Green carbon management method and platform based on cooperation of Internet of Things

Abstract

The invention discloses a green carbon management method and platform based on Internet of Things cooperation, and relates to the technical field of carbon emission management, and the method comprises the steps: firstly obtaining a carbon emission source and an emission reduction project of a target region, and building an emission list library and an emission reduction project library; using characteristics of a carbon emission source are obtained, carbon emission factors are determined according to the characteristics and an emission list library, and a carbon emission factor library is established; constructing a carbon emission factor classification instance module set by combining a carbon emission factor library based on the scene features of the carbon emission source; establishing a regional carbon emission instance model by using the module according to the business demand of the target region; and calculating a reference carbon emission value of the target area through the model and the emission reduction project library, and generating a carbon emission asset report. The technical problem that in the prior art, carbon emission management lacks accuracy and dynamic adjustment capacity is solved, and the technical effects of real-time dynamic monitoring, accurate management and automatic adjustment of carbon emission are achieved.

Description

Technical Field

[0001] The present application relates to the technical field of carbon emission management, and in particular to a green carbon management method and platform based on the collaboration of the Internet of Things. Background Art

[0002] In the carbon emission management scenario, with the global carbon neutrality goal being proposed, the complexity and importance of carbon emission management have become increasingly prominent, especially in areas involving multiple carbon emission sources, where the contradiction between carbon emission monitoring and management needs has become more prominent. How to effectively monitor and manage different types of carbon emission sources and accurately implement emission reduction measures has become a key link in achieving the carbon neutrality goal. Traditional carbon emission management methods are relatively simple, usually relying on static data, manual records, and regular reports, lacking real-time monitoring and dynamic adjustment capabilities, and unable to accurately classify and manage the complex situations of different carbon emission sources.

[0003] At the current stage, relevant technologies have the technical problem that carbon emission management lacks accuracy and dynamic adjustment capabilities. Summary of the invention

[0004] This application provides a green carbon management method and platform based on the collaboration of the Internet of Things. The method first obtains the carbon emission sources and emission reduction projects in the target area, establishes an emission inventory library and an emission reduction project library; obtains the usage characteristics of the carbon emission sources, determines the carbon emission factors according to the characteristics and the emission inventory library, and establishes a carbon emission factor library; constructs a carbon emission factor classification instance module set based on the scenario characteristics of the carbon emission sources and the carbon emission factor library; uses the modules to establish a regional carbon emission instance model based on the business needs of the target area; calculates the benchmark carbon emission value of the target area through the model and the emission reduction project library, and generates a carbon emission asset report, thereby achieving the technical effect of realizing real-time dynamic monitoring, precise management and automatic adjustment of carbon emissions.

[0005] This application provides a green carbon management method based on IoT collaboration, including:

[0006] Obtain the carbon emission sources and emission reduction projects of the target area, and establish an emission inventory library and an emission reduction project library; obtain the usage characteristics of the carbon emission sources, and based on the usage characteristics and the emission inventory library, obtain the carbon emission factors and establish a carbon emission factor library; based on the scenario characteristics of the carbon emission sources and in combination with the carbon emission factor library, establish a carbon emission factor classification instance module set; obtain the business needs of the target area, and based on the business needs and the carbon emission factor classification instance module set, establish a target area carbon emission instance model; calculate the benchmark carbon emission value of the target area through the target area carbon emission instance model and the emission reduction project library, and generate a carbon emission asset report.

[0007] This application also provides a green carbon management platform based on IoT collaboration, including:

[0008] An emission data set establishment module, the emission data set establishment module is used to obtain the carbon emission sources and emission reduction projects of the target area, and establish an emission inventory library and an emission reduction project library; a carbon emission factor library establishment module, the carbon emission factor library establishment module is used to obtain the usage characteristics of the carbon emission sources, and based on the usage characteristics and the emission inventory library, obtain the carbon emission factors and establish the carbon emission factor library; a carbon emission factor classification instance module set establishment module, the carbon emission factor classification instance module set establishment module is used to establish a carbon emission factor classification instance module set based on the scenario characteristics of the carbon emission sources and in combination with the carbon emission factor library; a target area carbon emission instance model establishment module, the target area carbon emission instance model establishment module is used to obtain the business needs of the target area, and based on the business needs and the carbon emission factor classification instance module set, establish a target area carbon emission instance model; a carbon emission asset report generation module, the carbon emission asset report generation module is used to calculate the benchmark carbon emission value of the target area through the target area carbon emission instance model and the emission reduction project library, and generate a carbon emission asset report.

[0009] Through the green carbon management method and platform based on the collaboration of the Internet of Things proposed in this application, it is planned to first obtain the carbon emission sources and emission reduction projects in the target area, establish an emission inventory library and an emission reduction project library; obtain the usage characteristics of the carbon emission sources, determine the carbon emission factors according to the characteristics and the emission inventory library, and establish a carbon emission factor library; based on the scenario characteristics of the carbon emission sources, in combination with the carbon emission factor library, construct a set of carbon emission factor classification instance modules; according to the business needs of the target area, use the modules to establish a regional carbon emission instance model; through the model and the emission reduction project library, calculate the baseline carbon emission value of the target area, and generate a carbon emission asset report, so as to achieve the technical effect of realizing real-time dynamic monitoring, precise management and automatic adjustment of carbon emissions. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the accompanying drawings of the embodiment of the present invention will be briefly introduced below. A flow chart is used in this application to illustrate the operations performed by the platform according to the embodiment of the present application. It should be understood that the previous or following operations are not necessarily performed precisely in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0011] Figure 1 A schematic diagram of a green carbon management method based on Internet of Things collaboration provided in an embodiment of the present application;

[0012] Figure 2 A schematic diagram of the structure of a green carbon management platform based on Internet of Things collaboration provided in an embodiment of the present application.

