Method and system for monitoring thermal efficiency of waste heat boiler of combined cycle unit in real time

Abstract

The application discloses a kind of methods and systems for real-time monitoring of combined cycle unit waste heat boiler thermal efficiency, belong to real-time monitoring technical field of electric power system.The method comprises: abnormality detection correction and steady-state identification are carried out to the original operation data of multiple-source heterogeneous unit, and steady-state condition is determined;Based on the environmental parameters under steady-state condition, the standard dry air component reference is combined to determine the thermal physical properties of wet air;Based on fuel component information and wet air thermal physical properties, flue gas calculation is carried out, and flue gas component and flow are determined;Based on the composition of wet air and flue gas, enthalpy calculation is carried out by combining temperature parameters, and the specific enthalpy of waste heat boiler inlet and outlet gas is determined;Based on flue gas flow and gas specific enthalpy, the thermal efficiency of waste heat boiler is determined by energy balance calculation.The application constructs closed-loop calculation system from data processing to counterbalance solution, without additional measurement point, to realize online monitoring of waste heat boiler thermal efficiency, and provides technical support for real-time analysis of combined cycle unit economy.

Description

Technical Field

[0001] This invention relates to the field of real-time monitoring technology for power systems, specifically to a method and system for real-time monitoring of the thermal efficiency of waste heat boilers in combined cycle power units. Background Technology

[0002] Currently, China's heavy-duty gas turbine power generation sector still relies heavily on imported units. Performance testing of these combined cycle units generally follows ASME standards, specifically ASME PTC46 "Standard for Overall Performance Testing of Power Plants," ASME PTC22 "Gas Turbine Performance Testing Procedures," and ASME PTC4.4 "Gas Turbine Waste Heat Boiler Performance Testing Procedures." Waste heat boiler thermal efficiency, a key performance indicator for evaluating the operational performance of waste heat boilers in combined cycle units, is strictly tested according to ASME PTC4.4 to ensure the reliability of test results. To meet the needs of domestic industry development, my country has also formulated a corresponding industry standard, DL / T1427 "Combined Cycle Waste Heat Boiler Performance Testing Procedures." This standard is largely consistent with ASME PTC4.4, only standardizing parameter units; the test content, test principles, and specific operating methods are fully aligned with international standards. Both the international ASME standard and the domestic DL / T industry standard revolve around the energy balance of waste heat boilers. They require precise testing and calculation of the enthalpy increase of the steam-water working fluid, iterative solution of the excess air flow in the gas turbine exhaust, and then completion of the calculation of the thermal efficiency of the waste heat boiler.

[0003] A key area of ​​concern is the extremely complex steam-water system of triple-pressure reheat waste heat boilers commonly used in combined cycle systems. This system comprises feedwater and steam systems at high, medium, and low pressure levels. This complexity significantly complicates testing. On one hand, a comprehensive overview of the entire steam-water system is required; on the other hand, precise measurements and calculations of steam and water flow, pressure, and temperature at multiple points are necessary, leading to a substantial increase in the workload for installing, commissioning, and measuring measurement points. These factors combined not only make the calculation of waste heat boiler thermal efficiency more cumbersome and significantly increase uncertainty, placing stringent demands on the professional skills and operational standards of testing personnel, but also prevent online monitoring of waste heat boiler thermal efficiency, hindering effective support for power plant personnel in conducting real-time economic analysis of the units. Summary of the Invention

[0004] To address the need for real-time and accurate monitoring of waste heat boiler thermal efficiency in real-time economic analysis of combined cycle units, this invention proposes a method and system for real-time monitoring of waste heat boiler thermal efficiency in combined cycle units. By improving data processing accuracy and simplifying computational complexity, this invention provides technical support for real-time economic analysis of combined cycle units.

[0005] This invention is achieved through the following technical solution: A method for real-time monitoring of the thermal efficiency of a waste heat boiler in a combined cycle unit includes the following steps: Step 1: Perform anomaly detection and correction on the multi-source heterogeneous raw operating data of each monitoring system of the combined cycle unit to obtain steady-state correction data, and perform steady-state identification on the steady-state correction data according to the operating characteristics of the combined cycle unit to determine the steady-state operating condition. Step 2: Based on the environmental parameters under the steady-state operating conditions and in conjunction with the standard dry air composition benchmark, determine the thermophysical properties of the humid air under the current environmental conditions; Step 3: Based on the fuel composition information and the thermophysical properties of the humid air, perform combustion flue gas calculations to determine the composition and mass flow rate of the combustion flue gas; Step 4: Based on the thermophysical properties of the humid air and the composition of the combustion flue gas, and combined with the temperature parameters under the steady-state operating conditions, calculate the gas enthalpy and determine the specific enthalpy of the gas at the inlet and outlet of the waste heat boiler. Step 5: Based on the mass flow rate of the combustion flue gas and the specific enthalpy of the gas at the inlet and outlet of the waste heat boiler, determine the thermal efficiency of the waste heat boiler through energy balance calculation.

