Carbon tracing and apportionment method and system based on carbon balance, storage medium and equipment

Abstract

The application discloses a carbon balance-based mixed combustion carbon tracing and apportioning method and system, a storage medium and equipment, relates to the technical field of carbon emission, and comprises the following steps: carbon source decomposition is performed on the corresponding carbon amount of carbon dioxide to obtain the corresponding carbon amount of coal source carbon dioxide and the corresponding carbon amount of biomass source carbon dioxide, and a biomass carbon apportioning coefficient is calculated; a bias constraint is introduced in the process of calculating the biomass carbon apportioning coefficient to close the solution, so that the inversion result of fossil carbon carbon dioxide emission, biomass carbon dioxide emission and / or blending ratio is output while satisfying the carbon balance closure constraint. The application forms a verifiable carbon amount closed chain under the mixed coal / biomass blending combustion condition, directly outputs the fossil carbon CO2 emission and the biomass carbon CO2 emission, and gives the biomass source proportion in flue gas CO2 and the blending ratio inversion result.

Description

Technical Field

[0001] This invention relates to the field of carbon emission technology, specifically to a method, system, storage medium, and device for carbon source tracing and allocation based on carbon balance in co-firing. Background Technology

[0002] Currently, coal-fired power plants reduce carbon dioxide emissions from fossil fuels by co-firing biomass. To meet the requirements of carbon emission accounting, low-carbon power certification, and carbon trading management, it is necessary to accurately distinguish between fossil carbon and biomass carbon emissions in flue gas under co-firing conditions. However, existing technologies such as emission factor methods, traditional carbon balance methods, fuel element analysis methods, and online CEMS measurement technologies are all insufficient to solve the core challenge of carbon source allocation in co-firing scenarios.

[0003] However, existing technologies generally have the following problems: First, they cannot quantitatively decompose flue gas CO2 according to carbon sources; second, they cannot accurately reflect the dynamic changes in fuel characteristics and combustion efficiency under co-firing conditions; third, carbon balance is difficult to stably close under actual operating conditions; fourth, they cannot effectively reverse emissions when there is a lack of online CO2 monitoring conditions; and fifth, they cannot meet the requirement in carbon verification that the error in blending ratio and carbon source allocation should not exceed 5%. Summary of the Invention

[0004] The purpose of this invention is to provide a method, system, storage medium, and device for carbon source tracing and allocation based on carbon balance in co-firing, in order to solve the problems that have arisen in the prior art as described in the background.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a carbon source tracing and allocation method based on carbon balance for co-firing, comprising:

[0006] Carbon source decomposition was performed on the carbon content corresponding to carbon dioxide to obtain the carbon content corresponding to carbon dioxide from coal source and carbon content corresponding to carbon dioxide from biomass source, and the biomass carbon allocation coefficient was calculated.

[0007] In the process of calculating the biomass carbon allocation coefficient, a bias constraint closure solution is introduced to satisfy the carbon balance closure constraint and output the inversion results of fossil carbon carbon dioxide emissions, biomass carbon dioxide emissions, and / or co-firing ratio.

[0008] Preferably, carbon source decomposition includes allocating unburned carbon from different sources to obtain the amount of unburned carbon from coal fuel and the amount of unburned carbon from biomass fuel, respectively satisfying the following formulas:

[0009] C coal,CO2 =C coal,in -C coal,unburnt C bio,CO2 =C bio,in -C bio,unburnt ;

[0010] In the formula, Ccoal,CO2 C represents the carbon content corresponding to carbon dioxide from coal sources. coal,in For the carbon input of coal fuel, C coal,unburnt C represents the amount of unburned carbon in coal fuel. bio,CO2 C represents the carbon content corresponding to carbon dioxide from biomass sources. bio,in For the carbon input of biomass fuel, C bio,unburnt This refers to the amount of unburned carbon in biomass fuels.

[0011] Preferably, the allocation of unburned carbon sources is estimated based on the fuel ash content ratio and the burnout difference coefficient, or based on the allocation function obtained by calibration of operating data.

[0012] Preferably, the deviation constraint closure solution aims to minimize the weighted sum of squared deviations, as shown in the following formula:

[0013] ;

[0014] And it satisfies the carbon balance constraint shown in the following formula:

[0015] ;

[0016] In the formula, Δ i w is a deviation variable introduced for at least one of the following: fuel carbon content, fuel metering, residual carbon in ash, and carbon oxidation rate. i For the corresponding weights.

[0017] Preferably, the inversion of the blending ratio includes:

[0018] The calculation is based on the biocarbon allocation factor, the difference in fuel carbon content and / or the difference in fuel lower heating value, and outputs the inversion value of the blending ratio and its confidence index.