[0013] Explanation of the reference numerals: emission data set establishing module 10 , carbon emission factor library establishing module 20 , carbon emission factor classification instance module set establishing module 30 , target area carbon emission instance model establishing module 40 , carbon emission asset report generating module 50 . DETAILED DESCRIPTION

[0014] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0015] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0016] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, platform, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0017] The present application embodiment provides a green carbon management method based on Internet of Things collaboration, such as Figure 1 As shown, the method includes:

[0018] Step S100, obtain the carbon emission sources and emission reduction projects in the target area, and establish an emission inventory library and an emission reduction project library. Specifically, first determine the target area for carbon management, which can be a city, industrial park, enterprise or specific building. Then obtain the carbon emission sources, including the energy use and production scale of the factory in industrial production, waste treatment; the number of various transportation vehicles, traffic flow and energy type in transportation; the energy use, age and installation of energy-saving facilities, and the use of electrical equipment in building facilities; the use of fertilizers and pesticides, farmland irrigation, livestock breeding and land use changes in agricultural activities. At the same time, obtain emission reduction projects, such as renewable energy utilization, including solar energy, wind power, hydropower plants and distributed energy applications; energy efficiency improvement, covering industrial energy-saving transformation, building energy-saving projects, and energy efficiency improvement in the transportation field; carbon capture and storage project planning or implementation and cooperation possibilities. Then sort and classify the obtained carbon emission source information, classify it according to different types, record the name, location, energy consumption type and quantity, carbon emission coefficient, etc., and use database management software to establish an emission inventory library to ensure that it has good query and update functions. The emission reduction project information will then be organized and entered into the emission reduction project database, and a tracking mechanism will be established to regularly update the implementation progress and emission reduction effects, conduct evaluations and analyses of cost-effectiveness, technical feasibility and sustainability, and provide a reference for carbon management decisions.

[0019] Step S200, obtain the usage characteristics of the carbon emission source, obtain the carbon emission factor based on the usage characteristics and the emission inventory library, and establish a carbon emission factor library. Specifically, after determining the carbon emission source in the target area and establishing the emission inventory library, it is necessary to obtain the usage characteristics of the carbon emission source. The usage characteristics include energy consumption characteristics, such as energy type, consumption, usage frequency and intensity; equipment technical characteristics, such as equipment type and specifications, operating status, maintenance status; production process characteristics, such as production process, raw material use, and waste treatment. Based on these usage characteristics and emission inventory library information, collect and organize relevant data, calculate the carbon emission factor, which is divided into carbon emission unit factor and carbon emission weight factor, and then establish a carbon emission factor library, use database management software to enter, record the name, usage characteristics and carbon emission factor of each carbon emission source and other information, and provide data support for subsequent carbon management work.

[0020] In a possible implementation, the use characteristics of the carbon emission source are obtained, and based on the use characteristics and the emission inventory library, the carbon emission factor is obtained, and the carbon emission factor library is established. Step S200 further includes step S210, and the carbon emission factor includes a carbon emission unit factor and a carbon emission weight factor. Specifically, the carbon emission factor includes a carbon emission unit factor and a carbon emission weight factor. When determining the carbon emission unit factor, first clarify the activity measurement indicators corresponding to different carbon emission sources and accurately count them, then use the corresponding measurement method to determine the carbon emissions to ensure that the measurement is accurate and reliable, and finally divide the carbon emissions by the activity to obtain the carbon emission unit factor and record it. When determining the carbon emission weight factor, first summarize the total carbon emissions of the target area according to the emission inventory library information, then calculate the proportion of carbon emissions of a single carbon emission source in the total carbon emissions, and then determine the carbon emission weight factor based on the proportion, and its value can be adjusted according to the actual situation to better reflect the importance differences of different carbon emission sources. These two factors provide important parameters and basis for subsequent carbon management work, help accurately evaluate the carbon emissions in the target area and formulate effective emission reduction strategies.

[0021] In a possible implementation, the use characteristics of the carbon emission source are obtained, and based on the use characteristics and the emission inventory library, the carbon emission factor is obtained, and the carbon emission factor library is established. Step S200 further includes step S220, traversing the emission inventory library to obtain a subset of carbon emission sources. Specifically, the emission inventory library contains all carbon emission source information in the target area. In order to more accurately determine the carbon emission factor, it is first necessary to select a portion of representative carbon emission sources from the emission inventory library to form a subset of carbon emission sources. According to the characteristics of the target area and the needs of carbon management, the standard for selecting the subset of carbon emission sources is determined. For example, the scale, industry type, energy consumption type and other factors of the carbon emission source can be considered to perform traversal screening. According to the determined selection criteria, all carbon emission sources in the emission inventory library are traversed, and each carbon emission source is analyzed one by one to see if it meets the selection criteria. The carbon emission sources that meet the criteria are included in the subset of carbon emission sources, and the obtained subset of carbon emission sources is evaluated to ensure that the subset is representative. If the subset is not comprehensive or has deviations, the selection criteria can be adjusted according to the evaluation results, and the traversal screening is performed again until a satisfactory subset of carbon emission sources is obtained.

[0022] Step S230, according to the carbon emission unit historical data of the carbon emission source subset, a plurality of carbon emission unit factors are obtained. Specifically, the carbon emission unit factor refers to the carbon emission generated per unit of activity. By analyzing the carbon emission unit historical data of the carbon emission source subset, the carbon emission unit factors of different carbon emission sources can be determined, and the carbon emission unit historical data of each carbon emission source in the carbon emission source subset is collected, including the total energy consumption, production activity, carbon emissions and other information in the past period of time. For each carbon emission source, its activity measurement index is determined. For example, for energy consumption carbon emission sources in industrial production, the activity can be the combustion amount per ton of fuel, the electricity consumption per kilowatt-hour, etc.; for the transportation field, the activity can be the mileage per kilometer, the transportation volume per ton of goods, etc. The activity of each carbon emission source is calculated according to the historical data, and the carbon emission of each carbon emission source is divided by its corresponding activity to obtain the carbon emission unit factor of the carbon emission source. All carbon emission sources in the carbon emission source subset are calculated to obtain multiple carbon emission unit factors.