[0006] Preferably, the step of performing anomaly detection and correction on the multi-source heterogeneous raw operating data of each monitoring system of the combined cycle unit to obtain steady-state correction data includes: Based on the data time alignment rules, the multi-source heterogeneous original running data is interpolated, matched and integrated to obtain preprocessed basic data; An improved Grubbs criterion is used to perform dynamic anomaly detection on the preprocessed basic data point by point. The identified outliers are replaced and corrected using the window midpoint to obtain the steady-state corrected data without any abnormal jumps throughout the time period.

[0007] Preferably, the step of performing dynamic anomaly detection on the preprocessed basic data point by point using the improved Grubbs criterion, and replacing and correcting the identified outliers using the window midpoint, includes: Sort the data within the dynamic sliding detection window by numerical value and calculate the median of the window data; Calculate the absolute value of the residuals between each data point and the median, and the median difference of all residuals; Calculate the Grubbs statistic for each data point and compare it with the Grubbs critical value for the corresponding window length. If the statistic is greater than or equal to the critical value, the data point is determined to be an outlier. Outliers are replaced by the middle value in the window. The detection is iterated until there are no outliers in the current window. The sliding window traverses all time period data to complete the anomaly correction of all parameters.

[0008] Preferably, determining the steady-state operating condition includes: Several operating parameters that significantly affect thermal efficiency are selected as steady-state judgment indicators. Multi-parameter collaborative steady-state identification is performed on the steady-state correction data to determine the unit's steady-state operating condition.

[0009] Preferably, determining the thermophysical properties of moist air under current environmental conditions includes: Based on the environmental parameters under the aforementioned steady-state operating conditions, the mass fraction and humidity ratio of dry air are calculated using thermodynamic correlations. Based on the dry air mass fraction and the mole fraction of each component of dry air, calculate the mole fraction of each component of actual humid air; Based on the mole fraction and relative molecular mass of each component of the actual humid air, the relative molecular mass of the humid air is calculated, and then the mass fraction of each component of the humid air is determined.

[0010] Preferably, step 3, calculating the total mass flow rate and mass fraction of each component of the combustion flue gas, includes: Based on the mole fraction of fuel gas components and real-time mass flow rate, the molar flow rate of fuel gas is calculated. Combined with the oxidation and combustion reaction coefficients of each component, the change in molar flow rate of each component of flue gas caused by fuel combustion is calculated. Based on the oxygen molar flow rate consumption, the theoretical dry air flow rate is calculated by combining the molar fraction of oxygen in the dry air, and then converted into the total flow rate of humid air for combustion and the molar flow rate of each component by the humidity ratio. The changes in the molar flow rates of the combustion products are superimposed with the molar flow rates of the humid air used for combustion to obtain the molar flow rates of each component of the combustion flue gas, and then the total mass flow rate and mass fraction of each component of the combustion flue gas are calculated.

[0011] Preferably, in step 4, determining the specific enthalpy of the gas at the inlet and outlet of the waste heat boiler includes: Based on the inlet and outlet temperatures of the waste heat boiler under the aforementioned steady-state operating conditions, and in conjunction with the mass fractions of each component of the humid air, the enthalpy of the humid air at the inlet and outlet of the waste heat boiler is calculated. Based on the inlet and outlet temperatures of the waste heat boiler under the aforementioned steady-state operating conditions, and in conjunction with the mass fractions of each component of the combustion flue gas, the specific enthalpy of the combustion flue gas at the inlet and outlet of the waste heat boiler is calculated.

