A smart electric energy meter for carbon emission monitoring

Abstract

This invention relates to the field of electricity meter control technology, and more particularly to a smart electricity meter for carbon emission monitoring. It includes a power distribution detection module to detect distributed power generation, an electricity meter detection module to detect consumed electricity, and a data storage module to store two types of data. A carbon emission statistics module calculates the corresponding carbon emissions; a data analysis module analyzes the electricity consumption difference within the detection period, generates a curve of distributed power generation versus consumed electricity, and compares the results to determine whether carbon emission compensation is necessary; a carbon emission compensation module compensates for the actual carbon emissions based on the electricity consumption difference; a control module controls each module based on the analysis results; and an alarm module alarms for non-compliant carbon emissions. This invention improves the accuracy of carbon emission data monitored by the smart electricity meter by comparing distributed power generation and consumed electricity and adjusting the carbon emission image compensation parameters.

Description

Technical Field

[0001] This invention relates to the field of electricity meter control technology, and in particular to a smart electricity meter for carbon emission monitoring. Background Technology

[0002] Smart meters are one of the basic devices for data acquisition in smart grids. They are responsible for the collection, measurement, and transmission of raw electrical energy data, and are the foundation for information integration, analysis, optimization, and presentation. In addition to the basic electricity metering function of traditional meters, smart meters also possess intelligent functions such as bidirectional multi-rate metering, user-end control, bidirectional data communication with multiple data transmission modes, and anti-theft features to adapt to smart grids and the use of new energy sources.

[0003] Chinese Patent Publication No. CN109470902A discloses a smart meter comprising a power metering device, a shunt trip unit, a residual current device (RCD), and an air switch. The power metering device is connected to the shunt trip unit and monitors a first current value of the electrical device. When the first current value exceeds a preset power-off current threshold, the device supplies power to the shunt trip unit. The shunt trip unit is connected to the air switch and trips upon receiving the power supply voltage from the power metering device, thereby tripping the air switch. The RCD is connected to both the shunt trip unit and the air switch and monitors a second current value of the electrical device. When the second current value exceeds a leakage current threshold, the device trips, thereby tripping both the air switch and the shunt trip unit. This invention solves the technical problems of low integration and data processing efficiency in existing smart meters, which hinders management of user electricity consumption.

[0004] Therefore, the existing technology has the following problems: when conducting carbon emission detection, the lack of carbon emission impact compensation parameters by comparing and adjusting the distributed power generation and consumed power generation leads to inaccurate carbon emission data monitored by smart energy meters. Summary of the Invention

[0005] Therefore, the present invention provides a smart energy meter for carbon emission monitoring, which overcomes the problem in the prior art that the carbon emission data monitored by the smart energy meter is inaccurate due to the lack of carbon emission impact compensation parameters that are adjusted by comparing the distributed power generation and consumed power generation.

[0006] To achieve the above objectives, the present invention provides a smart energy meter for carbon emission monitoring, comprising:

[0007] The power distribution detection module is used to detect the power generation generated by the substation.

[0008] The electricity meter detection module is used to detect the electricity consumption passing through the electricity meter;

[0009] A data storage module, which is connected to the power distribution detection module and the electricity meter detection module, is used to store power distribution data and power consumption data;

[0010] A carbon emission statistics module, which is connected to the data storage module, is used to count the corresponding carbon emissions of the electricity detected by each module;

[0011] The data analysis module is connected to the data storage module to analyze the power difference during the detection period, obtain a power distribution curve based on the power distribution, obtain a power consumption curve based on the power consumption, and compare the power distribution curve and the power consumption curve to determine whether carbon emissions need to be compensated.

[0012] A carbon emission compensation module is used to compensate for the actual carbon emissions based on the difference in electricity consumption.

[0013] A control module, which is connected to the data analysis module, is used to control the operation of each module according to the analysis results of the data analysis module;

[0014] An alarm module, which is connected to the data analysis module, is used to issue an alarm when the actual carbon emissions are not up to standard.

[0015] The power difference is the difference between the generated electricity and the consumed electricity.

[0016] Furthermore, the data analysis module includes,

[0017] The first data analysis unit adjusts the carbon emission impact compensation parameters based on the comparison results of the distributed power generation and the consumed power generation.

