Method and device for calculating carbon emission and electronic equipment

Abstract

The application discloses a carbon emission calculation method and device and electronic equipment. The method comprises the following steps: obtaining a process production route in a process design system, wherein each process production route comprises a plurality of production links; collecting energy data corresponding to a production dimension in the process production route, wherein the energy data comprises at least one of energy consumption data and output data; determining a carbon emission calculation model corresponding to the process production route according to the energy data; and determining the carbon emission according to the carbon emission calculation model. The application solves the technical problem that the prior art cannot accurately count carbon emission data of each link by manually collecting carbon emission, and there is a large error in the calculation of carbon emission.

Description

Technical Field

[0001] This application relates to the field of computer technology, and more specifically, to a method, apparatus, and electronic device for calculating carbon emissions. Background Technology

[0002] The rapid development of the internet is quickly changing the way we live and work. Discrete manufacturing enterprises have always adhered to creating value for customers, putting the interests of the country and customers first. While providing customers with better products and more comprehensive services, they are also responding to the national call for energy conservation and emission reduction. They make accurate calculations of carbon emissions in the production process and can identify potential emission reduction links and methods by analyzing carbon emission data at each stage, helping enterprises gain a greater competitive advantage.

[0003] Currently, traditional discrete manufacturing enterprises, while focusing on improving quality and output, also emphasize the construction of information technology, building MES based on IoT, SCADA, and cloud technologies. This improves production efficiency and allows them to use production data to refine management systems. However, this production data lacks in-depth application; for example, the calculation of carbon emissions is not being utilized. Given the national call for energy conservation and emission reduction, timely and real-time carbon emission data collection is crucial for enhancing a company's competitive advantage. Furthermore, carbon emissions are also a measure of energy consumption, which helps companies analyze the output or energy efficiency of energy-intensive equipment and production lines, enabling upgrades and improvements in production efficiency, energy conservation, and emission reduction.

[0004] In the past, carbon emissions were collected manually, making it impossible to accurately count the energy consumption of production equipment, raw materials, product transportation, office areas, and living areas at each stage. Or the data collected contained significant errors. Furthermore, quantitative analysis using the "emission factor method" and "off-site measurement" yielded even more erroneous data. As a result, companies may invest more resources to create false energy conservation and emission reduction.

[0005] There is currently no effective solution to the above problems. Summary of the Invention

[0006] This application provides a method, apparatus, and electronic device for calculating carbon emissions, which at least solves the technical problem that existing technologies, which rely on manual carbon emission collection, cannot accurately collect carbon emission data at each stage, resulting in significant errors in the calculation of carbon emissions.

[0007] According to one aspect of the embodiments of this application, a method for calculating carbon emissions is provided, comprising: acquiring a process production route in a process design system, wherein each process production route includes multiple production stages; collecting energy data corresponding to the production dimension in the process production route, wherein the energy data includes at least one of the following: energy consumption data and output data; determining a carbon emission calculation model corresponding to the process production route based on the energy data; and determining the carbon emission amount based on the carbon emission calculation model.

[0008] Optionally, the process production route is determined by: in response to the selection instruction of the target object, determining the target production device, wherein the number of target production devices is one or more; if the number of target production devices is multiple, determining the execution order of the multiple target production devices; determining the process production route based on the execution order, and determining the attribute information of the process production route.

[0009] Optionally, collecting energy data corresponding to the production dimension in the process production route includes: determining the production dimension of the energy data, wherein the production dimension is the production dimension corresponding to the production plan; determining the collection frequency of energy data based on the production dimension; and collecting energy data based on the collection frequency, wherein the energy data includes at least one of the following: actual production energy consumption data, external energy consumption data of production equipment, and office energy consumption data.

[0010] Optionally, determining the carbon emission calculation model corresponding to the process production route based on energy data includes: determining the data collection scenario for the carbon emission calculation model, wherein the data collection scenario includes instantaneous data collection and cumulative data collection; when the data collection scenario for the carbon emission calculation model is instantaneous data collection, obtaining the first data collection value corresponding to the current production unit at the end of the data collection, wherein the current production unit is used to generate energy data; determining the carbon emission calculation model corresponding to the instantaneous data collection scenario based on the first data collection value and the model correction coefficient; when the data collection scenario for the carbon emission calculation model is cumulative data collection, obtaining the second data collection value corresponding to the current production unit at the start of the data collection; and determining the carbon emission calculation model corresponding to the cumulative data collection scenario based on the first data collection value, the second data collection value, and the model correction coefficient.

