A system and method for measuring and tracing carbon emissions from biomass co-firing in coal-fired power units.

Abstract

This invention provides a system and method for measuring and tracing carbon emission reduction through biomass co-firing in coal-fired power units, belonging to the field of power energy and environmental protection technology. It can partially solve the problems of inaccurate biomass co-firing measurement, lagging carbon emission accounting, and insufficient data reliability in existing systems. The system includes a data acquisition module, a data processing module, a data storage module, and a data display and output module. The data processing module includes a dry basis correction unit, a combustion inversion calculation unit based on the carbon element conservation relationship, a biomass back-calculation unit, and a dynamic correction unit, used to verify the actual amount of biomass involved in combustion through multi-source data fusion and to calculate the co-firing ratio and carbon emission reduction. The data storage module is used to encrypt and store key data to ensure data immutability. The method, based on the above system, realizes online measurement and traceability of biomass co-firing amount and carbon emission reduction.

Description

Technical Field

[0001] This invention belongs to the field of power energy and environmental protection technology, specifically relating to a metering and traceability system and method for carbon emission reduction through biomass co-firing in coal-fired power units. Background Technology

[0002] The power industry, as a key area of ​​carbon emissions, faces severe pressure to reduce emissions. Coal-fired power units, due to their large installed capacity and stable operation, will continue to play a fundamental power source role for a considerable period. By co-firing biomass fuel into coal-fired boilers, partial fossil fuel substitution can be achieved without large-scale modifications to the main structure of the unit, thereby reducing the carbon emission intensity per unit of electricity supplied. Therefore, biomass co-firing has become an important technological path for coal-fired units to achieve low-carbon transformation. Meanwhile, with the gradual improvement of carbon trading markets and green electricity certification mechanisms, power plants are placing higher demands on the real-time, accurate, and traceable nature of carbon emission reduction data. Currently, when coal-fired units co-firing biomass, electronic belt scales are typically installed on the biomass conveyor belt for mass measurement, and carbon emission accounting is performed monthly or annually based on coal quality and biomass test data. In terms of carbon emission management, a post-hoc accounting method based on total fuel consumption is often used, i.e., calculating total carbon emissions based on the total amount of fuel fed into the furnace and its carbon content parameters. This method is mainly based on offline statistics and lacks dynamic reflection of the co-firing ratio and carbon emission reduction effect under real-time operating conditions of the unit.

[0003] Existing technologies have the following shortcomings: First, biomass fuels are characterized by large density fluctuations, high and uneven moisture content, and ordinary belt scales are easily affected by belt tension, deviation, and changes in material accumulation morphology, resulting in large measurement errors and making it difficult to accurately reflect the actual amount fed into the furnace. Second, a single mass measurement method cannot verify whether biomass actually participates in combustion, posing a risk of "false blending" or data distortion. Third, carbon emission accounting methods based on periodic statistics are outdated and cannot support real-time optimized operation of the unit. In addition, existing systems generally lack data tamper-proofing and reliable evidence storage mechanisms, making it difficult to meet the requirements of carbon trading and regulatory verification for data authenticity and traceability. Therefore, we propose a carbon emission reduction measurement and traceability system and method for biomass blending in coal-fired units. Summary of the Invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art, and to provide a system and method for measuring and tracing carbon emission reduction by biomass co-firing in coal-fired power units.

[0005] This invention provides a system for metering and tracing carbon emission reduction from biomass co-firing in coal-fired power units, comprising: A data acquisition module is connected to the coal-fired power unit to collect operating condition data of the coal-fired power unit. The data processing module is electrically connected to the data acquisition module to receive the operating condition data and perform correction calculations, carbon emission inversion analysis, co-firing ratio calculations, and carbon emission reduction calculations on the operating condition data. A data storage module, electrically connected to the data processing module, is used to receive the processed operating condition data, encrypt the operating condition data and calculation results, and generate an unalterable data identifier; and The data display and output module is electrically connected to the data processing module to display and output the calculated co-firing ratio, carbon emission intensity and carbon emission reduction. The data processing module uses a multi-source data fusion mechanism to correlate and verify the coal combustion metering data and flue gas emission data in the operating condition data, so as to improve the accuracy of the co-firing ratio and the calculation of carbon emission reduction in the coal-fired unit.

