A method and system for calculating urban carbon emissions based on energy flow analysis

Abstract

The present invention discloses a city carbon emission accounting method and system based on energy flow analysis, which relates to the field of carbon emission management technology, including: dividing a carbon emission accounting city into regions to obtain various carbon emission accounting regions, and monitoring energy consumption data and carbon emission data of each carbon emission accounting region; obtaining an energy characteristic change degree index of each carbon emission accounting region based on various energy characteristic data; monitoring carbon emission accounting equipment status data, and processing to obtain an abnormality index of carbon emission accounting equipment in each carbon emission accounting region; obtaining the adjacent update time interval of the carbon emission coefficient of each carbon emission accounting region, comprehensively analyzing to obtain a carbon emission coefficient update demand assessment index, and making a carbon emission coefficient update judgment based on the carbon emission coefficient update demand assessment index; and performing carbon emission accounting for each carbon emission accounting region based on various energy consumption amounts of each carbon emission accounting region and the updated carbon emission coefficient of each carbon emission accounting region.

Description

Technical Field

[0001] The present invention relates to the field of carbon emission technology, and in particular to a method and system for calculating urban carbon emissions based on energy flow analysis. Background Art

[0002] As cities continue to expand and energy consumption continues to grow, carbon emissions are becoming increasingly severe, posing enormous challenges to the city's ecological environment and sustainable development. This situation has prompted city managers to urgently need accurate and efficient carbon emission accounting methods to address this issue.

[0003] The existing urban carbon emission accounting method is implemented through steps such as energy data collection and integration, energy load pattern identification, carbon emission accounting execution, and carbon emission control optimization.

[0004] For example, the invention patent with announcement number CN115293413A discloses a method for determining highway carbon emission reduction paths based on the K-Means clustering algorithm, which includes the following steps: S1: Determine the carbon emissions at each level in the highway construction project, and determine the input cost of each level based on the carbon emissions at each level; S2: Determine cluster samples at different levels and allocate cluster samples; S3: Determine the carbon emission path based on the cluster sample allocation results, the carbon emissions at each level and the input cost.

[0005] For example, the invention patent with announcement number CN115375159B announces a real-time accounting method and system for the total carbon emissions of a city, which includes the following steps: Step 1, classify all energy-consuming enterprises in the city to obtain multiple energy-consuming enterprise categories; Step 2, obtain the basic information, energy types consumed and energy consumption corresponding to each energy-consuming enterprise in each energy-consuming enterprise category; Step 3, calculate the total carbon emissions of each energy-consuming enterprise category within a period T; Step 4, calculate the total carbon emissions of the city within a period T.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems: the existing carbon emission accounting methods often rely on limited data sources and data collection methods that may have errors, but at the actual operation and application level, due to technical limitations or improper operation, they may face problems of insufficient data reliability and delayed response, resulting in misreporting or omission of carbon emission data. Summary of the Invention

[0007] In response to the deficiencies of the existing technology, the present invention provides a method and system for calculating urban carbon emissions based on energy flow analysis, which can effectively solve the problems involved in the above-mentioned background technology.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: The first aspect of the present invention provides a city carbon emission accounting method based on energy flow analysis, including: dividing the carbon emission accounting city into regions to obtain various carbon emission accounting regions, and monitoring the energy consumption data and carbon emission data of each carbon emission accounting region, wherein the energy consumption data includes various energy characteristic data and various energy consumption amounts.

[0009] Based on the processing of various energy characteristic data, the energy characteristic change degree index of each carbon emission accounting area is obtained.

[0010] The status data of carbon emission accounting equipment is monitored and processed to obtain abnormal indicators of carbon emission accounting equipment in each carbon emission accounting area.

[0011] Obtain the adjacent update time intervals of the carbon emission coefficients of each carbon emission accounting area, conduct a comprehensive analysis based on the energy characteristics change index of each carbon emission accounting area, the abnormal index of carbon emission accounting equipment, the adjacent update time intervals of the carbon emission coefficients and the carbon emission data, and make a judgment on the update of the carbon emission coefficients based on the carbon emission coefficient update demand assessment index.

[0012] Carbon emission accounting is carried out for each carbon emission accounting area based on the various energy consumptions in each carbon emission accounting area and the updated carbon emission coefficients of each carbon emission accounting area.

[0013] As a further method, the energy characteristic change degree index of each carbon emission accounting area is obtained according to the processing of various energy characteristic data. The specific analysis process is: various energy characteristic data include coal carbon content, natural gas methane content and the proportion of clean energy power generation; reference coal carbon content, reference natural gas methane content, reference clean energy power generation proportion, allowable deviation coal carbon content, allowable deviation natural gas methane content and allowable deviation clean energy power generation proportion are extracted from the carbon emission database; energy characteristic change degree index of each carbon emission accounting area is obtained according to the analysis of various energy characteristic data, and the energy characteristic change degree index of each carbon emission accounting area is used to quantitatively evaluate the change amplitude of energy characteristics in each carbon emission accounting area.

[0014] As a further method, the carbon emission accounting equipment status data is monitored and processed to obtain abnormal indicators of carbon emission accounting equipment in each carbon emission accounting area. The specific analysis process is: the carbon emission accounting equipment status data includes the cumulative operating time of the equipment, the number of equipment failures, the equipment maintenance frequency and the time interval between adjacent maintenance of the equipment; the cumulative operating time of critical equipment, the number of critical equipment failures, the critical equipment maintenance frequency and the time interval between adjacent maintenance of critical equipment are extracted from the carbon emission database; the abnormal indicators of carbon emission accounting equipment in each carbon emission accounting area are obtained based on the analysis of the carbon emission accounting equipment status data, and the abnormal indicators of carbon emission accounting equipment in each carbon emission accounting area are used to quantitatively evaluate the operating abnormalities of carbon emission accounting equipment in each carbon emission accounting area; feedback and early warning are performed based on the abnormal indicators of carbon emission accounting equipment in each carbon emission accounting area.

[0015] As a further method, feedback and early warning are performed based on the abnormal indicators of the carbon emission accounting equipment in each carbon emission accounting area. The specific analysis process is: comparing the abnormal indicators of the carbon emission accounting equipment in each carbon emission accounting area with the abnormal threshold of the carbon emission accounting equipment preset in the carbon emission database; if the abnormal indicator of the carbon emission accounting equipment in a certain carbon emission accounting area is greater than or equal to the abnormal threshold of the carbon emission accounting equipment preset in the carbon emission database, it is determined that the carbon emission accounting equipment in the carbon emission accounting area is abnormal, and feedback and early warning are performed; if the abnormal indicator of the carbon emission accounting equipment in a certain carbon emission accounting area is less than the abnormal threshold of the carbon emission accounting equipment preset in the carbon emission database, it is determined that the carbon emission accounting equipment in the carbon emission accounting area can be used normally.

[0016] As a further method, the comprehensive analysis obtains a carbon emission coefficient update demand assessment index, and the specific analysis process is: the carbon emission data includes the carbon dioxide emissions at each monitoring time point; the critical carbon emission coefficient adjacent update time interval, reference carbon dioxide emissions and allowable deviation carbon dioxide emissions are extracted from the carbon emission database; the carbon emission coefficient adjacent update time interval of each carbon emission accounting area is obtained, and the carbon emission coefficient update demand assessment index of each carbon emission accounting area is obtained through comprehensive analysis based on the energy characteristic change degree index, carbon emission accounting equipment abnormality index, carbon emission coefficient adjacent update time interval and carbon emission data of each carbon emission accounting area. The carbon emission coefficient update demand assessment index of each carbon emission accounting area is used to quantitatively assess the degree of demand for carbon emission coefficient update in each carbon emission accounting area.