[0018] The second data analysis unit re-determines the actual carbon emissions based on the comparison results of the power distribution curve and the power consumption curve.

[0019] Furthermore, the power distribution detection module detects the quota power generation generated by the substation within a preset time period, and the carbon emission statistics module determines the first basic carbon emission within the corresponding time period based on the quota power generation.

[0020] Furthermore, the data analysis module determines the estimated carbon emissions based on the distributed electricity generation, determines the actual carbon emissions based on the consumed electricity, compares the estimated carbon emissions with the actual carbon emissions to obtain a carbon emissions comparison result, and determines whether the carbon emissions are accurate based on the carbon emissions comparison result.

[0021] Furthermore, the data analysis module obtains the actual carbon emission comparison difference based on the carbon emission comparison results, and compares the actual carbon emission comparison difference with the standard carbon emission comparison difference range.

[0022] If the difference between the actual carbon emissions and the standard carbon emissions exceeds the maximum value of the difference range, the control module will control the alarm module to issue an alarm.

[0023] For cases where the actual carbon emission comparison difference is within the standard carbon emission comparison difference range, the second data analysis unit analyzes the power distribution curve and the power consumption curve to obtain the actual power loss ratio.

[0024] If the difference between the actual carbon emissions and the standard carbon emissions is less than the minimum value of the difference range, the actual carbon emissions are deemed valid.

[0025] Furthermore, the first data analysis unit adjusts the carbon emission impact compensation parameter based on the difference between the actual carbon emission comparison difference and the maximum value of the standard carbon emission comparison difference range.

[0026] Furthermore, when the second data analysis unit performs actual power loss ratio analysis, it segments the power distribution curve and the power consumption curve to obtain the actual power loss ratio, and compares the actual power loss ratio with the standard power loss ratio range to determine whether the carbon emissions are within the standard range.

[0027] Furthermore, for cases where carbon emissions meet the standards, the current power generation will be maintained.

[0028] Furthermore, for cases where carbon emissions do not meet the standards, the carbon emission impact compensation parameters for the corresponding time period are adjusted.

[0029] Compared with existing technologies, the beneficial effect of this invention lies in that it dynamically adjusts the carbon emission impact compensation parameters by comparing the difference between distributed power generation and consumed power generation, making the carbon emission calculation more consistent with the actual energy supply and demand relationship. For example, when distributed power generation is higher than consumed power generation, it indicates that energy is not being fully utilized, and there may be transmission losses or inefficient allocation. In this case, adjusting the carbon emission impact compensation parameters can reflect the "hidden carbon emissions from ineffective energy utilization".

[0030] Furthermore, through the correlation analysis of time-of-use electricity consumption and carbon emission data, grid managers can intuitively identify high-carbon emission periods and take targeted peak-shaving and valley-filling measures. Enterprises can optimize production scheduling based on time-of-use carbon emission data, such as scheduling energy-intensive processes during off-peak hours to reduce the carbon intensity per unit of product. Accurate time-of-use carbon emission data can help enterprises rationally allocate carbon allowances and adopt more cost-effective trading strategies in the carbon market, such as purchasing allowances during peak hours and selling them during off-peak hours. By comparing the actual electricity consumption and power generation during off-peak hours, the level of clean energy utilization can be assessed. If carbon emissions are high during off-peak hours, it may indicate wind and solar power curtailment, requiring optimization of energy storage configuration or inter-regional power transmission. This module, through time-of-use electricity consumption monitoring and dynamic compensation parameter calculation, constructs a refined carbon emission metering system, which not only improves the accuracy of carbon data but also provides a data foundation for grid optimization, enterprise carbon management, and demand-side response. Under the dual carbon objectives, it will become a core supporting technology for the digital transformation of the energy system.