[0006] Furthermore, the data acquisition module includes a fuel metering unit, a moisture detection unit, and a flue gas detection unit. The operating condition data includes the coal metering data, biomass feeding data, unit operating parameter data, and flue gas emission data. The biomass feeding data includes biomass mass flow rate data and biomass moisture data.

[0007] Specifically, the data processing module includes a dry basis correction unit for performing dry basis conversion of biomass mass flow rate based on the biomass moisture data to obtain the corrected biomass dry basis consumption; an inversion calculation unit for calculating the total carbon emissions of the coal-fired unit based on the carbon conservation relationship and the flue gas emission data, and inverting the actual fossil carbon input of the fuel entering the furnace by combining the carbon content parameters of the coal; and a biomass inversion unit for determining the actual biomass consumption participating in combustion based on the difference between the actual fossil carbon input and the coal metering data.

[0008] Specifically, the data processing module further includes a deviation determination unit for comparing the deviation between the dry-based biomass consumption after dry-based correction and the actual biomass consumption participating in combustion, a dynamic correction unit for updating the biomass metering data correction coefficient when the deviation exceeds a preset threshold, and an emission reduction calculation unit for calculating the real-time co-firing ratio and corresponding carbon emission reduction based on the corrected biomass consumption.

[0009] Preferably, the multi-source data fusion mechanism includes consistency verification and error correction of the coal combustion metering data and carbon emission inversion results.

[0010] Specifically, the blending ratio is the energy ratio converted according to calorific value, and the correlation verification includes carbon emission inversion calculation based on the carbon element conservation relationship.

[0011] Furthermore, the data processing module also includes a time series filtering unit for dynamically smoothing the biomass mass flow data and the flue gas emission data to reduce the impact of instantaneous fluctuations on the inversion calculation.

[0012] Another aspect of the present invention provides a method for metering and tracing carbon emission reduction from biomass co-firing in coal-fired power units. The method is implemented using the aforementioned system for metering and tracing carbon emission reduction from biomass co-firing in coal-fired power units, and includes the following steps: S1: Collect data on biomass mass flow rate, moisture content, coal flow rate, carbon dioxide concentration in flue gas, and flue gas flow rate of the coal-fired unit; S2: The biomass mass flow rate is corrected on a dry basis according to the moisture content to obtain the corrected biomass consumption; the carbon dioxide concentration and flow rate data in the flue gas are used to calculate the carbon emissions, and the actual fuel consumption is deduced by combining the carbon content of the fuel in the coal-fired unit. S3: Compare the deviation of the data obtained in step S2; and perform error correction when the deviation exceeds a preset threshold; S4: Calculate the real-time co-firing ratio and carbon emission reduction based on the corrected biomass consumption, store the calculated data, and output the results.

[0013] Furthermore, in step S3, the deviation comparison adopts a relative error calculation method.

[0014] Furthermore, in step S4, the evidence storage includes generating a data summary of the blending ratio, emission reduction, and power generation data within a preset time period and storing it in encrypted form.

[0015] The beneficial effects of this invention are as follows: This invention improves the accuracy of biomass co-firing metering by performing dry-basis correction on biomass mass flow rate and combining it with carbon emission inversion calculations based on the carbon element conservation relationship to back-verify the actual biomass consumption involved in combustion, thus constructing a dual verification mechanism. By introducing a deviation judgment and dynamic correction mechanism, it achieves closed-loop compensation for metering errors, avoiding error accumulation and improving system operational stability. This invention can calculate the co-firing ratio and carbon emission reduction in real time, realizing a shift from post-event statistics to online metering, which is beneficial for unit operation optimization and emission reduction benefit assessment. By encrypting and storing key data, it improves the credibility and traceability of carbon emission reduction data, providing a reliable basis for carbon trading and regulatory verification. Attached Figure Description