[0023] Step S240, according to the carbon emission contribution historical data of the carbon emission source subset, obtain a plurality of the carbon emission weight factors. Specifically, the carbon emission weight factor reflects the relative importance of each carbon emission source in the total carbon emissions of the target area. By analyzing the carbon emission contribution historical data of the carbon emission source subset, the carbon emission weight factors of different carbon emission sources can be determined. The carbon emission contribution historical data of each carbon emission source in the carbon emission source subset are collected, including the proportion of the carbon emissions of the carbon emission source in the total carbon emissions of the target area in the past period of time and other information. According to the information in the emission inventory library, the total carbon emissions of the target area in the historical time period are calculated. It is necessary to ensure that the carbon emissions of each carbon emission source are calculated accurately and cover all the major carbon emission sources in the target area. For each carbon emission source, the proportion of its carbon emissions in the total carbon emissions of the target area is calculated, and the carbon emission weight factor of the carbon emission source is determined according to the proportion. The higher the proportion of the carbon emission source, the greater its carbon emission weight factor, indicating that the relative importance of the carbon emission source in the carbon emissions of the target area is higher.

[0024] Step S250, combining the plurality of carbon emission unit factors and the plurality of carbon emission weight factors to obtain the plurality of carbon emission factors, and establishing a carbon emission factor library. Specifically, the obtained carbon emission unit factors and carbon emission weight factors are combined to obtain the carbon emission factor of each carbon emission source, and a carbon emission factor library is established for use in subsequent carbon management work. For each carbon emission source, its carbon emission unit factor and carbon emission weight factor are combined. Simple multiplication or other appropriate methods can be used to combine to obtain the carbon emission factor of the carbon emission source, and the combined carbon emission factors can be sorted and entered into the carbon emission factor library. The carbon emission factor library can be established using database management software to ensure that it has good query and update functions. In the carbon emission factor library, the name, activity, carbon emissions, carbon emission unit factor, carbon emission weight factor, carbon emission factor and other information of each carbon emission source should be recorded in detail, and the carbon emission factor library should be maintained and updated regularly. With the passage of time and the accumulation of data, the activity and carbon emissions of carbon emission sources may change. Therefore, it is necessary to update the data in the carbon emission factor library in a timely manner to ensure the accuracy and timeliness of the carbon emission factors, establish a carbon emission factor library that accurately reflects the carbon emissions in the target area, and provide important data support for subsequent carbon management work.

[0025] In one possible implementation, multiple carbon emission unit factors and multiple carbon emission weight factors are combined to obtain multiple carbon emission factors, and a carbon emission factor library is established. Step S250 further includes step S251, monitoring the real-time carbon emission data of the carbon emission source in real time, and calculating the statistical carbon emissions of the carbon emission source within the statistical window time. Specifically, a system for real-time monitoring of carbon emission sources can be established. Sensors, Internet of Things technology and other means can be used to continuously collect data on carbon emission sources in the target area. For example, sensors can be installed at factory chimneys, major traffic arteries, energy entrances of buildings and other locations to monitor energy consumption and carbon emissions in real time. According to the needs of carbon management and the characteristics of the data, an appropriate statistical window time can be determined. The statistical window time can be one hour, one day, one week, etc., depending on the frequency of changes in carbon emission sources and the accuracy requirements of management. During the statistical window time, real-time data of carbon emission sources is continuously collected, including information such as the type, amount, and time of energy consumption. The collected data is processed in real time to calculate the carbon emissions of each carbon emission source within the statistical window time. For example, for energy consumption in industrial production, the carbon emissions can be calculated based on the energy type and consumption, combined with the corresponding carbon emission coefficient. The carbon emissions of all carbon emission sources in the target area within the statistical window time are summarized to obtain the statistical carbon emissions of the carbon emission sources.

[0026] Step S252, calling the carbon emission factor library to calculate the baseline carbon emissions of the carbon emission source within the statistical window time. Specifically, the established carbon emission factor library is called through database query or other means, and the carbon emission factor library contains information such as the carbon emission unit factor and the carbon emission weight factor of each carbon emission source. For each carbon emission source, its activity within the statistical window time is determined according to the real-time monitoring data. The measurement index of the activity is the same as that when determining the carbon emission unit factor. For example, for energy consumption carbon emission sources in industrial production, the activity can be the amount of fuel burned per ton, the amount of electricity consumed per kilowatt-hour, etc. The carbon emission unit factor and the carbon emission weight factor in the carbon emission factor library are used in combination with the determined activity to calculate the baseline carbon emissions of each carbon emission source within the statistical window time. A method similar to that for determining the carbon emission unit factor can be used to multiply the carbon emission unit factor by the activity amount, and then multiply it by the carbon emission weight factor to obtain the baseline carbon emissions. The baseline carbon emissions of all carbon emission sources in the target area within the statistical window time are summarized to obtain the baseline carbon emissions of the carbon emission source.

[0027] Step S253, determine the difference between the statistical carbon emissions of the carbon emission source and the benchmark carbon emissions of the carbon emission source, and generate a carbon emission factor correction model. Specifically, compare the statistical carbon emissions of the carbon emission source with the benchmark carbon emissions of the carbon emission source, and calculate the difference between the two. The difference can reflect the deviation between the actual carbon emissions and the expected carbon emissions. The difference is analyzed to find out the reasons for the deviation, including changes in the activity of the carbon emission source, inaccurate carbon emission factors, monitoring system errors, etc. According to the results of the difference analysis, a carbon emission factor correction model is established. A correction model is established using a neural network or other method to correct the carbon emission factor according to the difference between the actual carbon emissions and the benchmark carbon emissions. The established correction model is verified to ensure its accuracy and reliability. The effect of the correction model is evaluated by comparing the degree of agreement between the corrected carbon emission factor and the actual carbon emissions. If the effect is not ideal, the correction model can be adjusted and optimized.