[0012] Preferably, in step 5, determining the thermal efficiency of the waste heat boiler includes: Based on the fuel gas mass flow rate, fuel gas lower heating value, and gas turbine power generation under the steady-state operating conditions, combined with the combustion flue gas mass flow rate, the enthalpy of moist air at the inlet of the waste heat boiler, and the enthalpy of combustion flue gas, the excess combustion air flow rate is calculated according to the gas turbine energy balance equation. Based on the excess air flow rate and the mass flow rate of the combustion flue gas, combined with the enthalpy of the moist air and the enthalpy of the combustion flue gas at the inlet and outlet of the waste heat boiler, the thermal efficiency of the waste heat boiler is calculated according to the energy reverse balance principle of the waste heat boiler.

[0013] A system for real-time monitoring of the thermal efficiency of a waste heat boiler in a combined cycle unit, comprising: The data processing unit is used to perform anomaly detection and correction on the multi-source heterogeneous raw operating data of each monitoring system of the combined cycle unit to obtain steady-state correction data, and to perform steady-state identification on the steady-state correction data according to the operating characteristics of the combined cycle unit to determine the steady-state operating condition. An air composition calculation unit is used to determine the thermophysical properties of humid air under the current environmental conditions based on the environmental parameters under the steady-state operating conditions and in conjunction with the standard dry air composition benchmark. The combustion flue gas calculation unit is used to perform combustion flue gas calculations based on fuel composition information and the thermophysical properties of the humid air, and to determine the composition and mass flow rate of the combustion flue gas. The gas enthalpy calculation unit is used to calculate the gas enthalpy based on the thermophysical properties of the humid air and the composition of the combustion flue gas, combined with the temperature parameters under the steady-state operating conditions, and to determine the specific enthalpy of the gas at the inlet and outlet of the waste heat boiler. The energy balance calculation unit is used to determine the thermal efficiency of the waste heat boiler through energy balance calculation based on the mass flow rate of the combustion flue gas and the specific enthalpy of the gas at the inlet and outlet of the waste heat boiler.

[0014] An electronic device includes: a memory for storing a computer program; and a processor connected to the memory for executing the computer program to implement the step of real-time monitoring of the thermal efficiency of the waste heat boiler of a combined cycle unit.

[0015] Compared with the prior art, the present invention has the following beneficial technical effects: This application also proposes a method for real-time monitoring of the thermal efficiency of a combined cycle unit's waste heat boiler. First, it performs time-series alignment and anomaly correction on heterogeneous data from multiple sources, including the gas turbine control system, combustion monitoring system, and distributed control system. Then, it uses multi-parameter collaborative judgment to screen steady-state operating conditions. Next, starting from environmental parameters, it calculates the mass fraction of each component of humid air based on a standard dry air composition benchmark, avoiding errors caused by approximation with dry air. Then, using fuel composition and flow rate as the source, it uses chemical reaction stoichiometry to back-calculate the amount of humid air participating in combustion from oxygen consumption, superimposing this with combustion products to obtain flue gas composition and flow rate, avoiding the complex process of directly measuring or iteratively solving for the excess air coefficient. Subsequently, it uses NASA standard polynomials to decouple the mixed flue gas into two independent airflows: combustion flue gas and excess humid air, calculating their specific enthalpy at the inlet and outlet of the waste heat boiler respectively, achieving precise energy quantification. Finally, using the gas turbine energy balance equation, it back-calculates the unmeasurable excess air flow rate from measurable power generation and fuel input energy, and then uses an inverse balance method to deduct exhaust losses from the total input energy to obtain the thermal efficiency. This method eliminates the need for expensive measuring points such as flue gas flow meters. It can acquire all input parameters solely through the existing monitoring system of the unit. The calculation logic is clear and the physical meaning is well-defined, enabling online real-time evaluation of the performance of waste heat boilers and providing a reliable technical means for the economic analysis of power plants.

[0016] This application also proposes a system for real-time monitoring of the thermal efficiency of a waste heat boiler in a combined cycle unit, an electronic device, and a computer storage medium, which possess all the advantages of the aforementioned method for real-time monitoring of the thermal efficiency of a waste heat boiler in a combined cycle unit. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of the method for real-time monitoring of the thermal efficiency of a waste heat boiler in a combined cycle unit according to the present invention.

[0019] Figure 2 This invention presents the results of abnormal fuel flow detection in the #3 combined cycle unit of a gas turbine power plant. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0021] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0022] like Figure 1 As shown, a method for real-time monitoring of the thermal efficiency of a waste heat boiler in a combined cycle unit includes the following steps: Step 1: Perform anomaly detection and correction on the multi-source heterogeneous raw operating data of each monitoring system of the combined cycle unit to obtain steady-state correction data. Based on the operating characteristics of the combined cycle unit, perform steady-state identification on the steady-state correction data to determine the steady-state operating condition.

