumption, total carbon emissions, unit product indicators, and breakdown data of each production stage within the selected time range). Based on the user-defined time range, the module accurately extracts the corresponding field data from the integrated multi-source data and dynamically calculated indicator results, fills in the template logic, and generates standardized energy consumption and carbon emission reports. The format conversion unit has built-in conversion protocols for various common document formats (such as PDF and Excel). After receiving the structured report output by the report generation module, it automatically calls the corresponding conversion protocol to convert the report into a document format that supports offline storage, transmission, and distribution. After the conversion is completed, it provides the user with a document download entry and also supports local system caching and backup.

[0055] By generating structured reports, the system achieves systematic organization and standardized presentation of energy consumption and carbon emission data. Combined with document format conversion functions that can be stored and distributed offline, it meets the diverse needs of data archiving, cross-departmental collaborative transmission, and offline review, further enhancing the flexibility and practicality of data use.

[0056] It should be noted that the embodiments of this disclosure may include multiple steps. For ease of description, these steps are numbered, but these numbers are not a limitation on the execution time slots or execution order between the steps; these steps can be implemented in any order, and the embodiments of this disclosure do not limit this.

[0057] Corresponding to the above-described carbon emission accounting method for open-pit coal mines, this disclosure also proposes a carbon emission accounting device for open-pit coal mines. Since the device embodiments of this disclosure correspond to the method embodiments described above, details not disclosed in the device embodiments can be referred to the method embodiments described above, and will not be repeated here.

[0058] Figure 2 This is a schematic diagram of the structure of an open-pit coal mine carbon emission accounting device provided in an embodiment of the present disclosure, as shown below. Figure 2 As shown, it includes: The receiving unit 21 is used to receive the user's input time range setting instruction; The acquisition unit 22 is used to acquire and integrate multi-source energy consumption data, carbon emission-related parameters and carbon sink data of the mining area based on the time range setting instructions; The calculation unit 23 is used to dynamically calculate the energy consumption index and carbon emission index of each production link in the selected time period based on the multi-source energy consumption data, carbon emission related parameters and carbon sink data. The generation unit 24 is used to generate and display visual charts that characterize the distribution of energy consumption and carbon emissions. Building unit 25 is used to build and display models of changing trends in energy consumption and carbon emissions based on different time scales.

[0059] The open-pit coal mine carbon emission accounting device disclosed herein receives user-input time range setting instructions, collects and integrates multi-source energy consumption data, carbon emission-related parameters, and carbon sink data of the mining area based on these instructions, dynamically calculates energy consumption and carbon emission indicators for each production stage within the selected time period, generates visual charts representing energy consumption and carbon emission distribution, and constructs models to display the changing trends of energy consumption and carbon emissions based on different time scales. Therefore, it can solve the problems of data lag, error accumulation, single analysis dimensions, and lack of multi-time scale trend analysis and visualization of energy consumption and carbon emission distribution caused by the use of a combination of decentralized data collection and manual statistics, the lack of a unified data integration platform and dynamic analysis model in existing technologies. This achieves the technical effect of accurately integrating, dynamically calculating, intuitively presenting, and tracking multi-dimensional trends of energy consumption and carbon emission data in the mining area, helping to accurately grasp the energy consumption and carbon emission situation and support efficient management decisions.

[0060] Furthermore, in one possible implementation of this embodiment, the acquisition unit 22 is also used for: Receive energy consumption conversion parameter data uploaded by users, which is used to convert the consumption of electricity, diesel and explosives into standard energy consumption and carbon emissions; Receive carbon sequestration data uploaded by users, including carbon sequestration by vegetation in mining areas and carbon sequestration by ecological restoration projects.

[0061] Furthermore, in one possible implementation of this embodiment, the computing unit 23 is also used for: Receive user instructions on whether to calculate electricity-related emissions and fugitive emissions; Based on the selection instruction, the indirect carbon emissions from electricity consumption and the fugitive emissions from equipment operation are calculated using the corresponding calculation models. Net carbon emissions are calculated based on the difference between total carbon emissions and carbon sinks.

[0062] Furthermore, in one possible implementation of this embodiment, the generation unit 24 is also used for: In response to the user's selection of different display modes, a Sankey diagram is generated and switched to display the corresponding mode; the display modes include a self-operated mode for displaying the energy consumption or carbon emission flow of the self-operated production process in the mining area, an outsourced mode for displaying the energy consumption or carbon emission flow of the outsourced operation process, and an overview mode for displaying the overall energy consumption or carbon emission flow of the process. Based on user selection or preset rules, generate and display bar charts and pie charts to represent data in different dimensions.

[0063] Furthermore, in one possible implementation of this embodiment, the construction unit 25 is also used for: The annual trend is presented in a composite chart format, with a bar chart representing the total energy consumption or carbon emissions and a line chart representing the change in energy consumption or carbon emissions per unit product. Generate and display a process flow diagram containing multiple process steps, and display the real-time energy consumption data and carbon emission data of the corresponding steps in the flow diagram.

[0064] Furthermore, in one possible implementation of this embodiment, such as Figure 2 As shown, it also includes: The conversion unit 26 is used to generate structured energy consumption reports and carbon emission reports according to the selected time range, and convert the energy consumption reports and carbon emission reports into document formats that can be stored and distributed offline.