[0016] Figure 1 This is a structural connection block diagram of a biomass co-firing carbon emission reduction metering and traceability system for coal-fired power units, according to a specific embodiment of the present invention. Figure 2 This is a flowchart illustrating the steps of a method for measuring and tracing carbon emissions from biomass co-firing in coal-fired power units, according to a specific embodiment of the present invention. Figure 3 This is a schematic diagram of the overall structure of a biomass co-firing carbon emission reduction metering and traceability system for coal-fired power units, according to a specific embodiment of the present invention. Detailed Implementation

[0017] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0018] like Figure 1 As shown in the figure, a specific embodiment of the present invention provides a carbon emission reduction metering and traceability system for biomass co-firing in coal-fired power units, comprising: The system comprises the following modules: a data acquisition module connected to the coal-fired power unit to collect operating condition data; a data processing module electrically connected to the data acquisition module to receive the operating condition data and perform correction calculations, carbon emission inversion analysis, blending ratio calculations, and carbon emission reduction calculations; a data storage module electrically connected to the data processing module to receive the processed operating condition data, encrypt the operating condition data and calculation results, and generate tamper-proof data identifiers; and a data display and output module electrically connected to the data processing module to display and output the calculated blending ratio, carbon emission intensity, and carbon emission reduction. The data processing module uses a multi-source data fusion mechanism to correlate and verify the coal metering data and flue gas emission data in the operating condition data, thereby improving the accuracy of the blending ratio and carbon emission reduction calculations in the coal-fired power unit.

[0019] Specifically, such as Figure 3 As shown, the data acquisition module obtains operating condition data through online monitoring equipment installed in the fuel conveying system and flue gas system of the coal-fired unit. Among them, coal metering data can be obtained through electronic belt scales or weighing coal feeders, biomass mass flow rate data can be obtained through biomass feeding and weighing devices, the moisture detection unit obtains real-time biomass moisture content data through online moisture meters, and the flue gas detection unit obtains flue gas volume flow rate, carbon dioxide concentration, and oxygen concentration data through the flue gas online monitoring system.

[0020] Furthermore, the data processing module can be deployed in an industrial control server or edge computing terminal. By interacting with the distributed control system, it can realize real-time calculation and processing of the collected data. The calculation cycle can be set to the second, minute or hour level according to the unit's operating requirements.

[0021] Furthermore, through the above structure, this invention improves the metering accuracy of biomass co-firing and reduces the risk of accumulated metering errors through a triple verification mechanism of "dry basis correction + carbon emission inversion + closed-loop dynamic correction"; at the same time, the data storage mechanism ensures that the data is tamper-proof and improves the credibility of carbon emission reduction data.

[0022] Based on the above basic implementation method, the data acquisition module includes a fuel metering unit, a moisture detection unit, and a flue gas detection unit. The operating condition data includes coal metering data, biomass feeding data, unit operating parameter data, and flue gas emission data. The biomass feeding data includes biomass mass flow rate data and biomass moisture data.

[0023] Furthermore, the unit operating parameter data also includes auxiliary parameters such as unit load, main steam flow rate, boiler efficiency parameters, and excess air coefficient, to improve the accuracy of carbon emission inversion calculations; the fuel metering unit is used to acquire biomass fuel mass flow rate data and coal mass flow rate data respectively; the moisture detection unit is used to acquire real-time moisture content data of the biomass fuel; and the flue gas monitoring unit is used to acquire carbon dioxide concentration data, oxygen concentration data, and flue gas volume flow rate data in the flue gas.