[0028] Step S254, correct the multiple carbon emission factors in the carbon emission factor library through the carbon emission factor correction model. Specifically, the carbon emission factor correction model is applied to the multiple carbon emission factors in the carbon emission factor library, and the carbon emission unit factor and carbon emission weight factor of each carbon emission source are corrected according to the calculation results of the correction model, and the corrected carbon emission factor is updated to the carbon emission factor library to ensure that the data in the carbon emission factor library is always accurate and up-to-date. With the passage of time and the continuous accumulation of data, the carbon emission sources are continuously monitored in real time, and the correction model and the carbon emission factor library are continuously updated according to the new data to achieve dynamic adjustment and optimization of carbon emission factors, improve the accuracy and effect of carbon management, achieve real-time monitoring of carbon emission sources and dynamic correction of carbon emission factors, and provide strong support for accurate assessment and effective management of carbon emissions.

[0029] Step S300, based on the scenario characteristics of the carbon emission source, combined with the carbon emission factor library, establish a carbon emission factor classification instance module set. Specifically, analyze the scenario characteristics of the carbon emission source, including geographical scenario characteristics, geographically divide the target area, analyze the characteristics of carbon emission sources in different regions, such as coastal areas may have more port and shipping carbon emissions, mountainous areas may have hydropower resource development carbon emissions, etc., and record the characteristics; industry scenario characteristics, determine the main industry types in the target area, and conduct in-depth research on the carbon emission characteristics of each industry, such as industrial sub-industries, carbon emission differences in different modes of transportation, etc., summarize the laws and main carbon emission sources; equipment scenario characteristics, classify equipment in different industries, analyze the energy consumption and carbon emissions of each equipment, such as the differences between old equipment and new energy-saving equipment, and organize equipment information. Then, combined with the carbon emission factor library, call the information in the library, filter out the carbon emission factors related to specific scenarios, and analyze their applicability. Then, a collection of carbon emission factor classification instance modules is established, including the establishment of a geographic emission factor instance module, which establishes a module for each geographic region, including information on the main carbon emission sources in the region, applicable carbon emission factors, and case analysis; an industry emission factor instance module is established, which establishes a module for each major industry, covering the industry's carbon emission characteristics, main carbon emission sources, applicable carbon emission factors, emission reduction trends, and best practices; an equipment emission factor instance module is established, which establishes a module for each type of equipment, including basic equipment information, energy consumption and carbon emissions, applicable carbon emission factors, and maintenance management recommendations. Finally, these instance modules are integrated into a collection to provide a rich and practical tool library for carbon management work.

[0030] In a possible implementation, based on the scenario characteristics of the carbon emission source and in combination with the carbon emission factor library, a set of carbon emission factor classification instance modules is established, and step S300 further includes step S310, in which multiple geographic emission factor instance modules are established according to the geographical scenario characteristics of the carbon emission source. Specifically, a comprehensive geographical analysis is first conducted on the target area, taking into account factors such as the natural environment, climate conditions, and resource distribution of different geographical regions. For example, coastal areas may be affected by the marine climate, and energy demand and carbon emission patterns are different from those of inland areas; mountainous areas may have abundant hydropower resources, but inconvenient transportation may lead to specific carbon emissions. For different geographical regions, the main carbon emission sources in the region are determined, including industrial facilities, transportation, and residents' lives. For example, in coastal areas, port facilities and ship transportation may be the main sources of carbon emissions; in mountainous areas, carbon emissions from small industrial enterprises and mountain transportation may be more prominent. According to the determined carbon emission sources, relevant data are collected to calculate the emission factors of specific carbon emission sources in the geographical region. The emission factor refers to the carbon emissions generated per unit of activity. For example, for port facilities, the carbon emissions generated by loading and unloading each ton of cargo can be calculated; for ship transportation, the carbon emissions generated by each nautical mile of navigation can be calculated. Based on the calculated emission factors and the analysis of the carbon emission sources in the geographical area, a geographical emission factor instance module is established. The module should include the characteristics of the geographical area, the main carbon emission sources, the emission factor calculation method, and suggestions for emission reduction measures. For example, for the geographical emission factor instance module for coastal areas, the port's operating model, ship type, carbon emission characteristics and feasible emission reduction strategies can be introduced in detail, such as the use of clean energy ships and the optimization of port logistics.

[0031] Step S320: establishing multiple industry emission factor instance modules according to the industry scenario characteristics of the carbon emission source. Specifically, divide the industry types: classify the carbon emission sources in the target area by industry, and determine the main industry types, such as industry, transportation, construction, agriculture, etc. The production activities and energy consumption methods of different industries vary greatly, so the carbon emission characteristics are also different. In-depth research is conducted on the carbon emission characteristics and main carbon emission sources of each industry. For example, in the industrial industry, the carbon emission sources and emission patterns of different sub-industries such as steel production and chemical manufacturing are very different; in the transportation industry, the energy consumption and carbon emissions of road transportation, railway transportation, and air transportation are also different. For each industry, collect relevant data and calculate the emission factor of the industry. For example, for the steel industry, the carbon emissions generated by each ton of steel production can be calculated; for the air transportation industry, the carbon emissions generated per passenger-kilometer can be calculated. Based on the calculated industry emission factors and the analysis of the industry's carbon emissions, establish an industry emission factor instance module. The module should include the characteristics of the industry, the main carbon emission sources, the emission factor calculation method, the emission reduction technology and best practices within the industry. For example, for the example module of the steel industry, the process flow of steel production, the main carbon emission links, advanced energy-saving and emission reduction technologies, and industry development trends can be introduced.