[0011] Optionally, the model correction coefficients are determined by: determining the attribute information of the energy data, wherein the attribute information includes at least one of the following: the reliability of the energy data, the accuracy of the energy data, and the nature of the energy data; and determining the model correction coefficients based on the attribute information and the data type of the energy data.

[0012] Optionally, carbon emissions are determined based on a carbon emission calculation model, including: determining an energy factor, wherein the energy factor is a baseline factor determined in accordance with energy regulations; and determining carbon emissions based on the energy factor, the carbon emission calculation model, and model correction coefficients.

[0013] Optionally, after determining the carbon emissions based on the carbon emission calculation model, the method further includes: storing the carbon emissions in a database, wherein the types of carbon emissions include at least one of the following: carbon emissions from raw materials and auxiliary materials, carbon emissions from the production process, and carbon emissions from transportation and delivery; removing abnormal measurement data from the carbon emissions to obtain the target carbon emissions; and classifying the target carbon emissions according to their types.

[0014] According to another aspect of the embodiments of this application, a carbon emission calculation device is also provided, comprising: an acquisition module for acquiring a process production route in a process design system, wherein each process production route includes multiple production stages; a collection module for collecting energy data corresponding to the production dimension in the process production route, wherein the energy data includes at least one of the following: energy consumption data and output data; a first determination module for determining a carbon emission calculation model corresponding to the process production route based on the energy data; and a second determination module for determining the carbon emission amount based on the carbon emission calculation model.

[0015] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a memory for storing program instructions; and a processor connected to the memory for executing program instructions to perform the following functions: acquiring a process production route in a process design system, wherein each process production route includes multiple production stages; collecting energy data corresponding to the production dimension in the process production route, wherein the energy data includes at least one of the following: energy consumption data and output data; determining a carbon emission calculation model corresponding to the process production route based on the energy data; and determining the carbon emission amount based on the carbon emission calculation model.

[0016] According to another aspect of the embodiments of this application, a non-volatile storage medium is also provided, the non-volatile storage medium including a stored computer program, wherein the device on which the non-volatile storage medium is located executes the above-mentioned carbon emission calculation method by running the computer program.

[0017] In this embodiment, by acquiring the process production route in the process design system, wherein each process production route includes multiple production stages; collecting energy data corresponding to the production dimension in the process production route, wherein the energy data includes at least one of the following: energy consumption data and output data; determining the carbon emission calculation model corresponding to the process production route based on the energy data; and determining the carbon emission amount based on the carbon emission calculation model, the purpose of calculating the carbon emission amount based on the energy data in multiple production stages in the process production route is achieved. This realizes the technical effect of calculating the carbon emission amount in multiple production stages in the process production route based on the carbon emission calculation model, thereby solving the technical problem that the existing technology, which collects carbon emissions manually, cannot accurately count the carbon emission data of each stage, resulting in large errors in the calculation of carbon emissions. Attached Figure Description

[0018] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0019] Figure 1 This is a hardware structure block diagram of a computer terminal (or electronic device) for implementing a method for calculating carbon emissions according to an embodiment of this application;

[0020] Figure 2 This is a flowchart of a method for calculating carbon emissions according to an embodiment of this application;

[0021] Figure 3 This is a schematic diagram of the overall architecture of a carbon emission calculation scheme according to an embodiment of this application;

[0022] Figure 4 This is a structural diagram of a carbon emission calculation device according to an embodiment of this application. Detailed Implementation

[0023] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] The carbon emission calculation method provided in this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 A hardware block diagram of a computer terminal (or electronic device) for implementing a method to calculate carbon emissions is shown. Figure 1 As shown, the computer terminal 10 (or electronic device 10) may include one or more processors (shown as 102a, 102b, ..., 102n in the figure) (the processor may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 104 for storing data, and a transmission module 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0026] It should be noted that the aforementioned one or more processors and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be wholly or partially embodied in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuit may be a single, independent processing module, or may be wholly or partially integrated into any other element within the computer terminal 10 (or electronic device). As involved in the embodiments of this application, the data processing circuit serves as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0027] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the carbon emission calculation method in this embodiment. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the aforementioned carbon emission calculation method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0028] The transmission module 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission module 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission module 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0029] The display may be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of the computer terminal 10 (or electronic device).

