Carbon quota intelligent measuring and calculating system and method

Abstract

The invention provides a carbon quota intelligent measuring and calculating system and method. The system comprises a product management module which configures and manages product production data; the energy management module is used for configuring and managing energy production data; the raw material management module is used for configuring and managing raw material production data; the equipment management module is used for configuring and managing equipment data; the production process management module is used for configuring and managing process steps; the emission factor management module is used for providing energy emission factors; the production activity management module is used for integrating a production plan, actual production data and equipment data, matching the use conditions of each energy source and each raw material with process steps in the production process management module, and calculating data of each energy source carbon emission, product carbon emission and enterprise carbon emission according to process energy emission factors; and the carbon emission quota measuring and calculating module is used for measuring and calculating the carbon emission quota release amount by integrating the data of each module and an algorithm model. According to the invention, the production process of one product and the emission of greenhouse gases in different procedures in the process can be completely displayed.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission monitoring, and relates to a carbon quota intelligent calculation system and method. Background Art

[0002] The current status of the global environmental problem of greenhouse gas emissions is worrying. In 2022, the concentration of greenhouse gases in the global atmosphere reached a record high. The continuous increase in greenhouse gases has led to global warming, and the global average temperature is about 1.1°C higher than the pre-industrial level. To achieve the goal of the Paris Agreement of keeping the global temperature rise within 1.5°C, global greenhouse gas emissions need to peak by 2025 and decline rapidly. More forceful actions must be taken to slow down the process of climate change. However, we also have the basic need to develop the economy, but excessive restrictions on greenhouse gas emissions will seriously affect economic development and even trigger more serious social problems. Therefore, a scientific technical method for calculating carbon emission quotas is needed to help enterprises calculate the quantity of carbon emission quotas, facilitate enterprises to carry out energy conservation and emission reduction, and gain a surplus of carbon emission quotas, which will neither affect the production and operation activities of enterprises nor generate additional economic benefits. Therefore, it is very important to keep enterprises always motivated to participate in energy conservation and emission reduction for the early realization of the carbon neutrality goal. At present, the following problems still exist in the technical aspect of carbon quota calculation:

[0003] 1. Data quality and accuracy: The accuracy and reliability of production activity data are the basis for calculating carbon emission quotas. However, at present, most data collection and monitoring methods rely on manual ledger registration and manual system entry, which may have errors and uncertainties, resulting in the accuracy of the calculation results being affected.

[0004] 2. Inconsistent standards and methods: Different regions and industries may adopt different management standards and methods, which makes it difficult to compare and coordinate the calculation results of carbon emission quotas.

[0005] 3. Lack of real-time data: The activity data (such as energy consumption, raw material consumption, and product output) in the production process are usually collected and reported regularly, which results in the statistical results of production activity data lagging behind the actual situation, thus affecting the calculation results of carbon quotas.

[0006] 4. Complexity and technical threshold: Calculating carbon emission quotas involves complex calculations and models, which require professional knowledge and technical support. For some enterprises and institutions, they lack relevant technical capabilities and resources.

[0007] 5. Uncertainty and risk assessment: The calculation results of carbon emission quotas are affected by various factors, such as future policy changes, technological developments, and market dynamics. How to evaluate and respond to these uncertainties is a challenge.

[0008] 6. Cost and Benefit Analysis: Implementing carbon emission quota measurement requires certain costs, including data collection, monitoring equipment, and personnel training. At the same time, it is also necessary to evaluate the impact of the trial calculation results on the economic benefits and competitiveness of enterprises.

[0009] Patent document CN116663804A discloses a carbon emission data confirmation method, storage medium, and electronic device, which realizes the rationality analysis of all data involved in the carbon emission process of thermal power enterprises. This method is applied to a terminal installed with a carbon emission data confirmation application for thermal power enterprises. The method includes: displaying the operation interface of the carbon emission data confirmation application for thermal power enterprises and determining the current carbon emission data function interface; enabling the controls on the interface of the carbon emission data confirmation application for thermal power enterprises according to the carbon emission data function interface, and displaying the operation interface corresponding to the carbon emission data function interface on the interface of the carbon emission data confirmation application for thermal power enterprises; in response to the user's operation on the operation interface, generating a supervision result corresponding to the carbon emission data function interface, where the supervision result includes at least one of a carbon emission data template, a carbon emission data threshold inspection result, a carbon emission quota allocation plan, and a carbon emission quota measurement result. However, the current carbon quota inventions are only applicable to the thermal power industry and lack generality. Summary of the Invention

[0010] Aiming at the defects in the prior art, the purpose of the present invention is to provide a carbon quota intelligent measurement system and method.

[0011] According to a carbon quota intelligent measurement system provided by the present invention, it includes:

[0012] Product Management Module: Configure and manage product production data;

[0013] Energy Management Module: Configure and manage energy production data;

[0014] Raw Material Management Module: Configure and manage raw material production data;

[0015] Equipment Management Module: Configure and manage equipment data;

[0016] Production Process Management Module: Configure and manage process steps;

[0017] Emission Factor Management Module: Provide energy emission factors;

[0018] Production Activity Management Module: Integrate production plans, actual production data, and equipment data, match the usage of each energy and raw material with the process steps in the production process management module, and calculate the carbon emissions of each energy, the carbon emissions of products, and the carbon emissions data of the enterprise according to the energy emission factors of the process;

[0019] Carbon Emission Quota Calculation Module: Calculate the amount of carbon emission quotas issued by integrating the data and algorithm models of each module.

[0020] Preferably, in the said Product Management Module:

[0021] Manage the finished products of production enterprises. The product management functions include: maintaining the product classification name and maintaining the product information name;

[0022] Product Classification Maintenance: Establish a product classification information database. Enterprises manage product classification information according to actual situations, establish a product differentiation system. The maintenance of product classification names adds, modifies, and queries the types of products. When adding or modifying product classifications, the information entered includes the product classification number, product classification name, product classification description, and remarks. Before saving product classification information, verify the standardization and uniqueness of the involved classification numbers and classification names. When adding, the system automatically generates the product classification ID primary key. When modifying, based on the product classification ID primary key, change the classification information of specific products. When querying, retrieve relevant product classification information according to the entered conditions;

[0023] Product Name Maintenance: Establish a product name information database, which is associated with product classifications. Enterprises manage product name information according to actual situations to identify relevant products. The maintenance of product names performs operations of adding, modifying, and querying product name information;

[0024] In the said Energy Management Module:

[0025] Manage the energy used in enterprise production activities. Energy management includes: maintaining the energy name and maintaining the energy classification;

[0026] Energy Classification Maintenance: Establish an energy type information database, classify and manage the used energy, add, modify, and query energy classification information. When adding and modifying energy classifications, the information entered includes the energy classification number, energy classification name, energy classification description, and remarks. Before saving energy type information, verify the uniqueness and standardization of the energy classification number and energy classification name. When adding, the system automatically generates the corresponding energy classification ID primary key. When modifying, based on the energy classification ID primary key, change the specific energy classification information. When querying, retrieve energy classification information according to the entered conditions;

[0027] Energy Name Maintenance: Establish an energy name information database, which is associated with energy classification maintenance, manage the energy name. The maintenance of energy names adds, modifies, and queries the energy name. Before saving energy name information, verify the uniqueness and standardization of the energy number and energy name. When adding, the system automatically generates the corresponding energy name ID primary key. When modifying, based on the energy name ID primary key, change the corresponding energy name information. When querying, retrieve energy name information according to the entered conditions;

[0028] In the raw material management module:

[0029] Manage the input information of product production required for the purpose of production activities. The raw material management function includes raw material classification maintenance and raw material name maintenance;

[0030] Raw material classification maintenance: Establish a raw material classification information database to manage raw materials by classification. Raw material classification maintenance is the behavior of adding, modifying, and querying the raw material classification name. When adding or modifying the raw material classification, the information entered includes the raw material classification number, raw material classification name, and raw material classification description;

[0031] Raw material name maintenance: Establish a raw material name information database, which is associated with the raw material classification, to manage raw material information. Raw material information maintenance adds, modifies, and queries the raw material name. When adding or modifying the raw material, the information entered includes the raw material number, raw material name, raw material classification information, raw material attributes, raw material uses, whether carbon emissions are involved, and remarks information.

[0032] Preferably, in the equipment management module:

[0033] Manage the intelligent networked equipment used in the enterprise's production activities, obtain production activity data through the equipment, and provide a data source for carbon quota calculation. The equipment management function includes equipment information maintenance, operation data management, and operation monitoring management:

[0034] Equipment information maintenance: Manage the intelligent networked equipment information involved in activity data collection during the production process. Through the application of Internet of Things technology, collect production activity data from the equipment. The equipment information maintenance function includes equipment name information maintenance and equipment parameter information maintenance. Equipment name maintenance adds, modifies, and queries the basic information of the equipment. When adding or modifying equipment information, the information entered includes the equipment number, equipment name, equipment model, equipment serial number, equipment manufacturer, production date, installation location, installation date, technical parameters, communication protocol, startup status, and remarks; Equipment parameter information maintenance, based on equipment name information maintenance, manages the production activity parameter information that can be collected from the equipment, adds, modifies, and queries this information, and the information entered includes the equipment measurement activity number, measurement activity name, equipment number, measurement type, and measurement unit;

[0035] Operation data management: Collect production activity data from the source of intelligent networked equipment, and according to the actual management needs of the enterprise and the characteristics of different intelligent devices, collect and extract the results of equipment operation activities at the smallest time interval, master the production operation activity data associated with each equipment, and conduct summary and classification, which are divided into source data collection and data format processing, and data classification and summary:

[0036] Source data collection and data format processing: First step: Collect raw data from source devices, develop a set of scheduled task programs, deploy them in intelligent devices, and set an appropriate frequency to generate data files in the original format. Then transfer these files to the background server through the Internet of Things connection for the backend program to read and subsequent processing; Second step: After the data files are transferred to the server, develop a backend program for data file processing and build an original database of device activities to re-organize and store the format of these activity data, achieving data aggregation and format unification. After processing, summarize the parameter information collected from the devices according to different device characteristics; Third step: Regularly perform data archiving to transfer the data outside the time statistics range to the archive database;

[0037] Data classification and summarization: Summarize the statistical information of different measurement types according to different time spans, and establish statistical databases for different time spans respectively. The statistical information includes: summary statistical number, summary statistical name, measurement activity number, start date, end date, statistical value, measurement type, calculation date;

[0038] Operation monitoring and management: Establish and develop a set of device operation monitoring programs. Based on the device basic information maintenance function, master the current operation status of these intelligent devices to facilitate users to ensure that each device always maintains a normal operation status. The device operation monitoring and management includes the device operation status monitoring function and the device fault maintenance function. Regarding the device operation status monitoring function, when the device information is initially entered into the system, the original operation status information of the device is the initial status, and the last data processing time is empty information. When determining the device operation status, according to the data sending frequency and the system's last data processing time, combined with the system's current time, determine whether the device operation status is normal. Through the execution of the scheduled task mechanism, when the last data processing time is later than the specified time, the device operation status is determined to be abnormal; when data collection is abnormal, the system feeds back the abnormal status of the corresponding device for device management personnel to process in a timely manner to ensure that the intelligent device always maintains a normal data collection status. Regarding the device fault maintenance function, for devices in an abnormal state, when the device repair and processing are completed, fill in the fault repair information, and the input content should include the modification activity number, problem content description, fault start time, fault end time, and solution method description.

[0039] Preferably, in the production process management module:

[0040] Manage the production activities of the enterprise, collect and count the data consumed by the products in the production processes passed through within a preset time through the device management function. The production process management function includes production process flow maintenance and production process activity statistics.