[0017] As a further method, the carbon emission coefficient update judgment is made according to the carbon emission coefficient update demand assessment index. The specific analysis process is: comparing the carbon emission coefficient update demand assessment index of each carbon emission accounting area with the carbon emission coefficient update demand assessment threshold preset in the carbon emission database; if the carbon emission coefficient update demand assessment index of a carbon emission accounting area is greater than or equal to the carbon emission coefficient update demand assessment threshold preset in the carbon emission database, the carbon emission coefficient of the carbon emission accounting area is updated; if the carbon emission coefficient update demand assessment index of a carbon emission accounting area is less than the carbon emission coefficient update demand assessment threshold preset in the carbon emission database, no additional operation is performed.

[0018] As a further method, the carbon emission coefficient of the carbon emission accounting area is updated, and the specific analysis process is: subtracting the carbon emission coefficient update demand assessment index of each carbon emission accounting area from the carbon emission coefficient update demand assessment threshold preset in the carbon emission database to obtain a carbon emission coefficient update deviation value; judging whether the carbon emission coefficient corresponding to each type of energy needs to be updated based on the characteristic data of each type of energy, and updating the carbon emission coefficient corresponding to each type of energy based on the carbon emission coefficient update deviation value to obtain an updated carbon emission coefficient corresponding to each type of energy.

[0019] As a further method, the carbon emission accounting is performed on each carbon emission accounting area based on the various energy consumption amounts and the updated carbon emission coefficients of each carbon emission accounting area. The specific analysis process is: multiplying the various energy consumption amounts of each carbon emission accounting area with the corresponding updated carbon emission coefficients of each carbon emission accounting area to obtain the carbon emissions of various energy consumption amounts of each carbon emission accounting area; adding the carbon emissions of various energy consumption amounts of each carbon emission accounting area to obtain the total carbon emissions of each area.

[0020] The second aspect of the present invention provides an urban carbon emission accounting system based on energy flow analysis, including: a regional division and data monitoring module, which is used to divide the carbon emission accounting city into regions to obtain various carbon emission accounting regions, and monitor the energy consumption data and carbon emission data of each carbon emission accounting region, wherein the energy consumption data includes various energy characteristic data and various energy consumption amounts.

[0021] The energy characteristic index module is used to obtain the energy characteristic change degree index of each carbon emission accounting area based on various energy characteristic data processing.

[0022] The equipment status indicator module is used to monitor the status data of carbon emission accounting equipment and process it to obtain abnormal indicators of carbon emission accounting equipment in each carbon emission accounting area.

[0023] The coefficient update judgment module is used to obtain the carbon emission coefficient update time interval of each carbon emission accounting area, and comprehensively analyze the carbon emission coefficient update demand assessment index based on the energy characteristics change degree index, carbon emission accounting equipment abnormality index, carbon emission coefficient update time interval and carbon emission data of each carbon emission accounting area, and make a carbon emission coefficient update judgment based on the carbon emission coefficient update demand assessment index.

[0024] The carbon emission accounting module is used to perform carbon emission accounting for each carbon emission accounting area based on the various energy consumption amounts of each carbon emission accounting area and the updated carbon emission coefficients of each carbon emission accounting area.

[0025] Compared with the prior art, the embodiments of the present invention have at least the following beneficial effects:

[0026] (1) The present invention provides a method and system for calculating urban carbon emissions based on energy flow analysis. Based on real-time monitored energy data and real-time updated carbon emission coefficients, the carbon emission values ​​of each region are precisely calculated, achieving high-precision and high-timeliness in carbon emission quantification. This helps to accurately locate the source of high carbon emissions, provide a basis for the targeted formulation of emission reduction measures, and improve the quality of the urban ecological environment.

[0027] (2) The present invention introduces energy characteristic variation indexes and carbon emission accounting equipment anomaly indexes to implement refined management and early warning of carbon emission accounting areas. When energy characteristics change significantly or carbon emission accounting equipment experiences anomalies, the system can promptly issue an early warning, prompting relevant departments to take appropriate measures to prevent excessive increases in carbon emissions and ensure the effectiveness and timeliness of carbon emission management.

[0028] (3) This invention achieves comprehensive, systematic, and dynamic monitoring of carbon emissions by constructing a comprehensive carbon emissions accounting system, including the collection and processing of energy characteristic data, the monitoring and analysis of the status of carbon emissions accounting equipment, and the updating and evaluation of carbon emissions coefficients. This comprehensive carbon emissions accounting system not only improves the accuracy and reliability of carbon emissions data, but also provides strong data support for carbon emissions management and reduction.

[0029] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 Schematic diagram of the method of the present invention.

[0031] Figure 2 This is a schematic diagram of system module connections of the present invention. DETAILED DESCRIPTION

[0032] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0033] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0034] Reference Figure 1 As shown, the first aspect of the present invention provides a city carbon emission accounting method based on energy flow analysis, including: dividing the carbon emission accounting city into regions to obtain various carbon emission accounting regions, and monitoring the energy consumption data and carbon emission data of each carbon emission accounting region, wherein the energy consumption data includes various energy characteristic data and various energy consumption amounts.

[0035] In this example, the city's functional zoning is used. For example, commercial areas are home to office buildings and shopping malls, where energy consumption primarily comes from electricity for lighting, air conditioning, and natural gas for restaurants, resulting in significant seasonal fluctuations in carbon emissions. Industrial areas are densely populated, with energy consumption and carbon emissions varying significantly across different industries, with coal and oil consumption being prominent. Residential areas are densely populated, where electricity is used for daily life, while some areas rely on gas for heating. Carbon emissions are dispersed and stable, and are linked to daily routines. Cultural and educational areas encompass schools and research institutions, where energy consumption is concentrated in teaching, research, and laboratory equipment, resulting in carbon emissions that fluctuate with the patterns of teaching and research. The layout of transportation hubs is centered around airports, train stations, and ports, extending outward. These areas experience frequent transportation, resulting in significant fuel consumption and exhaust emissions. Furthermore, supporting facilities consume energy, intertwining with the urban transportation network to form specific carbon emission zones. Combined with topography and climate zoning, mountainous and plain terrains influence energy infrastructure and transportation. For example, hydropower in mountainous areas offers advantages, but transmission is difficult. High-latitude, cold regions experience high carbon emissions during the heating season. Categorizing climate into temperature and wind zones allows for precise identification of key emission reduction areas.

[0036] Based on the processing of various energy characteristic data, the energy characteristic change degree index of each carbon emission accounting area is obtained.

[0037] Specifically, the energy characteristic change degree index of each carbon emission accounting area is obtained based on the processing of various energy characteristic data. The specific analysis process is: various energy characteristic data include coal carbon content, natural gas methane content and the proportion of clean energy power generation; reference coal carbon content, reference natural gas methane content, reference clean energy power generation proportion, allowable deviation coal carbon content, allowable deviation natural gas methane content and allowable deviation clean energy power generation proportion are extracted from the carbon emission database; energy characteristic change degree index of each carbon emission accounting area is obtained based on the analysis of various energy characteristic data. The energy characteristic change degree index of each carbon emission accounting area is used to quantitatively evaluate the change amplitude of energy characteristics in each carbon emission accounting area.