[0030] It should be noted here that, in some optional embodiments, the above... Figure 1 The computer device (or electronic device) shown may include hardware elements (including circuitry), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware and software elements. It should be noted that... Figure 1 This is only one instance of a particular specific instance, and is intended to illustrate the types of components that may exist in the aforementioned computer equipment (or electronic equipment).

[0031] Under the above operating environment, this application provides an embodiment of a method for calculating carbon emissions. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Also, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0032] Figure 2This is a flowchart of a method for calculating carbon emissions according to an embodiment of this application, such as... Figure 2 As shown, the method includes the following steps:

[0033] Step S202: Obtain the process production route from the process design system, wherein each process production route includes multiple production stages;

[0034] Step S204: Collect energy data corresponding to the production dimension in the process production route, wherein the energy data includes at least one of the following: energy consumption data and output data;

[0035] Step S206: Determine the carbon emission calculation model corresponding to the process production route based on energy data;

[0036] Step S208: Determine the carbon emissions based on the carbon emission calculation model.

[0037] In steps S202 to S208 above, carbon emission calculation is based on a combination of carbon metering and on-site measurement. It utilizes dual optimization based on the accuracy of real-time production data at each stage to improve the accuracy of carbon accounting calculations. Furthermore, it leverages powerful IoT SCADA data acquisition technology to achieve direct data collection from the workshop production line, enhancing the accuracy of production activity data and reducing carbon emission calculation errors. The following is a detailed explanation.

[0038] The carbon emission calculation method provided in this application relies on a customer-shared platform (OTC) for data collection, filtering, calculation, and publishing. The overall technical architecture is as follows: Figure 3 As shown in the diagram. The overall architecture diagram includes the following modules:

[0039] The energy factor collection on the cloud platform side is achieved by automatically or manually collecting industry-published energy factor specifications through Internet cloud technology, and using these energy factors as the benchmark factors for carbon measurement, providing a standard calculation basis for upstream and downstream industries.

[0040] The industry product database on the cloud platform uses Internet cloud technology to automatically or manually collect data on products, semi-finished products, and raw materials of industries and enterprises, which serve as the industry standard UDI (Unique Identifier) ​​to connect the upstream and downstream of the industry.

[0041] In addition, the cloud platform is also used to process purchase orders, sales orders, production orders, etc.

[0042] The IoT-based Supervisory Control and Data Acquisition (SCADA) system on the production activity data side collects as much energy consumption data as possible—including water, electricity, gas, and wind power—as well as separately collected green energy data (solar, wind, etc.)—through the IoT-implemented SCADA technology. It also allows enterprises to manually calculate energy consumption data for each production dimension, categorized by shift, day, week, month, and year. Specifically, the collected data can be production data from the Manufacturing Execution System (MES), management data from the Enterprise Resource Planning (ERP) system, or process data from the Computational Process Planning (CAPP) system, etc.

[0043] Carbon emissions are calculated, analyzed, and carbon footprint determined within the green energy platform. This carbon analysis involves data cleaning, removal of outlier data, and data classification, providing a basis for effective improvements in energy conservation and emission reduction at all stages of the enterprise's operations. The carbon footprint, utilizing calculated carbon emission data combined with production process data and procurement and sales data, accurately describes the carbon emission "footprint" from raw material production and transportation to the final product's production and transportation, presenting customers with a green journey for their desired products in a more concise manner.

[0044] In the above method for calculating carbon emissions, the process production route is determined in the following way: in response to the selection instruction of the target object, the target production unit is determined, wherein the number of target production units is one or more; when the number of target production units is multiple, the execution order of the multiple target production units is determined; the process production route is determined according to the execution order, and the attribute information of the process production route is determined.