[0041] Process Flow Maintenance: Establish an information database for production process flows. Based on the actual production process of the enterprise, each process from raw material input to finished product output is defined in terms of the final product output. Production process flow maintenance includes adding and modifying production process information, and then configuring production materials and associated intelligent device information for each process. The first step: associate with the product information of the product management function; the second step: associate with the basic production process information, and configure detailed information for each established production process, including columns for energy information, raw material information, waste treatment information, gas recovery information, and by-product generation information; the third step: associate with the device information maintenance and monitoring activity information, and configure specific device monitoring activity information for the specific content of each column item in each column of each process. Based on the measurement record data accumulated in the device operation activity management function, automatically obtain the quantified index data of specific production material consumption and processing, and realize the collection of device operation data;

[0042] Process Activity Data Statistics: Based on the data established by the device operation activity data management function and the production process flow maintenance function, display the quantified data information of energy consumption, raw material consumption, waste treatment, gas recovery, and by-product generation involved in each process in terms of product output.

[0043] Preferably, in the emission factor management module:

[0044] Establish a set of carbon emission factor databases for the enterprise's production and operation activities, including raw material consumption, energy consumption, waste treatment, gas recovery, by-product generation, and product output. The emission factor management function includes accounting standard maintenance, emission factor parameter and calculation formula configuration;

[0045] Accounting Standard Maintenance: Establish an information database for accounting method standards, provide operation standards for carbon emission accounting during product production, and improve the pertinence and accuracy of carbon emission quota measurement. The accounting standard maintenance function includes adding, modifying, and querying accounting standards; when adding and modifying, the information entered includes the accounting standard number, accounting standard name, release year, applicable industry, remarks information, and upload of document standard information. Before saving the accounting standard information, verify the uniqueness and standardization of the accounting standard number and accounting standard name;

[0046] Factor Parameter and Calculation Formula Configuration: Associate with the accounting standard maintenance function, establish an emission factor parameter and calculation formula rule library, and configure emission factor parameters and related calculation formulas for production materials and products according to the actual management needs of the enterprise. The factor parameter and calculation formula configuration is divided into establishing basic calculation rule information and configuring detailed calculation rule information:

[0047] Establish basic information of calculation rules: It shows the overview information of factor parameters and calculation formulas. The established basic information includes calculation rule number, calculation rule name, accounting standard information, and remarks information;

[0048] Configure detailed information of calculation rules: Establish corresponding detailed information, configure production data information, and configure emission factor parameters information and calculation formula information for specific columns of production data. Regarding energy consumption and raw material consumption emission factors, before configuring emission factor parameters, first complete the configuration of production data information involved in the energy management and raw material management functions, and configure emission factor parameters and calculation formulas of emission factors for these name information respectively; for emission factor parameter information, reserve ten factor parameter fields. In terms of emission factor calculation formulas, configure parameter value fields for independent fields to configure mathematical calculation formulas to obtain comprehensive emission factor values. In other production processes, involving by-product generation, gas recovery, waste treatment, and product output, according to the requirements of accounting standards and combined with the actual situation of the enterprise, configure emission factor parameters and calculation formulas, and according to process characteristics, the result summary method of relevant factor formulas should be indicated as reduction or increase. Combine a series of calculated comprehensive emission factor values with the corresponding production data processing volume to obtain the corresponding carbon emissions.

[0049] Preferably, in the carbon emission quota calculation module:

[0050] Based on the production quantity of the product and the comprehensive greenhouse gas emission quantity of the product during the production process, obtain the product carbon emission intensity of the current year, and combine the carbon emission quota quantity received over the years and the approved product carbon emission benchmark to analyze the development trend of carbon emission quotas, and calculate the carbon emission quota and quota surplus quantity of the current year; the carbon emission quota calculation function includes analysis of carbon emission quota distribution trend, analysis of product carbon emission intensity trend, and calculation of carbon emission quota and quota surplus quantity;

[0051] Analysis of carbon emission quota distribution trend: Analyze the average growth rate of carbon emission quota quantity distribution. Regarding the maintenance of quota distribution information, establish a carbon emission quota management information database, and add and maintain carbon emission quota information received over the years. The detailed information of carbon emission quota distribution includes the carbon emission benchmark information of the enterprise's products, which shows the approved carbon emission intensity of each product produced by the enterprise. The input content includes product number, product type name, approved product output, product emission benchmark value, and information remarks; analyze the total quota allocation, analyze the quotas received in the first year and the second year until the current year, and calculate the average growth rate of carbon emission quotas over the years; analyze the carbon emission intensity and the number of qualified products of each product approved for production by the enterprise, analyze the production emission intensity and approved product production quantity information of each product approved in the first year and the second year until the current year, and calculate the average growth rate of the two;

[0052] Analysis of the Trend of Carbon Emission Intensity in Product Production: Analyze the carbon emission intensity of the products in the enterprise's production activities to understand the development trend of the carbon emission intensity of the enterprise's own product production. Based on the data accumulated in the maintenance of emission quota distribution information and the production process activities, compare the carbon emission intensity of the products in the first year, the second year, and until the previous year, and estimate the carbon emission benchmark of each product in the current year. In the production process of each product every year, energy consumption, raw material consumption, by-product generation, gas recovery, and waste treatment all generate greenhouse gas emissions. By collecting the energy consumption data in the above production activities and combining the comprehensive emission factor value, obtain the comprehensive greenhouse gas emissions, and combine with the product output to obtain the greenhouse gas emission intensity of each product every year, and calculate the average growth rate of the carbon emission intensity of the enterprise's product production;

[0053] Calculation of Carbon Quota and Carbon Quota Surplus Quantity: Based on the analysis of the trend of emission quota distribution and the trend of carbon emission intensity in product production, calculate the carbon emission quota and the carbon quota surplus quantity from two aspects respectively, providing data support for the formulation of the carbon quota trading plan and the implementation of the carbon emission compliance plan:

[0054] Calculation of the Current Year's Carbon Emission Quota Quantity Based on the Carbon Emission Quotas Allocated over the Years: The enterprise analyzes the carbon emission quotas allocated over the years. The enterprise collects the carbon emission quotas and analyzes the annual changes of these quotas to obtain the average growth rate. Based on this growth rate and combined with the carbon emission quota of the previous year, obtain the calculated quantity of the current year's carbon emission quota. By collecting the data on energy consumption, raw material consumption, by-product generation, gas recovery, and waste treatment in the production process, calculate the surplus quantity of the carbon emission quota;

[0055] Calculation of the Carbon Emission Quota Quantity Based on the Carbon Emission Intensity of Products over the Years: The enterprise analyzes the carbon emission intensity of the products produced over the years to obtain the average growth rate every year. If the growth rate in a certain year is greater than the preset standard, take the growth rate of the latest subsequent year. Based on this growth rate and combined with the carbon emission intensity of the relevant products in the previous year, obtain the estimated carbon emission intensity of the products to be approved in the current year. By evaluating the quantity of qualified products in product production, calculate the carbon emission quota quantity in the current year, and combine with the comprehensive emissions in product production to calculate the carbon quota surplus quantity in the current year.

[0056] According to a carbon quota intelligent calculation method provided by the present invention, using any one of the described carbon quota intelligent calculation systems, the execution includes:

[0057] Step S1: Configure basic information, maintain product classification and name, energy classification and name, raw material classification and name, equipment information, accounting standards, and process flow, and configure factor parameters and calculation formulas;

[0058] Step S2: Manage production activity data, manage equipment operation monitoring and data, and count process activity data;

[0059] Step S3: Calculate carbon emission quotas based on the configured basic information and production activity data, analyze the emission quota allocation trend, the carbon emission intensity trend of product production, and the calculation of carbon emission quotas and quota surpluses.

[0060] Preferably, in the said Step S1:

[0061] Establish a basis for the calculation of the carbon quota quantity, and the specific steps are as follows:

[0062] Step S1.1: Configure production material information: Complete the collection of production material information through product management function, energy management function, raw material management function, and equipment management function, including product information, energy information, raw material information, and equipment information; In terms of product management, energy management, and raw material management, according to the actual business situation of the enterprise, first set classification information, and then set name information;

[0063] Step S1.2: Configure emission factors and calculation formulas: Through the accounting standard maintenance function, establish the content of accounting standard information to provide a basis for the configuration of carbon emission factors and calculation formulas; According to its own actual needs, the enterprise configures emission factor parameters and calculation formulas for comprehensive emission factors for preset specific products, energy, raw materials, waste treatment, and by-product generation in the factor parameter and calculation formula configuration function;

[0064] Step S1.3: Configure intelligent networked equipment: Through the equipment information maintenance function, add and maintain the intelligent equipment information involved in the production process activities of production enterprises, indicating the data types that can be collected by different equipment for production material processing;

[0065] Step S1.4: Configure process flow: Through the process flow maintenance function, taking different product outputs as dimensions, configure the required production processes according to the actual production situation of the enterprise, configure the production material information involved in each process, and then configure the intelligent networked equipment information for these column contents to realize the information collection of production material consumption or processing data.

[0066] Preferably, in the said Step S2:

[0067] By applying Internet of Things technology, data collection of production activities is realized from intelligent connected devices, and the energy consumption data and product output data of each production process in the product production process are mastered, providing a complete data basis for the calculation of the carbon quota quantity of production enterprises, and proceeding as follows:

[0068] Step S2.1: Application of source data generation program: Applied to the device side, developed by the device manufacturer or by a designated software developer, and deployed on the intelligent connected device to enable relevant devices to send data regularly;

[0069] Step S2.2: Operation data management: Through the device operation data management function, summary information and average value information within a preset time for the data extracted from each device are realized;

[0070] Step S2.3: Device operation monitoring: Through the device operation monitoring management function, the operation status of each device is monitored to ensure that the device is in a preset normal state, ensuring that the backend service processes data regularly. When a preset abnormality occurs, the management personnel check and maintain the device, promptly restore the abnormal device to normal, and collect data for the affected time period again;

[0071] Step S2.4: Statistical data of process activities: Through the statistical function of process activity data, data summary of energy consumption, raw material consumption, waste treatment, gas recovery, and by-product generation involved in the relevant processes passed during the product production process is carried out, and relevant data that cannot be collected by the device is supplemented.

[0072] Preferably, in the said Step S3:

[0073] For enterprises with a carbon compliance activity time lower than the preset standard, through the product production carbon emission intensity trend analysis function, the carbon emission intensity of different product productions is obtained, and for the energy consumption of different product productions, combined with the product output, the enterprise's carbon emission quota quantity is calculated; for enterprises whose participation time in the carbon compliance market meets the preset standard, according to the trend of historical emission quota allocation, the average growth rate is obtained, the enterprise's current quota is calculated, and combined with the product production carbon emission intensity information, the carbon emission surplus quantity is obtained.

[0074] Compared with the prior art, the present invention has the following beneficial effects:

[0075] 1. The present invention masters the carbon emission intensity of the enterprise's product output;

[0076] 2. The present invention can calculate the enterprise's emission quota;

[0077] 3. The present invention can completely display the production process of a product and the greenhouse gas emissions of different processes in this process. Description of the Drawings

[0078] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments read in conjunction with the accompanying drawings:

[0079] Figure 1 It is a schematic diagram for the blueprint design of carbon emission quota measurement;

[0080] Figure 2 It is a schematic diagram for the carbon emission quota measurement process. Specific Embodiments

[0081] The present invention will be described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those of ordinary skill in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0082] Embodiment 1:

[0083] The present invention provides a carbon quota intelligent measurement system and method, which measures the current year's carbon emission quota quantity and carbon emission quota surplus quantity of an enterprise, and helps the enterprise plan the carbon compliance and carbon trading plan in advance.

[0084] The present invention relates to the measurement of carbon emission quotas for an enterprise's production and operation activities. Within the enterprise's accounting boundary, modern information technology methods are used to obtain data on energy consumption, raw material consumption, waste treatment volume, greenhouse gas recovery volume, by-product generation volume, and product output over a period of time, obtain the product carbon emission intensity quantity, and analyze the change trend of the product carbon emission intensity and the development trend of carbon emission quota allocation over the years to obtain the measurement results of the enterprise's current year's carbon emission quota quantity and emission quota surplus quantity.