[0038] It should be understood that in this embodiment, coal is a complex mixture composed of multiple elements. Carbon content refers to the percentage of carbon in the coal to its total mass. Coal carbon content is an important indicator of coal quality and combustion performance. Natural gas is primarily composed of methane, and its methane content refers to the percentage of methane in its volume to its total volume. The percentage of clean energy power generation refers to the ratio of clean energy generation (such as solar, wind, hydro, and biomass) to the total power generation within a carbon emissions accounting region, reflecting the cleanliness of the region's energy mix. Coal carbon content can be determined using an elemental analyzer. Natural gas methane content can be determined using a laser spectrometer gas analyzer. Based on laser absorption spectroscopy, lasers of a specific wavelength interact with methane molecules in natural gas, and the methane concentration is measured based on the intensity of the absorbed light. The percentage of clean energy power generation can be determined using a power monitoring system. Power monitoring equipment such as smart meters installed at grid access points can record the power generation of various energy generation facilities (including both clean and traditional energy generation facilities) in real time. By analyzing and calculating this data, the percentage of clean energy power generation can be determined. The reference coal carbon content, reference natural gas methane content, and reference clean energy power generation ratio serve as standard values ​​for comparison with actual energy characteristic data. The allowable deviations for coal carbon content, natural gas methane content, and clean energy power generation ratio specify whether fluctuations within these ranges are normal. These values ​​can be directly obtained from the carbon emissions database.

[0039] In a specific embodiment, the energy characteristic variation index of each carbon emission accounting area is obtained as follows:

[0040] ;

[0041] Where, represents the energy characteristic change index of the i-th carbon emission accounting area, e represents the natural constant, represents the coal carbon content in the i-th carbon emission accounting area, represents the methane content of natural gas in the i-th carbon emission accounting area, represents the proportion of clean energy power generation in the i-th carbon emission accounting area, represents the reference coal carbon content of the i-th carbon emission accounting area, represents the reference natural gas methane content in the i-th carbon emission accounting area, represents the reference clean energy power generation ratio of the i-th carbon emission accounting area, Indicates the allowable deviation of coal carbon content, Indicates the allowable deviation of natural gas methane content, Indicates the percentage of clean energy power generation with allowable deviation, Indicates the impact weight of the energy characteristics change index of the carbon emission accounting area corresponding to the preset coal carbon content, Indicates the impact weight of the energy characteristic change index of the carbon emission accounting area corresponding to the preset natural gas methane content, It represents the impact weight of the energy characteristic change index of the carbon emission accounting area corresponding to the preset clean energy power generation ratio. i represents the number of the carbon emission accounting area, i=1, 2, 3, ..., k, and k represents the total number of carbon emission accounting areas.

[0042] When implementing the energy characteristics change degree index, 、 and The impact weights of the energy characteristic change indicators for carbon emission accounting regions corresponding to coal carbon content, natural gas methane content, and the proportion of clean energy power generation can be directly obtained from the carbon emission database. These weights reflect the degree of impact on the energy characteristic change indicators, and there are preset mapping rules for their correspondence. For example, a mapping set is formed between the area of ​​urban carbon emissions and the impact weights of the energy characteristic change indicators for carbon emission accounting regions corresponding to coal carbon content, natural gas methane content, and the proportion of clean energy power generation obtained from the carbon emission database. By inputting the area of ​​urban carbon emissions into the mapping set, the impact weights of the energy characteristic change indicators for carbon emission accounting regions corresponding to coal carbon content, natural gas methane content, and the proportion of clean energy power generation can be obtained. The mapping method can be one-to-one or many-to-one. In this example, the weight values ​​are limited to the range between 0 and 1 (excluding 0 and 1).

[0043] In this example, the Energy Characteristics Variation Index is used to quantitatively assess the extent of energy characteristics variation within each carbon emission accounting region. The smaller the deviation between the carbon content of coal, the methane content of natural gas, or the percentage of clean energy generation, the smaller the corresponding Energy Characteristics Variation Index, indicating a smaller extent of energy characteristics variation within that carbon emission accounting region.

[0044] The algorithm in this embodiment combines coal carbon content, natural gas methane content, and the proportion of clean energy power generation to comprehensively analyze and derive an energy characteristics change index. In this formula, coal carbon content, natural gas methane content, and the proportion of clean energy power generation interact with each other. High coal carbon content and increased coal usage will inhibit natural gas use, causing natural gas methane content to remain relatively stable or decline. This will also compress the development space for clean energy, slowing the growth or even decreasing the proportion of clean energy power generation. An increase in natural gas methane content means a greater share of natural gas in the energy mix, reducing reliance on coal and lowering coal carbon content. An increase in the proportion of clean energy power generation reduces demand for coal and natural gas, thereby decreasing the contribution of coal carbon content and natural gas methane content to the overall energy characteristics. By comprehensively analyzing coal carbon content, natural gas methane content, and the proportion of clean energy power generation, an energy characteristics change index can be accurately derived, quantitatively reflecting the overall changes in energy characteristics within each carbon emissions accounting region.

[0045] The status data of carbon emission accounting equipment is monitored and processed to obtain abnormal indicators of carbon emission accounting equipment in each carbon emission accounting area.

[0046] Specifically, the status data of carbon emission accounting equipment is monitored and processed to obtain abnormal indicators of carbon emission accounting equipment in each carbon emission accounting area. The specific analysis process is: the carbon emission accounting equipment status data includes the cumulative operating time of the equipment, the number of equipment failures, the equipment maintenance frequency and the time interval between adjacent maintenance of the equipment; the cumulative operating time of critical equipment, the number of critical equipment failures, the critical equipment maintenance frequency and the time interval between adjacent maintenance of critical equipment are extracted from the carbon emission database; the abnormal indicators of carbon emission accounting equipment in each carbon emission accounting area are obtained based on the analysis of the carbon emission accounting equipment status data, and the abnormal indicators of carbon emission accounting equipment in each carbon emission accounting area are used to quantitatively evaluate the operating abnormalities of carbon emission accounting equipment in each carbon emission accounting area; feedback and early warning are performed based on the abnormal indicators of carbon emission accounting equipment in each carbon emission accounting area.

[0047] In this embodiment, the cumulative operating time of a device refers to the total operating time from the time the device was first put into use to the current moment. This is a cumulative time measurement that intuitively reflects the level of device usage. For example, if a carbon emissions accounting device has been running 24 hours a day since installation, after one year, its cumulative operating time is 8,760 hours. The longer the cumulative operating time of a device, the more susceptible its components are to wear and aging, increasing the risk of device failure. Furthermore, prolonged operation can also lead to performance degradation, such as reduced sensor accuracy and decreased data transmission stability, which in turn affects the accuracy of carbon emissions accounting. The number of device failures refers to the total number of failures that have occurred during operation. Each failure indicates a problem with a component or system of the device, requiring repair or adjustment. For example, a carbon emissions monitoring device experienced a total of 10 failures over the past five years. The number of device failures is an important indicator of device reliability. A higher number of failures indicates a lower device stability, which impacts its uptime. Frequent failures can lead to data loss or calculation errors, increasing repair costs and device downtime. Equipment maintenance frequency refers to the number of times a piece of equipment undergoes maintenance per unit time, typically expressed as the number of times the equipment undergoes maintenance within a certain period (e.g., a year). For example, if a piece of equipment was repaired five times in the past year, its maintenance frequency is 5 times / year. A high maintenance frequency means the equipment requires frequent maintenance and repairs. This high maintenance frequency not only increases maintenance costs and manpower, but may also affect the equipment's lifespan and performance. The interval between adjacent maintenance visits refers to the time interval between the two most recent maintenance visits. For example, if a piece of equipment was last repaired on March 1st, and the previous repair was on January 1st, the interval between these two repairs is two months. A short interval between adjacent maintenance visits indicates frequent equipment failures and maintenance requirements, reflecting lower equipment reliability. Shorter maintenance intervals increase the time the equipment is not functioning properly, impacting the continuity of carbon emissions accounting. Furthermore, frequent maintenance prevents the equipment from achieving optimal performance, thus affecting the accuracy of accounting data.