[0024] In one specific embodiment, the data processing module includes a dry basis correction unit for performing dry basis conversion of biomass mass flow rate based on biomass moisture data to obtain the corrected biomass dry basis consumption; a back-calculation unit for calculating the total carbon emissions of the coal-fired unit based on the carbon conservation relationship and flue gas emission data, and for inversely deducing the actual fossil carbon input of the fuel entering the furnace by combining the carbon content parameters of the coal; and a biomass back-calculation unit for determining the actual biomass consumption participating in combustion based on the difference between the actual fossil carbon input and the coal metering data. The data processing module also includes a deviation determination unit for comparing the deviation between the dry basis corrected biomass dry basis consumption and the actual biomass consumption participating in combustion; a dynamic correction unit for updating the correction coefficient of the biomass metering data when the deviation exceeds a preset threshold; and an emission reduction calculation unit for calculating the real-time blending ratio and the corresponding carbon emission reduction based on the corrected biomass consumption.

[0025] In this embodiment, total carbon emissions are calculated based on the carbon conservation principle. The basic principle is that carbon elements input into the fuel are mainly emitted as carbon dioxide under complete combustion conditions. Therefore, the amount of carbon dioxide emitted in the flue gas can be used as a measure of the amount of carbon input into the fuel. Carbon emissions can be calculated as follows: Carbon emissions = flue gas volumetric flow rate × carbon dioxide volume fraction × carbon mass conversion factor; wherein, the carbon mass conversion factor is used to convert the volume fraction into mass emissions.

[0026] Furthermore, to improve calculation accuracy, the excess air coefficient can be corrected based on the oxygen concentration in the flue gas, thereby correcting the carbon emission calculation results and reducing errors caused by incomplete combustion or changes in the excess air coefficient.

[0027] Furthermore, the deviation determination unit uses a relative error method for calculation: Deviation value = |Dry basis consumption The consumption is calculated by dividing the dry basis consumption by the actual consumption. When the deviation exceeds the preset threshold, the dynamic correction unit generates a correction coefficient. This correction coefficient is used to proportionally compensate for the biomass metering data in subsequent cycles, thus forming a closed-loop error correction mechanism. The preset threshold can be determined based on historical operating data statistics.

[0028] In another specific embodiment, the multi-source data fusion mechanism includes consistency verification and error correction of coal combustion metering data and carbon emission inversion results; the data storage module adopts blockchain technology, digital signature technology, or other storage technologies with data immutability characteristics; the blending ratio is the energy ratio converted according to calorific value; the correlation verification includes carbon emission inversion calculation based on the carbon element conservation relationship; the carbon emission inversion calculation is preferably performed according to the following carbon element conservation relationship: the formula for calculating the mass flow rate of carbon dioxide in flue gas is:

[0029] in, The mass flow rate of carbon dioxide is (kg / h). The volumetric flow rate of dry flue gas under standard conditions (Nm³ / h); This represents the volume fraction of carbon dioxide. The density of carbon dioxide under standard conditions is 1.977 kg / Nm³. The formula for calculating the carbon mass flow rate of flue gas is:

[0030] in, This is the molecular weight conversion factor between carbon and carbon dioxide. When considering the correction for flue gas moisture content, the dry flue gas volumetric flow rate is calculated as follows:

[0031] in, The moisture content of the flue gas by volume; When considering combustion efficiency correction, the actual fossil carbon input is:

[0032] in, For carbon combustion efficiency, the optimal value is determined based on the oxygen content of the flue gas; The excess air coefficient can be calculated based on the oxygen concentration in the flue gas:

[0033] in, The volume fraction of oxygen in flue gas (%) The preferred method for calculating the coal carbon input is as follows:

[0034] in, This refers to the mass flow rate of coal. The mass fraction of carbon in coal; The theoretical carbon input for biomass is:

[0035] The actual biomass mass flow rate involved in combustion is:

[0036] This formula is based on the carbon conservation relationship and forms the mathematical foundation of the biomass reverse calculation model.

[0037] In this embodiment, the multi-source data fusion mechanism includes: calculating the theoretical biomass consumption based on metering data; calculating the actual biomass consumption involved in combustion based on carbon emission inversion; verifying the consistency of the two sets of data; and compensating for errors when the deviation exceeds a threshold. Through the above fusion logic, the accumulation of errors caused by a single metering method can be avoided.