[0045] In this embodiment, the process route or production route is a standard or customized process route of the synchronous process design system, or a production process route defined by the enterprise itself. Energy consumption, resource consumption, and output data are recorded at each stage of the process route, laying the foundation for the enterprise's carbon metering and also being the biggest factor affecting the accuracy of carbon metering. Since a single production route may include multiple production units, the selected production units must be determined first when determining the production route. In the case of multiple production units in a single production route, the execution order of the production units also needs to be determined, as well as the attribute information of each production route. This attribute information may include, for example, production route ID, production route description, order quantity, order number, etc.

[0046] In step S204 of the above carbon emission calculation method, energy data corresponding to the production dimension in the process production route is collected, specifically including the following steps: determining the production dimension of the energy data, wherein the production dimension is the production dimension corresponding to the production plan; determining the energy data collection frequency based on the production dimension; collecting energy data based on the collection frequency, wherein the energy data includes at least one of the following: actual production energy consumption data, external energy consumption data of production equipment, and office energy consumption data.

[0047] In this embodiment, the production dimension refers to the production dimension corresponding to production plans under different time dimensions. That is, if the time dimension corresponding to the production plan is calculated on a daily basis, then the corresponding production dimension is also calculated on a daily basis. The aforementioned daily calculation can be replaced by time dimensions such as shift, week, month, and year. Different production dimensions correspond to different data collection frequencies. For example, if statistics are collected on a daily basis, the collection frequency is higher than that corresponding to weekly statistics.

[0048] In step S206 of the aforementioned carbon emission calculation method, determining the carbon emission calculation model corresponding to the process production route based on energy data specifically includes the following steps: determining the data collection scenario for the carbon emission calculation model, wherein the data collection scenario includes instantaneous data collection and cumulative data collection; when the data collection scenario for the carbon emission calculation model is instantaneous data collection, obtaining the first data collection value corresponding to the current production unit at the end of the data collection time, wherein the current production unit is used to generate energy data; determining the carbon emission calculation model corresponding to the instantaneous data collection scenario based on the first data collection value and the model correction coefficient; when the data collection scenario for the carbon emission calculation model is cumulative data collection, obtaining the second data collection value corresponding to the current production unit at the start of the data collection time; determining the carbon emission calculation model corresponding to the cumulative data collection scenario based on the first data collection value, the second data collection value, and the model correction coefficient.

[0049] In this embodiment, data fluctuations and errors are inevitable during the entire energy collection process, and the boundaries between actual production energy consumption, external equipment production energy consumption, and office energy consumption are unclear. This is the biggest factor affecting the accuracy of carbon emission calculations. To minimize the impact of such data, a carbon emission calculation model TV is developed for each process stage based on actual production activities. The energy consumption calculation factors include model correction coefficient a and mapping formula f(), where {TG} is the tag number collection value, and f() is the model correction coefficient a. k Let be the k-th formula in the set of time-dimensional mapping formulas, where st is the start time of formula k (i.e., the start time of the data collection mentioned above), and et is the end time of formula k (i.e., the end time of the data collection mentioned above). The formula corresponding to the carbon emission calculation model is as follows:

[0050]

[0051] Among them, {TG} et {TG} represents the first digit of the data collection end time. st This represents the second digit of the data collection value corresponding to the start time of data collection.

[0052] In the above method for calculating carbon emissions, the model correction coefficients are determined as follows: the attribute information of the energy data is determined, wherein the attribute information includes at least one of the following: the reliability of the energy data, the accuracy of the energy data, and the nature of the energy data; the model correction coefficients are determined based on the attribute information and the data type of the energy data.