[0085] According to a carbon quota intelligent measurement method provided by the present invention, any one of the described carbon quota intelligent measurement systems is adopted, and the execution includes:

[0086] Step S1: Configure basic information, maintain product classification and name, energy classification and name, raw material classification and name, equipment information, accounting standards, process flow, and configure factor parameters and calculation formulas;

[0087] Specifically, in the step S1:

[0088] Establish a basis for the measurement of carbon quota quantity, and the specific steps are as follows:

[0089] Step S1.1: Production data information configuration: The production data information is collected through the product management function, energy management function, raw material management function, and equipment management function, including product information, energy information, raw material information, and equipment information; in terms of product management, energy management, and raw material management, according to the actual business situation of the enterprise, the classification information is set first, and then the name information is set.

[0090] Step S1.2: Emission factor and calculation formula configuration: Through the accounting standard maintenance function, the accounting standard information content is established to provide a basis for the configuration of carbon emission factors and calculation formulas; according to its actual needs, the enterprise configures the emission factor parameters and the calculation formulas of the comprehensive emission factor for the preset specific products, energy, raw materials, waste treatment, and by-product generation in the factor parameter and calculation formula configuration function.

[0091] Step S1.3: Intelligent connected device configuration: Through the device information maintenance function, the intelligent device information involved in the production process activities of the production enterprise is newly added and maintained, indicating the data types that can be collected by different devices for production data processing.

[0092] Step S1.4: Process flow configuration: Through the process flow maintenance function, taking different product outputs as the dimension, the required production processes are configured according to the actual production situation of the enterprise, the production data information involved in each process is configured, and then the intelligent connected device information is configured for these column contents to realize the information collection of the production data consumption or processing data.

[0093] Step S2: Manage the production activity data, manage the equipment operation monitoring and data, and statistically analyze the process activity data.

[0094] Specifically, in the said Step S2:

[0095] Through the application of the Internet of Things technology, the production activity data is collected from the intelligent connected devices, and the energy consumption data and product output data of each production process in the product production process are mastered, providing a complete data basis for the calculation of the carbon quota quantity of the production enterprise, and proceeding as follows:

[0096] Step S2.1: Application of the source data generation program: Applied to the device side, developed by the device manufacturer or by a contracted software developer, and deployed on the intelligent connected device to enable the relevant device to send data regularly.

[0097] Step S2.2: Operation data management: Through the device operation data management function, the summary information and average value information within a preset time are realized for the data extracted from each device.

[0098] Step S2.3: Equipment operation monitoring: Through the equipment operation monitoring and management function, monitor the operation status of each device to ensure that the device is in a preset normal state, ensure that the backend service processes data regularly. When a preset anomaly occurs, the management staff checks and maintains the device, promptly restores the abnormal device to normal, and re-collects the data for the affected time period;

[0099] Step S2.4: Process activity data statistics: Through the process activity data statistics function, summarize the data on energy consumption, raw material consumption, waste treatment, gas recovery, and by-product generation involved in the relevant processes passed during product production, and supplement the relevant data that cannot be collected by the device.

[0100] Step S3: Calculate the carbon emission quota based on the configured basic information and production activity data, analyze the emission quota distribution trend, the carbon emission intensity trend of product production, and the calculation of carbon emission quota and quota surplus.

[0101] Specifically, in the said Step S3:

[0102] For enterprises with a carbon compliance activity time lower than the preset standard, through the carbon emission intensity trend analysis function of product production, obtain the carbon emission intensity of different product productions, and combine the energy consumption of different product productions with the product output to calculate the enterprise's carbon emission quota quantity; for enterprises that meet the preset standard for participating in the carbon compliance market, based on the trend of historical emission quota allocation, obtain the average growth rate, calculate the enterprise's current quota, and combine the carbon emission intensity information of product production to obtain the carbon emission surplus quantity.

[0103] Embodiment 2:

[0104] Embodiment 2 is a preferred example of Embodiment 1 to more specifically illustrate the present invention.

[0105] The present invention also provides a carbon quota intelligent calculation system, and the carbon quota intelligent calculation system can be realized by executing the process steps of the carbon quota intelligent calculation method, that is, those skilled in the art can understand the carbon quota intelligent calculation method as the preferred implementation manner of the carbon quota intelligent calculation system.

[0106] According to a carbon quota intelligent calculation system provided by the present invention, it includes:

[0107] Product management module: Configure and manage product production data;

[0108] Specifically, in the said product management module:

[0109] Manage the finished products of production enterprises, and the product management functions include: product classification name maintenance, product information name maintenance;

[0110] Product Classification Maintenance: Establish a product classification information database. Enterprises manage product classification information according to actual situations, establish a product differentiation system. Product classification name maintenance involves adding, modifying, and querying product types. When adding or modifying product classifications, the information entered includes product classification numbers, product classification names, product classification descriptions, and remarks. Before saving product classification information, verify the standardization and uniqueness of the classification numbers and classification names involved. When adding, the system automatically generates the primary key of the product classification ID. When modifying, based on the primary key of the product classification ID, change the classification information of specific products. When querying, retrieve relevant product classification information according to the entered conditions.

[0111] Product Name Maintenance: Establish a product name information database, which is associated with product classifications. Enterprises manage product name information according to actual situations to identify relevant products. Product name maintenance involves operations of adding, modifying, and querying product name information.

[0112] Energy Management Module: Configure and manage energy production data.

[0113] In the energy management module:

[0114] Manage the energy used in enterprise production activities. Energy management includes: Energy Name Maintenance, Energy Classification Maintenance.

[0115] Energy Classification Maintenance: Establish an energy type information database, classify and manage the energy used, add, modify, and query energy classification information. When adding and modifying energy classifications, the information entered includes energy classification numbers, energy classification names, energy classification descriptions, and remarks. Before saving energy type information, verify the uniqueness and standardization of energy classification numbers and energy classification names. When adding, the system automatically generates the corresponding primary key of the energy classification ID. When modifying, based on the primary key of the energy classification ID, change specific energy classification information. When querying, retrieve energy classification information according to the entered conditions.

[0116] Energy Name Maintenance: Establish an energy name information database, which is associated with energy classification maintenance, manage energy names. Energy name maintenance involves adding, modifying, and querying energy names. Before saving energy name information, verify the uniqueness and standardization of energy numbers and energy names. When adding, the system automatically generates the corresponding primary key of the energy name ID. When modifying, based on the primary key of the energy name ID, change the corresponding energy name information. When querying, retrieve energy name information according to the entered conditions.

[0117] Raw Material Management Module: Configure and manage raw material production data.

[0118] In the raw material management module:

[0119] Manage the input information for product production required for the purpose of production activities. The raw material management function includes raw material classification maintenance and raw material name maintenance;

[0120] Raw material classification maintenance: Establish a raw material classification information database to manage raw materials by classification. Raw material classification maintenance is the act of adding, modifying, and querying raw material classification names. When adding or modifying raw material classifications, the information entered includes the raw material classification number, raw material classification name, and raw material classification description;

[0121] Raw material name maintenance: Establish a raw material name information database, which is associated with raw material classifications to manage raw material information. Raw material information maintenance performs addition, modification, and querying of raw material names. When adding or modifying raw materials, the information entered includes the raw material number, raw material name, raw material classification information, raw material attributes, raw material uses, whether carbon emissions are involved, and remarks information.

[0122] Equipment management module: Configure and manage equipment data;

[0123] Specifically, in the said equipment management module:

[0124] Manage the intelligent networked equipment used in the enterprise's production activities, obtain production activity data through the equipment, and provide a data source for carbon quota calculation. The equipment management function includes equipment information maintenance, operation data management, and operation monitoring management:

[0125] Equipment information maintenance: Manage the information of intelligent networked equipment participating in activity data collection during the production process. Through the application of Internet of Things technology, collect production activity data from the equipment. The equipment information maintenance function includes equipment name information maintenance and equipment parameter information maintenance. Equipment name maintenance performs addition, modification, and querying of basic equipment information. When adding or modifying equipment information, the information entered includes the equipment number, equipment name, equipment model, equipment serial number, equipment manufacturer, production date, installation location, installation date, technical parameters, communication protocol, startup status, and remarks description, etc.; Equipment parameter information maintenance, based on equipment name information maintenance, manages the production activity parameter information that can be collected from the equipment, performs addition, modification, and querying of this information, and the information entered includes the equipment measurement activity number, measurement activity name, equipment number, measurement type, and measurement unit;

[0126] Operation data management: Collect production activity data from the source of intelligent networked equipment. According to the actual management needs of the enterprise and the characteristics of different intelligent devices, collect and extract the results of equipment operation activities at the smallest time interval, master the production operation activity data associated with each equipment, and perform summarization and classification, which are divided into source data collection and data format processing, and data classification and summarization:

[0127] Source data collection and data format processing: First step: Collect raw data from source devices, develop a set of scheduled task programs, deploy them in intelligent devices, and set an appropriate frequency to generate data files in the original format, and transfer these files to the background server through the Internet of Things connection for the backend program to read and subsequent processing; Second step: After the data files are transferred to the server, develop a backend program for data file processing and build an original database of device activities, re-organize and store the formats of these activity data, realize the aggregation and format unification of data, and after processing, summarize the parameter information collected from the devices according to different device characteristics. Third step: Regularly archive data, and transfer the data outside the time statistics range to the archive database;

[0128] Data classification and summarization: Summarize the statistical information of different measurement types according to different time spans, and establish statistical databases with different time spans respectively. The statistical information includes: summary statistical number, summary statistical name, measurement activity number, start date, end date, statistical value, measurement type, calculation date;

[0129] Operation monitoring and management: Establish and develop a set of device operation monitoring programs. Based on the device basic information maintenance function, master the current operation status of these intelligent devices to facilitate users to ensure that each device always maintains a normal operation status. The device operation monitoring and management include the device operation status monitoring function and the device fault maintenance function. Regarding the device operation status monitoring function, when the device information is first entered into the system, the original operation status information of the device is the initial status, and the last data processing time is empty information. When determining the device operation status, according to the data sending frequency and the system's last data processing time, combined with the system's current time, determine whether the device operation status is normal. Through the execution of the scheduled task mechanism, when the last data processing time is later than the specified time, the device operation status is determined to be abnormal; when data collection is abnormal, the system feedbacks the abnormal status of the corresponding device for the device management personnel to process in time to ensure that the intelligent device always maintains a normal data collection status. Regarding the device fault maintenance function, for the devices in the abnormal status, when the device repair and processing are completed, fill in the fault repair information, and the input content should include the modification activity number, problem content description, fault start time, fault end time, and solution description.

[0130] Production process management module: Configure and manage process steps;

[0131] Specifically, in the production process management module:

[0132] Manage the production activities of enterprises, collect and count the data consumed by products in the production processes passed through within a preset time through the equipment management function. The production process management function includes production process flow maintenance and production process activity statistics.

[0133] Process flow maintenance: Establish a production process flow information database. Enterprises define each process from raw material input to finished product output according to the actual production process situation, taking the final product output as the dimension. Production process flow maintenance includes the addition and modification of production process information, and then configure the production materials and associated intelligent equipment information for each process. The first step: Associate with the product information of the product management function; the second step: Associate with the basic production process information, and configure detailed information for each established production process, configuring columns for energy information, raw material information, waste treatment information, gas recovery information, and by-product generation information. The third step: Associate with the equipment information maintenance and monitoring activity information. In each column of each process, configure specific equipment monitoring activity information for the specific content of each column item. Based on the measurement record data accumulated in the equipment operation activity management function, automatically obtain the quantitative index data of specific production material consumption and processing, and realize the collection of equipment operation data.