[0032] Step S330: Establish multiple equipment emission factor instance modules according to the equipment scenario characteristics of the carbon emission source. Specifically, classify the equipment in different industries and determine the types and characteristics of various equipment. The equipment may include production equipment, transportation equipment, energy conversion equipment, etc. For example, in the industrial sector, equipment can be divided into furnaces, compressors, generators, etc.; in the transportation industry, equipment can be divided into cars, trains, airplanes, etc. The energy consumption and carbon emissions of each type of equipment are studied, and the impact of factors such as the equipment's technical level, service life, and operating status on carbon emissions is considered. For example, old equipment may have low energy efficiency and high carbon emissions; while new energy-saving equipment may have lower carbon emission levels. For each type of equipment, relevant data is collected and the emission factor of the equipment is calculated. For example, for cars, the carbon emissions generated per kilometer of driving can be calculated; for generators, the carbon emissions generated per kilowatt-hour of electricity generation can be calculated. Based on the calculated equipment emission factor and the analysis of the equipment's carbon emissions, an equipment emission factor instance module is established. The module contains the characteristics of the equipment, energy consumption and carbon emissions, emission factor calculation method, equipment maintenance and management recommendations, etc. For example, for the instance module of automotive equipment, the performance characteristics of different types of cars, fuel consumption and carbon emission data, energy-saving and emission reduction technologies, and the impact of driving habits on carbon emissions can be introduced.

[0033] Step S340, count the multiple geographical emission factor instance modules, the multiple industry emission factor instance modules, and the multiple equipment emission factor instance modules to establish a carbon emission factor classification instance module set. Specifically, integrate the multiple geographical emission factor instance modules, the multiple industry emission factor instance modules, and the multiple equipment emission factor instance modules to ensure that the content of each module is accurate and complete, and there is no duplication or contradiction between each other, establish a carbon emission factor classification instance module set, and include the integrated various instance modules into it. The set should have a good organizational structure to facilitate user query and use. The set can be organized by a database management system or a file directory structure. As time goes by and data continues to accumulate, the carbon emission factor may change, and new geographical regions, industries, or equipment may also appear. It is necessary to regularly maintain and update the carbon emission factor classification instance module set to ensure that it always maintains accuracy and practicality, and establish a comprehensive and accurate carbon emission factor classification instance module set to provide strong support for carbon emission management and emission reduction decisions.

[0034] Step S400, obtain the business needs of the target area, and establish a carbon emission instance model for the target area based on the business needs and the carbon emission factor classification instance module set. Specifically, first, determine the business needs focus of carbon emission management in the target area by communicating with stakeholders in the target area, analyzing policies and regulations, and considering industry development trends. Then, select applicable instance modules from the carbon emission factor classification instance module set according to the business needs focus, and integrate the information therein, paying attention to the accuracy and consistency of the information. Then, determine the model parameters based on the integrated information and the actual situation of the target area, and establish the carbon emission instance model framework for the target area, which can be achieved by mathematical models, computer simulation and other technical means. Finally, verify and optimize the established model, which can be achieved by comparing with actual data, performing sensitivity analysis and other methods. If the results are biased, adjust the optimization model until it can accurately reflect the carbon emission situation and emission reduction effect of the target area, thereby providing a scientific basis for carbon emission management and emission reduction decision-making in the target area.

[0035] In a possible implementation, the business needs of the target area are obtained, and based on the business needs and the carbon emission factor classification instance module set, a carbon emission instance model of the target area is established. Step S400 further includes step S410, setting a statistical time window, and determining a scene feature set of the target area based on the business needs. Specifically, the statistical time window is set, and a suitable statistical time window is determined considering the time span requirements of the business needs, as well as the availability and stability of carbon emission data. The time window can be short-term (such as one week, one month), medium-term (such as one quarter, half a year) or long-term (such as one year, several years). For example, if the business need is to evaluate the carbon emission impact of a specific project in the target area, a shorter time window may be selected to obtain more detailed real-time data; if a long-term carbon emission reduction strategy is to be formulated, a longer time window may be selected to observe trend changes, determine the scene feature set based on the business needs, analyze the business needs, clarify the specific goals and key areas of focus of the target area in carbon emission management, and determine the scene feature set of the target area according to the business needs. The scenario feature set includes aspects such as geographical scenario features, industry scenario features and equipment scenario features. For example, if the business requirement is to reduce industrial carbon emissions in the target area, then the scenario feature set may focus on industrial concentration areas (geographic scenario features), major industrial industries (industry scenario features) and key equipment in industrial production (equipment scenario features) within the region.

[0036] Step S420, traverse the scenario feature set, select the multiple geographical emission factor instance modules, the multiple industry emission factor instance modules, and the multiple equipment emission factor instance modules of the carbon emission factor classification instance module set, and establish a target area carbon emission instance model. Specifically, analyze and traverse the determined scenario feature set one by one, starting with the geographical scenario features, understand the carbon emission characteristics and needs of different geographical areas in the target area; then analyze the industry scenario features to determine the main carbon emission industries; finally consider the equipment scenario features, and pay attention to the carbon emissions of specific equipment. For example, first analyze the carbon emission differences of different geographical divisions in the target area, such as the city center, industrial park, suburbs, etc.; then determine the main carbon emission industries such as industry, transportation, and construction; finally, examine the carbon emissions of specific production equipment, transportation vehicles, etc. in the factory, and select the corresponding geographical emission factor instance module, industry emission factor instance module, and equipment emission factor instance module from the carbon emission factor classification instance module set according to the results of traversing the scenario feature set. For example, if the scenario feature set includes a specific industrial park (geographical scenario feature), Chemical industry (industry scenario characteristics) and a specific reactor equipment (equipment scenario characteristics), then select the instance modules related to the industrial park, chemical industry and reactor equipment from the instance module set, integrate and optimize the selected multiple instance modules, and establish a target area carbon emission instance model. In the model, the carbon emission factors, emission reduction measures and other information in each instance module are combined to comprehensively consider the overall carbon emissions of the target area. For example, the data in the selected geographic, industry and equipment instance modules are integrated to determine the carbon emission sources of the target area, calculate the total carbon emissions, evaluate the emission reduction potential, and formulate corresponding carbon emission reduction strategies, thereby forming a complete target area carbon emission instance model. A target area carbon emission instance model based on business needs and scenario feature sets is established to provide strong support for carbon emission management and decision-making in the target area.