[0048] It should be understood that in this embodiment, the cumulative operating time of the equipment can be obtained through system records. The equipment will be equipped with an operating time recording system that uses a built-in timer or software to record the equipment's startup and shutdown time and automatically calculate the cumulative operating time. These records can be stored in the device's local storage unit or transmitted to the management system's database via a network. The number of equipment failures and the frequency of equipment repairs can be obtained through a maintenance record system. Enterprises or institutions will establish an equipment maintenance record system. Each time a device fails and is repaired, maintenance personnel will record information such as the time of the failure, cause, repair content, and parts used in the system. By statistically analyzing the maintenance records, the number of equipment failures and the frequency of equipment repairs can be obtained. The time interval between adjacent equipment repairs can be calculated based on maintenance records. By reviewing the maintenance time records in the equipment maintenance record system and calculating the difference between two adjacent repair times, the time interval between adjacent equipment repairs can be obtained. The cumulative operating time of critical equipment, the number of critical equipment failures, the critical equipment repair frequency, and the time interval between adjacent critical equipment repairs can be directly obtained from the carbon emissions database.

[0049] In a specific embodiment, the method for obtaining the abnormality index of the carbon emission accounting equipment in each carbon emission accounting area is as follows:

[0050] ;

[0051] Where, represents the abnormal index of carbon emission accounting equipment in the i-th carbon emission accounting area, e represents a natural constant, represents the cumulative operating time of the equipment in the i-th carbon emission accounting area, represents the number of equipment failures in the i-th carbon emission accounting area, represents the equipment maintenance frequency of the i-th carbon emission accounting area, represents the time interval between the maintenance of equipment in the i-th carbon emission accounting area, Indicates the cumulative operating time of critical equipment. Indicates the number of critical equipment failures, Indicates the maintenance frequency of critical equipment, Indicates the time interval for critical equipment to be repaired. Indicates the impact weight of abnormal indicators of carbon emission accounting equipment in the carbon emission accounting area corresponding to the preset cumulative running time of the equipment. Indicates the impact weight of the carbon emission accounting equipment abnormality index in the carbon emission accounting area corresponding to the preset number of equipment failures. Indicates the impact weight of the abnormal index of carbon emission accounting equipment in the carbon emission accounting area corresponding to the preset equipment maintenance frequency. It represents the impact weight of the abnormal index of the carbon emission accounting equipment in the carbon emission accounting area corresponding to the preset equipment maintenance time interval. i represents the number of the carbon emission accounting area, i=1, 2, 3, ..., k, and k represents the total number of carbon emission accounting areas.

[0052] When executing abnormal indicators of carbon emission accounting equipment, 、 、 and The impact weights of carbon emission accounting equipment anomaly indicators for a carbon emission accounting area, corresponding to the cumulative equipment operating time, number of equipment failures, equipment maintenance frequency, and equipment maintenance interval, can be directly obtained from the carbon emission database. These weights reflect the degree of their impact on the carbon emission accounting equipment anomaly indicators, and there are preset mapping rules for their correspondence. For example, a mapping set is formed between the area of ​​a city's carbon emissions and the impact weights of carbon emission accounting equipment anomaly indicators for the carbon emission accounting area corresponding to the cumulative equipment operating time, number of equipment failures, equipment maintenance frequency, and equipment maintenance interval obtained from the carbon emission database. By inputting the area of ​​a city's carbon emissions into the mapping set, the impact weights of carbon emission accounting equipment anomaly indicators for the carbon emission accounting area corresponding to the cumulative equipment operating time, number of equipment failures, equipment maintenance frequency, and equipment maintenance interval can be obtained. The mapping method can be one-to-one or many-to-one. In this example, the weight value range is limited to 0 to 1 (excluding 0 and 1).

[0053] In this embodiment, the carbon emission accounting equipment anomaly index is primarily used to quantitatively assess the operational anomalies of carbon emission accounting equipment within each carbon emission accounting area. The longer the cumulative operating time of a device, the more frequent equipment failures, the more frequent equipment maintenance, or the shorter the time between maintenance intervals, the larger the corresponding carbon emission accounting equipment anomaly index, indicating a more abnormal operational situation for the carbon emission accounting equipment within that carbon emission accounting area.

[0054] The algorithm in this embodiment combines the cumulative operating time of the equipment, the number of equipment failures, the equipment maintenance frequency, and the time interval between upcoming maintenance attempts to comprehensively analyze and determine the equipment anomaly index for carbon emissions accounting. In this formula, the cumulative operating time, the number of equipment failures, the equipment maintenance frequency, and the time interval between upcoming maintenance attempts interact with each other. The longer the cumulative operating time of the equipment, the greater the wear and aging of its components, leading to a higher probability of equipment failure and a greater number of equipment failures. The longer the cumulative operating time of the equipment, the greater the likelihood of equipment failure, the more frequent maintenance needs, and the higher the maintenance frequency. Longer cumulative operating time leads to decreased equipment performance and more frequent failures, shortening the time interval between upcoming maintenance attempts. More equipment failures increase the number of maintenance requests and the frequency of maintenance increases. More equipment failures shorten the time interval between successive maintenance attempts. Frequent failures mean that the equipment requires constant maintenance, resulting in a shorter time interval between successive maintenance attempts. A higher maintenance frequency indicates that the equipment requires frequent maintenance, shortening the time interval between successive maintenance attempts. By comprehensively analyzing the cumulative operating time of the equipment, the number of equipment failures, the equipment maintenance frequency and the time interval between adjacent equipment maintenance, the abnormal indicators of the carbon emission accounting equipment can be accurately obtained, which quantitatively reflects the degree to which the carbon emission accounting equipment in each carbon emission accounting area deviates from the normal operating state.

[0055] Specifically, feedback and early warning are performed based on the abnormal indicators of carbon emission accounting equipment in each carbon emission accounting area. The specific analysis process is: comparing the abnormal indicators of carbon emission accounting equipment in each carbon emission accounting area with the abnormal thresholds of carbon emission accounting equipment preset in the carbon emission database; if the abnormal indicator of carbon emission accounting equipment in a certain carbon emission accounting area is greater than or equal to the abnormal threshold of carbon emission accounting equipment preset in the carbon emission database, it is determined that the carbon emission accounting equipment in the carbon emission accounting area is abnormal, and feedback and early warning are performed; if the abnormal indicator of carbon emission accounting equipment in a certain carbon emission accounting area is less than the abnormal threshold of carbon emission accounting equipment preset in the carbon emission database, it is determined that the carbon emission accounting equipment in the carbon emission accounting area can be used normally.