[0134] Process activity data statistics: Based on the data established by the equipment operation activity data management function and the production process flow maintenance function, display the quantitative data information of energy consumption, raw material consumption, waste treatment, gas recovery, and by-product generation involved in each process, taking the product output as the dimension.

[0135] Emission factor management module: Provide energy emission factors.

[0136] Specifically, in the emission factor management module:

[0137] Establish a set of carbon emission factor databases for the production and operation activities of enterprises, including raw material consumption, energy consumption, waste treatment, gas recovery, by-product generation, and product output. The emission factor management function includes accounting standard maintenance, emission factor parameter and calculation formula configuration.

[0138] Accounting standard maintenance: Establish an accounting method standard information database to provide operation standards for carbon emission accounting in the product production process, and improve the pertinence and accuracy of carbon emission quota measurement. The accounting standard maintenance function includes the addition, modification, and query of accounting standards. When adding and modifying, the information entered includes the accounting standard number, accounting standard name, release year, applicable industry, remarks information, and upload of document standard information. Before saving the accounting standard information, verify the uniqueness and standardization of the accounting standard number and accounting standard name.

[0139] Factor Parameter and Calculation Formula Configuration: Associated with the accounting standard maintenance function, establish an emission factor parameter and calculation formula rule library. Combining the actual management needs of the enterprise, configure emission factor parameters and related calculation formulas for production materials and products. The factor parameter and calculation formula configuration is divided into establishing basic calculation rule information and configuring detailed calculation rule information:

[0140] Establishing Basic Calculation Rule Information: Indicating the overview information of factor parameters and calculation formulas, the established basic information includes calculation rule number, calculation rule name, accounting standard information, and note information;

[0141] Configuring Detailed Calculation Rule Information: Establish corresponding detailed information, configure production material information, and configure emission factor parameter information and calculation formula information for specific columns of production materials. Regarding energy consumption and raw material consumption emission factors, before configuring emission factor parameters, first complete the configuration of the production material information involved in the energy management and raw material management functions, and configure emission factor parameters and calculation formulas for emission factors respectively for these name information; for emission factor parameter information, reserve ten factor parameter fields. In terms of the emission factor calculation formula, by configuring parameter value fields for independent fields to configure mathematical calculation formulas, obtain the comprehensive emission factor value. In other production processes, involving by-product generation, gas recovery, waste treatment, and product output, according to the requirements of the accounting standard and combining the actual situation of the enterprise, configure emission factor parameters and calculation formulas, and according to the process characteristics, the result summary method of relevant factor formulas should be indicated as reduction or increase. Combine a series of calculated comprehensive emission factor values with the corresponding production material treatment volume to obtain the corresponding carbon emissions.

[0142] Production Activity Management Module: Integrate production plans, actual production data, and equipment data, match the usage of each energy and raw material with the process steps in the production process management module, and calculate the carbon emissions of each energy, product carbon emissions, and enterprise carbon emissions data according to the energy emission factor of the process;

[0143] Carbon Emission Quota Calculation Module: Calculate the amount of carbon emission quota issued through integrating the data and algorithm models of each module.

[0144] Specifically, in the carbon emission quota calculation module:

[0145] Based on the production quantity of the product and the comprehensive greenhouse gas emission quantity during the production process of the product, obtain the product carbon emission intensity of the current year, and combine the carbon emission quota quantity received over the years and the approved product carbon emission benchmark to analyze the development trend of carbon emission quotas, and calculate the carbon emission quota and quota surplus quantity of the current year; the carbon emission quota calculation function includes carbon emission quota issuance trend analysis, product carbon emission intensity trend analysis, and carbon emission quota and quota surplus quantity calculation;

[0146] Analysis of the trend of emission quota allocation: Analyze the average growth rate of the number of carbon emission quotas allocated. Regarding the maintenance of quota allocation information, establish an emission quota management information database, add and maintain the carbon emission quota information received over the years. The detailed information on emission quota allocation includes the carbon emission baseline information of the enterprise's products, indicating the approved carbon emission intensity of each product produced by the enterprise. The input content includes product number, product type name, approved product output, product emission baseline value, and information remarks; Analyze the total value of quota allocation, analyze the quotas received in the first year and the second year up to the current year, and calculate the average growth rate of carbon emission quotas over the years; Analyze the carbon emission intensity and the number of qualified products of each product approved for production by the enterprise, analyze the production emission intensity and the approved product production quantity information of each product approved in the first year and the second year up to the current year, and calculate the average growth rate of the two.

[0147] Analysis of the trend of carbon emission intensity in product production: Analyze the carbon emission intensity of the products in the enterprise's production activities to understand the development trend of the carbon emission intensity of the enterprise's own products. Based on the data accumulated in the maintenance of emission quota allocation information and the production process activities, compare the carbon emission intensity of the products in the first year, the second year up to the previous year, and estimate the carbon emission baseline of each product in the current year. In the production process of products every year, each process will generate energy consumption, raw material consumption, by-product generation, gas recovery, and waste treatment, all of which will generate greenhouse gas emissions. By collecting the energy consumption data in the above production activities and combining the comprehensive emission factor value, the comprehensive greenhouse gas emissions are obtained. Combining with the product output, the greenhouse gas emission intensity of each product in each year is obtained, and the average growth rate of the carbon emission intensity in the enterprise's product production is measured.

[0148] Calculation of carbon quota and carbon quota surplus quantity: Based on the analysis of the trend of emission quota allocation and the trend of carbon emission intensity in product production, calculate the carbon emission quota and the carbon quota surplus quantity from two aspects respectively, providing data support for the formulation of the carbon quota trading plan and the implementation of the carbon emission compliance plan:

[0149] Calculate the current-year carbon emission quota quantity based on the carbon emission quotas allocated over the years: The enterprise analyzes the carbon emission quotas allocated over the years. The enterprise collects the carbon emission quotas and analyzes the annual changes of these quotas to obtain the average growth rate. Based on this growth rate and combined with the carbon emission quota of the previous year, the measured quantity of the current-year carbon emission quota is obtained. Combining with the data collection of energy consumption, raw material consumption, by-product generation, gas recovery, and waste treatment in the production process, the surplus quantity of the carbon emission quota is measured.

[0150] Calculating the carbon emission quota quantity based on the carbon emission intensity of products over the years: The enterprise analyzes the carbon emission intensity of the products produced over the years to obtain the average annual growth rate. If the growth rate in a certain year is greater than the preset standard, the growth rate of the latest subsequent year is taken. Based on this growth rate, combined with the carbon emission intensity of the relevant products in the previous year, the expected carbon emission intensity of the products to be verified in the current year is obtained. By evaluating the quantity of qualified products in the product production, the carbon emission quota quantity in the current year is calculated, and combined with the comprehensive emissions of the product production, the surplus quantity of the carbon emission quota in the current year is calculated.

[0151] Embodiment 3:

[0152] Embodiment 3 is a preferred example of Embodiment 1 to more specifically illustrate the present invention.

[0153] The intelligent carbon quota calculation model mainly includes the following: product management, energy management, raw material management, equipment management, production activity management, emission factor management, production process management, and carbon emission quota calculation. The product management, energy management, raw material management, equipment management, and production process management modules respectively configure and manage the basic production-related data such as products, energy, raw materials, equipment, and processes. The production activity management module integrates the production plan and actual production data, and the equipment acquisition data, matches the usage of each energy and raw material with the process steps in the production process management module, and calculates data such as the carbon emissions of each energy, the carbon emissions of products, and the carbon emissions of the enterprise according to the process, combined with the emission factors of energy provided by the emission factor management module. Finally, the carbon emission quota calculation module calculates the reasonable carbon emission quota issuance quantity through integrating the data of each module, relevant algorithm models, and according to relevant policies and goals. This process not only ensures the comprehensiveness and accuracy of the data, but also improves the efficiency and transparency of carbon emission management. For the detailed technical function blueprint, see Figure 1 , and for the detailed calculation flowchart, see Figure 2 .

[0154] Among them, (1) The function description of the function blueprint is as follows:

[0155] 101 Product management: Manage the finished products of the production enterprise, providing an essential basis for carbon quota calculation. The product management function includes: maintaining the product classification name and maintaining the product information name.

[0156] Among them,

[0157] a) Product Classification Maintenance: Establish a product classification information database. Enterprises manage product classification information according to actual situations, establish a clear product differentiation system, and improve product management efficiency. Product classification name maintenance involves adding, modifying, and querying product types. Specifically, when adding or modifying product classifications, the information entered includes product classification numbers, product classification names (for example, in the steel industry, product classification names can be stainless steel, medium and heavy plates, etc.), product classification descriptions, and remarks. Before saving product classification information, the standardization and uniqueness of the classification numbers and names involved should be verified. When either of these two pieces of information duplicates other product classification information, the system will prompt that the information is duplicated, and only non-duplicated product classification information can be accepted. When adding, the system automatically generates the primary key of the product classification ID; when modifying, specific product classification information is changed based on the product classification ID primary key; when querying, relevant product classification information is retrieved according to the entered conditions (such as classification numbers, classification names).

[0158] b) Product Name Maintenance: Establish a product name information database, which is associated with product classifications. Enterprises manage product name information according to actual situations to accurately identify relevant products. Product name maintenance involves operations of adding, modifying, and querying product name information. Specifically, when adding or modifying product names, the information entered includes product numbers, product names, product types, product attributes, product uses, product remarks, etc. Before saving product information data, the uniqueness and standardization of the product numbers and names involved should be verified. When either of these two pieces of information duplicates other product name information, the system will prompt that the information is duplicated, and only non-duplicated product name information can be accepted. When adding, the system automatically generates the corresponding product name ID primary key within the system; when modifying, specific product name information is changed based on the product name ID primary key. When querying, relevant product name information is retrieved according to the entered conditions (note: product numbers, product names, product types).

[0159] 102 Energy Management: Manage the energy used in enterprise production activities to establish a necessary basis for carbon quota calculation. Energy management includes: energy name maintenance and energy classification maintenance.

[0160] Among them,

[0161] a) Energy Classification Maintenance: Establish an energy type information database. Enterprises classify and manage the energy they use according to actual situations, establish a clear energy type differentiation system, adapt to the development and changes of the market and production operations, and improve energy management efficiency. Energy classification maintenance involves adding, modifying, and querying energy classification information. Specifically, when adding or modifying energy classifications, the information entered includes the energy classification number, energy classification name (e.g., fossil energy, renewable energy, etc.), energy classification description, and remarks information, etc. Before saving the energy type information, the uniqueness and standardization of the energy classification number and energy classification name should be verified. When either of these two pieces of information duplicates with other energy classification information, the system prompts that the information is duplicate, and only non-duplicate information can be accepted. When adding, the system automatically generates the corresponding primary key of the energy classification ID; when modifying, specific energy classification information is changed based on the primary key of the energy classification ID; when querying, energy classification information is retrieved based on the entered conditions (note: energy classification number, energy classification name).

[0162] b) Energy Name Maintenance: Establish an energy name information database, which is associated with energy classification maintenance, manage energy names, achieve accurate identification of energy information, and adapt to the development and changes of the market and production operations. Energy name maintenance involves adding, modifying, and querying energy names. Specifically, when adding or modifying energy information, the information entered mainly includes the energy number, energy name, energy type, energy attribute, remarks description, etc. Before saving the energy name information, the uniqueness and standardization of the energy number and energy name should be verified. When either of these two pieces of information duplicates with other energy information names, the system prompts that the information is duplicate, and only non-duplicate classification information can be accepted. When adding, the system automatically generates the corresponding primary key of the energy name ID; when modifying, the corresponding energy name information is changed based on the primary key of the energy name ID; when querying, energy name information is retrieved based on the entered conditions (note: energy number, energy name, energy type, energy attribute). 103 Raw Material Management: Manage the input information of product production required for the purpose of production activities, and establish an essential basis for carbon quota calculation. The raw material management function includes raw material classification maintenance and raw material name maintenance.