[0019] Preferably, the steps for obtaining the carbon content corresponding to the carbon dioxide entering the flue gas are as follows:

[0020] Obtain parameters for coal fuel and biomass fuel within a preset time window;

[0021] Calculate the carbon input from coal fuel and the carbon input from biomass fuel, and obtain the total carbon input;

[0022] Obtain the emission amounts and residual carbon parameters of fly ash and slag, or estimate the amount of unburned carbon based on boiler operating parameters;

[0023] The amount of carbon corresponding to the carbon dioxide entering the flue gas is calculated based on the carbon conservation law.

[0024] Preferably, the formulas for calculating the carbon input from coal fuel and the carbon input from biomass fuel are as follows:

[0025] C coal,in =mcoal ·(1−w M,coal )·w C,coal C bio,in =m bio ·(1−w M,bio )·w C,bio ;

[0026] In the formula, m is the fuel consumption or mass flow rate, and w M w represents the water content by mass. C The carbon content is expressed as a dry basis by mass fraction.

[0027] Preferably, the formula for calculating the total carbon input is as follows:

[0028] C in = C coal,in + C bio,in ;

[0029] In the formula, C in This represents the total carbon input.

[0030] Preferably, the amount of unburned carbon is calculated based on the residual carbon in fly ash and slag, using the following formula:

[0031] C unburnt =m ash ·w C,ash +m slag ·w C,slag ;

[0032] In the formula, C unburnt m represents the amount of unburned carbon. ash For fly ash emissions, m slag For slag emissions, w C,ash The residual carbon content of fly ash or the residual carbon parameter obtained from the loss on ignition, w C,slag This refers to the mass fraction of residual carbon in the slag or the residual carbon parameter obtained by converting it from the loss on ignition.

[0033] Preferably, the boiler operating parameters for estimating the amount of unburned carbon based on boiler operating parameters include at least two of the following as inputs: boiler load, flue gas oxygen content, flue gas temperature and / or furnace characteristic temperature, fuel volatile matter, moisture, and ash content.

[0034] Preferably, the calculation of the carbon content corresponding to the carbon dioxide entering the flue gas includes:

[0035] Introducing the carbon oxidation rate ξ as a variable parameter, satisfying: C CO2,total =C in ·ξ and C unburnt =C in ·(1−ξ); and dynamically correct ξ using boiler operating parameters.

[0036] Preferably, the dynamic correction of the carbon oxidation rate ξ is based on the following functional formula:

[0037] ξ=F(Load,O2,T,VM bio Ash bio Mix);

[0038] In the formula, Load is the load, O2 is the oxygen content parameter, T is the temperature parameter, and VM is the oxygen content parameter. bio For biomass volatile matter parameters, Ash bio is the biomass ash content parameter, and Mix is ​​the blending ratio parameter.

[0039] A carbon balance-based co-firing carbon traceability and allocation system, used to execute the aforementioned carbon balance-based co-firing carbon traceability and allocation method, includes:

[0040] The data acquisition device is used to access fuel metering, test data and boiler operation data;

[0041] A computing and storage device for performing carbon balance calculations, parameter calibration, and result output;

[0042] A human-computer interaction device is used to display the blending ratio, fossil CO2, biological CO2, and confidence level information.

[0043] Preferably, the data acquisition device is connected to the plant-level DCS / historical database via an industrial Ethernet, or acquires operating parameters via a standard industrial communication interface;

[0044] The computing and storage device communicates with the human-computer interaction device via a local area network.

[0045] Preferably, the system further includes a flue gas monitoring device, wherein the CO2 concentration and flue gas flow signals of the flue gas monitoring device are transmitted to the data acquisition device via analog, digital or industrial communication protocols.

[0046] An electronic device, the device comprising:

[0047] At least one processor; and

[0048] A memory communicatively connected to the at least one processor; wherein,

[0049] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to execute the carbon balance-based co-firing carbon traceability and allocation method.

[0050] A computer-readable storage medium storing computer instructions for causing a processor to execute the aforementioned carbon balance-based carbon traceability and allocation method for co-firing.

[0051] Compared with the prior art, the beneficial effects of the present invention are:

[0052] This invention can form a verifiable closed-loop carbon balance under co-fired coal / biomass combustion conditions, directly outputting fossil carbon CO2 emissions and biomass CO2 emissions, and providing the biomass source proportion in flue gas CO2 and the inversion results of the co-fired ratio. Because the model explicitly distinguishes the carbon input from fuel sources and introduces dynamic estimation of unburned carbon residue and a bias-constrained closed-loop solution mechanism, compared to existing methods that only calculate total CO2 or use fixed emission factors / fixed carbon oxidation rates, it can maintain a stable closed-loop carbon balance in co-fired scenarios with significant variations in fuel characteristics, load, and combustion efficiency. This significantly improves the stability and interpretability of emission accounting results, avoiding result drift and fluctuations caused by input data errors or operating condition variations.