[0056] It should be understood that in this embodiment, the carbon emission database pre-sets a carbon emission accounting equipment abnormality threshold value to measure whether the equipment is in a normal state. The carbon emission accounting equipment abnormality index of each carbon emission accounting area is compared one by one with the carbon emission accounting equipment abnormality threshold value preset in the carbon emission database. When the carbon emission accounting equipment abnormality index of a certain carbon emission accounting area is greater than or equal to the carbon emission accounting equipment abnormality threshold value preset in the carbon emission database, it means that the operating state of the equipment has deviated from the normal range. There may be problems such as failure, aging, external interference, etc., which make it unable to accurately and stably perform carbon emission accounting work. Therefore, at this time, the system will determine that the carbon emission accounting equipment has an abnormality and immediately start the feedback warning mechanism. The warning information can be sent to relevant operation and maintenance personnel and management personnel, so that they can be informed in time and take maintenance, debugging and other measures to avoid inaccurate or missing carbon emission accounting data due to equipment abnormality. Conversely, if the abnormality indicator for carbon emission accounting equipment in a particular carbon emission accounting area is less than the abnormality threshold for carbon emission accounting equipment preset in the carbon emission database, it indicates that all operating parameters of the equipment are within a reasonable and controllable normal range and can reliably complete carbon emission accounting tasks without additional intervention and continuous monitoring of its operating status. Through the process of comparison, judgment, feedback and early warning, we can effectively ensure that the equipment relied on for carbon emission accounting is always in good operating condition, providing a solid foundation for accurate carbon emission accounting.

[0057] It should be understood that the feedback warning mechanism in this embodiment includes determining warning methods: system notifications, which display device anomaly information, including the device name, anomaly indicators, and severity, to relevant personnel within the relevant carbon emissions accounting and management system via pop-up windows or push notifications; email notifications, which send emails to specific personnel or teams detailing the device anomaly to facilitate their timely review and resolution; SMS notifications, which send SMS messages to relevant personnel via the SMS platform to ensure they receive notification of the device anomaly immediately. SMS content should be concise and include key information; and voice calls, which can directly contact relevant personnel via voice calls for particularly important anomalies to ensure they are immediately aware and can take action. The warning content should be clearly defined, including basic device information, including device name, model, and accounting region, to enable personnel to quickly locate the anomaly; and anomaly severity description, which assesses the severity of the anomaly, such as mild, moderate, or severe, based on the difference between the anomaly indicators and the threshold, to provide personnel with a reference for prioritizing handling. Establish an early warning record and tracking mechanism to record early warning information, and keep detailed records of each feedback warning issued, including warning time, equipment information, abnormal indicators, warning methods, etc., for subsequent query and analysis; track processing progress, establish a tracking mechanism, track the processing process of abnormal equipment in real time, and record information such as processing personnel, processing time, and processing results; feedback and confirmation, after the staff takes processing measures, require the staff to provide feedback on the processing results to confirm whether the equipment has returned to normal. If the equipment is still abnormal, continue to issue early warnings and reschedule processing.

[0058] It should be understood that the abnormality level in this embodiment is determined based on the following criteria: when the abnormality index exceeds the preset threshold, but the amplitude is within 10%, it is determined to be a mild abnormality. For example, if the data transmission delay threshold in the abnormality index of the carbon emission accounting equipment is set to 50 milliseconds, and the actual monitored data transmission delay is 55 milliseconds, it is a mild abnormality. When the abnormality index exceeds the preset threshold by between 10% and 50%, it is defined as a moderate abnormality. For example, the carbon emission coefficient adjacent update time interval threshold of a carbon emission accounting area is 30, and the actual interval has reached 40 days, exceeding the threshold by about 33%, which is a moderate abnormality. When the abnormality index exceeds the preset threshold by more than 50%, it is determined to be a severe abnormality. For example, if the measurement deviation threshold of the pressure monitoring equipment is ±5%, and the actual measurement deviation reaches -8%, it is a severe abnormality.

[0059] Obtain the adjacent update time intervals of the carbon emission coefficients of each carbon emission accounting area, conduct a comprehensive analysis based on the energy characteristics change index of each carbon emission accounting area, the abnormal index of carbon emission accounting equipment, the adjacent update time intervals of the carbon emission coefficients and the carbon emission data, and make a judgment on the update of the carbon emission coefficients based on the carbon emission coefficient update demand assessment index.

[0060] Specifically, a comprehensive analysis is conducted to obtain a carbon emission coefficient update demand assessment index, and the specific analysis process is as follows: the carbon emission data include the carbon dioxide emissions at each monitoring time point; the critical carbon emission coefficient adjacent update time interval, the reference carbon dioxide emissions and the allowable deviation carbon dioxide emissions are extracted from the carbon emission database; the carbon emission coefficient adjacent update time interval of each carbon emission accounting area is obtained, and the carbon emission coefficient update demand assessment index of each carbon emission accounting area is obtained through a comprehensive analysis based on the energy characteristic change degree index of each carbon emission accounting area, the carbon emission accounting equipment abnormality index, the carbon emission coefficient adjacent update time interval and the carbon emission data. The carbon emission coefficient update demand assessment index of each carbon emission accounting area is used to quantitatively assess the degree of demand for carbon emission coefficient update in each carbon emission accounting area.

[0061] In this embodiment, the energy characteristic change degree index reflects the change in energy characteristics, the carbon emission accounting equipment abnormality index reflects the abnormal operation of the equipment, the carbon emission coefficient adjacent update time interval records the time interval between the last carbon emission coefficient update operation and the current time, and the carbon emission data includes the carbon dioxide emissions at each monitoring time point.

[0062] It should be understood that in this embodiment, the carbon emission coefficient update interval refers to the time interval from the last carbon emission coefficient update to the current time, reflecting the timeliness of the carbon emission coefficient. The carbon emission coefficient update interval can be obtained from the carbon emission coefficient update recording system. Each time the carbon emission coefficient is updated, the update timestamp is recorded. The interval is then calculated by subtracting the last update time from the current time. Carbon dioxide emissions at each monitoring time point are direct data for measuring carbon emissions. By monitoring emissions at different time points, the changing trends of carbon emissions can be observed. Carbon dioxide emissions can be obtained by installing carbon dioxide sensors at carbon emission sources (such as factory chimneys and vehicle exhaust outlets). Carbon dioxide sensors can measure and record carbon dioxide emissions in real time. The critical carbon emission coefficient update interval serves as a reference standard for update time, while the reference carbon dioxide emissions and the allowable deviation of carbon dioxide emissions are used to measure the normal fluctuation range of carbon emission data. The critical carbon emission coefficient update interval, reference carbon dioxide emissions, and allowable deviation of carbon dioxide emissions can be directly obtained from the carbon emissions database.