[0053] In this embodiment, the model correction coefficient 'a' ranges from 0 to 1. Different coefficients a1, a2, a3...an can be defined based on different types and dimensions. These types can be categorized as external (based on enterprise type) and internal (automatic data collection by the enterprise's instruments, manual data collection by the enterprise's instruments, and manual recording by the enterprise). The data type or dimension of energy data can be classified as data reliability, data accuracy, and the physicochemical properties of energy, etc. Correction coefficients 'a' are defined for each type and dimension of energy data. Furthermore, the correction coefficient 'a' is redefined based on data generated from enterprise production operations and carbon emission calculations, combined with standard data from product libraries in different industries. This is illustrated by the following example:

[0054] A company generates product database data with mean m and maximum deviation r for m1, m2, m3...mn. At the same time, it calculates the mean M and maximum deviation R of product standard database data M1, M2, M3...Mn for different industries. Let t = mM, where t represents the error with the product standard data of different industries. The model correction coefficient a is modified based on the average value of t to minimize the error of t. However, whether to make corrections depends on the company's actual internal production data and is subject to human evaluation. For the tag number acquisition value {TG}, {TG} can be defined in many ways. It can be defined as data from different industry standards on the Internet, with the latest value automatically updated at intervals. It can also be defined as some analytical data from external companies or the company itself, with the latest value being actively pushed when changes occur. It supports using field automated instruments as {TG}, recording the instantaneous or cumulative values ​​of the instruments at high frequencies. At the same time, it can also set energy (water, electricity, gas, wind) data from instruments that do not have automatic acquisition capabilities or manually measured data as {TG}, with the measurement values ​​being updated manually in real time. The obtained data includes the energy carbon emission factor, the energy and raw materials consumed by the company in production, and the correction coefficients 'a' for each category and dimension.

[0055] In step S208 of the above carbon emission calculation method, the carbon emission amount is determined based on the carbon emission calculation model, which specifically includes the following steps: determining the energy factor, wherein the energy factor is a benchmark factor determined in accordance with energy regulations; and determining the carbon emission amount based on the energy factor, the carbon emission calculation model, and the model correction coefficient.

[0056] In this embodiment of the application, each production stage is decomposed according to the process production route. Combined with the production execution data provided by MES, the accurate production operation time and equipment non-production operation time are recorded. The energy consumption data collected in each stage is obtained, and the carbon emission is calculated by "energy factor" × a × TV.

[0057] In step S208 of the above carbon emission calculation method, after determining the carbon emission amount based on the carbon emission calculation model, the method further includes the following steps: storing the carbon emission amount in a database, wherein the type of carbon emission amount includes at least one of the following: carbon emission amount of raw and auxiliary materials, carbon emission amount of production process, and carbon emission amount of transportation and delivery; removing abnormal measurement data from the carbon emission amount to obtain the target carbon emission amount; and classifying the target carbon emission amount according to the type of carbon emission amount.

[0058] In this embodiment, the carbon emissions from raw materials, production processes, and transportation are aggregated into a carbon measurement database for further analysis and verification. Specifically, the obtained carbon emissions are cleaned to remove abnormal data and categorized. Further processing is then performed based on the categorized results.

[0059] The carbon emission calculation method provided in this application can effectively eliminate data collection errors. By combining "emission factors," "on-site measurements," and the real-time accuracy of each stage, it minimizes errors, identifies potential emission reduction points and methods for enterprises, and provides downstream enterprises with complete production line-based carbon emission data, more accurately calculating the carbon emissions generated at each production stage. Furthermore, the above-mentioned carbon emission calculation method has the following advantages: 1. The energy factors used are implemented by the industry, resulting in comprehensive and authoritative data, rarely maintained by internal personnel; 2. Relying on the information infrastructure of production enterprises, it automatically collects energy consumption data and automatically corrects discrepancies by combining instrument calibration, providing accurate, real-time, and reliable carbon emission benchmark data; 3. Combining the theoretical basis of carbon emission calculation, it uses real-time and reliable benchmark data to calculate carbon emissions at each stage in real time and writes the data into the carbon emission database.

[0060] Figure 4 This is a structural diagram of a carbon emission calculation device according to an embodiment of this application, such as... Figure 4 As shown, the device includes:

[0061] The acquisition module 402 is used to acquire the process production route in the process design system, wherein each process production route includes multiple production stages;

[0062] The data acquisition module 404 is used to acquire energy data corresponding to the production dimension in the process production route, wherein the energy data includes at least one of the following: energy consumption data and output data;

[0063] The first determining module 406 is used to determine the carbon emission calculation model corresponding to the process production route based on energy data;

[0064] The second determining module 408 is used to determine the amount of carbon emissions based on the carbon emission calculation model.