[0163] 103 Raw Material Management

[0164] a) Raw material classification maintenance: Establish a raw material classification information database. Enterprises classify and manage raw materials according to actual situations, establish a clear raw material differentiation system, adapt to the development and changes of the market and production operations, and improve the comprehensive management efficiency of raw materials. Raw material classification maintenance involves adding, modifying, and querying raw material classification names. Specifically, when adding or modifying raw material classifications, the information entered includes, but is not limited to, raw material classification numbers, raw material classification names (such as main raw materials, auxiliary raw materials, outsourced semi-finished products, etc.), and raw material classification descriptions. Before saving raw material classification information, the uniqueness and standardization of raw material classification numbers and raw material classification names should be verified. When the above information is repeated with other information, the system prompts that the information is repeated, and only non-repeated raw material classification information can be accepted. When adding, the system automatically generates the primary key of the raw material classification ID; when modifying, specific raw material classification information is changed based on the raw material classification ID primary key; when querying, raw material classification information is retrieved based on the entered conditions (raw material classification number, raw material classification name).

[0165] b) Raw material name maintenance: Establish a raw material name information database, which is associated with raw material classifications, manage raw material information, achieve accurate identification of raw material information, adapt to the development and changes of the market and production operations, and improve the management efficiency of raw materials. Raw material information maintenance involves adding, modifying, and querying raw material names. Specifically, when adding or modifying raw materials, the information entered includes, but is not limited to, raw material numbers, raw material names, raw material classification information, raw material attributes, raw material uses, whether carbon emissions are involved, and remarks information. Before saving raw material information, the uniqueness and standardization of raw material numbers and raw material names should be verified. When either of the two pieces of information is repeated with other raw material information, the system prompts that the information is repeated, and only non-repeated raw material information can be accepted. When adding, the system automatically generates the primary key of the raw material name ID; when modifying, specific raw material name information is changed based on the raw material name ID primary key; when querying, raw material name information is retrieved based on the entered conditions (raw material number, raw material name, raw material classification information, raw material attribute, raw material use, whether carbon emissions are involved).

[0166] 104 Equipment management: Manage the intelligent networked equipment used in enterprise production activities, obtain production activity data through the equipment, and provide an important data source for carbon quota calculation. The equipment management function includes equipment information maintenance, operation data management, and operation monitoring management.

[0167] Among them,

[0168] a) Equipment Information Maintenance: Manage the information of intelligent connected devices (such as intelligent flow meters, intelligent weighing machines, intelligent sensors, etc.) that participate in activity data collection during the production process. Through the application of Internet of Things technology, collect production activity data from these devices. By maintaining this equipment information, ensure the accuracy of equipment information management and the integrity of data collection. The equipment information maintenance function includes equipment name information maintenance and equipment parameter information maintenance. Among them, equipment name maintenance is to add, modify, and query the basic information of the equipment. Specifically, when adding or modifying equipment information, the information entered includes equipment number, equipment name, equipment model, equipment serial number, equipment manufacturer, production date, installation location, installation date, technical parameters, communication protocol, startup status, and remarks. Before saving the equipment information, the uniqueness and standardization of the equipment number, equipment name, and equipment serial number should be verified. When any one of the information is repeated with other equipment name information, the system prompts that the information is repeated, and only non-repeated equipment information can be received. When adding, the system automatically generates the equipment name ID primary key; when modifying, based on the equipment name ID primary key, change the equipment name information; when querying, retrieve the equipment name information according to the input of conditions (equipment number, equipment name, equipment model, equipment serial number, equipment manufacturer, production date, installation location, installation date, technical parameters, communication protocol, startup status). Equipment parameter information maintenance is based on equipment name information maintenance, manage the production activity parameter information that can be collected from the equipment, and add, modify, and query this information. The information entered includes equipment measurement activity number, measurement activity name, equipment number, measurement type, and measurement unit. When adding, the system automatically generates the equipment parameter ID primary key; when modifying, based on the equipment parameter ID primary key, change the equipment parameter information; when querying, retrieve the equipment parameter information according to the input of conditions (measurement activity number, measurement activity name, equipment number, measurement type).

[0169] b) Operation Data Management: Collect production activity data from the source of intelligent connected devices. According to the actual management needs of the enterprise and the characteristics of different intelligent devices, collect and extract the results of equipment operation activities at the minimum time interval (such as extracting by day), master the production operation activity data associated with each equipment, and perform summary and classification. It is mainly divided into two stages:

[0170] 1. Source Data Collection and Data Format Processing

[0171] Data collection should be carried out in the following steps: The first step: Collect raw data from source devices. Develop a set of scheduled task programs, deploy them in intelligent devices, and set an appropriate frequency to generate data files in the original format. The file formats can be CSV, XML, JSON, etc. Transfer these files to the background server through the Internet of Things connection for the backend program to read and subsequent processing. The second step: After the data files are transferred to the server, considering the phenomenon of inconsistent data formats caused by the characteristics of different devices, develop a set of backend programs for data file processing and build a raw database of device activities to re-organize and store the formats of these activity data, realizing data aggregation and format unification. After processing, according to the characteristics of different devices, summarize the parameter information in the production field such as quality information, volume information, concentration information, etc. collected from the devices. The content should include measurement record number, measurement record name, measurement activity number, device number, measurement record time, measurement value, measurement type, and explanatory remarks. The last step: To ensure the operation efficiency of the system and prevent the reduction of the system operation efficiency caused by the massive data in the database, data archiving should be carried out regularly. Data outside the time statistics range should be transferred to the archive database to improve the processing efficiency of the subject data table.

[0172] 2. Data Classification and Summarization

[0173] According to the actual management needs, summarize the statistical information of different measurement types with different time spans. Different statistical databases with different time spans (for example: monthly) can be established respectively to ensure the effective operation of the summary data display. The statistical information includes: summary statistics number, summary statistics name, measurement activity number, start date, end date, statistical value, measurement type, calculation date.

[0174] c) Operation Monitoring and Management: Establish and develop a set of device operation monitoring programs. Based on the device basic information maintenance function, master the current operation status of these intelligent devices to facilitate users to ensure that each device always maintains a normal operation status. Device operation monitoring and management includes device operation status monitoring function and device fault maintenance function. Regarding the device operation status monitoring function, the information content includes device number, device name, data transmission frequency, device operation status, and last data processing time. When the device information is initially entered into the system, the original operation status information of the device is the initial status, and the last data processing time is empty information. When determining the device operation status, based on the data sending frequency and the system's last data processing time, combined with the system's current time, determine whether the device operation status is normal. Through the execution of the scheduled task mechanism, when the last data processing time is later than the specified time, the device operation status can be determined as abnormal. When data collection is abnormal, the system promptly feedbacks the abnormal status of the corresponding device for device management personnel to handle in a timely manner to ensure that the intelligent device always maintains a normal data collection status. Regarding the device fault maintenance function, for devices in an abnormal state, when the device repair and processing are completed, fill in the fault repair information. The input content should include the modification activity number, problem content description, fault start time, fault end time, and solution method description.

[0175] 105 Emission Factor Management: Establish a set of carbon emission factor databases for the enterprise's production and business activities, including raw material consumption, energy consumption, waste treatment, gas recovery, by-product generation, and product output. Through this function, configure carbon emission factor parameters for the above specific contents, establishing an important bridge for the calculation of carbon emission quotas and carbon quota surplus quantities. The emission factor management function includes accounting standard maintenance, emission factor parameter and calculation formula configuration.

[0176] Among them,

[0177] a) Accounting Standard Maintenance: Establish an accounting method standard information database to provide operation standards for carbon emission accounting during the product production process, improving the pertinence and accuracy of carbon emission quota calculation. The accounting standard maintenance function includes the addition, modification, and query of accounting standards. When adding and modifying, the information entered includes accounting standard number, accounting standard name, release year, applicable industry, remarks information, and upload of document standard information. Before saving the accounting standard information, verify the uniqueness and standardization of the accounting standard number and name. Only non-repeated numbers and names can be accepted. When adding, the system automatically generates the accounting standard ID primary key; when modifying, based on the accounting standard ID method primary key, change the information content of the accounting standard method; when querying, relevant accounting standard information can be retrieved according to conditions (accounting standard number, accounting standard name, release year, start year of use, applicable industry).

[0178] b) Factor parameter and calculation formula configuration: Associated with the accounting standard maintenance function, establish a library of emission factor parameters and calculation formula rules. Combine the actual management needs of the enterprise to configure emission factor parameters and related calculation formulas for production materials (such as energy, raw materials, waste, by-products) and products to ensure the compliance and transparency of the measurement. The configuration of factor parameters and calculation formulas is mainly divided into two stages:

[0179] 1. Establish basic information of calculation rules: Indicate the overview information of factor parameters and calculation formulas. The established basic information includes calculation rule number, calculation rule name, accounting standard information, and remarks information. Before adding or modifying basic information, the uniqueness and standardization of the calculation rule number and calculation rule name should be verified. When either of the two pieces of information is repeated with other information, the system prompts that the information is repeated, and only non-repeated information can be accepted. When adding, the system automatically generates the primary key of the accounting rule ID; when modifying, the content of the basic information is changed according to the primary key of the basic information ID; when querying, the content of the basic information is retrieved based on the input of conditions (calculation rule number, calculation rule name, accounting standard name);

[0180] 2. Configure detailed calculation rules: Establish corresponding details, configure production material information, and configure emission factor parameter information and calculation formula information for specific columns of production materials. Regarding emission factors for energy consumption and raw material consumption, before configuring emission factor parameters, the configuration of production material information involved should be completed in the energy management and raw material management functions first. Emission factor parameters and calculation formulas for emission factors should be configured respectively for these name information. The content entered includes production material number, production material name, emission factor parameter information, emission factor calculation formula, and remarks; when each piece of information is established, the system automatically generates the production material ID primary key. For emission factor parameter information, ten factor parameter fields are reserved to meet the diversity of factor parameters in the production process. Each factor parameter field includes parameter name, parameter value, parameter unit, parameter type (note: default value or detection value), and summary method (note: increase or decrease). In terms of emission factor calculation formulas, since each factor parameter consists of one or more independent factor parameters, by configuring parameter value fields for independent fields with mathematical calculation formulas, the comprehensive emission factor value is finally obtained. The parameter value can be configured with the default value in the accounting standard or the detection value according to the requirements of the accounting standard. For example: In terms of energy, the emission factors of energy (such as anthracite, gasoline, natural gas, etc.) are generally composed of three parameters: net calorific value at constant volume, carbon content per unit calorific value, and carbon oxidation rate. Each parameter has specific parameter values, parameter units, and parameter types (such as default value or detection value). Finally, a calculation formula needs to be configured to associate these three parameters to obtain the comprehensive emission factor (such as net calorific value at constant volume x carbon content per unit calorific value x carbon oxidation rate x 44 / 12). When calculating, the summary method should be indicated as "increase". At the same time, in other production processes, by-products generation, gas recovery, waste treatment, and product output are involved, and there are also multiple emission factor parameter phenomena. According to the requirements of the accounting standard and combined with the actual situation of the enterprise, the configuration of emission factor parameters and calculation formulas should be carried out, and according to the process characteristics, the summary method of the results of relevant factor formulas should be indicated as "decrease" or "increase". Finally, a series of calculated comprehensive emission factor values are combined with the corresponding production material treatment volume to obtain the corresponding carbon emissions.

[0181] 106 Production process management: Manage the production activities of the enterprise. Through the equipment management function, collect and count the quantified data of energy consumed, raw materials consumed, waste treated, gas recovered, by-products generated, and products produced by the products in the production processes passed through over a period of time, so as to comprehensively master the energy consumption information and output quantity information of the entire production process of the products, providing a complete data basis for carbon quota calculation. The production process management function includes production process flow maintenance and production process activity statistics.