[0031] Furthermore, the carbon emission factor calculation based on the distributed power generation reflects the theoretical carbon release. The carbon emission factor calculation based on the consumed power generation reflects the actual carbon footprint. If the difference between the two exceeds the standard range, it indicates potential parameter deviation or energy structure fluctuations, requiring alarm triggering and manual verification. If within the range, it proceeds to the in-depth power loss analysis stage. When the carbon emission difference is within a reasonable range, based on the power loss ratio of the difference between distributed power generation and consumed power, segmented monitoring and refined adjustment achieve energy supply and demand balance. Dynamic comparison between estimated and actual carbon emissions enables self-calibration of carbon emissions, improving the accuracy of carbon emission data and providing a reliable basis for corporate carbon trading and carbon neutrality goals. For power loss differences at different times, "on-demand power replenishment" avoids power shortages, while slope analysis identifies trend problems for early intervention and control, reducing line losses and energy waste. The monitoring frequency is dynamically adjusted based on the rate of change of power loss, ensuring control accuracy while optimizing system resource utilization. The segmented regulation logic divides peak hours into three segments, making the power generation and distribution adjustment process transparent and facilitating subsequent energy efficiency analysis and accountability. Quantitative calculation formulas ensure that the regulation intensity is scientifically controllable, avoiding subjective biases from human intervention. When power losses are below standard values, the power generation and distribution are proactively reduced to prevent renewable energy curtailment and improve the absorption rate.

[0032] Furthermore, based on a quantitative comparison between the actual carbon emission difference and the standard range, combined with the dynamic adjustment formula of the compensation parameters, gradient regulation can be implemented for periods of high carbon emissions. By strengthening the regulation, excess carbon emissions can be precisely compressed, helping to achieve regional or industry carbon neutrality goals. The second data analysis unit uses the power loss ratio as an indirect assessment indicator of carbon emissions. Through segmented analysis of the distribution and consumption curves, cross-validation of carbon emission status is achieved. When the power loss ratio is abnormal, high-energy-consuming links such as excessive transmission losses and inefficient equipment operation can be quickly located, and a dual judgment can be made in conjunction with the carbon emission difference to improve the accuracy of anomaly detection. For scenarios where carbon emissions meet the standards, the distribution and generation remain unchanged to ensure the stability and economy of the power grid operation; while when they exceed the standards, by dynamically adjusting the compensation parameters, the power generation plan or distribution strategy can be flexibly adjusted, such as reducing thermal power output and increasing the proportion of new energy sources, ensuring power supply reliability while avoiding the impact of "one-size-fits-all" regulation on system operation. The standard range is set based on historical data, and the compensation parameter calculation model is continuously optimized through real-time data feedback. As operational data accumulates, the system can adapt to different operating conditions, such as peak-valley load changes and fluctuations in renewable energy output, gradually forming a more realistic carbon emission management strategy and improving long-term control efficiency. Precise control reduces carbon emissions, not only mitigating the risk of environmental penalties for exceeding emission standards but also reducing fuel procurement costs and equipment maintenance expenses by optimizing the energy structure, such as lowering the proportion of high-carbon electricity. Simultaneously, efficient power loss monitoring helps identify and repair problems such as line losses and equipment failures, further reducing operating costs. Attached Figure Description

[0033] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0034] Figure 1 This is a schematic diagram of the structure of the smart energy meter used for carbon emission monitoring in the embodiment;

[0035] Figure 2 This is a flowchart illustrating the process of determining the actual power loss ratio of a smart energy meter used for carbon emission monitoring in this embodiment.

[0036] Figure 3 This is a flowchart illustrating the process of determining the slope of the power loss ratio curve of a smart energy meter used for carbon emission monitoring in this embodiment.

[0037] Figure 4 This is a schematic diagram of the data analysis module structure of a smart energy meter used for carbon emission monitoring in the embodiment. Detailed Implementation

[0038] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0039] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0040] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0041] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0042] Please see Figures 1-4 As shown, Figure 1 This is a schematic diagram of the structure of the smart energy meter used for carbon emission monitoring in the embodiment; Figure 2 This is a flowchart illustrating the process of determining the actual power loss ratio of a smart energy meter used for carbon emission monitoring in this embodiment. Figure 3 This is a flowchart illustrating the process of determining the slope of the power loss ratio curve of a smart energy meter used for carbon emission monitoring in this embodiment. Figure 4 This is a schematic diagram of the data analysis module structure of a smart energy meter used for carbon emission monitoring in the embodiment.

[0043] This embodiment provides a smart energy meter for carbon emission monitoring, including:

[0044] The power distribution detection module is used to detect the power generation generated by the substation.