[0053] This invention uses a combustion efficiency-carbon oxidation rate coupled model to dynamically correct unburned carbon residue, so that the carbon oxidation rate is no longer regarded as a fixed constant. Thus, it can still accurately reflect the degree of carbon to CO2 conversion under conditions such as changes in co-firing ratio, fluctuations in biomass moisture / volatile matter, and changes in furnace oxygen and temperature field. At the same time, through the equilibrium closed-loop solution of deviation constraints, it performs consistency correction on fuel testing deviations, measurement errors, and ash detection errors, so that the final calculation results meet the engineering verification requirements.

[0054] This invention does not rely on mandatory online CO2 monitoring equipment. For units without a CO2-CEMS, CO2 emissions and their source composition can be derived from conventionally available data such as fuel metering, fuel analysis, boiler load, oxygen content, temperature, and fly ash / slag residual carbon, enabling low-cost deployment and widespread adoption. Compared to the hardware investment and maintenance costs of a new CO2-CEMS, this invention, primarily based on software-based models and data closure correction, significantly reduces the cost of building a carbon verification system and minimizes maintenance burdens caused by instrument drift and flue gas humidity fluctuations, offering better replicability and scalability.

[0055] This invention provides power plants with auditable, traceable, and explainable carbon emission composition data, forming a foundational data support for carbon verification, carbon trading, green electricity certification, and biomass substitution calculation. By separating fossil carbon CO2 emissions, quota calculation and carbon asset management can be conducted more accurately, reducing compliance risks caused by calculation errors. Biomass CO2 emissions and biomass carbon allocation coefficients support the calculation and verification of the emission reduction contribution of biomass co-firing, reducing regulatory risks and economic disputes arising from false or misreported co-firing ratios. It improves the accuracy and consistency of co-firing carbon emission calculation, reducing the workload of manual sampling calculation, repeated verification, and multi-department data coordination, thereby simplifying the calculation process and improving management efficiency.

[0056] This invention provides a quantifiable and verifiable technical approach for the emission reduction effect of biomass co-firing in coal-fired power plants, which is conducive to promoting the standardized application of biomass co-firing and the transparent display of emission reduction results. By improving the accuracy and stability of fossil carbon emission accounting, it helps to form a more credible carbon emission data system, providing a reliable data foundation for carbon emission supervision, emission reduction assessment, and policy formulation. Attached Figure Description

[0057] The accompanying drawings, as part of this invention, are provided to further illustrate the invention. The illustrative embodiments and descriptions of the invention are used to explain the invention, but do not constitute an undue limitation thereof. Clearly, the drawings described below are merely some embodiments, and those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0058] Figure 1 This is a flowchart of the carbon source tracing and allocation method for co-firing based on carbon balance in this invention;

[0059] Figure 2 This is a flowchart of an embodiment of the carbon source tracing and allocation method for co-firing based on carbon balance of the present invention;

[0060] Figure 3 This is a structural diagram of the carbon source tracing and allocation system for co-firing based on carbon balance according to the present invention;

[0061] Figure 4 This is a schematic diagram of the electronic device for the carbon source tracing and allocation method based on carbon balance in co-firing according to the present invention. Detailed Implementation

[0062] To enable those skilled in the art to better understand the present invention, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention. It should be understood that the various steps described in the method embodiments of the present invention can be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0063] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0064] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, any variations of the terms "comprising" and "having," etc., are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0065] It should be noted that the terms "a" and "a plurality of" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0066] The names of the messages or information exchanged between the multiple devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0067] Currently, the emission factor method, traditional carbon balance method, fuel element analysis method, and online CEMS measurement technology commonly used in the industry are all unable to solve the core problem of carbon source allocation in co-firing scenarios.

[0068] The emission factor method calculates CO2 emissions based on fuel consumption and emission factors. While simple to implement, its calculation process only involves total carbon content, assuming a single source of CO2 in the flue gas and failing to identify the portion originating from biomass combustion. Under co-firing conditions, this method cannot reflect the differences in carbon release caused by the carbon content, volatile matter, and moisture content of biomass fuels, nor can it be used to verify biomass substitution and emission reduction amounts. Furthermore, with the diversification of biomass sources in power plants and significant fluctuations in fuel quality, the error of this static calculation method further increases.

[0069] Traditional carbon balance methods, based on the principle of mass conservation, calculate CO2 emissions by the difference between the carbon input from fuel and the unburned carbon. However, this method treats all carbon sources as a unified whole, only yielding the total CO2, and cannot separate fossil carbon CO2 from biomass CO2. Under biomass co-firing conditions, due to the complex fuel composition, unstable combustion process, and significant fluctuations in carbon oxidation rate with load, temperature, and oxygen levels, traditional carbon balance models often fail to maintain a closed carbon balance, leading to substantial deviations in emission calculations. Furthermore, the high volatile matter and high moisture content of biomass affect the amount of unburned carbon residue, making traditional carbon balance models based on a fixed carbon oxidation rate assumption unsuitable for engineering accuracy requirements.