[0038] Specifically, the blending ratio is preferably calculated based on the energy ratio after calorific value conversion, that is: Blending ratio = Biomass input heat ÷ (Coal input heat + Biomass input heat); where the input heat is calculated from the mass flow rate and lower heating value parameters. The formula for calculating biomass input heat is:

[0039] The calorific value of coal is:

[0040] The formula for calculating the blending ratio is:

[0041] The carbon emission reduction per unit time is calculated as follows:

[0042] in:

[0043] The carbon dioxide emission reduction is: .

[0044] In another specific embodiment, the data processing module further includes a time series filtering unit for dynamically smoothing biomass mass flow data and flue gas emission data to reduce the impact of instantaneous fluctuations on the inversion calculation.

[0045] Furthermore, the time series filtering unit employs a moving average filtering algorithm or a Kalman filtering algorithm to smooth the instantaneous fluctuation data, thereby reducing the impact of fuel delivery fluctuations and flue gas disturbances on the inversion calculation results.

[0046] In one specific implementation, such as Figure 2 As shown, the present invention also provides a method for metering and tracing carbon emission reduction from biomass co-firing in coal-fired power units. The method is implemented using the aforementioned system for metering and tracing carbon emission reduction from biomass co-firing in coal-fired power units, and includes the following steps: S1: Collect data on biomass mass flow rate, moisture content, coal flow rate, carbon dioxide concentration in flue gas, and flue gas flow rate of coal-fired power units; S2: The biomass mass flow rate is corrected on a dry basis according to the moisture content to obtain the corrected biomass consumption; the carbon emissions are calculated based on the carbon dioxide concentration and flow rate data in the flue gas, and the actual fuel consumption is deduced by combining the carbon content of the fuel in the coal-fired unit. S3: Compare the deviation of the data obtained in step S2; and perform error correction when the deviation exceeds a preset threshold; S4: Calculate the real-time co-firing ratio and carbon emission reduction based on the corrected biomass consumption, store the calculated data, and output the results.

[0047] Specifically, in step S3, the deviation comparison adopts the relative error calculation method.

[0048] Furthermore, in step S4, the evidence storage includes generating a data summary of the blending ratio, emission reduction, and power generation data within a preset time period and storing it in encrypted form.

[0049] In one specific embodiment, the present invention is applied to a 600MW supercritical coal-fired power generating unit that operates with biomass co-firing. The system is deployed in the unit's control system server, and the data acquisition cycle is set to 1 hour. Within a certain statistical period, the collected operating data are as follows: coal mass flow rate is 210 t / h, lower heating value of coal is 20.5 MJ / kg, and carbon content of coal is 65%; biomass wet-basis mass flow rate is 32 t / h, biomass moisture content is 18%, lower heating value of biomass dry-basis is 16 MJ / kg, and carbon content of biomass is 48%; flue gas volume flow rate is 1,450,000 Nm³ / h, and the volume fraction of carbon dioxide and oxygen in the flue gas is 14.2% and 4.5%, respectively.

[0050] In this embodiment, the wet-basis mass flow rate is converted to a dry-basis rate based on the biomass moisture content: Biomass dry-basis consumption = 32 × (1 0.18) = 26.24 t / h; the volumetric flow rate of carbon dioxide in the flue gas is: 1450000 × 14.2% = 205900 Nm³ / h; calculated based on the carbon dioxide density of 1.977 kg / Nm³ under standard conditions, the mass of carbon dioxide is: 205900 × 1.977 = 406100 kg / h; converting the mass of carbon dioxide to the mass of carbon (carbon mass accounts for 12 / 44 of the mass of carbon dioxide), the carbon emission is: 406100 × (12 / 44) ≈ 110.76 t / h; considering the influence of oxygen concentration on the excess air coefficient, assuming a correction factor of 0.92, the corrected actual fossil carbon emission is: 110.76 ÷ 0.92 ≈ 120.39 t / h; the coal-fired carbon input is: 210 × 0.65 = 136.5 t / h; according to the carbon conservation law, the non-fossil carbon source is: 136.5 120.39 = 16.11 t / h; Based on a biomass carbon content of 48%, the actual biomass consumption for combustion is calculated as: 16.11 ÷ 0.48 ≈ 33.56 t / h; The dry-basis corrected biomass consumption is 26.24 t / h, therefore the calculated biomass consumption for combustion is 33.56 t / h; the relative deviation is: |26.24 33.56 ÷ 26.24 ≈ 27.9%; When the preset deviation threshold is set to 10%, the deviation exceeds the threshold, triggering a dynamic correction mechanism; The correction coefficient is: 33.56 ÷ 26.24 ≈ 1.279; In the next statistical period, the biomass measurement result is multiplied by this correction coefficient for compensation, thus forming a closed-loop verification mechanism.