[0045] The electricity meter detection module is used to detect the electricity consumption passing through the electricity meter;

[0046] A data storage module, which is connected to the power distribution detection module and the electricity meter detection module, is used to store power distribution data and power consumption data;

[0047] A carbon emission statistics module, which is connected to the data storage module, is used to count the corresponding carbon emissions of the electricity detected by each module;

[0048] The data analysis module is connected to the data storage module to analyze the power difference during the detection period, obtain a power distribution curve based on the power distribution, obtain a power consumption curve based on the power consumption, and compare the power distribution curve and the power consumption curve to determine whether carbon emissions need to be compensated.

[0049] A carbon emission compensation module is used to compensate for the actual carbon emissions based on the difference in electricity consumption.

[0050] A control module, which is connected to the data analysis module, is used to control the operation of each module according to the analysis results of the data analysis module;

[0051] An alarm module, which is connected to the data analysis module, is used to issue an alarm when the actual carbon emissions are not up to standard.

[0052] The power difference is the difference between the generated electricity and the consumed electricity.

[0053] In this embodiment, the smart energy meter for monitoring carbon emissions can be used to monitor carbon emissions from electricity consumption in industrial parks. The power distribution detection module installed at the power output port of the power distribution station can detect the power generation generated by the power distribution station. The energy meter detection module can determine the power consumption of each enterprise in the industrial park by detecting their power consumption. The data storage module can store the power generation and power consumption data in an initial time period. The initial time period can be adjusted according to peak electricity consumption periods or carbon emission monitoring needs. For example, the power generation and power consumption data can be stored once every hour.

[0054] The carbon emissions statistics module can calculate the carbon emissions generated by the electricity generated and the carbon emissions generated by the electricity consumed within the same time period.

[0055] Specifically, the data analysis module includes,

[0056] The first data analysis unit adjusts the carbon emission impact compensation parameters based on the comparison results of the distributed power generation and the consumed power generation.

[0057] The second data analysis unit re-determines the actual carbon emissions based on the comparison results of the power distribution curve and the power consumption curve.

[0058] Specifically, the power distribution detection module detects the quota power generation generated by the substation within a preset time period, and the carbon emission statistics module determines the first basic carbon emission within the corresponding time period based on the quota power generation.

[0059] The quota power generation of the substation varies at different times.

[0060] For example, during peak electricity consumption hours from 9:00 AM to 9:00 PM, the standard power generation from the distribution station is set at 3500 kWh; during off-peak hours from 10:00 PM to 6:00 AM, the standard power generation is set at 1500 kWh. This standard power generation is determined based on historical electricity consumption data for the region. If electricity consumption in the region shows an increasing trend within a week, the corresponding standard power generation increases; conversely, if electricity consumption shows a decreasing trend within a week, the corresponding standard power generation decreases. For instance, if electricity consumption increases by 5% daily within a week, the standard power generation increases by 5%; conversely, it decreases by 5%.

[0061] The primary basic carbon emissions are determined based on the quota power generation and the compensation parameter for the impact of the quota power generation on the primary basic carbon emissions. The compensation parameter for the impact of the quota power generation on the primary basic carbon emissions is set to 0.85. The compensation parameter for the impact of the quota power generation on the primary basic carbon emissions is determined based on the preset compensation parameter. If the power generation is 5000 kWh, then the primary basic carbon emissions are 5000 × 0.85 = 4250 kg.

[0062] By comparing the difference between distributed electricity generation and consumed electricity, the carbon emission impact compensation parameters are dynamically adjusted to make the carbon emission calculation more closely reflect the actual energy supply and demand relationship. For example, when distributed electricity generation is higher than consumed electricity, it indicates that energy is not being fully utilized, and there may be transmission losses or inefficient allocation. In this case, adjusting the carbon emission impact compensation parameters can reflect the "hidden carbon emissions from inefficient energy utilization".

[0063] Specifically, the electricity meter detection module detects the actual electricity consumption through the electricity meter within a preset time period, and the carbon emission statistics module determines the second basic carbon emission amount within the corresponding time period based on the actual electricity consumption.

[0064] The actual electricity consumption detected by the electricity meter varies at different times.

[0065] For example, during peak electricity consumption hours from 9:00 AM to 9:00 PM, the electricity meter detected an actual power consumption of 3200 kWh; during off-peak hours from 10:00 PM to 6:00 AM, the electricity meter detected an actual power consumption of 1200 kWh.