[0065] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of this embodiment, and the principle is the same, so it is not limited in this embodiment.

[0066] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0067] Figure 3 A schematic block diagram of an example electronic device 300 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0068] like Figure 3 As shown, the electronic device 300 includes a computing unit 301, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 302 or a computer program loaded from storage unit 308 into RAM (Random Access Memory) 303. The RAM 303 may also store various programs and data required for the operation of the electronic device 300. The computing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An I / O (Input / Output) interface 305 is also connected to the bus 304.

[0069] Multiple components in electronic device 300 are connected to I / O interface 305, including: input unit 306, such as keyboard, mouse, etc.; output unit 307, such as various types of displays, speakers, etc.; storage unit 308, such as disk, optical disk, etc.; and communication unit 309, such as network card, modem, wireless transceiver, etc. Communication unit 309 allows electronic device 300 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0070] The computing unit 301 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processors, controllers, microcontrollers, etc. The computing unit 301 performs the various methods and processes described above, such as the open-pit coal mine carbon emission accounting method. For example, in some embodiments, the open-pit coal mine carbon emission accounting method can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 300 via ROM 302 and / or communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, one or more steps of the methods described above can be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform the aforementioned open-pit coal mine carbon emission accounting method by any other suitable means (e.g., by means of firmware).

[0071] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0072] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0073] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0074] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0075] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0076] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0077] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0078] The various numerical designations such as "first," "second," etc., used in this disclosure are merely for ease of description and are not intended to limit the scope of the embodiments of this disclosure, nor do they indicate a sequential order.

[0079] At least one of the features described in this disclosure can also be described as one or more, and multiple features can be two, three, four or more, and this disclosure does not impose any limitations. In the embodiments of this disclosure, for a technical feature, the technical features in that technical feature are distinguished by "first", "second", "third", "A", "B", "C" and "D", etc., and there is no sequential order or size order among the technical features described by "first", "second", "third", "A", "B", "C" and "D".

[0080] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0081] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for carbon emission accounting in open-pit coal mines, characterized in that, include: Receive user input for setting the time range; Based on the time range setting command, collect and integrate multi-source energy consumption data, carbon emission-related parameters and carbon sink data of the mining area; Based on the multi-source energy consumption data, carbon emission-related parameters, and carbon sink data, the energy consumption and carbon emission indicators for each production stage within the selected time period are dynamically calculated. Generate and display visual charts to characterize energy consumption and carbon emission distribution; Based on different time scales, we construct and demonstrate the changing trends of energy consumption and carbon emissions.

2. The method according to claim 1, characterized in that, The collection and integration of multi-source energy consumption data, carbon emission-related parameters, and carbon sink data in the mining area includes: Receive energy consumption conversion parameter data uploaded by users, which is used to convert the consumption of electricity, diesel and explosives into standard energy consumption and carbon emissions; Receive carbon sequestration data uploaded by users, including carbon sequestration by vegetation in mining areas and carbon sequestration by ecological restoration projects.

3. The method according to claim 1, characterized in that, The dynamic calculation yields energy consumption and carbon emission indicators for each production stage within the selected time period, including: Receive user instructions on whether to calculate electricity-related emissions and fugitive emissions; Based on the selection instruction, the indirect carbon emissions from electricity consumption and the fugitive emissions from equipment operation are calculated using the corresponding calculation models. Net carbon emissions are calculated based on the difference between total carbon emissions and carbon sinks.

4. The method according to claim 1, characterized in that, The generation and display of visual charts characterizing energy consumption and carbon emission distributions includes: In response to the user's selection of different display modes, a Sankey diagram is generated and switched to display the corresponding mode; the display modes include a self-operated mode for displaying the energy consumption or carbon emission flow of the self-operated production process in the mining area, an outsourced mode for displaying the energy consumption or carbon emission flow of the outsourced operation process, and an overview mode for displaying the overall energy consumption or carbon emission flow of the process. Based on user selection or preset rules, generate and display bar charts and pie charts to represent data in different dimensions.

5. The method according to claim 1, characterized in that, The model that constructs and displays the changing trends of energy consumption and carbon emissions includes: The annual trend is presented in a composite chart format, with a bar chart representing the total energy consumption or carbon emissions and a line chart representing the change in energy consumption or carbon emissions per unit product. Generate and display a process flow diagram containing multiple process steps, and display the real-time energy consumption data and carbon emission data of the corresponding steps in the flow diagram.

6. The method according to claim 1, characterized in that, Also includes: Based on the selected time range, generate structured energy consumption reports and carbon emission reports, and convert the energy consumption reports and carbon emission reports into document formats that can be stored and distributed offline.

7. A carbon emission accounting device for open-pit coal mines, characterized in that, include: The receiving unit is used to receive the user's input instruction for setting the time range; The data acquisition unit is used to collect and integrate multi-source energy consumption data, carbon emission-related parameters, and carbon sink data of the mining area based on the time range setting instructions. The calculation unit is used to dynamically calculate the energy consumption index and carbon emission index of each production link in the selected time period based on the multi-source energy consumption data, carbon emission related parameters and carbon sink data. The generation unit is used to generate and display visual charts that characterize the distribution of energy consumption and carbon emissions. The building blocks are used to construct and display models of changing trends in energy consumption and carbon emissions based on different time scales.

8. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1-6.

Images