[0070] Fuel elemental analysis estimates emissions by measuring the carbon content of fuel in the laboratory. However, biomass fuels are affected by their source, processing methods, and storage conditions, resulting in significant fluctuations in composition. Indicators such as carbon content, ash content, and moisture content change markedly during actual operation. This method cannot reflect the dynamic changes in fuel properties in real time, is ill-suited to rapid fluctuations in boiler load, airflow distribution, and combustion status, and cannot provide real-time corrections for combustion efficiency and unburned carbon residue. Furthermore, it cannot be used for carbon source decomposition.

[0071] For some units, although the online CO2 monitoring system (CEMS) can measure the overall CO2 concentration in the flue gas, the CEMS measurement results still cannot distinguish between fossil carbon CO2 and biomass CO2. At the same time, fluctuations in flue gas humidity, flow rate, and temperature under co-firing conditions will affect the stability of the measurement, and most small and medium-sized units have not installed CO2-CEMS, which limits the applicability of this method.

[0072] While existing research has explored the burnout behavior, particulate characteristics, and combustion mechanisms of biomass fuels, these studies have largely focused on the combustion process itself, failing to develop carbon emission accounting models applicable to continuous power plant operation. Furthermore, they lack a systematic approach to source separation of fossil and biomass carbon under co-firing conditions. In addition, current technologies generally rely on fixed model parameters, making it impossible to update combustion efficiency, unburned carbon residue, and carbon oxidation rate based on real-time boiler operating conditions. This leads to accumulated emission estimation errors, making them unsuitable for inversion of co-firing ratios or meeting regulatory accuracy requirements.

[0073] The purpose of this invention is to establish a carbon balance model based on carbon conservation and capable of distinguishing fuel sources. This model separates the fuel carbon entering the boiler into fossil carbon and biomass carbon, describing their transformation and emission behavior during combustion, thereby enabling quantitative calculation of fossil carbon dioxide and biomass carbon dioxide in flue gas. To address the inaccuracy of carbon balance caused by variations in combustion efficiency, carbon oxidation rate, and unburned carbon residue under co-firing conditions, this invention further introduces a coupled description of combustion efficiency and carbon oxidation rate. This allows unburned carbon to be dynamically estimated based on operating parameters such as boiler load, oxygen content, temperature, and fuel characteristics, avoiding systematic errors caused by using fixed parameters.

[0074] Meanwhile, the present invention also aims to construct a calculation method that can maintain carbon balance closure even when there are reasonable errors in fuel analysis data and operational measurement data. By introducing a deviation constraint mechanism in the carbon balance solution process, the key input parameters are corrected for consistency, thereby improving the stability and reliability of carbon emission calculation results. Based on this, the present invention can invert flue gas carbon dioxide emissions from boiler operating data in units lacking online carbon dioxide monitoring conditions, and invert the actual biomass co-firing ratio by combining carbon source allocation results.

[0075] Example 1

[0076] like Figure 1 As shown, the carbon source tracing and allocation method based on carbon balance for co-firing achieves independent quantitative calculation of fossil carbon CO2 and biological carbon CO2 in flue gas by splitting the carbon flow into sources, constructing a combustion efficiency coupling model, establishing a carbon balance solution mechanism with deviation constraints, and introducing a biocarbon allocation coefficient.

[0077] In this embodiment: the total carbon input is divided into fossil carbon and biological carbon according to their sources using the principle of carbon conservation, and independent carbon balance equations are constructed for each; at the same time, boiler operating conditions and fuel characteristics are introduced into the carbon oxidation rate prediction process, so that the model can reflect the dynamic changes of unburned carbon residue under actual co-firing conditions; and a deviation calibration mechanism is used to ensure that the carbon balance remains closed under actual operating fluctuations, thereby achieving high-precision carbon source allocation and CO2 emission inversion.

[0078] The specific steps in this embodiment include:

[0079] Obtain parameters for coal fuel and biomass fuel within a preset time window.

[0080] Combination Figure 2 As further explanation: the formulas for calculating the carbon input of coal fuel and the carbon input of biomass fuel are as follows:

[0081] C coal,in =m coal ·(1−wM,coal )·w C,coal C bio,in =m bio ·(1−w M,bio )·w C,bio ;

[0082] In the formula, C coal,in For the carbon input of coal fuel, C bio,in Where m is the carbon input of biomass fuel, and w is the fuel consumption or mass flow rate. M w represents the water content by mass. C The carbon content is expressed as a dry basis by mass fraction.

[0083] Calculate the carbon input from coal fuel and the carbon input from biomass fuel, and obtain the total carbon input.

[0084] As a further explanation: the formula for calculating total carbon input is as follows:

[0085] C in = C coal,in + C bio,in ;

[0086] In the formula, C in This represents the total carbon input.