[0066] The second basic carbon emission is determined based on the actual electricity consumption and the compensation parameter for the impact of the actual electricity consumption on the second basic carbon emission. The compensation parameter for the impact of the actual electricity consumption on the second basic carbon emission is set to 0.8. The compensation parameter for the impact of the actual electricity consumption on the second basic carbon emission is determined according to the preset impact compensation parameter. The actual electricity consumption is 4400 kWh, so the second basic carbon emission is 4400 × 0.8 = 3520 kg.

[0067] By analyzing the correlation between time-of-use electricity consumption and carbon emission data, grid managers can intuitively identify periods of high carbon emissions and implement targeted peak-shaving and valley-filling measures. Enterprises can optimize production scheduling based on time-of-use carbon emission data, placing energy-intensive processes during off-peak hours to reduce the carbon intensity per unit of product. Accurate time-of-use carbon emission data helps enterprises rationally allocate carbon allowances and adopt more cost-effective trading strategies in the carbon market, purchasing allowances during peak hours and selling them during off-peak hours. By comparing actual electricity consumption with distributed generation during off-peak hours, the level of clean energy utilization can be assessed. High carbon emissions during off-peak hours may indicate wind and solar power curtailment, requiring optimization of energy storage configuration or inter-regional power transmission. This module, through time-of-use electricity monitoring and dynamic compensation parameter calculation, constructs a refined carbon emission metering system, not only improving the accuracy of carbon data but also providing a data foundation for grid optimization, enterprise carbon management, and demand-side response. Under the dual carbon objectives, it will become a core supporting technology for the digital transformation of the energy system.

[0068] Specifically, the data analysis module determines the estimated carbon emissions based on the distributed electricity generation, determines the actual carbon emissions based on the consumed electricity, compares the estimated carbon emissions with the actual carbon emissions to obtain a carbon emissions comparison result, and determines whether the carbon emissions are accurate based on the carbon emissions comparison result.

[0069] Specifically, the data analysis module obtains the actual carbon emission comparison difference based on the carbon emission comparison results, and compares the actual carbon emission comparison difference with the standard carbon emission comparison difference range.

[0070] If the difference between the actual carbon emissions and the standard carbon emissions exceeds the maximum value of the difference range, the control module will control the alarm module to issue an alarm.

[0071] For cases where the actual carbon emission comparison difference is within the standard carbon emission comparison difference range, the second data analysis unit analyzes the power distribution curve and the power consumption curve to obtain the actual power loss ratio.

[0072] If the difference between the actual carbon emissions and the standard carbon emissions is less than the minimum value of the difference range, the actual carbon emissions are deemed valid.

[0073] When the difference between the actual carbon emissions and the standard carbon emissions exceeds the maximum value of the difference range, the control module will activate the alarm module to trigger an alarm and push the abnormal information to the administrator's mobile phone.

[0074] When the difference between actual carbon emissions and standard carbon emissions is within the range of the difference between standard carbon emissions and standard carbon emissions, the distribution power curve and the consumption power curve are segmented to obtain the distribution-consumption power segmented curve, and the actual power loss ratio is calculated on the distribution-consumption power segmented curve.

[0075] If the actual power loss ratio is greater than the standard power loss ratio, the power generation in the corresponding segment of the power distribution-consumption segment curve is increased by the difference between the actual power loss ratio and the standard power loss ratio to avoid insufficient power generation, which would result in insufficient power consumption during that period.

[0076] For cases where the actual power loss ratio is greater than the standard power loss ratio, the slope of the actual power loss ratio curve in the power distribution-consumption segmented curve is calculated. For cases where the slope of the actual power loss ratio curve is greater than the preset slope of the standard power loss ratio curve, the initial detection cycle is reduced based on the difference between the slope of the standard power loss ratio curve and the slope of the actual power loss ratio curve to better control the power distribution and refine the power distribution to reduce energy waste or energy shortage.

[0077] If the slope of the actual power loss ratio curve is less than or equal to the preset standard power loss ratio curve slope, the original initial detection cycle shall be maintained.

[0078] If the actual power loss ratio is equal to the standard power loss ratio, then the original power generation will be maintained.