[0037] Step S500, through the target area carbon emission example model and the emission reduction project library, calculate the benchmark carbon emission value of the target area and generate a carbon emission asset report. Specifically, first call the target area carbon emission example model, analyze the parameters and variables therein to understand the current status of carbon emissions, and open the emission reduction project library to review each project information and its potential impact on carbon emissions. Then, deeply study the model to extract the carbon emission factor set and determine the activity level data, calculate the initial carbon emission value by traversing the carbon emission factor set combined with the activity level, and then traverse the emission reduction project library to calculate the initial carbon emission reduction value according to the expected emission reduction effect and implementation progress of the project, and finally calculate the difference between the two to obtain the benchmark carbon emission value. In order to generate a carbon emission asset report, it is necessary to collect relevant information about the target area, design the report structure to make it clear and logical and easy to read, use accurate and clear language to describe the current status of carbon emissions, emission reduction projects and the meaning of the benchmark carbon emission value when writing the content, and use charts and other tools to enhance readability. After the first draft is completed, it will be reviewed and proofread and modified according to the opinions. Finally, the report will be published for decision-making reference to provide support for carbon management and sustainable development in the target area.

[0038] In a possible implementation, the target area carbon emission example model and the emission reduction project library are used to calculate the benchmark carbon emission value of the target area and generate a carbon emission asset report. Step S500 further includes step S510, analyzing the target area carbon emission example model and extracting the carbon emission factor set of the target area. Specifically, first, the target area carbon emission example model is deeply analyzed to understand the construction principle of the model, the parameters included and the relationship between the various parts. The model usually comprehensively considers the geographical scene characteristics, industry scene characteristics and equipment scene characteristics of the target area, and can more accurately reflect the carbon emission situation of the area. On the basis of understanding the model structure, the position of the carbon emission factor in the model is determined. The carbon emission factor is a key parameter for calculating carbon emissions, which is usually associated with different carbon emission sources and activity levels. Through the analysis of the model, the carbon emission factor set of the target area is extracted. The set includes carbon emission factors corresponding to various carbon emission sources, such as carbon emission factors for energy consumption in industrial production and carbon emission factors for fuel combustion in transportation. These factors are organized into a set for subsequent calculation and analysis.

[0039] Step S520, traverse the carbon emission factor set to calculate the initial carbon emission value of the target area. Specifically, before calculating the initial carbon emission value, it is necessary to determine the activity level data of various carbon emission sources in the target area. The activity level can be specific indicators such as energy consumption, output, and mileage. These data will be combined with the carbon emission factor to calculate the carbon emissions. The extracted carbon emission factor set is traversed, and for each carbon emission factor, the corresponding activity level data is combined for calculation. For example, if a carbon emission factor represents the carbon dioxide emissions generated by the combustion of each ton of coal, and the coal consumption in the target area is a certain amount, then the carbon emissions generated by coal combustion can be calculated by multiplying the coal consumption by the carbon emission factor. After calculating the carbon emissions of each carbon emission source, the carbon emissions of all carbon emission sources are added to obtain the initial carbon emission value of the target area. The initial value reflects the carbon emissions of the target area without considering the emission reduction project.

[0040] Step S530, traverse the emission reduction project library, and calculate the initial value of carbon emission reduction in the target area. Specifically, open the established emission reduction project library, which stores information on various emission reduction projects being implemented or planned to be implemented in the target area, analyze each project in the emission reduction project library, understand the type of project, implementation progress, expected emission reduction effect, etc. Different emission reduction projects may use different technologies and methods, and their emission reduction effects may also be different. For each emission reduction project, calculate the carbon emission reduction of the project at the current stage according to its expected emission reduction effect and implementation progress. For example, if the expected emission reduction of an emission reduction project is 100 tons of carbon dioxide per year and the implementation progress is 50%, then the carbon emission reduction of the project at the current stage is 50 tons of carbon dioxide. After calculating the carbon emission reduction of all emission reduction projects, add them up to obtain the initial value of carbon emission reduction in the target area. The initial value reflects the total emission reduction of all emission reduction projects in the target area at the current stage.

[0041] Step S540, calculate the difference between the initial carbon emission value and the initial carbon emission reduction value to obtain the benchmark carbon emission value. Specifically, clarify the method of calculating the benchmark carbon emission value, that is, obtain it by calculating the difference between the initial carbon emission value and the initial carbon emission reduction value. The difference reflects the actual carbon emissions of the target area under the condition of considering the emission reduction project. Substitute the previously calculated initial carbon emission value and the initial carbon emission reduction value into the calculation formula to perform the difference calculation. For example, if the initial carbon emission value is 1,000 tons of carbon dioxide and the initial carbon emission reduction value is 200 tons of carbon dioxide, then the benchmark carbon emission value is 800 tons of carbon dioxide. Explain and analyze the calculated benchmark carbon emission value to understand its significance in the carbon management of the target area. The benchmark carbon emission value can be used as an important indicator for evaluating the carbon emission situation and emission reduction effect of the target area, providing a basis for formulating further emission reduction strategies, accurately calculating the benchmark carbon emission value of the target area, and providing strong support for the carbon management and sustainable development of the target area.

[0042] The embodiment of the present application adopts the method of first acquiring the carbon emission sources and emission reduction projects in the target area, establishing an emission inventory library and an emission reduction project library; acquiring the usage characteristics of the carbon emission sources, determining the carbon emission factors according to the characteristics and the emission inventory library, and establishing a carbon emission factor library; constructing a set of carbon emission factor classification instance modules based on the scenario characteristics of the carbon emission sources in combination with the carbon emission factor library; establishing a regional carbon emission instance model using the modules according to the business needs of the target area; calculating the baseline carbon emission value of the target area through the model and the emission reduction project library, and generating a carbon emission asset report, thereby achieving the technical effect of realizing real-time dynamic monitoring, precise management and automatic adjustment of carbon emissions.