[0051] Specifically, the heat input from coal combustion is: 210000kg×20.5MJ / kg=4305000MJ / h; The biomass input heat is: 26240 kg × 16 MJ / kg = 419840 MJ / h; the co-firing ratio calculated based on calorific value is: 419840 ÷ (4305000 + 419840) ≈ 8.89%; if all power generation is done using coal, the theoretical carbon emissions are: (4724840 MJ ÷ 20.5 MJ / kg) × 0.65 ≈ 149.8 t / h; the actual carbon emissions are 120.39 t / h; the carbon emission reduction is: 149.8 120.39 = 29.41 t / h; converted to CO2 emission reduction: 29.41 × (44 / 12) ≈ 107.86 tCO2 / h; as can be seen from the above examples, this invention achieves accurate identification of the actual amount of biomass involved in combustion through a multi-source data fusion mechanism of "dry basis correction + carbon emission inversion + closed-loop dynamic correction". Compared with relying solely on a single weighing and metering method, this invention can automatically identify metering deviations and perform dynamic compensation during operation, improving the accuracy of co-firing ratio and carbon emission reduction calculation. Simultaneously, key data is encrypted and stored, providing reliable data evidence for carbon trading verification.

[0052] To aid in a better understanding of the present invention, a more comprehensive and specific embodiment is described. In this embodiment, the present invention provides a biomass co-firing carbon reduction metering and traceability system for coal-fired power units, comprising: The system comprises the following modules: a data acquisition module connected to the coal-fired power unit to collect operating condition data; a data processing module electrically connected to the data acquisition module to receive the operating condition data and perform correction calculations, carbon emission inversion analysis, blending ratio calculations, and carbon emission reduction calculations; a data storage module electrically connected to the data processing module to receive the processed operating condition data, encrypt the operating condition data and calculation results, and generate tamper-proof data identifiers; and a data display and output module electrically connected to the data processing module to display and output the calculated blending ratio, carbon emission intensity, and carbon emission reduction. The data processing module uses a multi-source data fusion mechanism to correlate and verify the coal metering data and flue gas emission data in the operating condition data, thereby improving the accuracy of the blending ratio and carbon emission reduction calculations in the coal-fired power unit.

[0053] In this embodiment, the data acquisition module includes a fuel metering unit, a moisture detection unit, and a flue gas detection unit. Operating condition data includes coal metering data, biomass feed data, unit operating parameter data, and flue gas emission data. Biomass feed data includes biomass mass flow rate data and biomass moisture data. The data processing module includes a dry basis correction unit for performing dry basis conversion of biomass mass flow rate based on biomass moisture data to obtain the corrected biomass dry basis consumption; a back-calculation unit for calculating the total carbon emissions of the coal-fired unit based on the carbon conservation relationship and flue gas emission data, and for inversely deriving the actual fossil carbon input of the fuel entering the furnace by combining the carbon content parameter of the coal; and a biomass back-calculation unit for determining the actual biomass consumption involved in combustion based on the difference between the actual fossil carbon input and the coal metering data. The data processing module also includes a deviation determination unit for comparing the deviation between the dry-basis corrected biomass consumption and the actual biomass consumption involved in combustion; a dynamic correction unit for updating the correction coefficient of biomass metering data when the deviation exceeds a preset threshold; and an emission reduction calculation unit for calculating the real-time blending ratio and corresponding carbon emission reduction based on the corrected biomass consumption. The multi-source data fusion mechanism includes consistency verification and error correction of coal combustion metering data and carbon emission inversion results. The blending ratio is the energy ratio converted according to calorific value, and the correlation verification includes carbon emission inversion calculation based on the carbon element conservation relationship. The data processing module also includes a time series filtering unit for dynamically smoothing biomass mass flow data and flue gas emission data to reduce the impact of instantaneous fluctuations on the inversion calculation.