[0087] After undergoing processes such as drying, volatile matter release, combustion, and gasification in the boiler, both types of fuels will form some unburned solid residues. The amount of unburned carbon in these residues is expressed as follows: Unburned carbon content C of coal fuel. coal,unburnt And the unburned carbon content (C) of biomass fuel bio,unburnt .

[0088] The total carbon dioxide emissions in flue gas can be calculated by extrapolating the carbon content corresponding to carbon dioxide from coal-based sources and biomass-based sources, using the following formula:

[0089] C CO2,total = C coal, CO2 + C bio, CO2 ;

[0090] In the formula, C CO2,total This represents the total carbon dioxide emissions in the flue gas.

[0091] It should be noted that by independently solving the two paths, the composition and structure of fossil carbon (CO2) and biomass carbon (CO2) in the flue gas can be obtained, providing a foundation for subsequent co-firing ratio inversion, low-carbon power assessment, and carbon asset accounting. To accurately determine the amount of unburned carbon residue, this invention establishes a coupled combustion efficiency-carbon oxidation rate model. Under co-firing conditions, combustion efficiency depends not only on factors such as pulverized coal particle size, ventilation coefficient, and temperature field distribution, but also on the moisture content, volatile matter content, and particle structure of biomass. Traditional fixed carbon oxidation rate assumptions are difficult to accurately reflect the actual carbon conversion under such conditions.

[0092] Obtain the emissions and residual carbon parameters of fly ash and slag, or estimate the amount of unburned carbon based on boiler operating parameters.

[0093] Combination Figure 2 As a further explanation: the amount of unburned carbon is calculated based on the residual carbon in fly ash and slag, using the following formula:

[0094] C unburnt =m ash ·w C,ash +m slag ·w C,slag ;

[0095] In the formula, C unburnt m represents the amount of unburned carbon. ash For fly ash emissions, m slag For slag emissions, w C,ash The residual carbon content of fly ash or the residual carbon parameter obtained from the loss on ignition, w C,slag This refers to the mass fraction of residual carbon in the slag or the residual carbon parameter obtained by converting it from the loss on ignition.

[0096] In another embodiment: when fly ash and / or slag emissions and residual carbon parameters are unavailable, the unburned carbon content is estimated using a soft sensor model. This model takes boiler operating parameters as input, including at least two of the following: boiler load, flue gas oxygen content, flue gas temperature and / or furnace characteristic temperature, fuel volatile matter, moisture, and ash content. The soft sensor model is trained or calibrated based on boiler operating data, experimental data, or physical mechanism models to output predicted values ​​of unburned carbon content in fly ash and slag in real time under dynamic operating conditions.

[0097] Among them, the carbon oxidation rate ξ is introduced as a variable parameter, satisfying: C CO2,total =C in ·ξ and C unburnt =C in ·(1−ξ); and dynamically correct ξ using boiler operating parameters.

[0098] The dynamic correction for the carbon oxidation rate ξ is based on the following functional formula:

[0099] ξ=F(Load,O2,T,VM bio Ash bio Mix);

[0100] In the formula, Load is the load, O2 is the oxygen content parameter, T is the temperature parameter, and VM is the oxygen content parameter. bio For biomass volatile matter parameters, Ash bio is the biomass ash content parameter, and Mix is ​​the blending ratio parameter.

[0101] The amount of carbon corresponding to the carbon dioxide entering the flue gas is calculated based on the carbon conservation law.

[0102] Carbon source decomposition was performed on the carbon content corresponding to carbon dioxide to obtain the carbon content corresponding to carbon dioxide from coal source and carbon content corresponding to carbon dioxide from biomass source, and the biomass carbon allocation coefficient was calculated.

[0103] As further explanation: Carbon source decomposition includes allocating unburned carbon from its sources to obtain the amount of unburned carbon from coal fuel and the amount of unburned carbon from biomass fuel, respectively satisfying the following formulas:

[0104] C coal,CO2 =C coal,in -C coal,unburnt C bio,CO2 =C bio,in -C bio,unburnt ;

[0105] In the formula, C coal,CO2 C represents the carbon content corresponding to carbon dioxide from coal sources. bio,CO2 Let f be the carbon content corresponding to carbon dioxide from biomass sources. From this, we obtain the biomass carbon allocation factor: f bio = C bio CO2 / (C coal,CO2 + C bio,CO2 ), where the denominator is the carbon content corresponding to the total carbon dioxide entering the flue gas; this f bio It is one of the core estimates output by the carbon source tracing and allocation method described in this invention, used to quantify the proportion of CO2 in flue gas that comes from biomass combustion.

[0106] Among them, the allocation of unburned carbon sources is estimated based on the fuel ash content ratio and the burnout difference coefficient, or based on the allocation function obtained by calibration of operating data.