[0023] In some embodiments, the method for determining the steady-state operating condition is as follows: S1.1 Based on the data time alignment rules, interpolation matching and integration are performed on the multi-source heterogeneous original running data to obtain preprocessed basic data; S1.2. The improved Grubbs criterion is used to perform dynamic anomaly detection on the preprocessed basic data point by point. The identified outliers are replaced and corrected using the window midpoint to obtain steady-state corrected data without abnormal jumps throughout the time period.

[0024] S1.3. Based on the operating characteristics of the combined cycle unit, select multiple relevant operating parameters as the basis for judging steady-state operation, perform steady-state identification on the steady-state correction data, and determine the steady-state operating condition.

[0025] In a further embodiment, the method for determining the preprocessed basic data is as follows: Based on the data time alignment rules, interpolation matching and integration are performed on multi-source heterogeneous raw running data to obtain preprocessed basic data.

[0026] As a specific example, given the complex situation where the field operation data of combined cycle units have different sources, frequencies, structures, and types, the raw data collected by all monitoring systems of the unit are interpolated, matched, and integrated according to the rule of "data time alignment" to obtain preprocessed basic data.

[0027] To address the issues of inconsistent sampling frequencies and time bases in operational data collected from different systems such as the Turbine Control System (TCS), Combustion Dynamics Monitoring (CDM), and Distributed Control System (DCS), a globally unified time base is established. Linear interpolation is used to resample parameters with gradual changes in temperature and pressure, while cubic spline interpolation is used to resample dynamically changing parameters such as power and flow rate. This ensures timestamp alignment for all monitored parameters and generates a standardized preprocessed basic data matrix, expressed as:

[0028] In the formula, For unit operating status monitoring parameters In time The monitoring data.

[0029] Due to factors such as scattered data storage, varying data acquisition system configurations, and harsh operating conditions of monitoring instruments, data acquired from the aforementioned systems generally suffers from time discrepancies and misalignments. To facilitate real-time monitoring, [the following text is missing]. As needed, parameters can be calculated using linear interpolation. At the same time j The values ​​constitute the preprocessing base data.

[0030] As an alternative, the data time alignment rule can be implemented using Lagrange interpolation, spline interpolation, or data resampling techniques (such as nearest neighbor interpolation), in addition to linear interpolation.

[0031] In a further embodiment, the method for determining the steady-state correction data is as follows: Considering that the random errors of industrial field measurement data follow a normal distribution, the improved Grubbs criterion is used to carry out dynamic anomaly detection and correction on each point of the preprocessed parameters to obtain steady-state correction data.

[0032] As an example, for a certain parameter i Assuming j Given the current running time series, the known current running data series for this parameter is... , . The dynamic detection window period n Sort the data in ascending order to obtain an ordered sequence. ,in n The dynamic window period for data anomaly detection is set to a value of [value]. The median, residuals, median difference, and Grubbs statistic of the window data are calculated sequentially, using the following formulas: Median of window period data ,for:

[0033] Window Period Data Residual ,for:

[0034] Median of window period data ,for:

[0035] Calculate Grubbs statistics ,have to:

[0036] According to the window period The critical values ​​for the corresponding confidence levels can be obtained by consulting the Grubbs statistical critical value table. If the statistics of the current data point satisfy If the data point is not found to be an outlier, the outlier is replaced by the middle value in the window to complete the outlier correction. After removing the outlier, the statistical features are recalculated and iteratively detected on the updated window data until no outliers are detected in the current window. The sliding detection window traverses the data for the entire time period to complete the outlier correction of all parameters and obtain the steady-state correction data.

[0037] Table 1 Statistical Critical Value Table

[0038] In a further embodiment, the step of selecting multiple relevant operating parameters as the basis for determining steady-state operation based on the operating characteristics of the combined cycle unit includes: Based on the operating characteristics of combined cycle units, multiple relevant parameters are selected as the criteria for determining the steady-state operation of the unit. The deviation of the relevant parameter data from the mean within each identification window period is dynamically judged to determine whether it is within the threshold range specified for steady-state operation, thereby identifying the unit as being in steady-state condition, which facilitates the subsequent online calculation of the thermal efficiency of the waste heat boiler.