[0063] In a specific embodiment, the carbon emission coefficient update demand assessment index of each carbon emission accounting area is obtained as follows:

[0064] ;

[0065] Where, represents the carbon emission coefficient update demand assessment index of the i-th carbon emission accounting area, e represents the natural constant, represents the energy characteristic change index of the i-th carbon emission accounting area, represents the abnormal index of carbon emission accounting equipment in the i-th carbon emission accounting area, represents the adjacent update time interval of the carbon emission coefficient of the i-th carbon emission accounting area, represents the carbon dioxide emissions of the i-th carbon emission accounting area, represents the reference carbon dioxide emissions of the i-th carbon emission accounting area, Indicates the critical carbon emission coefficient update time interval, Indicates the allowable deviation of carbon dioxide emissions, Indicates the impact weight of the carbon emission coefficient update demand assessment index of the carbon emission accounting area corresponding to the preset energy characteristics change degree index, Indicates the impact weight of the carbon emission coefficient update demand assessment index of the carbon emission accounting area corresponding to the preset carbon emission accounting equipment abnormality index, Indicates the impact weight of the carbon emission coefficient update demand assessment index of the carbon emission accounting area corresponding to the preset carbon emission coefficient update time interval. It represents the impact weight of the carbon emission coefficient update demand assessment index of the carbon emission accounting area corresponding to the preset carbon dioxide emissions, i represents the number of the carbon emission accounting area, i=1, 2, 3, ..., k, k represents the total number of carbon emission accounting areas.

[0066] When performing the carbon emission coefficient update demand assessment index, 、 、 and The impact weights of the carbon emission coefficient update need assessment index for the energy characteristic variation index, carbon emission accounting equipment anomaly index, carbon emission coefficient update interval, and carbon emission accounting area corresponding to CO2 emissions can be directly obtained from the carbon emission database. These weights reflect their respective impacts on the carbon emission coefficient update need assessment index, and there are preset mapping rules for their correspondence. For example, a mapping set is formed between the area of ​​a city's carbon emissions and the impact weights of the carbon emission coefficient update need assessment index for the energy characteristic variation index, carbon emission accounting equipment anomaly index, carbon emission coefficient update interval, and carbon emission accounting area corresponding to CO2 emissions obtained from the carbon emission database. Entering the area of ​​a city's carbon emissions into this mapping set yields the impact weights of the energy characteristic variation index, carbon emission accounting equipment anomaly index, carbon emission coefficient update interval, and carbon emission accounting area corresponding to CO2 emissions. The mapping can be one-to-one or many-to-one. In this example, the weight values ​​are limited to a range between 0 and 1 (excluding 0 and 1).

[0067] In this embodiment, the carbon emission coefficient update demand assessment index is used to quantitatively assess the need for carbon emission coefficient updates within each carbon emission accounting region. A higher carbon emission coefficient update demand assessment index indicates a greater need for carbon emission coefficient updates within that carbon emission accounting region, as indicated by a greater energy characteristic variation index, a greater carbon emission accounting equipment anomaly index, a longer interval between carbon emission coefficient updates, or a greater deviation between carbon dioxide emissions and the reference value.

[0068] The algorithm in this embodiment combines the energy characteristic variation index, the carbon emission accounting equipment anomaly index, the carbon emission coefficient update interval, and carbon dioxide emissions to comprehensively analyze and calculate the carbon emission coefficient update need assessment index. In this formula, the energy characteristic variation index, the carbon emission accounting equipment anomaly index, the carbon emission coefficient update interval, and carbon dioxide emissions interact with each other. When energy characteristics change, the measurement accuracy of the carbon emission accounting equipment may be affected, leading to equipment anomalies. A larger energy characteristic variation index indicates a larger carbon emission accounting equipment anomaly index. Changes in energy characteristics render the existing carbon emission coefficient inapplicable, necessitating an update to reflect the new energy characteristics. Changes in energy characteristics affect carbon dioxide emissions. For example, if the fuel type switches from high-carbon fuel to low-carbon fuel, carbon dioxide emissions may decrease accordingly. If the carbon emission accounting equipment experiences an anomaly, the recorded carbon emission data will be inaccurate, affecting the accuracy of the carbon emission coefficient. A larger carbon emission accounting equipment anomaly index indicates a shorter carbon emission coefficient update interval. Abnormalities in carbon emission accounting equipment can lead to inaccurate recorded CO2 emissions. If equipment failures result in emissions being underestimated or overestimated, this will directly impact the accurate assessment of carbon emissions. If the carbon emission coefficient remains unupdated for an extended period, it may not accurately reflect current emissions, potentially causing a discrepancy between recorded CO2 emissions and actual emissions. By comprehensively analyzing energy characteristic fluctuation indicators, carbon emission accounting equipment abnormality indicators, the interval between carbon emission coefficient updates, and CO2 emissions, we can accurately derive a carbon emission coefficient update need assessment index, quantitatively reflecting the urgency and necessity of real-time carbon emission coefficient updates within each carbon emission accounting region.

[0069] Specifically, the carbon emission coefficient update judgment is made according to the carbon emission coefficient update demand assessment index. The specific analysis process is: compare the carbon emission coefficient update demand assessment index of each carbon emission accounting area with the carbon emission coefficient update demand assessment threshold preset in the carbon emission database; if the carbon emission coefficient update demand assessment index of a carbon emission accounting area is greater than or equal to the carbon emission coefficient update demand assessment threshold preset in the carbon emission database, the carbon emission coefficient of the carbon emission accounting area is updated; if the carbon emission coefficient update demand assessment index of a carbon emission accounting area is less than the carbon emission coefficient update demand assessment threshold preset in the carbon emission database, no additional operation is performed.

[0070] It should be understood that the carbon emission database in this embodiment pre-sets a carbon emission coefficient update demand assessment threshold. The carbon emission coefficient update demand assessment index of each region is obtained through the energy characteristic change degree index, the carbon emission accounting equipment abnormality index, the carbon emission coefficient adjacent update time interval and the carbon dioxide emissions, which comprehensively reflects the current adaptation of the carbon emission coefficient of the region. When making an update judgment, the carbon emission coefficient update demand assessment index of each carbon emission accounting region is compared with the carbon emission coefficient update demand assessment threshold preset in the carbon emission database. If the carbon emission coefficient update demand assessment index of a carbon emission accounting region is greater than or equal to the carbon emission coefficient update demand assessment threshold preset in the carbon emission database, it means that the carbon emission accounting region has a comprehensive situation in terms of energy utilization, equipment operation, carbon emission accounting timeliness and actual emission and expected deviation, and has reached a level where the carbon emission coefficient must be adjusted. At this time, the carbon emission coefficient of the carbon emission accounting region needs to be updated. On the contrary, if the carbon emission coefficient update demand assessment index of a carbon emission accounting area is less than the carbon emission coefficient update demand assessment threshold preset in the carbon emission database, it means that the current carbon emission accounting area is in a relatively stable and controllable state under comprehensive conditions such as energy utilization, equipment operation, carbon emission accounting timeliness, and actual emissions and expected deviations. At this time, no additional operation is required, and the existing carbon emission coefficient can be maintained and the monitoring of various indicators can be continued to avoid data confusion and resource waste caused by unnecessary frequent adjustments, so as to ensure the smooth and efficient operation of the carbon emission accounting system.

[0071] Specifically, the carbon emission coefficient of the carbon emission accounting area is updated, and the specific analysis process is: subtract the carbon emission coefficient update demand assessment index of each carbon emission accounting area from the carbon emission coefficient update demand assessment threshold preset in the carbon emission database to obtain the carbon emission coefficient update deviation value; judge whether the carbon emission coefficient corresponding to each type of energy needs to be updated based on the characteristic data of each type of energy, and update the carbon emission coefficient corresponding to each type of energy based on the carbon emission coefficient update deviation value to obtain the updated carbon emission coefficient corresponding to each type of energy.