[0054] Specifically, on the other hand, a method for measuring and tracing carbon emission reduction from biomass co-firing in coal-fired power units is provided. The method is implemented using the aforementioned system for measuring and tracing carbon emission reduction from biomass co-firing in coal-fired power units, and includes the following steps: S1: Collect data on biomass mass flow rate, moisture content, coal flow rate, carbon dioxide concentration in flue gas, and flue gas flow rate of coal-fired power units; S2: The biomass mass flow rate is corrected on a dry basis based on the moisture content to obtain the corrected biomass consumption; carbon emissions are calculated based on the carbon dioxide concentration and flow rate data in the flue gas, and the actual fuel consumption is deduced by combining the carbon content of the fuel in the coal-fired unit. S3: Compare the deviation of the data obtained in step S2; and perform error correction when the deviation exceeds a preset threshold; S4: Calculate the real-time co-firing ratio and carbon emission reduction based on the corrected biomass consumption, store the calculated data and output the results; in step S3, the deviation comparison adopts the relative error calculation method; in step S4, the storage includes generating a data summary of the co-firing ratio, emission reduction and power generation data within the preset time period and storing it in encryption.

[0055] In summary, the embodiments disclosed herein have at least the following technical effects: This invention corrects the biomass mass flow rate on a dry basis and combines it with carbon emission inversion calculation based on the carbon element conservation relationship to back-calculate the actual biomass consumption involved in combustion. It constructs a dual metering mechanism of "direct metering + inversion verification", which effectively overcomes the metering error problem caused by large fluctuations in the moisture content and significant changes in the density of biomass fuel, and improves the accuracy of biomass blending measurement. This invention uses carbon dioxide emission data in flue gas to deduce the actual amount of fossil carbon input and determines the actual amount of biomass involved in combustion based on coal combustion metering data. It can identify the deviation between metering data and actual combustion state, avoid the risk of "false blending" or metering distortion caused by relying solely on weighing data, and improve the authenticity of blending data. This invention automatically generates a correction coefficient when the deviation exceeds a preset threshold and participates in the measurement calculation of subsequent statistical periods, forming a dynamic closed-loop verification mechanism to achieve adaptive compensation of measurement errors, avoid error accumulation, and improve system operation stability. This invention calculates the real-time co-firing ratio based on the actual biomass consumption after inversion and converts it according to the calorific value, and calculates the carbon emission reduction accordingly. It realizes the transformation from traditional monthly or annual ex-post accounting to hourly or minute-level online calculation, which is conducive to unit operation optimization and emission reduction benefit assessment. This invention generates data summaries and encrypts and stores key data such as blending ratio, carbon emission reduction, and power generation through a data storage module, ensuring that the data cannot be tampered with, improving the credibility of carbon emission data, and providing reliable data support for carbon trading verification, green power certification, and regulatory audit. By introducing oxygen concentration correction for excess air coefficient and time series filtering, this invention can reduce the impact of unit load fluctuations and combustion disturbances on calculation results, and improve the system's adaptability and stability under different operating conditions.

[0056] It is understood that the above embodiments are merely exemplary implementations used to illustrate the principles of the present invention, and the present invention is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A biomass blending carbon emission reduction measurement and tracing system for coal-fired units, characterized in that, include: A data acquisition module is connected to the coal-fired power unit to collect operating condition data of the coal-fired power unit. The data processing module is electrically connected to the data acquisition module to receive the operating condition data and perform correction calculations, carbon emission inversion analysis, co-firing ratio calculations, and carbon emission reduction calculations on the operating condition data. The data storage module is electrically connected to the data processing module to receive the processed operating condition data, encrypt the operating condition data and calculation results, and generate an unalterable data identifier. as well as The data display and output module is electrically connected to the data processing module to display and output the calculated co-firing ratio, carbon emission intensity and carbon emission reduction. The data processing module uses a multi-source data fusion mechanism to correlate and verify the coal combustion metering data and flue gas emission data in the operating condition data, so as to improve the accuracy of the co-firing ratio and the calculation of carbon emission reduction in the coal-fired unit.