[0107] To further reduce the impact of factors such as fuel testing deviations, operating instrument errors, and combustion fluctuations on carbon balance solutions, a deviation constraint closed-loop solution is introduced in the calculation of biomass carbon allocation coefficients. This ensures that the carbon balance closed-loop constraints are met and outputs the inversion results of fossil carbon dioxide emissions, biomass carbon dioxide emissions, and / or blending ratios.

[0108] As a further explanation: the deviation constraint closure solution aims to minimize the weighted sum of squared deviations, as shown in the following formula:

[0109] ;

[0110] And it satisfies the carbon balance constraint shown in the following formula:

[0111] ;

[0112] In the formula, Δ i w is a deviation variable introduced for at least one of the following: fuel carbon content, fuel metering, residual carbon in ash, and carbon oxidation rate. i For the corresponding weights.

[0113] It should be noted that, through deviation calibration, this invention can still output a reliable carbon emission composition even when there are errors in fuel analysis or large fluctuations in boiler operating conditions, thereby ensuring that the allocation error of fossil carbon and biocarbon can be controlled within the engineering requirements.

[0114] The blending ratio inversion includes: calculation based on the biomass carbon allocation factor, fuel carbon content difference and / or fuel lower heating value difference, and outputting the inversion value of the blending ratio and its confidence index.

[0115] It should be noted that in some units without an online CO2 monitoring system, this invention can use operating parameters such as boiler load, flue gas temperature, theoretical air volume, and oxygen content to invert the flue gas volumetric flow rate, and combine the calculation results of the two types of carbon pathways to estimate the flue gas CO2 concentration or emission, thus achieving CO2 emission estimation without a CEMS. Therefore, this invention can not only provide independent emission data for fossil carbon CO2 and biomass carbon CO2, but also invert the actual biomass blending ratio, providing directly usable quantitative results for carbon verification, carbon trading, and biomass substitution assessment.

[0116] Based on the technical solutions of the above embodiments, this invention provides several specific implementation methods.

[0117] Data alignment and calculations were performed using fixed time windows Δt (e.g., 1 min, 5 min, or 1 h). For each time window, the consumption m of coal and biomass was first obtained. coal m bio (t / h or kg / h), received basis moisture (w) M,coal ,w M,bio With dry basis carbon mass fraction w C,coal , w C,bio Based on this, the fuel carbon input is calculated as: C coal,in =m coal ·(1-w M,coal)·w C,coal C bio,in =m bio ·(1-w M,bio )·w C,bio C in =C coal,in + C bio,in Subsequently, ash and slag information was obtained and unburned carbon was calculated. If fly ash / slag discharge volume (m) is available... ash m slag and its residual carbon mass fraction (w) C,ash, w C,slag (This can be obtained by converting the loss on ignition (LOI) or residual carbon content), then: C unburnt =m ash w C,ash +m slag w C,slag If the ash discharge rate or residual carbon cannot be obtained online, it is preferable to use boiler load, flue gas oxygen content (O2), flue gas temperature / furnace characteristic temperature (T), fuel characteristics (e.g., biomass volatile matter / ash content / moisture content) as inputs, and employ a soft measurement function to measure (C) unburnt Alternatively, the carbon oxidation rate can be dynamically estimated and updated adaptively with changes in operating conditions. Based on carbon conservation, the carbon content corresponding to CO2 entering the flue gas is: C CO2,total = C in - C unburnt ;

[0118] To obtain the source composition of CO2 in flue gas, this invention further solves for the biomass carbon allocation factor:

[0119] Among them, (C) bio,CO2 The solution for ) can be achieved through a biochar input-unburned biochar residue allocation model. This allocation model can be estimated using the fuel ash content ratio and the burnout difference coefficient, or implemented using a trainable function calibrated based on operational data. To suppress the influence of fuel testing errors, measurement errors, and sampling errors on the equilibrium closure, this invention preferably introduces a deviation-constrained equilibrium closure solution mechanism, introducing key input quantities into the deviation variable (Δi) with the objective of minimizing the weighted sum of squared deviations: ;

[0120] And satisfy the carbon balance constraint:

[0121] The resulting C CO2, total f bio Fossil CO2 and biological CO2 output have better stability and verifiability.

[0122] Select a period of stable boiler load (e.g., 2 consecutive hours with load fluctuations less than a set threshold), record fuel metering data and operating parameters during this period, and take at least one sample of fly ash and slag. For fuel sampling, take representative samples from both coal and biomass, and use elemental analysis to obtain the dry basis carbon mass fraction (w / w). C,coal , w C,bio ), and the received basis moisture content (w) was measured. M,coal , w M,bio The ash sample was mixed and then tested for loss on ignition or residual carbon. C,ash ,w C,slag The system executes the above formula with (Δt=1h) as the window to calculate (C). CO2,total ), and obtain (f) through the amortization model. bio ) and (C bio,CO2 When the balance deviation caused by laboratory and measurement errors exceeds the threshold, the deviation constraint solution module is activated for closed-loop correction, outputting the corrected fossil CO2 and biological CO2 emission results, and providing the correction amount and confidence index for that window. To illustrate the result presentation format, a relative error index can be used to compare with the flue gas monitoring reference value: Under low-blending conditions and stable operating conditions, the output of this invention typically exhibits small fluctuations, good closure, and a suppressive effect on short-term fuel fluctuations, and can stably provide (f bio Used for verifying the authenticity of adulteration.