[0079] If the actual power loss ratio is less than the standard power loss ratio, the power generation in the corresponding segment of the power distribution-consumption segment curve is reduced by the power loss ratio difference between the standard power loss ratio and the actual power loss ratio.

[0080] When the difference between the actual carbon emissions and the standard carbon emissions is less than the minimum value of the difference range, the actual carbon emissions are deemed valid.

[0081] For example, in this embodiment, the standard carbon emission comparison difference range is set to [100kg, 150kg], and the standard electricity loss ratio is 5%. The standard electricity loss ratio is determined based on historical electricity loss ratio parameters for this region, and the slope of the standard electricity loss ratio curve is 0.02. The initial detection cycle is set to detect the electricity loss ratio every three hours, and the standard carbon emission comparison difference range is determined based on historical data.

[0082] The difference between the actual carbon emissions and the estimated carbon emissions is calculated by subtracting the actual carbon emissions from the estimated carbon emissions. When the difference between the actual carbon emissions and the estimated carbon emissions exceeds the maximum value of the difference range, the control module will trigger the alarm module to sound an alarm.

[0083] The peak electricity consumption period is divided into two segments. The first segment is from 9:00 AM to 12:00 PM. The detected power generation is 3500 kWh, and the power consumption is 3200 kWh. The power loss ratio is calculated as (power generation - power consumption) / power generation. The power loss ratio for the first segment of the peak electricity consumption period is (3500 - 3200) / 3500 = 0.0857.

[0084] In the segmented distribution-consumption power curve diagram, the distribution power is the product of the difference between the actual power loss ratio and the standard power loss ratio, and the consumed power.

[0085] The increased power generation during the first peak electricity consumption period is (8.57%-5%)×3200=114kWh, and the adjusted power generation is 3500+114=3614kWh. The slope of its actual power loss ratio curve is 0.0857 for the first period.

[0086] The second period is from 12:00 to 15:00. The detected power generation is 3800 kWh, and the power consumption is 3600 kWh. The power loss ratio for the second peak period is (3800-3600) / 3800 = 5.26%. The increased power generation for the second peak period is (5.26%-5%)×3600 = 9.36 kWh. The adjusted power generation is 3800 + 9.36 = 3809.36 kWh. The slope of the actual power loss ratio curve is (current power loss ratio - previous period's power loss ratio) / 3, i.e., the current power loss ratio is (3800-3600) / 3800 = 0.052. (0.052-0.0857) / 3 = -0.011 is less than the standard power loss ratio curve slope. Therefore, the initial detection cycle is maintained.

[0087] The third peak period is from 15:00 to 21:00. The detected power generation is 3500 kWh, and the power consumption is 3100 kWh. The power loss ratio for the third peak period is (3500-3100) / 3500 = 11.43%. The increase in power generation during the third peak period is (11.43%-5%) × 3100 = 199.3 kWh. The adjusted power generation is 3500 + 199.3 = 3699.3 kW. h, the slope of its actual power loss ratio curve is (current power loss ratio - previous power loss ratio) / 3, that is, (0.1143-0.0526) / 3=0.0206, which is greater than the slope of the standard power loss ratio curve. Therefore, the reduced detection cycle is the product of the initial detection cycle and 1 minus the difference between the slope of the actual power loss ratio curve and the slope of the standard power loss ratio curve, that is, 3×[1-(0.0206-0.02) / 0.02]=2.91h.

[0088] The carbon emission factor calculation based on power generation reflects the theoretical carbon release. The carbon emission factor calculation based on electricity consumption reflects the actual carbon footprint. If the difference between the two exceeds the standard range, it indicates potential parameter deviation or energy structure fluctuations, requiring alarm triggering and manual verification. If within the range, it proceeds to the in-depth power loss analysis stage. When the carbon emission difference is within a reasonable range, energy supply and demand balance is achieved through segmented monitoring and refined adjustment based on the power loss ratio (the difference rate between power generation and consumption). Dynamic comparison between estimated and actual carbon emissions enables self-calibration of carbon emissions, improving the accuracy of carbon emission data and providing a reliable basis for corporate carbon trading and carbon neutrality goals. "On-demand power replenishment" is used to address power loss differences at different times to avoid power shortages. Slope analysis identifies trends and allows for early intervention and control, reducing line losses and energy waste. Monitoring frequency is dynamically adjusted based on the rate of change in power loss, ensuring control accuracy while optimizing system resource utilization. The segmented regulation logic divides peak hours into three segments, making the power generation and distribution adjustment process transparent and facilitating subsequent energy efficiency analysis and accountability. Quantitative calculation formulas ensure that the regulation intensity is scientifically controllable, avoiding subjective biases from human intervention. When power losses are below standard values, the power generation and distribution are proactively reduced to prevent renewable energy curtailment and improve the absorption rate.