[0065] In the aforementioned carbon emission calculation device, the process production route is determined in the following manner: in response to the selection instruction of the target object, the target production device is determined, wherein the number of target production devices is one or more; when the number of target production devices is multiple, the execution order of the multiple target production devices is determined; the process production route is determined according to the execution order, and the attribute information of the process production route is determined.

[0066] In the data acquisition module of the aforementioned carbon emission calculation device, energy data corresponding to the production dimension in the process production route is acquired. Specifically, the process includes the following steps: determining the production dimension of the energy data, wherein the production dimension is the production dimension corresponding to the production plan; determining the data acquisition frequency of the energy data based on the production dimension; and acquiring energy data based on the acquisition frequency, wherein the energy data includes at least one of the following: actual production energy consumption data, external energy consumption data of the production equipment, and office energy consumption data.

[0067] In the first determining module of the aforementioned carbon emission calculation device, a carbon emission calculation model corresponding to the process production route is determined based on energy data. This process specifically includes the following steps: determining the data acquisition scenario for the carbon emission calculation model, where the acquisition scenario includes instantaneous acquisition and cumulative acquisition; when the acquisition scenario for the carbon emission calculation model is instantaneous acquisition, obtaining the first acquisition value corresponding to the current production device at the end of the acquisition, where the current production device is used to generate energy data; determining the corresponding carbon emission calculation model for the instantaneous acquisition scenario based on the first acquisition value and the model correction coefficient; when the acquisition scenario for the carbon emission calculation model is cumulative acquisition, obtaining the second acquisition value corresponding to the current production device at the start of the acquisition; and determining the corresponding carbon emission calculation model for the cumulative acquisition scenario based on the first acquisition value, the second acquisition value, and the model correction coefficient.

[0068] In the first determining module of the aforementioned carbon emission calculation device, the model correction coefficients are determined by: determining the attribute information of the energy data, wherein the attribute information includes at least one of the following: the reliability of the energy data, the accuracy of the energy data, and the nature of the energy data; and determining the model correction coefficients based on the attribute information and the data type of the energy data.

[0069] In the second determining module of the aforementioned carbon emission calculation device, the carbon emission amount is determined based on the carbon emission calculation model, specifically including the following processes: determining the energy factor, wherein the energy factor is a benchmark factor determined in accordance with energy regulations; and determining the carbon emission amount based on the energy factor, the carbon emission calculation model, and the model correction coefficient.

[0070] In the second determining module of the aforementioned carbon emission calculation device, after determining the carbon emission amount based on the carbon emission calculation model, the second determining module is further used to store the carbon emission amount in a database, wherein the type of carbon emission amount includes at least one of the following: carbon emission amount of raw and auxiliary materials, carbon emission amount of production process, and carbon emission amount of transportation and delivery; abnormal measurement data in the carbon emission amount are removed to obtain the target carbon emission amount; and the target carbon emission amount is classified according to the type of carbon emission amount.

[0071] It should be noted that, Figure 4 The carbon emission calculation device shown is used to perform Figure 2 The carbon emission calculation method shown above also applies to the carbon emission calculation device, and will not be repeated here.

[0072] This application embodiment also provides a non-volatile storage medium, which includes a stored computer program. The device containing the non-volatile storage medium executes the following carbon emission calculation method by running the computer program: acquiring a process production route from a process design system, wherein each process production route includes multiple production stages; collecting energy data corresponding to the production dimension in the process production route, wherein the energy data includes at least one of the following: energy consumption data and output data; determining a carbon emission calculation model corresponding to the process production route based on the energy data; and determining the carbon emission amount based on the carbon emission calculation model.

[0073] In the aforementioned non-volatile storage medium, the process production route is determined in the following manner: in response to a target object selection instruction, a target production device is determined, wherein the number of target production devices is one or more; when the number of target production devices is multiple, the execution order of the multiple target production devices is determined; the process production route is determined based on the execution order, and the attribute information of the process production route is determined.