[0123] Compared with the prior art, the present invention has the following significant advantages:

[0124] This invention constructs a carbon traceability method system applicable to biomass co-firing conditions, with dynamic adaptability and deviation correction capabilities. It solves the problems of existing technologies that cannot accurately separate carbon sources under co-firing conditions, cannot reflect changes in combustion efficiency, cannot invert CO2 emissions under conditions without online monitoring, and cannot meet the requirements for high-precision co-firing ratio inversion. It provides a new technical path for coal-fired power plants to achieve low-carbon operation and refined carbon emission management.

[0125] Example 2

[0126] like Figure 3 As shown, the carbon balance-based co-firing carbon traceability and allocation system, used to execute the carbon balance-based co-firing carbon traceability and allocation method, includes:

[0127] The data acquisition device is used to input fuel metering, test data and boiler operation data, while the calculation and storage device is used to perform carbon balance calculation, parameter calibration and result output.

[0128] Computing and storage devices are used to perform carbon balance solutions, parameter calibration, and result output.

[0129] The human-computer interaction device is used to display information such as the blending ratio, fossil CO2, biological CO2, and confidence level.

[0130] As further explanation: The data acquisition device is connected to the plant-level DCS / historical database via industrial Ethernet, or collects operating parameters via a standard industrial communication interface.

[0131] It should be noted that operating parameters include, but are not limited to, load, flue gas oxygen content, flue gas temperature, and feedwater flow rate.

[0132] The computing and storage device communicates with the human-computer interaction device via a local area network to achieve real-time display, report export, and interface upload.

[0133] In one embodiment, the system further includes a flue gas monitoring device, wherein the CO2 concentration and flue gas flow signals of the flue gas monitoring device are transmitted to a data acquisition device via analog, digital or industrial communication protocols.

[0134] It should be noted that test data can be entered manually or imported into the computing and storage device through an interface with the laboratory information system.

[0135] Example 3

[0136] Figure 4 A schematic diagram of an electronic device 10, which can be used to implement embodiments of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0137] like Figure 4As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0138] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0139] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as carbon balance-based co-firing carbon traceability and allocation methods.

[0140] In some embodiments, the carbon balance-based co-firing carbon traceability and allocation method can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the carbon balance-based co-firing carbon traceability and allocation method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the carbon balance-based co-firing carbon traceability and allocation method by any other suitable means (e.g., by means of firmware).

[0141] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0142] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0143] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0144] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0145] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0146] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0147] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A carbon source tracing and allocation method for co-firing based on carbon balance, characterized in that, include: Carbon source decomposition was performed on the carbon content corresponding to carbon dioxide to obtain the carbon content corresponding to carbon dioxide from coal source and carbon content corresponding to carbon dioxide from biomass source, and the biomass carbon allocation coefficient was calculated. In the process of calculating the biomass carbon allocation coefficient, a bias constraint closure solution is introduced to satisfy the carbon balance closure constraint and output the inversion results of fossil carbon carbon dioxide emissions, biomass carbon dioxide emissions, and / or co-firing ratio.

2. The carbon source tracing and allocation method based on carbon balance for co-firing according to claim 1, characterized in that, Carbon source decomposition involves allocating unburned carbon from its sources to obtain the amount of unburned carbon from coal fuel and biomass fuel, respectively, satisfying the following formulas: C coal,CO2 =C coal,in −C coal,unburnt ,C bio,CO2 =C bio,in −C bio,unburnt ; In the formula, C coal,CO2 C represents the carbon content corresponding to carbon dioxide from coal sources. coal,in For the carbon input from coal fuel, C coal,unburnt C represents the amount of unburned carbon in coal fuel. bio,CO2 C represents the carbon content corresponding to carbon dioxide from biomass sources. bio,in For the carbon input of biomass fuel, C bio,unburnt This refers to the amount of unburned carbon in biomass fuels.

3. The carbon source tracing and allocation method for co-firing based on carbon balance according to claim 2, characterized in that, The allocation of unburned carbon sources is estimated based on the fuel ash content ratio and the burnout difference coefficient, or based on the allocation function obtained by calibration of operating data.

4. The carbon source tracing and allocation method for co-firing based on carbon balance according to claim 3, characterized in that, The deviation constraint closure solution aims to minimize the weighted sum of squared deviations, and the formula is as follows: ； And it satisfies the carbon balance constraint shown in the following formula: ； In the formula, Δ i w is a deviation variable introduced for at least one of the following: fuel carbon content, fuel metering, residual carbon in ash, and carbon oxidation rate. i For the corresponding weights.