[0182] Among them,

[0183] a) Process Flow Maintenance: Establish a production process flow information database. Based on the actual production process situation, the enterprise defines each process from raw material input to finished product output in terms of the final product output, forming clear and complete process flow information. Production process flow maintenance includes adding and modifying production process information, and then configuring production materials and associated intelligent device information for each process. The first step: Associate with the product information in the product management function. For each product, add or modify the basic production process information of the product. The input basic information includes process number, process name, process description, process sequence number, and remarks information. Before saving the production process information, the uniqueness and standardization of the process number and process name should be verified; when the process number and process name are repeated with other process information, the system prompts that the process information is repeated. Only non-repeated process information can be received by the system. When adding, the system automatically generates the primary key of the production process information ID and the process sequence number increases sequentially; when modifying, based on the production process information ID primary key, specific production process basic information is changed (note: the process sequence number cannot be changed); when querying, based on the input conditions (process number, process name), the content of the production process information is retrieved. The second step: Associate with the basic production process information and configure detailed information for each established production process, including detailed energy information, raw material information, waste treatment information, gas recovery information, and by-product generation information columns. The third step: Associate with the equipment information maintenance and monitoring activity information. For each column item in each process, configure specific equipment monitoring activity information. Based on the measurement record data accumulated in the equipment operation activity management function, automatically obtain the quantified index data of specific production material consumption and treatment, and realize the collection of equipment operation data.

[0184] b) Process Activity Data Statistics: Based on the data established by the equipment operation activity data management function and the production process flow maintenance function, display the quantified data information of energy consumption, raw material consumption, waste treatment, gas recovery, and by-product generation involved in each process in terms of product output. Specifically as follows:

[0185] *In terms of energy, according to actual management needs, establish an energy statistics database for a specific time period (e.g., monthly). Based on the association between specific energy names and equipment measurement activities, automatically generate consumption information for specific energy names. The information collected includes energy consumption number, energy classification, energy name, cumulative energy statistical value, equipment measurement activity number, measurement start time, measurement end time, data statistics date, etc. When data is created, the system automatically generates a product energy name consumption primary key ID for each piece of data; in addition, considering factors such as equipment scheduled maintenance, shutdown, and other reasons that result in the inability to collect data in an automated manner, data should be collected manually and supplemented. Develop an energy comprehensive statistics collection database, which is manually entered through the system page. The content collected includes: energy name statistical number (manual), energy classification, energy number, energy name, statistical time range, comprehensive energy statistical value, energy statistical value type, and proof material upload, etc.;

[0186] *In terms of raw material consumption, according to actual management needs, establish a raw material consumption statistics database for a specific time period (e.g., monthly). Based on the association between specific raw material names and equipment measurement activities, automatically generate consumption information for raw material names. The information collected includes raw material statistics number, raw material name, raw material classification, measurement activity number, raw material comprehensive statistical value, measurement start time, measurement end time, data statistics date, etc. When data is created, the system automatically generates a raw material name consumption primary key ID for each piece of data; in addition, considering factors such as equipment scheduled maintenance, shutdown, and other reasons that result in the inability to collect data in an automated manner, data should be collected manually. Develop a raw material comprehensive statistics collection database, which is manually entered through the system page. The content collected includes: raw material name statistical number (manual), raw material classification, raw material number, raw material name, statistical start time, statistical end time, raw material comprehensive statistical value, raw material statistical value type, and proof material upload, etc.

[0187] *In terms of waste treatment, according to actual management needs, establish a waste treatment statistics database for a specific time period (e.g., monthly). Based on the association between specific waste names and equipment measurement activities, automatically generate consumption information for specific waste names. The information collected includes waste treatment number, waste number, waste name, measurement activity number, waste treatment comprehensive statistical value, measurement start time, measurement end time, data statistics date, etc. When data is created, the system automatically generates a waste treatment system primary key ID for each piece of data; in addition, considering factors such as equipment scheduled maintenance, shutdown, and other reasons that result in the inability to collect data in an automated manner, data should be collected manually. Develop a waste treatment data collection database and program, which is manually entered through the system page. The content collected includes: waste number, waste name, waste treatment report time period, waste treatment comprehensive statistical value, waste treatment value type, and proof material upload, etc.

[0188] *In terms of gas recovery, according to the actual carbon management needs, a gas recovery database for a specific time period (e.g., monthly) is established. Based on the association between specific waste item columns and equipment measurement activities, the recovery information for specific gas items is automatically generated. The information collected includes the recovered gas number, recovered gas name, gas recovery volume, average greenhouse gas concentration, measurement start time, measurement end time, data statistics date, etc. When the data is created, the system automatically generates a primary key ID for the recovered greenhouse gas system for each piece of data; in addition, considering factors such as equipment scheduled maintenance, shutdown, and other reasons that prevent data from being collected in an automated manner, data should be collected manually. A greenhouse gas recovery data collection database and program are developed, and manual entry is made through the system page. The content collected includes: recovered gas number, recovered gas name, comprehensive statistical value of recovered gas, type of recovered gas statistical value, measurement activity start time, measurement activity end time, and upload of supporting materials, etc.

[0189] *In terms of product output, according to the actual management needs, a product output information database for a specific time period (e.g., monthly) is established. Based on the association between specific product item columns and equipment measurement activities, the output information for specific products is automatically generated. The information collected includes the product number, product name, product output, measurement start time, measurement end time, data statistics date, etc. When the data is created, the system automatically generates a primary key ID for product output for each piece of data; in addition, considering factors such as equipment scheduled maintenance, shutdown, and other reasons that prevent data from being collected in an automated manner, data should be collected manually. A gas recovery data collection database and program are established and developed, and manual entry is made through the system page. The content collected includes: product number, product name, product output, start time, end time, and upload of supporting materials, etc.

[0190] 107 Carbon emission quota calculation:

[0191] For power generation enterprises included in the national carbon market, the quota will be calculated based on the enterprise's generating units.

[0192] 1) Determine the unit type, which is mainly divided into coal-fired units and gas-fired units, and will be specifically divided into four categories according to the fuel type: conventional coal-fired units above 300MW, conventional coal-fired units at and below 300MW, unconventional coal-fired units such as coal gangue, coal slime, and water coal slurry (including coal-fired circulating fluidized bed units), and gas-fired units.

[0193] 2) For the unit categories under different unit types, judge the basic data such as the installed capacity level of the unit, the cooling method of the condenser, the unit load (output) coefficient, the unit heat supply ratio, the unit heat supply, and the unit power supply, and obtain the power supply emission reference value, the cooling method correction coefficient, the unit heat supply correction coefficient, the unit load (output) correction coefficient, and the heat supply emission reference value of the unit, which are used to calculate the power supply quota and the heat supply quota of each unit.

[0194] 3) Calculation method for the quota of coal-fired units: Total unit quota = Total power supply quota + Total heat supply quota. Among them, Total power supply quota = Actual power supply × Power supply emission reference value × Cooling method correction coefficient × Unit heat supply correction coefficient × Unit load (output) correction coefficient; Heat supply quota = Heat supply × Heat supply reference value.

[0195] 4) Calculation method for the quota of gas-fired units: Total unit quota = Total power supply quota + Total heat supply quota. Among them, Total power supply quota = Actual power supply × Power supply emission reference value × Unit heat supply correction coefficient; Heat supply quota = Heat supply × Heat supply reference value.

[0196] Specifically, based on the production quantity of the product and the comprehensive greenhouse gas emission quantity during the production process of the product, obtain the product carbon emission intensity in the current year, and combine the carbon emission quota quantity received over the years and the approved product carbon emission reference to analyze the development trend of the carbon emission quota, and measure the carbon emission quota and the quota surplus quantity in the current year. The carbon emission quota measurement function includes the analysis of the carbon emission quota issuance trend, the analysis of the product carbon emission intensity trend, and the measurement of the carbon emission quota and the quota surplus quantity. Among them,

[0197] a) Analysis of the trend of emission quota allocation: Analyze the average growth rate of the quantity of carbon emission quotas allocated. Regarding the maintenance of quota allocation information, establish an emission quota management information database, add and maintain the carbon emission quota information received over the years, and provide reference for the calculation of the enterprise's current-year carbon quota. The maintenance of emission quota allocation information includes operations such as adding, modifying, and querying emission quota allocation information. Emission quota allocation information includes basic quota information and detailed quota information. Among them, basic quota information includes emission quota number, emission quota name, emission quota year, quantity of carbon emission quota allocated, attachment upload, and remarks. Before saving the information, the uniqueness and standardization of the emission quota number and emission quota name should be verified. When either of these two pieces of information is repeated with other information, the system prompts that the information is repeated, and only non-repeated information can be accepted. When adding, the primary key of the basic emission quota information ID is automatically generated by the system; when modifying, the content of the basic emission quota information is changed based on the primary key of the basic emission quota information ID; when querying, the content of the basic emission quota information is retrieved according to the input of conditions (emission quota number, emission quota name). The detailed emission quota allocation information includes the carbon emission benchmark information of the enterprise's products, indicating the approved carbon emission intensity of each product produced by the enterprise. The input content includes product number, product type name, approved product output, product emission benchmark value, information remarks, etc. From the perspective of the development trend of emission quota allocation, it can be analyzed from two dimensions. First, analyze the total value of quota allocation, analyze the quotas received in the first year and the second year until the current year, and calculate the average growth rate of carbon emission quotas over the years. Second, analyze the carbon emission intensity and the quantity of qualified products of each product approved for production by the enterprise, analyze the production emission intensity and the approved product production quantity information of each product approved in the first year, the second year until the current year, and calculate the average growth rate of the two.

[0198] b) Analysis of the trend of carbon emission intensity in product production: Analyze the carbon emission intensity of the enterprise's products in production activities to understand the development trend of the carbon emission intensity of the enterprise's own product production. Based on the data accumulated in the maintenance of emission quota allocation information and the production process activity function, compare the carbon emission intensity of the products in the first year, the second year until the previous year, and estimate the carbon emission benchmark of each product in the current year. Specifically, every year during the product production process of the enterprise, energy consumption, raw material consumption, by-product generation, gas recovery, and waste treatment in each process all generate greenhouse gas emissions. By collecting the energy consumption data in the above production activities and combining with the comprehensive emission factor value, the comprehensive greenhouse gas emissions are obtained. Combining with the product output, the greenhouse gas emission intensity of each product in each year is obtained, and the average growth rate of the carbon emission intensity of the enterprise's product production is calculated.

[0199] c) Carbon quota and carbon quota surplus quantity measurement: Based on the analysis of the emission quota issuance trend and the carbon emission intensity trend of product production, measure the carbon emission quota and carbon quota surplus quantity from two aspects respectively, providing data support for the formulation of the carbon quota trading plan and the implementation of the carbon emission compliance plan. Enterprises can use the following two methods to measure the carbon emission quota quantity:

[0200] 1) Measure the current-year carbon emission quota quantity based on the carbon emission quotas allocated over the years: Enterprises can analyze according to the carbon emission quotas allocated over the years. This method is applicable to production enterprises that have carried out carbon compliance activities and whose production capacity scale and production technology process have not changed much. Enterprises collect the carbon emission quotas over the years, analyze the annual changes of these quotas, and obtain the average growth rate. Based on this growth rate and combined with the carbon emission quota of the previous year, the measured quantity of the current-year carbon emission quota is obtained. Further combined with the data collection of energy consumption, raw material consumption, by-product generation, gas recovery, and waste treatment in the production process of each product of the present invention, the surplus quantity of the carbon emission quota is measured.