[0089] Specifically, the first data analysis unit adjusts the carbon emission impact compensation parameter based on the difference between the actual carbon emission comparison difference and the maximum value of the standard carbon emission comparison difference range.

[0090] Specifically, when the second data analysis unit performs actual power loss ratio analysis, it segments the power distribution curve and the power consumption curve to obtain the actual power loss ratio, and compares the actual power loss ratio with the standard power loss ratio range to determine whether the carbon emissions are within the standard range.

[0091] Specifically, for cases where carbon emissions meet the standards, the current power generation will be maintained.

[0092] Specifically, for cases where carbon emissions do not meet the standards, the carbon emission impact compensation parameters for the corresponding time period are adjusted.

[0093] In this embodiment, the initial carbon emission impact compensation parameter is set to 0.8.

[0094] When the difference between the actual carbon emissions and the standard carbon emissions is greater than the difference between the two maximum values ​​in the range of the actual carbon emissions, and the difference between the actual carbon emissions and the standard carbon emissions is 195, the additional carbon emissions impact compensation parameter is the product of the initial carbon emissions impact compensation parameter and 1 plus the difference between the actual carbon emissions and the standard carbon emissions difference range of the two maximum values ​​divided by the standard carbon emissions difference range of the two maximum values, i.e., 0.8×[1+(195-150 / 150)]=1.04;

[0095] For cases where carbon emissions meet the standards, the current power generation capacity will be maintained.

[0096] If carbon emissions do not meet the standards, adjust the carbon emission impact compensation parameters for the corresponding time period.

[0097] Based on a quantitative comparison of the actual carbon emission difference with the standard range, and combined with the dynamic adjustment formula of the compensation parameters, gradient regulation can be implemented for periods of high carbon emissions. By strengthening the regulation, excess carbon emissions can be precisely compressed, helping to achieve regional or industry carbon neutrality goals. The second data analysis unit uses the power loss ratio as an indirect assessment indicator of carbon emissions. Through segmented analysis of the distribution and consumption curves, cross-validation of carbon emission status is achieved. When the power loss ratio is abnormal, excessive transmission losses and inefficient equipment operation in high-energy-consuming links can be quickly located, and a dual judgment can be made in conjunction with the carbon emission difference to improve the accuracy of anomaly detection. For scenarios where carbon emissions meet the standards, the distribution and generation remain unchanged to ensure the stability and economy of the power grid operation; while when emissions exceed the standards, by dynamically adjusting the compensation parameters, the power generation plan or distribution strategy can be flexibly adjusted to reduce thermal power output or increase the proportion of new energy sources, ensuring power supply reliability while avoiding the impact of "one-size-fits-all" regulation on system operation. The standard range is set based on historical data, and the compensation parameter calculation model is continuously optimized through real-time data feedback. As operational data accumulates, the system can adapt to peak and valley load changes and fluctuations in renewable energy output under different operating conditions, gradually forming a more realistic carbon emission management strategy and improving long-term control efficiency. Precise control reduces carbon emissions, not only mitigating the risk of environmental penalties for exceeding emission standards but also reducing the proportion of high-carbon electricity by optimizing the energy structure, thereby reducing fuel procurement costs and equipment maintenance expenses. Simultaneously, efficient power loss monitoring helps identify and repair problems such as line losses and equipment failures, further reducing operating costs.