5. The carbon source tracing and allocation method for co-firing based on carbon balance according to claim 4, characterized in that, The inversion of the blending ratio includes: The calculation is based on the biocarbon allocation factor, the difference in fuel carbon content and / or the difference in fuel lower heating value, and outputs the inversion value of the blending ratio and its confidence index.

6. The carbon balance-based carbon traceability and allocation method for co-firing according to any one of claims 1-5, characterized in that, The specific steps for obtaining the carbon content corresponding to the carbon dioxide entering the flue gas are as follows: Obtain parameters for coal fuel and biomass fuel within a preset time window; Calculate the carbon input from coal fuel and the carbon input from biomass fuel, and obtain the total carbon input; Obtain the emission amounts and residual carbon parameters of fly ash and slag, or estimate the amount of unburned carbon based on boiler operating parameters; The amount of carbon corresponding to the carbon dioxide entering the flue gas is calculated based on the carbon conservation law.

7. The carbon source tracing and allocation method for co-firing based on carbon balance according to claim 6, characterized in that, The formulas for calculating the carbon input from coal fuel and the carbon input from biomass fuel are as follows: C coal,in =m coal ·(1−w M,coal )·w C,coal ,C bio,in =m bio ·(1−w M,bio )·w C,bio ; In the formula, m is the fuel consumption or mass flow rate, and w M w represents the water content by mass. C The carbon content is expressed as a dry basis by mass fraction.

8. The carbon source tracing and allocation method for co-firing based on carbon balance according to claim 7, characterized in that, The formula for calculating total carbon input is as follows: C in = C coal,in + C bio,in ; In the formula, C in This represents the total carbon input.

9. The carbon source tracing and allocation method for co-firing based on carbon balance according to claim 6, characterized in that, The amount of unburned carbon is calculated based on the residual carbon in fly ash and slag, using the following formula: C unburnt =m ash ·w C,ash +m slag ·w C,slag ; In the formula, C unburnt m represents the amount of unburned carbon. ash For fly ash emissions, m slag For slag emissions, w C,ash The residual carbon content of fly ash or the residual carbon parameter obtained from the loss on ignition, w C,slag This refers to the mass fraction of residual carbon in the slag or the residual carbon parameter obtained by converting it from the loss on ignition.

10. The carbon source tracing and allocation method for co-firing based on carbon balance according to claim 6, characterized in that, Boiler operating parameters used to estimate the amount of unburned carbon based on boiler operating parameters include at least two of the following as inputs: boiler load, flue gas oxygen content, flue gas temperature and / or furnace characteristic temperature, fuel volatile matter, moisture, and ash content.

11. The carbon source tracing and allocation method for co-firing based on carbon balance according to claim 9, characterized in that: Introducing the carbon oxidation rate ξ as a variable parameter, satisfying: C CO2,total =C in ·ξ and C unburnt =C in ·(1−ξ); and dynamically correct ξ using boiler operating parameters.

12. The carbon source tracing and allocation method for co-firing based on carbon balance according to claim 10, characterized in that, The dynamic correction of the carbon oxidation rate ξ is based on the following functional formula: ξ=F(Load,O2,T,VM bio ,Ash bio ,Mix); In the formula, Load is the load, O2 is the oxygen content parameter, T is the temperature parameter, and VM is the oxygen content parameter. bio For biomass volatile matter parameters, Ash bio is the biomass ash content parameter, and Mix is ​​the blending ratio parameter.

13. A carbon source traceability and allocation system for co-firing based on carbon balance, characterized in that, The method for implementing the carbon balance-based carbon traceability and allocation method for co-firing as described in any one of claims 1-12 includes: The data acquisition device is used to access fuel metering, test data and boiler operation data; A computing and storage device for performing carbon balance calculations, parameter calibration, and result output; A human-computer interaction device is used to display the blending ratio, fossil CO2, biological CO2, and confidence level information.

14. The carbon balance-based co-firing carbon traceability and allocation system according to claim 13, characterized in that: The data acquisition device is connected to the plant-level DCS / historical database via industrial Ethernet, or collects operating parameters via a standard industrial communication interface. The computing and storage device communicates with the human-computer interaction device via a local area network.

15. The carbon balance-based co-firing carbon traceability and allocation system according to claim 13, characterized in that: The system also includes a flue gas monitoring device, which transmits CO2 concentration and flue gas flow signals to the data acquisition device via analog, digital or industrial communication protocols.

16. An electronic device, characterized in that, The device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the carbon balance-based carbon traceability and allocation method for co-firing as described in any one of claims 1-12.

17. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the carbon balance-based carbon traceability and allocation method for co-firing as described in any one of claims 1-12.

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