[0074] In the aforementioned non-volatile storage medium, the process of collecting energy data corresponding to the production dimension in the production process route includes the following steps: determining the production dimension of the energy data, wherein the production dimension is the production dimension corresponding to the production plan; determining the collection frequency of the energy data based on the production dimension; and collecting energy data based on the collection frequency, wherein the energy data includes at least one of the following: actual production energy consumption data, external energy consumption data of the production unit, and office energy consumption data.

[0075] In the aforementioned non-volatile storage medium, determining the carbon emission calculation model corresponding to the process production route based on energy data specifically includes the following process: determining the acquisition scenario of the carbon emission calculation model, wherein the acquisition scenario includes instantaneous acquisition and cumulative acquisition; when the acquisition scenario of the carbon emission calculation model is instantaneous acquisition, obtaining the first acquisition value corresponding to the current production unit at the acquisition end time, wherein the current production unit is used to generate energy data; determining the carbon emission calculation model corresponding to the instantaneous acquisition scenario based on the first acquisition value and the model correction coefficient; when the acquisition scenario of the carbon emission calculation model is cumulative acquisition, obtaining the second acquisition value corresponding to the current production unit at the acquisition start time; determining the carbon emission calculation model corresponding to the cumulative acquisition scenario based on the first acquisition value, the second acquisition value, and the model correction coefficient.

[0076] In the aforementioned non-volatile storage medium, the model correction coefficients are determined as follows: the attribute information of the energy data is determined, wherein the attribute information includes at least one of the following: the reliability of the energy data, the accuracy of the energy data, and the nature of the energy data; the model correction coefficients are determined based on the attribute information and the data type of the energy data.

[0077] In the aforementioned non-volatile storage media, the carbon emission amount is determined based on the carbon emission calculation model, specifically including the following process: determining the energy factor, wherein the energy factor is a benchmark factor determined in accordance with energy regulations; and determining the carbon emission amount based on the energy factor, the carbon emission calculation model, and the model correction coefficient.

[0078] In the aforementioned non-volatile storage medium, after determining the carbon emissions based on the carbon emission calculation model, the following process is also included: storing the carbon emissions in a database, wherein the type of carbon emissions includes at least one of the following: carbon emissions from raw materials and auxiliary materials, carbon emissions from the production process, and carbon emissions from transportation and delivery; removing abnormal measurement data from the carbon emissions to obtain the target carbon emissions; and classifying the target carbon emissions according to the type of carbon emissions.

[0079] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0080] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0081] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0082] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0083] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0084] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0085] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for calculating carbon emissions, characterized in that, include: Obtain the process production routes from the process design system, where each process production route includes multiple production stages; Collect energy data corresponding to the production dimension in the process production route, wherein the energy data includes at least one of the following: energy consumption data and output data; Based on the energy data, a carbon emission calculation model corresponding to the process production route is determined; Carbon emissions are determined based on the aforementioned carbon emission calculation model; Determining a carbon emission calculation model corresponding to the process production route based on the energy data includes: determining the data collection scenario for the carbon emission calculation model, wherein the data collection scenario includes instantaneous data collection and cumulative data collection; when the data collection scenario for the carbon emission calculation model is instantaneous data collection, obtaining the first data collection value corresponding to the current production unit at the end time of data collection, wherein the current production unit is used to generate the energy data; determining the carbon emission calculation model corresponding to the instantaneous data collection scenario based on the first data collection value and the model correction coefficient; when the data collection scenario for the carbon emission calculation model is cumulative data collection, obtaining the second data collection value corresponding to the current production unit at the start time of data collection; and determining the carbon emission calculation model corresponding to the cumulative data collection scenario based on the first data collection value, the second data collection value, and the model correction coefficient.

2. The method according to claim 1, characterized in that, The production process route is determined in the following way: In response to a selection instruction for a target object, a target production unit is determined, wherein the number of the target production units is one or more; When there are multiple target production units, the execution order of the multiple target production units is determined; The process production route is determined based on the execution order, and the attribute information of the process production route is determined.