[0043] In the above, refer to Figure 1 The green carbon management method based on Internet of Things collaboration according to an embodiment of the present invention is described in detail. Figure 2 A green carbon management platform based on Internet of Things collaboration according to an embodiment of the present invention is described.

[0044] The green carbon management platform based on the collaboration of the Internet of Things according to the embodiment of the present invention is used to solve the technical problem that the carbon emission management in the prior art lacks accuracy and dynamic adjustment capabilities, and achieves the technical effect of realizing real-time dynamic monitoring, precise management and automatic adjustment of carbon emissions. The green carbon management platform based on the collaboration of the Internet of Things includes: an emission data set establishment module 10, a carbon emission factor library establishment module 20, a carbon emission factor classification instance module set establishment module 30, a target area carbon emission instance model establishment module 40, and a carbon emission asset report generation module 50.

[0045] The emission data set building module 10 is used to obtain the carbon emission sources and emission reduction projects in the target area, and to build an emission inventory library and an emission reduction project library.

[0046] The carbon emission factor library establishment module 20 is used to obtain the usage characteristics of the carbon emission source, obtain the carbon emission factor based on the usage characteristics and the emission inventory library, and establish the carbon emission factor library.

[0047] The carbon emission factor classification instance module set establishment module 30 is used to establish a carbon emission factor classification instance module set based on the scenario characteristics of the carbon emission source and in combination with the carbon emission factor library.

[0048] The target area carbon emission instance model establishment module 40 is used to obtain the business demand of the target area, and establish the target area carbon emission instance model based on the business demand and the carbon emission factor classification instance module set.

[0049] The carbon emission asset report generation module 50 is used to calculate the baseline carbon emission value of the target area through the target area carbon emission example model and the emission reduction project library, and generate a carbon emission asset report.

[0050] The specific configuration of the carbon emission factor library establishment module 20 will be described in detail below. As described above, the usage characteristics of the carbon emission source are obtained, and based on the usage characteristics and the emission inventory library, the carbon emission factor is obtained, and the carbon emission factor library is established. The carbon emission factor library establishment module 20 further includes: a carbon emission factor composition unit, and the carbon emission factor composition unit is used for the carbon emission factor to include a carbon emission unit factor and a carbon emission weight factor.

[0051] Among them, the carbon emission factor library establishment module 20 further includes: a carbon emission source subset acquisition unit, the carbon emission source subset acquisition unit is used to traverse the emission inventory library to obtain the carbon emission source subset; a carbon emission unit factor acquisition unit, the carbon emission unit factor acquisition unit is used to obtain multiple carbon emission unit factors based on the carbon emission unit historical data of the carbon emission source subset; a carbon emission weight factor acquisition unit, the carbon emission weight factor acquisition unit is used to obtain multiple carbon emission weight factors based on the carbon emission contribution historical data of the carbon emission source subset; a carbon emission factor library establishment unit, the carbon emission factor library establishment unit is used to combine multiple carbon emission unit factors and multiple carbon emission weight factors to obtain multiple carbon emission factors and establish a carbon emission factor library.

[0052] Among them, multiple carbon emission unit factors and multiple carbon emission weight factors are combined to obtain multiple carbon emission factors, and a carbon emission factor library is established. The carbon emission factor library establishment unit further includes: a statistical carbon emissions calculation subunit, which is used to monitor the real-time data of carbon emissions of the carbon emission source in real time, and calculate the statistical carbon emissions of the carbon emission source within the statistical window time; a benchmark carbon emissions calculation subunit, which is used to call the carbon emission factor library and calculate the benchmark carbon emissions of the carbon emission source within the statistical window time; a carbon emission factor correction model generation subunit, which is used to determine the difference between the statistical carbon emissions of the carbon emission source and the benchmark carbon emissions of the carbon emission source, and generate a carbon emission factor correction model; a correction subunit, which is used to correct multiple carbon emission factors in the carbon emission factor library through the carbon emission factor correction model.

[0053] The specific configuration of the carbon emission factor classification instance module set establishment module 30 will be described in detail below. As described above, based on the scenario characteristics of the carbon emission source and in combination with the carbon emission factor library, a carbon emission factor classification instance module set is established, and the carbon emission factor classification instance module set establishment module 30 further includes: a geographical emission factor instance module establishment unit, the geographical emission factor instance module establishment unit is used to establish multiple geographical emission factor instance modules according to the geographical scenario characteristics of the carbon emission source; an industry emission factor instance module establishment unit, the industry emission factor instance module establishment unit is used to establish multiple industry emission factor instance modules according to the industry scenario characteristics of the carbon emission source; an equipment emission factor instance module establishment unit, the equipment emission factor instance module establishment unit is used to establish multiple equipment emission factor instance modules according to the equipment scenario characteristics of the carbon emission source; a carbon emission factor classification instance module set establishment unit, the carbon emission factor classification instance module set establishment unit is used to count the multiple geographical emission factor instance modules, the multiple industry emission factor instance modules, and the multiple equipment emission factor instance modules to establish a carbon emission factor classification instance module set.

[0054] The specific configuration of the target area carbon emission instance model establishment module 40 will be described in detail below. As described above, the business needs of the target area are obtained, and based on the business needs and the carbon emission factor classification instance module set, the target area carbon emission instance model is established. The target area carbon emission instance model establishment module 40 further includes: a scene feature set determination unit, the scene feature set determination unit is used to set a statistical time window, and based on the business needs, the scene feature set of the target area is determined; a target area carbon emission instance model establishment unit, the target area carbon emission instance model establishment unit is used to traverse the scene feature set, select the multiple geographic emission factor instance modules, the multiple industry emission factor instance modules, and the multiple equipment emission factor instance modules of the carbon emission factor classification instance module set, and establish the target area carbon emission instance model.