[0072] In a specific embodiment, energy types include coal, natural gas, and electricity. For the coal carbon content in the carbon emission accounting area, if the coal carbon content is equal to the reference coal carbon content, the carbon emission coefficient corresponding to the coal is not updated; if the coal carbon content is higher than the reference coal carbon content, the carbon emission coefficient corresponding to the coal is added to the carbon emission coefficient update deviation value to obtain an updated carbon emission coefficient; if the coal carbon content is lower than the reference coal carbon content, the carbon emission coefficient corresponding to the coal is subtracted from the carbon emission coefficient update deviation value to obtain an updated carbon emission coefficient. For the natural gas methane content in the carbon emission accounting area, if the natural gas methane content is equal to the reference natural gas methane content, the carbon emission coefficient corresponding to the natural gas is not updated; if the natural gas methane content is higher than the reference natural gas methane content, the carbon emission coefficient corresponding to the natural gas is added to the carbon emission coefficient update deviation value to obtain an updated carbon emission coefficient; if the natural gas methane content is lower than the reference natural gas methane content, the carbon emission coefficient corresponding to the natural gas is subtracted from the carbon emission coefficient update deviation value to obtain an updated carbon emission coefficient. For the proportion of clean energy power generation in the carbon emission accounting area, if the proportion of clean energy power generation is equal to the reference proportion of clean energy power generation, the carbon emission coefficient corresponding to electricity will not be updated; if the proportion of clean energy power generation is higher than the reference proportion of clean energy power generation, the carbon emission coefficient corresponding to electricity will be added to the updated deviation value of the carbon emission coefficient to obtain the updated carbon emission coefficient; if the proportion of clean energy power generation is lower than the reference proportion of clean energy power generation, the carbon emission coefficient corresponding to electricity will be subtracted from the updated deviation value of the carbon emission coefficient to obtain the updated carbon emission coefficient.

[0073] Carbon emission accounting is carried out for each carbon emission accounting area based on the various energy consumptions in each carbon emission accounting area and the updated carbon emission coefficients of each carbon emission accounting area.

[0074] Specifically, carbon emissions are calculated for each carbon emission accounting area based on the various energy consumption amounts and the updated carbon emission coefficients of each carbon emission accounting area. The specific analysis process is: multiplying the various energy consumption amounts of each carbon emission accounting area with the corresponding updated carbon emission coefficients of each carbon emission accounting area to obtain the carbon emissions of various energy consumption amounts in each carbon emission accounting area; adding the carbon emissions of various energy consumption amounts in each carbon emission accounting area to obtain the total carbon emissions of each area.

[0075] It should be understood that in this embodiment, energy consumption refers to the amount of various types of energy consumed in each carbon emission accounting area. The energy types may include coal, oil, natural gas, electricity, etc., and the consumption of each type of energy will generate corresponding carbon emissions. The carbon emission coefficient refers to the carbon emissions generated by unit energy consumption, which reflects the ability of different energy sources to release carbon dioxide during combustion or use. The energy consumption of each type of energy in each carbon emission accounting area is multiplied by the corresponding updated carbon emission coefficient, and the energy consumption is converted into carbon emissions, that is, the carbon dioxide emissions generated by the consumption of each energy in a certain carbon emission accounting area, and the carbon emissions of each type of energy in the carbon emission accounting area are obtained. The carbon emissions of the various types of energy consumption in the carbon emission accounting area are added together to obtain the total carbon emissions of the carbon emission accounting area. The carbon emissions of all energy sources in the area are summarized to obtain a comprehensive carbon emission status.

[0076] Reference Figure 2 As shown, the second aspect of the present invention provides an urban carbon emission accounting system based on energy flow analysis, including: a regional division and data monitoring module, an energy characteristic indicator module, an equipment status indicator module, a coefficient update judgment module and a carbon emission accounting module.

[0077] The regional division and data monitoring module is used to divide the carbon emission accounting city into regions to obtain various carbon emission accounting regions, and monitor the energy consumption data and carbon emission data of each carbon emission accounting region. The energy consumption data includes various energy characteristic data and various energy consumption amounts.

[0078] The energy characteristic index module is used to obtain the energy characteristic change degree index of each carbon emission accounting area based on various energy characteristic data processing.

[0079] The equipment status indicator module is used to monitor the status data of carbon emission accounting equipment and process it to obtain abnormal indicators of carbon emission accounting equipment in each carbon emission accounting area.

[0080] The coefficient update judgment module is used to obtain the carbon emission coefficient update time interval of each carbon emission accounting area, and comprehensively analyze the carbon emission coefficient update demand assessment index based on the energy characteristics change degree index, carbon emission accounting equipment abnormality index, carbon emission coefficient update time interval and carbon emission data of each carbon emission accounting area, and make a carbon emission coefficient update judgment based on the carbon emission coefficient update demand assessment index.

[0081] The carbon emission accounting module is used to perform carbon emission accounting for each carbon emission accounting area based on the various energy consumption amounts of each carbon emission accounting area and the updated carbon emission coefficients of each carbon emission accounting area.

[0082] The carbon emissions database is used to store various data related to carbon emissions accounting and management, including reference coal carbon content, reference natural gas methane content, reference clean energy power generation ratio, allowable deviation coal carbon content, allowable deviation natural gas methane content, allowable deviation clean energy power generation ratio, cumulative operating time of critical equipment, number of critical equipment failures, critical equipment maintenance frequency, and time interval between near-term maintenance of critical equipment. Data in the carbon emissions database can be obtained from energy consumption monitoring systems, enterprise environmental management systems, emission factor libraries published by government environmental protection departments, and professional carbon emissions data collection and analysis platforms.

[0083] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made based on the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can better understand and utilize the present invention. As long as they do not deviate from the structure of the present invention or exceed the scope defined by the present invention, they should fall within the scope of protection of the present invention.

Claims

1. A method for calculating urban carbon emissions based on energy flow analysis, characterized by: include: Divide the carbon emission accounting cities into regions to obtain carbon emission accounting regions, and monitor the energy consumption data and carbon emission data of each carbon emission accounting region, wherein the energy consumption data includes various energy characteristic data and various energy consumption amounts; The energy characteristic change index of each carbon emission accounting area is obtained by processing various energy characteristic data; Monitor the status data of carbon emission accounting equipment and process it to obtain abnormal indicators of carbon emission accounting equipment in each carbon emission accounting area; Obtain the carbon emission coefficient update interval for each carbon emission accounting area, and comprehensively analyze the carbon emission coefficient update demand assessment index based on the energy characteristic change degree index, carbon emission accounting equipment abnormality index, carbon emission coefficient update interval and carbon emission data of each carbon emission accounting area. Make a judgment on the carbon emission coefficient update demand assessment index based on the carbon emission coefficient update demand assessment index; Carry out carbon emission accounting for each carbon emission accounting area based on the various energy consumption amounts and updated carbon emission coefficients of each carbon emission accounting area; Obtain an abnormality index of carbon emission accounting equipment in each carbon emission accounting area based on the carbon emission accounting equipment status data analysis, and compare the abnormality index of carbon emission accounting equipment in each carbon emission accounting area with the abnormality threshold of carbon emission accounting equipment preset in the carbon emission database; If the abnormality index of the carbon emission accounting equipment in a certain carbon emission accounting area is greater than or equal to the abnormality threshold of the carbon emission accounting equipment preset in the carbon emission database, it is determined that the carbon emission accounting equipment in the carbon emission accounting area is abnormal, and a feedback warning is issued; If the abnormality index of the carbon emission accounting equipment in a certain carbon emission accounting area is less than the abnormality threshold of the carbon emission accounting equipment preset in the carbon emission database, it is determined that the carbon emission accounting equipment in the carbon emission accounting area can be used normally; Obtain the carbon emission coefficient update interval for each carbon emission accounting area, and comprehensively analyze the carbon emission coefficient update demand assessment index for each carbon emission accounting area based on the energy characteristic change degree index, carbon emission accounting equipment abnormality index, carbon emission coefficient update interval, and carbon emission data of each carbon emission accounting area; Compare the carbon emission coefficient update demand assessment index of each carbon emission accounting area with the carbon emission coefficient update demand assessment threshold preset in the carbon emission database; If the carbon emission coefficient update demand assessment index of a carbon emission accounting area is greater than or equal to the carbon emission coefficient update demand assessment threshold preset in the carbon emission database, the carbon emission coefficient of the carbon emission accounting area will be updated; If the carbon emission coefficient update demand assessment index of a carbon emission accounting area is less than the carbon emission coefficient update demand assessment threshold preset in the carbon emission database, no additional operation will be performed.