[0201] 2) Measure the carbon emission quota quantity based on the carbon emission intensity of products over the years: Enterprises can analyze according to the carbon emission intensity of the products produced over the years. This is applicable to enterprises that have carried out carbon compliance for a short time or have undergone technological reforms. Enterprises collect the carbon emission intensity information of each product over the years, analyze the annual changes of the emission intensity of each product, and obtain the average growth rate each year. If the growth rate in a certain year is too large (for example: a change rate of 30%), then take the growth rate of the latest subsequent years. Based on this growth rate and combined with the carbon emission intensity of the relevant products in the previous year, the predicted carbon emission intensity of the products to be verified in the current year is obtained. By evaluating the quantity of qualified products in product production, the carbon emission quota quantity in the current year is measured. At the same time, combined with the comprehensive emissions of product production, the carbon emission quota surplus quantity in the current year is measured.

[0202] (2) The carbon emission quota measurement process is described as follows:

[0203] By conducting research on the production and operation activities of different industries, conducting relevant business investigations on key users to determine the measurement data sources, measurement methods, and measurement columns, and carrying out corresponding customized development and comprehensive configuration for some complex functional requirements to meet the requirements in the calculation process.

[0204] 1. Basic information configuration

[0205] Basic information configuration is the first stage of carrying out the planning and design of carbon quota measurement, laying a foundation for the measurement of carbon quota quantity. The specific steps are as follows:

[0206] 1) Production data information configuration: The collection of production data information (product information, energy information, raw material information, equipment information) is completed through the product management function, energy management function, raw material management function, and equipment management function. Specifically, in terms of product management, energy management, and raw material management, classification information is first set according to the actual business situation of the enterprise. Secondly, name information is set.

[0207] 2) Emission factor and calculation formula configuration: Through the accounting standard maintenance function, the content of accounting standard information is established, providing a basis for the configuration of carbon emission factors and calculation formulas. According to its actual needs, the enterprise configures emission factor parameters and calculation formulas for comprehensive emission factors for specific products, energy, raw materials, waste treatment, and by-product generation in the factor parameter and calculation formula configuration function. Among them, specific waste names and by-product information are configured in this function.

[0208] 3) Intelligent connected device configuration: Through the equipment information maintenance function, the intelligent device information involved in the production process activities of the production enterprise is added and maintained, indicating the data types (such as quality, volume, concentration, etc.) that can be collected by different devices for production data processing.

[0209] 4) Process flow configuration: Through the process flow maintenance function, taking different product outputs as the dimension, the required production processes are configured according to the actual production situation of the enterprise, and the production data information (energy, raw materials, by-products, waste, etc. column content) involved in each process is configured. Then, intelligent connected device information is configured for these column contents to realize the information collection of production data consumption or processing data. 2. Production activity data management

[0210] 2. Production activity data management

[0211] Production activity data management is the second stage of carbon quota measurement. By applying Internet of Things technology, production activity data is collected from intelligent connected devices, and the energy consumption data and product output data of each production process in the product production process are mastered, providing a complete data basis for the measurement of the carbon quota quantity of the production enterprise. To ensure data integrity, the following steps are taken:

[0212] a) Application of source data generation program: This step is applied to the device side and can be developed by the device manufacturer or by a contracted software developer and deployed on the intelligent connected device to enable relevant devices to send data regularly.

[0213] b) Operation data management: Through the device operation data management function, the summary information and average value information of the data extracted from each device over a period of time are realized. For example: information such as quality information, volume information, concentration, etc. that can be provided by intelligent devices. These information and data are all associated with production data and product output.

[0214] c) Equipment operation monitoring: Through the equipment operation monitoring and management function, monitor the operation status of each device to ensure that the device is in a "normal" state and ensure that the backend service processes data regularly. In case of anomalies, managers can quickly inspect and maintain the equipment, restore the abnormal equipment to normal in a timely manner, and re-collect the data for the affected time period.

[0215] d) Process activity data statistics: Through the process activity data statistics function, summarize the data on energy consumption, raw material consumption, waste treatment, gas recovery, and by-product generation involved in the relevant processes passed through during product production. At the same time, through this function, supplement the relevant data that cannot be collected by the equipment.

[0216] 3. Carbon emission quota calculation

[0217] After completing the above two stages, the carbon emission quota calculation can be carried out. For enterprises that have been carrying out carbon compliance activities for a short time, the carbon emission intensity of different product productions can be obtained through the carbon emission intensity trend analysis function of product production, and combined with the energy consumption of different product productions and the product output, calculate the enterprise's carbon emission quota quantity. For enterprises that have participated in the carbon compliance market for many years, the average growth rate can be obtained based on the trend of historical emission quota allocation, calculate the enterprise's current quota, and combined with the carbon emission intensity information of product production, further obtain the carbon emission surplus quantity.

[0218] Those skilled in the art know that in addition to implementing the system and its various devices, modules, and units provided by the present invention in the form of pure computer-readable program code, the method steps can be logically programmed to enable the system and its various devices, modules, and units provided by the present invention to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers, etc. to achieve the same function. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be regarded as the structure within the hardware component; the devices, modules, and units for implementing various functions can also be regarded as either software modules for implementing the method or the structure within the hardware component.

[0219] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Without conflict, the embodiments of the present application and the features in the embodiments can be arbitrarily combined with each other.

Claims

1. An intelligent carbon quota measurement system, characterized in that, Including: Product management module: Configure and manage product production data; Energy management module: Configure and manage energy production data; Raw material management module: Configure and manage raw material production data; Equipment management module: Configure and manage equipment data; Production process management module: Configure and manage process steps; Emission factor management module: Provide energy emission factors; Production activity management module: Integrate production plans, actual production data, and equipment data, match the usage of each energy and raw material with the process steps in the production process management module, and calculate the carbon emissions of each energy, product carbon emissions, and enterprise carbon emissions data according to the process energy emission factors; Carbon emission quota calculation module: Calculate the amount of carbon emission quota issued through comprehensive data and algorithm models of each module.

2. The intelligent carbon quota calculation system according to claim 1, characterized in that: In the said product management module: Manage the finished products of production enterprises. The product management functions include: maintenance of product classification names and maintenance of product information names; Product classification maintenance: Establish a product classification information library. Enterprises manage product classification information according to actual situations, establish a product differentiation system. The maintenance of product classification names adds, modifies, and queries the types of products. When adding or modifying product classifications, the information entered includes product classification numbers, product classification names, product classification descriptions, and remarks. Before saving product classification information, verify the standardization and uniqueness of the involved classification numbers and classification names. When adding, the system automatically generates the primary key of the product classification ID. When modifying, change the classification information of specific products based on the product classification ID primary key. When querying, retrieve relevant product classification information according to the entered conditions; Product name maintenance: Establish a product name information library, which is associated with product classifications. Enterprises manage product name information according to actual situations to identify relevant products. The maintenance of product names performs operations of adding, modifying, and querying product name information; In the said energy management module: Manage the energy used in enterprise production activities. Energy management includes: maintenance of energy names and maintenance of energy classifications; Energy classification maintenance: Establish an energy type information library, classify and manage the used energy, add, modify, and query energy classification information. When adding and modifying energy classifications, the information entered includes energy classification numbers, energy classification names, energy classification descriptions, and remarks. Before saving energy type information, verify the uniqueness and standardization of energy classification numbers and energy classification names. When adding, the system automatically generates the corresponding energy classification ID primary key. When modifying, change specific energy classification information based on the energy classification ID primary key. When querying, retrieve energy classification information according to the entered conditions; Energy Name Maintenance: Establish an energy name information database, associate it with energy classification maintenance, manage energy names, perform addition, modification, and query operations on energy names. Before saving energy name information, verify the uniqueness and standardization of energy numbers and energy names. When adding, the system automatically generates the corresponding energy name ID primary key; when modifying, change the corresponding energy name information based on the energy name ID primary key; when querying, retrieve energy name information according to the entered conditions. In the raw material management module: Manage the input information of products required for production activities. The raw material management functions include raw material classification maintenance and raw material name maintenance. Raw Material Classification Maintenance: Establish a raw material classification information database, classify and manage raw materials. Raw material classification maintenance is the act of adding, modifying, and querying raw material classification names. When adding or modifying raw material classifications, the entered information includes raw material classification numbers, raw material classification names, and raw material classification descriptions. Raw Material Name Maintenance: Establish a raw material name information database, associate it with raw material classifications, manage raw material information, perform addition, modification, and query operations on raw material names. When adding or modifying raw materials, the entered information includes raw material numbers, raw material names, raw material classification information, raw material attributes, raw material uses, whether carbon emissions are involved, and remarks information.

3. The carbon quota intelligent calculation system according to claim 1, characterized in that In the equipment management module: Manage the intelligent networked equipment used in enterprise production activities, obtain production activity data through the equipment, and provide a data source for carbon quota calculation. The equipment management functions include equipment information maintenance, operation data management, and operation monitoring management: Equipment Information Maintenance: Manage the intelligent networked equipment information involved in collecting activity data during production. Through the application of Internet of Things technology, collect production activity data from the equipment. The equipment information maintenance function includes equipment name information maintenance and equipment parameter information maintenance. Equipment name maintenance performs addition, modification, and query operations on the basic equipment information. When adding or modifying equipment information, the entered information includes equipment numbers, equipment names, equipment models, equipment serial numbers, equipment manufacturers, production dates, installation locations, installation dates, technical parameters, communication protocols, startup status, and remarks; Equipment parameter information maintenance manages the production activity parameter information that can be collected from the equipment on the basis of equipment name information maintenance, performs addition, modification, and query operations on this information, and the entered information includes equipment measurement activity numbers, measurement activity names, equipment numbers, measurement types, and measurement units. Operation Data Management: Collect production activity data from the source of intelligent networked equipment, according to the actual management needs of the enterprise and the characteristics of different intelligent devices, collect and extract the results of equipment operation activities at the smallest time interval, master the production operation activity data associated with each equipment, and perform summary and classification, which are divided into source data collection and data format processing and data classification and summary. Source data collection and data format processing: Step 1: Collect raw data from source devices, develop a set of scheduled task programs, deploy them in intelligent devices, and set an appropriate frequency to generate raw format data files, and transfer these files to the background server through the Internet of Things connection for the backend program to read and subsequent processing; Step 2: After the data files are transferred to the server, develop a set of backend programs for data file processing and build a raw database of device activities, re-organize and store the formats of these activity data to achieve data aggregation and format unification. After processing, summarize the parameter information collected from the devices according to different device characteristics. Step 3: Regularly perform data archiving, and transfer the data outside the time statistics range to the archive database; Data classification and summarization: Summarize the statistical information of different measurement types according to different time spans, and establish statistical libraries with different time spans respectively. The statistical information includes: summary statistical number, summary statistical name, measurement activity number, start date, end date, statistical value, measurement type, calculation date; Operation monitoring and management: Establish and develop a set of device operation monitoring programs. Based on the device basic information maintenance function, master the current operation status of these intelligent devices to facilitate users to ensure that each device always maintains a normal operation status. Device operation monitoring and management includes device operation status monitoring function and device fault maintenance function. Regarding the device operation status monitoring function, when the device information is initially entered into the system, the original operation status information of the device is the initial status, and the last data processing time is empty information. When determining the device operation status, according to the data sending frequency and the system's last data processing time, combined with the system's current time, determine whether the device operation status is normal. Through the execution of the scheduled task mechanism, when the last data processing time is later than the specified time, the device's operation status is determined to be abnormal; when data collection is abnormal, the system feedbacks the abnormal status of the corresponding device for device management personnel to handle in a timely manner to ensure that the intelligent device always maintains a normal data collection status. Regarding the device fault maintenance function, for devices in an abnormal state, when the device repair and processing are completed, fill in the fault repair information, and the input content should include the modified activity number, problem content description, fault start time, fault end time, and solution description.