[0055] The specific configuration of the carbon emission asset report generation module 50 will be described in detail below. As described above, the benchmark carbon emission value of the target area is calculated through the target area carbon emission instance model and the emission reduction project library, and the carbon emission asset report is generated. The carbon emission asset report generation module 50 further includes: a carbon emission factor set extraction unit, the carbon emission factor set extraction unit is used to analyze the target area carbon emission instance model, and extract the carbon emission factor set of the target area; a carbon emission initial value calculation unit, the carbon emission initial value calculation unit is used to traverse the carbon emission factor set, and calculate the initial carbon emission value of the target area; a carbon emission reduction initial value calculation unit, the carbon emission reduction initial value calculation unit is used to traverse the emission reduction project library, and calculate the initial carbon emission reduction value of the target area; a benchmark carbon emission value acquisition unit, the benchmark carbon emission value acquisition unit is used to calculate the difference between the initial carbon emission value and the initial carbon emission reduction value, and obtain the benchmark carbon emission value.

[0056] The green carbon management platform based on Internet of Things collaboration provided by the embodiment of the present invention can execute the green carbon management method based on Internet of Things collaboration provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0057] Although the present application makes various references to certain modules in the platform according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be implemented; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0058] The above specific implementation manner does not constitute a limitation to the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be performed in an order different from that in the embodiment and can still achieve the desired results. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A green carbon management method based on Internet of Things collaboration, characterized in that: include: Obtain carbon emission sources and emission reduction projects in the target area, and establish an emission inventory database and an emission reduction project database; Obtaining usage characteristics of the carbon emission source, obtaining carbon emission factors based on the usage characteristics and the emission inventory library, and establishing a carbon emission factor library; Based on the scenario characteristics of the carbon emission source and in combination with the carbon emission factor library, a carbon emission factor classification instance module set is established; Acquire the business needs of the target area, and establish a carbon emission instance model for the target area based on the business needs and the carbon emission factor classification instance module set; The benchmark carbon emission value of the target area is calculated through the target area carbon emission example model and the emission reduction project library to generate a carbon emission asset report.

2. The green carbon management method based on Internet of Things collaboration according to claim 1 is characterized in that: The carbon emission factor includes a carbon emission unit factor and a carbon emission weight factor.

3. The green carbon management method based on Internet of Things collaboration according to claim 2 is characterized in that: Establish a carbon emission factor library, including: Traversing the emission inventory library to obtain a subset of carbon emission sources; Obtaining a plurality of carbon emission unit factors according to the carbon emission unit historical data of the subset of carbon emission sources; Obtaining a plurality of carbon emission weighting factors according to the carbon emission contribution historical data of the carbon emission source subset; A plurality of the carbon emission unit factors and a plurality of the carbon emission weight factors are combined to obtain a plurality of the carbon emission factors, and a carbon emission factor library is established.

4. The green carbon management method based on Internet of Things collaboration according to claim 3 is characterized in that: include: Real-time monitoring of the carbon emission data of the carbon emission source, and calculation of the carbon emission amount of the carbon emission source within the statistical window time; Calling the carbon emission factor library to calculate the baseline carbon emissions of the carbon emission sources within the statistical window time; Determine the difference between the statistical carbon emissions of the carbon emission source and the benchmark carbon emissions of the carbon emission source, and generate a carbon emission factor correction model; The multiple carbon emission factors in the carbon emission factor library are corrected by the carbon emission factor correction model.

5. The green carbon management method based on Internet of Things collaboration according to claim 1 is characterized in that: Establish a set of carbon emission factor classification instance modules, including: Establish multiple geographic emission factor instance modules according to the geographic scenario characteristics of the carbon emission sources; Establish multiple industry emission factor instance modules based on the industry scenario characteristics of the carbon emission sources; Establish multiple equipment emission factor instance modules according to the equipment scenario characteristics of the carbon emission source; The multiple geographic emission factor instance modules, the multiple industry emission factor instance modules, and the multiple equipment emission factor instance modules are counted to establish a carbon emission factor classification instance module set.

6. The green carbon management method based on Internet of Things collaboration according to claim 5 is characterized in that: Establish a carbon emission example model for the target area, including: Setting a statistical time window, and determining a scene feature set of the target area based on the business requirements; The scenario feature set is traversed, and the multiple geographic emission factor instance modules, the multiple industry emission factor instance modules, and the multiple equipment emission factor instance modules of the carbon emission factor classification instance module set are selected to establish a target area carbon emission instance model.

7. The green carbon management method based on Internet of Things collaboration according to claim 1 is characterized in that: Calculate the baseline carbon emission value of the target area, including: Analyze the carbon emission example model of the target area and extract the carbon emission factor set of the target area; Traversing the carbon emission factor set, and calculating the initial value of carbon emission of the target area; Traversing the emission reduction project library to calculate the initial value of carbon emission reduction in the target area; The difference between the initial carbon emission value and the initial carbon emission reduction value is calculated to obtain the benchmark carbon emission value.

8. The green carbon management platform based on the collaboration of the Internet of Things is characterized by: The platform is used to implement the green carbon management method based on Internet of Things collaboration according to any one of claims 1 to 7, and the platform includes: An emission data set establishment module, which is used to obtain carbon emission sources and emission reduction projects in the target area and establish an emission inventory library and an emission reduction project library; A carbon emission factor library establishment module, the carbon emission factor library establishment module is used to obtain the usage characteristics of the carbon emission source, obtain the carbon emission factor based on the usage characteristics and the emission inventory library, and establish a carbon emission factor library; A carbon emission factor classification instance module set establishment module, wherein the carbon emission factor classification instance module set establishment module is used to establish a carbon emission factor classification instance module set based on the scenario characteristics of the carbon emission source and in combination with the carbon emission factor library; A target area carbon emission instance model establishment module, the target area carbon emission instance model establishment module is used to obtain the business needs of the target area, and establish a target area carbon emission instance model based on the business needs and the carbon emission factor classification instance module set; A carbon emission asset report generation module is used to calculate the baseline carbon emission value of the target area through the target area carbon emission example model and the emission reduction project library to generate a carbon emission asset report.

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