2. The urban carbon emissions accounting method based on energy flow analysis according to claim 1 is characterized by: The energy characteristic change index of each carbon emission accounting area is obtained by processing various energy characteristic data. The specific analysis process is as follows: Various energy characteristic data include coal carbon content, natural gas methane content and the proportion of clean energy power generation; Extract reference coal carbon content, reference natural gas methane content, reference clean energy power generation ratio, allowable deviation coal carbon content, allowable deviation natural gas methane content and allowable deviation clean energy power generation ratio from the carbon emission database; The energy characteristic change degree index of each carbon emission accounting area is obtained based on the analysis of various energy characteristic data. The energy characteristic change degree index of each carbon emission accounting area is used to quantitatively evaluate the change range of energy characteristics in each carbon emission accounting area.

3. The urban carbon emissions accounting method based on energy flow analysis according to claim 1 is characterized by: The monitoring of the carbon emission accounting equipment status data and processing to obtain abnormal indicators of the carbon emission accounting equipment in each carbon emission accounting area also includes: The carbon emission accounting equipment status data includes the equipment's cumulative operating time, equipment failure times, equipment maintenance frequency, and equipment upcoming maintenance time intervals; Extract the cumulative operating time of critical equipment, the number of critical equipment failures, the maintenance frequency of critical equipment, and the time interval between adjacent maintenance of critical equipment from the carbon emission database; The carbon emission accounting equipment abnormality index of each carbon emission accounting area is used to quantitatively evaluate the operational abnormality of the carbon emission accounting equipment in each carbon emission accounting area; Feedback and early warning are provided based on abnormal indicators of carbon emission accounting equipment in each carbon emission accounting area.

4. The urban carbon emissions accounting method based on energy flow analysis according to claim 1 is characterized by: The comprehensive analysis to obtain the carbon emission coefficient update demand assessment index also includes: The carbon emission data includes the carbon dioxide emissions at each monitoring time point; Extracting the critical carbon emission coefficient adjacent update time interval, reference carbon dioxide emissions and allowable deviation carbon dioxide emissions from the carbon emission database; The carbon emission coefficient update demand assessment index of each carbon emission accounting area is used to quantitatively assess the demand for carbon emission coefficient update in each carbon emission accounting area.

5. The urban carbon emissions accounting method based on energy flow analysis according to claim 1 is characterized by: The carbon emission coefficient of the carbon emission accounting area is updated, and the specific analysis process is as follows: Subtract the carbon emission coefficient update demand assessment index of each carbon emission accounting area from the carbon emission coefficient update demand assessment threshold preset in the carbon emission database to obtain the carbon emission coefficient update deviation value; Based on the characteristic data of each type of energy, it is determined whether the carbon emission coefficient corresponding to each type of energy needs to be updated, and the carbon emission coefficient corresponding to each type of energy is updated according to the carbon emission coefficient update deviation value to obtain the updated carbon emission coefficient corresponding to each type of energy.

6. The urban carbon emissions accounting method based on energy flow analysis according to claim 1 is characterized by: According to the various energy consumptions of each carbon emission accounting area and the updated carbon emission coefficients of each carbon emission accounting area, carbon emission accounting is performed on each carbon emission accounting area. The specific analysis process is as follows: Multiply the energy consumption of each carbon emission accounting area by the updated carbon emission coefficient corresponding to each energy source in each carbon emission accounting area to obtain the carbon emissions of each energy source in each carbon emission accounting area; Add up the carbon emissions of various energy sources in each carbon emission accounting area to obtain the total carbon emissions of each carbon emission accounting area.

7. The urban carbon emissions accounting method based on energy flow analysis according to claim 1 is characterized by: The carbon emission coefficient update demand assessment index is obtained as follows: ； Where, represents the carbon emission coefficient update demand assessment index of the i-th carbon emission accounting area, e represents the natural constant, represents the energy characteristic change index of the i-th carbon emission accounting area, represents the abnormal index of carbon emission accounting equipment in the i-th carbon emission accounting area, represents the adjacent update time interval of the carbon emission coefficient of the i-th carbon emission accounting area, represents the carbon dioxide emissions of the i-th carbon emission accounting area, represents the reference carbon dioxide emissions of the i-th carbon emission accounting area, Indicates the time interval between updates of the critical carbon emission coefficient. Indicates the allowable deviation of carbon dioxide emissions, Indicates the impact weight of the carbon emission coefficient update demand assessment index of the carbon emission accounting area corresponding to the preset energy characteristics change degree index, Indicates the impact weight of the carbon emission coefficient update demand assessment index of the carbon emission accounting area corresponding to the preset carbon emission accounting equipment abnormality index, Indicates the impact weight of the carbon emission coefficient update demand assessment index of the carbon emission accounting area corresponding to the preset carbon emission coefficient update time interval. It represents the impact weight of the carbon emission coefficient update demand assessment index of the carbon emission accounting area corresponding to the preset carbon dioxide emissions, i represents the number of the carbon emission accounting area, i=1, 2, 3, ..., k, k represents the total number of carbon emission accounting areas.

8. A system using the urban carbon emissions accounting method based on energy flow analysis as described in any one of claims 1 to 7, characterized in that: include: Regional division and data monitoring module, energy characteristic indicator module, equipment status indicator module, coefficient update judgment module and carbon emission accounting module; The regional division and data monitoring module is used to divide the carbon emission accounting city into various carbon emission accounting areas, and monitor the energy consumption data and carbon emission data of each carbon emission accounting area. The energy consumption data includes various energy characteristic data and various energy consumption amounts. The energy characteristic index module is used to process various energy characteristic data to obtain energy characteristic change degree indicators for each carbon emission accounting area; The equipment status indicator module is used to monitor the carbon emission accounting equipment status data and process it to obtain the carbon emission accounting equipment abnormality indicators of each carbon emission accounting area; The coefficient update judgment module is used to obtain the carbon emission coefficient update interval of each carbon emission accounting area, and comprehensively analyze the carbon emission coefficient update demand assessment index based on the energy characteristic change degree index, carbon emission accounting equipment abnormality index, carbon emission coefficient update interval and carbon emission data of each carbon emission accounting area, and make a carbon emission coefficient update judgment based on the carbon emission coefficient update demand assessment index; The carbon emission accounting module is used to perform carbon emission accounting for each carbon emission accounting area based on various energy consumption amounts of each carbon emission accounting area and the updated carbon emission coefficient of each carbon emission accounting area.

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