3. The method according to claim 1, characterized in that, Collect energy data corresponding to the production dimension in the aforementioned process production route, including: Determine the production dimension of the energy data, wherein the production dimension is the production dimension corresponding to the production plan; The frequency of energy data collection is determined based on the aforementioned production dimension; The energy data is collected according to the collection frequency, wherein the energy data includes at least one of the following: actual production energy consumption data, external energy consumption data of production equipment, and office energy consumption data.

4. The method according to claim 1, characterized in that, The model correction coefficients are determined in the following way: Determine the attribute information of the energy data, wherein the attribute information includes at least one of the following: the reliability of the energy data, the accuracy of the energy data, and the nature of the energy data; Based on the attribute information and the data type of the energy data, the model correction coefficient is determined.

5. The method according to claim 1, characterized in that, Determining carbon emissions based on the aforementioned carbon emission calculation model includes: Determine the energy factor, wherein the energy factor is a benchmark factor determined in accordance with energy specifications; The carbon emissions are determined based on the energy factor, the carbon emission calculation model, and the model correction coefficient.

6. The method according to claim 1, characterized in that, After determining the carbon emissions based on the carbon emission calculation model, the method further includes: The carbon emissions are stored in a database, wherein the types of carbon emissions include at least one of the following: carbon emissions from raw materials and auxiliary materials, carbon emissions from the production process, and carbon emissions from transportation and delivery. By removing outlier measurement data from the carbon emissions, the target carbon emissions are obtained. The target carbon emissions are classified according to the type of carbon emissions.

7. A carbon emission calculation device, characterized in that, include: The acquisition module is used to acquire the process production routes in the process design system, where each process production route includes multiple production stages. The data acquisition module is used to acquire energy data corresponding to the production dimension in the process production route, wherein the energy data includes at least one of the following: energy consumption data and output data; The first determining module is used to determine a carbon emission calculation model corresponding to the process production route based on the energy data, including: determining the acquisition scenario of the carbon emission calculation model, wherein the acquisition scenario includes instantaneous acquisition and cumulative acquisition; when the acquisition scenario of the carbon emission calculation model is instantaneous acquisition, obtaining the first acquisition value corresponding to the current production device at the acquisition end time, wherein the current production device is used to generate the energy data; determining the carbon emission calculation model corresponding to the instantaneous acquisition scenario based on the first acquisition value and the model correction coefficient; when the acquisition scenario of the carbon emission calculation model is cumulative acquisition, obtaining the second acquisition value corresponding to the current production device at the acquisition start time; and determining the carbon emission calculation model corresponding to the cumulative acquisition scenario based on the first acquisition value, the second acquisition value, and the model correction coefficient. The second determining module is used to determine the amount of carbon emissions based on the carbon emission calculation model.

8. An electronic device, characterized in that, include: Memory, used to store program instructions; A processor, connected to the memory, is configured to execute program instructions to perform the following functions: acquiring a process production route in a process design system, wherein each process production route includes multiple production stages; collecting energy data corresponding to the production dimension in the process production route, wherein the energy data includes at least one of the following: energy consumption data and output data; determining a carbon emission calculation model corresponding to the process production route based on the energy data; determining the carbon emission amount based on the carbon emission calculation model; determining the carbon emission calculation model corresponding to the process production route based on the energy data includes: determining the acquisition scenario of the carbon emission calculation model, wherein the acquisition scenario includes instantaneous acquisition and cumulative acquisition. Data collection; in the case of instantaneous data collection in the carbon emission calculation model, the first digit of the data collection value corresponding to the current production device at the end of the data collection is obtained, wherein the current production device is used to generate the energy data; based on the first digit of the data collection value and the model correction coefficient, the carbon emission calculation model corresponding to the instantaneous data collection scenario is determined; in the case of cumulative data collection in the carbon emission calculation model, the second digit of the data collection value corresponding to the current production device at the start of the data collection is obtained; based on the first digit of the data collection value, the second digit of the data collection value and the model correction coefficient, the carbon emission calculation model corresponding to the cumulative data collection scenario is determined.

9. A non-volatile storage medium, characterized in that, The non-volatile storage medium includes a stored computer program, wherein the device containing the non-volatile storage medium executes the carbon emission calculation method according to any one of claims 1 to 6 by running the computer program.

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