4. The carbon quota intelligent calculation system according to claim 1, characterized in that In the production process management module: Manage the production activities of the enterprise, collect and statistically analyze the data consumed by the products in the production processes passed through within a preset time through the device management function. The production process management function includes production process flow maintenance and production process activity statistics. Process flow maintenance: Establish a production process flow information library. According to the actual production process situation of the enterprise, define each process from raw material input to finished product output with the final product output as the dimension. Production process flow maintenance includes the addition and modification of production process information, and then configure the production materials and associated intelligent device information for each process. Step 1: Associate with the product information of the product management function; Step 2: Associate with the basic production process information, and configure detailed information for each established production process, including columns for energy information, raw material information, waste treatment information, gas recovery information, and by-product generation information. Step 3: Associate with the equipment information maintenance and monitoring activity information, and configure specific equipment monitoring activity information for the specific content of each column item in each column of each process. Based on the measurement record data accumulated in the equipment operation activity management function, automatically obtain the quantified index data of specific production material consumption and processing, and achieve the collection of equipment operation data; Process activity data statistics: Based on the data established by the equipment operation activity data management function and the production process flow maintenance function, display the quantified data information of energy consumption, raw material consumption, waste treatment, gas recovery, and by-product generation involved in each process in terms of product output.

5. The carbon quota intelligent calculation system according to claim 1, characterized in that, In the emission factor management module: Establish a set of carbon emission factor databases for the enterprise's production and operation activities, including raw material consumption, energy consumption, waste treatment, gas recovery, by-product generation, and product output. The emission factor management function includes accounting standard maintenance, emission factor parameter and calculation formula configuration; Accounting standard maintenance: Establish an accounting method standard information database to provide operation standards for carbon emission accounting during the product production process, and improve the pertinence and accuracy of carbon emission quota calculation. The accounting standard maintenance function includes the addition, modification, and query of accounting standards. When adding and modifying, the information entered includes the accounting standard number, accounting standard name, release year, applicable industry, remarks information, and upload of document standard information. Before saving the accounting standard information, verify the uniqueness and standardization of the accounting standard number and accounting standard name; Factor parameter and calculation formula configuration: Associate with the accounting standard maintenance function, establish an emission factor parameter and calculation formula rule library, and configure emission factor parameters and related calculation formulas for production materials and products according to the actual management needs of the enterprise. The factor parameter and calculation formula configuration are divided into establishing basic calculation rule information and configuring detailed calculation rule information: Establish basic calculation rule information: Indicate the overview information of factor parameters and calculation formulas. The established basic information includes the calculation rule number, calculation rule name, accounting standard information, and remarks information; Configure calculation rule details: Establish corresponding details, configure production material information, and configure emission factor parameter information and calculation formula information for specific columns of production materials. Regarding energy consumption and raw material consumption emission factors, before configuring emission factor parameters, first complete the configuration of the production material information involved in the energy management and raw material management functions, and configure emission factor parameters and calculation formulas for emission factors for these name information respectively; for emission factor parameter information, reserve ten factor parameter fields. In terms of the emission factor calculation formula, by configuring parameter value fields for independent fields with mathematical calculation formulas, a comprehensive emission factor value is obtained. In other production processes, involving by-product generation, gas recovery, waste treatment, and product output, according to the requirements of the accounting standard and combined with the actual situation of the enterprise, configure emission factor parameters and calculation formulas, and according to the process characteristics, the result summary method of relevant factor formulas should be indicated as reduction or increase. Combine a series of calculated comprehensive emission factor values with the corresponding production material processing volume to obtain the corresponding carbon emissions.

6. The carbon quota intelligent measurement system according to claim 1, characterized in that: In the production activity management module: Calculation of energy carbon emissions: E 能源 = AD 能源 × EF 能源 E 能源 be the carbon emissions related to energy; AD 能源 is the energy consumption; EF 能源 is the carbon emission factor of energy; Calculation of product carbon emissions: E 产品 = AD 产品 × EF 产品 E 产品 is the carbon emission related to the product; AD 产品 is the product output; EF 产品 is the carbon emission factor of the product; Calculation of the total carbon emissions of the enterprise: E = E 燃烧 + E 电 E is the carbon dioxide emissions of power generation facilities; E 燃烧 is the emissions from fossil fuel combustion; E 电 Emissions generated from the purchase of electricity for use E 燃烧 Emissions from fossil fuel combustion; AD i is the activity data for the i-th fossil fuel; EF i is the carbon dioxide emission factor for the i-th fossil fuel; i is the code for the type of fossil fuel; E 电 = AD 电 × EF 电 E 电 Emissions resulting from the purchase of electricity for use, in tonnes of carbon dioxide; AD 电 For the electricity consumption purchased for use; EF 电 is the grid emission factor; In the carbon emission quota measurement module: Based on the production quantity of the product and the comprehensive greenhouse gas emission quantity of the product during the production process, obtain the product carbon emission intensity of the current year, and combine the carbon emission quota quantity received over the years and the approved product carbon emission benchmark to analyze the development trend of carbon emission quotas, and measure the carbon emission quota and quota surplus quantity of the current year; The carbon emission quota measurement function includes analysis of the carbon emission quota issuance trend, analysis of the product carbon emission intensity trend, and measurement of the carbon emission quota and quota surplus quantity; Analysis of the carbon emission quota issuance trend: Analyze the average growth rate of the carbon emission quota quantity issuance. Regarding the maintenance of quota issuance information, establish a carbon emission quota management information database, add and maintain the carbon emission quota information received over the years. The detailed carbon emission quota issuance information includes the carbon emission benchmark information of the enterprise's products, indicating the approved carbon emission intensity of each product produced by the enterprise. The input content includes product number, product type name, approved product output, product emission benchmark value, and information remarks; analyze the total quota allocation, analyze the quotas received in the first year and the second year until the current year, and calculate the average growth rate of the carbon emission quotas over the years; analyze the carbon emission intensity and the number of qualified products of each product approved for production by the enterprise, analyze the production emission intensity and approved product production quantity information of each product approved in the first year and the second year until the current year, and calculate the average growth rate of the two; Trend Analysis of Carbon Emission Intensity in Product Production: Analyze the carbon emission intensity of products in the enterprise's production activities to understand the development trend of the carbon emission intensity of the enterprise's own product production. Based on the data accumulated in the emission quota allocation information maintenance and production process activity functions, compare the carbon emission intensity of products in the first year, the second year, and until the previous year, and estimate the carbon emission benchmark for each product in the current year. During the production process of each product every year, energy consumption, raw material consumption, by-product generation, gas recovery, and waste treatment in the processes all generate greenhouse gas emissions. By collecting the energy consumption data in the above production activities and combining the comprehensive emission factor values, obtain the comprehensive greenhouse gas emissions, and combine with the product output to obtain the greenhouse gas emission intensity of each product every year, and calculate the average growth rate of the carbon emission intensity of the enterprise's product production; Calculation of Carbon Quota and Carbon Quota Surplus Quantity: Based on the trend analysis of emission quota allocation and the trend analysis of carbon emission intensity in product production, calculate the carbon emission quota and carbon quota surplus quantity from two aspects respectively, providing data support for the formulation of the carbon quota trading plan and the implementation of the carbon emission compliance plan: Calculate the current-year carbon emission quota quantity based on the carbon emission quotas allocated over the years: The enterprise analyzes the carbon emission quotas allocated over the years. The enterprise collects the carbon emission quotas and conducts an annual change analysis on these quotas to obtain the average growth rate. Based on this growth rate and combined with the carbon emission quota of the previous year, obtain the estimated quantity of the current-year carbon emission quota. Combine the data collection of energy consumption, raw material consumption, by-product generation, gas recovery, and waste treatment in the production process to calculate the surplus quantity of the carbon emission quota; Calculate the carbon emission quota quantity based on the carbon emission intensity of products over the years: The enterprise analyzes the carbon emission intensity of the products produced over the years to obtain the average growth rate every year. If the growth rate in a certain year is greater than the preset standard, take the growth rate of the latest subsequent year. Based on this growth rate and combined with the carbon emission intensity of the relevant products in the previous year, obtain the estimated carbon emission intensity of the products to be verified in the current year. By evaluating the quantity of qualified products in product production, calculate the carbon emission quota quantity in the current year, and combine with the comprehensive emissions in product production to calculate the carbon quota surplus quantity in the current year.

7. A method for intelligent calculation of carbon quotas, characterized in that, Adopt the carbon quota intelligent calculation system described in any one of claims 1-6, and the execution includes: Step S1: Configure basic information, maintain the product classification and name, energy classification and name, raw material classification and name, equipment information, accounting standard, and process flow, and configure the factor parameters and calculation formulas; Step S2: Manage the production activity data, manage the equipment operation monitoring and data, and count the process activity data; Step S3: Calculate the carbon emission quota based on the configured basic information and production activity data, and analyze the emission quota allocation trend, the carbon emission intensity trend in product production, the calculation of carbon emission quota and quota surplus.

8. The carbon quota intelligent calculation method according to claim 7, characterized in that In the said Step S1: Establish a basis for the calculation of the carbon quota quantity, and the specific steps are as follows: Step S1.1: Production data information configuration: The production data information is collected through the product management function, energy management function, raw material management function, and equipment management function, including product information, energy information, raw material information, and equipment information; in terms of product management, energy management, and raw material management, according to the actual business situation of the enterprise, the classification information is set first, and then the name information is set. Step S1.2: Emission factor and calculation formula configuration: Through the accounting standard maintenance function, the accounting standard information content is established to provide a basis for the configuration of carbon emission factors and calculation formulas; according to its own actual needs, the enterprise configures the emission factor parameters and the calculation formulas of the comprehensive emission factor for the preset specific products, energy, raw materials, waste treatment, and by-product generation in the factor parameter and calculation formula configuration function. Step S1.3: Intelligent connected device configuration: Through the equipment information maintenance function, the intelligent device information involved in the production process activities of the production enterprise is added and maintained, indicating the data types related to production data processing that can be collected by different devices. Step S1.4: Process flow configuration: Through the process flow maintenance function, taking different product outputs as the dimension, the required production processes are configured according to the actual production situation of the enterprise, the production data information involved in each process is configured, and then the intelligent connected device information is configured for these column contents to realize the information collection of the data on the consumption or processing of production data.

9. The carbon quota intelligent calculation method according to claim 7, characterized in that, In the said Step S2: By applying the Internet of Things technology, the production activity data is collected from the intelligent connected devices, and the energy consumption data and product output data of each production process in the product production process are mastered, providing a complete data basis for the calculation of the carbon quota quantity of the production enterprise, and proceeding as follows: Step S2.1: Application of the source data generation program: Applied to the device side, developed by the device manufacturer or by a contracted software developer, and deployed on the intelligent connected device to enable the relevant device to send data regularly. Step S2.2: Operation data management: Through the device operation data management function, the summary information and average value information within a preset time are realized for the data extracted from each device. Step S2.3: Device operation monitoring: Through the device operation monitoring management function, the operation status of each device is monitored to ensure that the device is in the preset normal state, ensure that the backend service processes data regularly, and when a preset abnormality occurs, the management personnel check and maintain the device, promptly restore the abnormal device to normal, and collect the data for the affected time period again. Step S2.4: Process activity data statistics: Through the process activity data statistics function, the data on energy consumption, raw material consumption, waste treatment, gas recovery, and by-product generation involved in the relevant processes passed through in the product production process are summarized, and the relevant data that cannot be collected by the device is supplemented.

10. The carbon quota intelligent calculation method according to claim 7, characterized in that, In the said Step S3: For enterprises with a carbon compliance activity time lower than the preset standard, through the function of analyzing the trend of carbon emission intensity in product production, obtain the carbon emission intensity of different product productions, and combine the energy consumption of different product productions with the product output to calculate the enterprise's carbon emission quota quantity; for enterprises that meet the preset standard for participating in the carbon compliance market, based on the trend of historical emission quota allocation, obtain the average growth rate, calculate the enterprise's current quota, and combine the carbon emission intensity information of product production to obtain the carbon emission surplus quantity.

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