[0098] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0099] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A smart energy meter for carbon emission monitoring, characterized in that, include, The power distribution detection module is used to detect the power generation generated by the substation. The electricity meter detection module is used to detect the electricity consumption passing through the electricity meter; A data storage module, which is connected to the power distribution detection module and the electricity meter detection module, is used to store power distribution data and power consumption data; A carbon emission statistics module, which is connected to the data storage module, is used to count the corresponding carbon emissions of the electricity detected by each module; The data analysis module is connected to the data storage module to analyze the power difference during the detection period, obtain a power distribution curve based on the power distribution, obtain a power consumption curve based on the power consumption, and compare the power distribution curve and the power consumption curve to determine whether carbon emissions need to be compensated. A carbon emission compensation module is used to compensate for the actual carbon emissions based on the difference in electricity consumption. The data analysis module includes a first data analysis unit and a second data analysis unit; The data analysis module determines the estimated carbon emissions based on the distributed electricity generation, determines the actual carbon emissions based on the consumed electricity, compares the estimated carbon emissions with the actual carbon emissions to obtain a carbon emissions comparison result, and determines whether the carbon emissions are accurate based on the carbon emissions comparison result. The data analysis module obtains the actual carbon emission comparison difference based on the carbon emission comparison results, and compares the actual carbon emission comparison difference with the standard carbon emission comparison difference range. If the difference between the actual carbon emissions and the standard carbon emissions exceeds the maximum value of the difference range, the control module will control the alarm module to issue an alarm. For cases where the actual carbon emission comparison difference is within the standard carbon emission comparison difference range, the second data analysis unit analyzes the power distribution curve and the power consumption curve to obtain the actual power loss ratio, which is the power difference divided by the power distribution. If the difference between the actual carbon emissions and the standard carbon emissions is less than the minimum value of the difference range, the actual carbon emissions are deemed valid. If the actual power loss ratio is greater than the standard power loss ratio, the power generation in the corresponding segment of the power distribution-consumption segment curve is increased by the difference between the actual power loss ratio and the standard power loss ratio. If the actual power loss ratio is greater than the standard power loss ratio, the slope of the actual power loss ratio curve in the power distribution-consumption segment curve is calculated. If the slope of the actual power loss ratio curve is greater than the preset slope of the standard power loss ratio curve, the initial detection cycle is reduced based on the difference between the slope of the standard power loss ratio curve and the slope of the actual power loss ratio curve. If the actual power loss ratio is equal to the standard power loss ratio, the original power generation is maintained. If the actual power loss ratio is less than the standard power loss ratio, the power generation in the corresponding segment of the power distribution-consumption segment curve is reduced by the power loss ratio difference between the standard power loss ratio and the actual power loss ratio. When the difference between the actual carbon emissions and the standard carbon emissions is less than the minimum value of the difference range, the actual carbon emissions are deemed valid. The first data analysis unit adjusts the carbon emission impact compensation parameters based on the difference between the actual carbon emission comparison difference and the maximum value of the standard carbon emission comparison difference range. When the second data analysis unit performs actual power loss ratio analysis, it segments the power distribution curve and the power consumption curve to obtain the actual power loss ratio, and compares the actual power loss ratio with the standard power loss ratio range to determine whether the carbon emissions are within the standard range. For cases where carbon emissions meet the standards, the current power generation capacity will be maintained. For cases where carbon emissions do not meet the standards, adjust the carbon emission impact compensation parameters for the corresponding time period. A control module, which is connected to the data analysis module, is used to control the operation of each module according to the analysis results of the data analysis module; An alarm module, which is connected to the data analysis module, is used to issue an alarm when the actual carbon emissions are not up to standard. The power difference is the difference between the generated electricity and the consumed electricity.

2. The smart energy meter for carbon emission monitoring according to claim 1, characterized in that, The first data analysis unit adjusts the carbon emission impact compensation parameters based on the comparison results of the distributed power generation and the consumed power generation. The second data analysis unit re-determines the actual carbon emissions based on the comparison results of the power distribution curve and the power consumption curve.

3. The smart energy meter for carbon emission monitoring according to claim 2, characterized in that, The power distribution detection module detects the quota power generation generated by the substation within a preset time period, and the carbon emission statistics module determines the first basic carbon emission within the corresponding time period based on the quota power generation.

4. The smart energy meter for carbon emission monitoring according to claim 3, characterized in that, The electricity meter detection module detects the actual electricity consumption through the electricity meter within a preset time period, and the carbon emission statistics module determines the second basic carbon emission amount within the corresponding time period based on the actual electricity consumption.

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