2. The system of claim 1, wherein, The data acquisition module includes a fuel metering unit, a moisture detection unit, and a flue gas detection unit. The operating condition data includes the coal metering data, biomass feeding data, unit operating parameter data, and flue gas emission data. The biomass feeding data includes biomass mass flow rate data and biomass moisture data.

3. The system of claim 2, wherein, The data processing module includes a dry basis correction unit for performing dry basis conversion of biomass mass flow rate based on biomass moisture data to obtain the corrected biomass dry basis consumption; an inversion calculation unit for calculating the total carbon emissions of the coal-fired unit based on the carbon conservation relationship and the flue gas emission data, and inverting the actual fossil carbon input of the fuel entering the furnace by combining the carbon content parameters of the coal; and a biomass inversion unit for determining the actual biomass consumption participating in combustion based on the difference between the actual fossil carbon input and the coal metering data.

4. The system of claim 3, wherein, The data processing module further includes a deviation determination unit for comparing the deviation between the dry-basis biomass consumption after dry-basis correction and the actual biomass consumption participating in combustion, a dynamic correction unit for updating the biomass metering data correction coefficient when the deviation exceeds a preset threshold, and an emission reduction calculation unit for calculating the real-time co-firing ratio and corresponding carbon emission reduction based on the corrected biomass consumption.

5. The biomass co-firing carbon emission reduction metering and traceability system for coal-fired power units according to claim 1, characterized in that, The multi-source data fusion mechanism includes consistency verification and error correction of the coal combustion metering data and carbon emission inversion results.

6. The biomass co-firing carbon emission reduction metering and traceability system for coal-fired power units according to claim 1, characterized in that, The blending ratio is the energy ratio converted according to calorific value, and the correlation verification includes carbon emission inversion calculation based on the carbon element conservation relationship.

7. The biomass co-firing carbon emission reduction metering and traceability system for coal-fired power units according to any one of claims 1 to 6, wherein the data processing module further includes a time series filtering unit for dynamically smoothing the biomass mass flow data and the flue gas emission data to reduce the impact of instantaneous fluctuations on the inversion calculation.

8. A method for metering and tracing carbon emission reduction from biomass co-firing in coal-fired power units, characterized in that, The method is implemented using the biomass co-firing carbon emission reduction metering and traceability system for coal-fired power units according to any one of claims 1 to 7, and includes the following steps: S1: Collect data on biomass mass flow rate, moisture content, coal flow rate, carbon dioxide concentration in flue gas, and flue gas flow rate of the coal-fired unit; S2: The biomass mass flow rate is corrected on a dry basis according to the moisture content to obtain the corrected biomass consumption; the carbon dioxide concentration and flow rate data in the flue gas are used to calculate the carbon emissions, and the actual fuel consumption is deduced by combining the carbon content of the fuel in the coal-fired unit. S3: Compare the deviation of the data obtained in step S2; and perform error correction when the deviation exceeds a preset threshold; S4: Calculate the real-time co-firing ratio and carbon emission reduction based on the corrected biomass consumption, store the calculated data, and output the results.

9. The method for metering and tracing carbon emission reduction from biomass co-firing in coal-fired power units according to claim 8, characterized in that, In step S3, the deviation comparison is performed using a relative error calculation method.

10. The method for metering and tracing carbon emission reduction from biomass co-firing in coal-fired power units according to claim 8, characterized in that, In step S4, the evidence storage includes generating a data summary of the blending ratio, emission reduction and power generation data within a preset time period and storing it in encrypted form.

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