[0039] Specifically, based on the operating characteristics of combined cycle units, several parameters that significantly affect thermal efficiency, such as gas turbine power, fuel gas flow rate, compressor inlet flow rate, and turbine exhaust temperature, are selected as steady-state judgment indicators, and a dynamic identification window period is set. relative deviation threshold from steady state For each recognition window, calculate the mean and maximum relative deviation within each parameter window: Window data mean :

[0040] In the formula, The dynamic window period for data steady-state identification. .

[0041] Maximum deviation of window data from the mean ,for:

[0042] Determine if the maximum deviation is greater than the specified threshold. Small, if Then the parameters can be determined. The data within this window period is steady-state data.

[0043] As a preferred approach, multiple pre-selected relevant parameters are collaboratively evaluated within the same identification window period. Only when all selected parameters are determined to be steady-state data is the gas turbine combined cycle unit ultimately determined to be operating in steady state within that window period. After completing the data identification for the current window period, the window is dynamically slid, and the above identification process is repeated to continuously identify the steady-state operating condition of the unit.

[0044] Step 1 addresses the issue that heterogeneous multi-source data from the field cannot be directly used for accurate calculations due to varying acquisition frequencies and inconsistent timestamps. Building upon this, a dynamic detection and correction method based on an improved Grubbs criterion is introduced to address the common random errors and anomalous jumps in measurement data. This method employs a sliding window, iterative elimination, and robust statistical strategies based on the median and median difference to effectively identify and replace outliers that deviate from the normal distribution, improving the accuracy and robustness of subsequent thermal efficiency calculations. Finally, since thermal efficiency calculations fluctuate significantly and have poor representativeness under unsteady-state conditions, a multi-parameter collaborative steady-state identification logic ensures that efficiency calculations are triggered only when the unit is operating stably, guaranteeing the reliability and analyzability of the monitoring results.

[0045] Step 2: Based on the environmental parameters under steady-state conditions and in conjunction with the standard dry air composition benchmark, determine the thermophysical properties of the humid air under the current environmental conditions.

[0046] In some embodiments, the method for determining the thermophysical properties of moist air under the current environmental conditions is as follows: S2.1 Based on environmental parameters such as atmospheric pressure, dry-bulb temperature, and relative humidity under steady-state conditions, the mass fraction and humidity ratio of dry air are calculated using thermodynamic correlations. S2.2 Based on the dry air mass fraction and humidity ratio, and combined with the mole fraction benchmark of each component of dry air, calculate the mole fraction of each component of actual humid air; S2.3. Based on the mole fraction of each component of the actual humid air and the known relative molecular mass of each component, calculate the relative molecular mass of the humid air, and then determine the mass fraction of each component of the humid air.

[0047] In a further embodiment, the method for determining the mass fraction and humidity ratio of the dry air is as follows: Based on environmental parameters such as atmospheric pressure, dry-bulb temperature, and relative humidity obtained under steady-state conditions, the saturated vapor pressure of water at the dry-bulb temperature and the actual partial pressure of water vapor in the gas are calculated in sequence, thereby obtaining the mass fraction and humidity ratio of dry air.

[0048] The method for calculating the saturated vapor pressure of water at dry-bulb temperature is as follows:

[0049] In the formula, The vapor pressure of water at dry bulb temperature. . , Dry bulb temperature, . The constant for calculating the vapor pressure of water. , , , , -0.0000000024780681, , .

[0050] The actual partial pressure of water vapor in a gas is calculated as follows:

[0051] In the formula, This is the partial pressure of water vapor in the gas. . Relative humidity, .

[0052] The method for calculating the mass fraction of dry air is as follows:

[0053] In the formula, This represents the mass fraction of dry air. . Atmospheric pressure, .

[0054] The humidity ratio is calculated as follows:

[0055] In the formula, Humidity ratio .

[0056] In a further embodiment, the method for determining the mole fraction of each component of the actual humid air is as follows: Based on dry air mass fraction Based on the humidity ratio and the mole fraction of each component in dry air as determined by the standard specification GPA 2145-2016, the mole fraction of each component in actual humid air is calculated.

[0057] It should be noted that the dry air mass fraction determines the total amount of dry air in humid air, while the humidity ratio determines the ratio of water vapor mass to dry air mass.

[0058] As a concrete example, the mole fraction of each component in actual moist air is calculated as follows:

[0059]

[0060] In the formula, actual humid air components mole fraction, . , representing the six common components in air / flue gas, as shown in Table 2 above. dry air components mole fraction, , , , , .

[0061] Table 2 Six common components in air / flue gas

[0062] As an alternative, the dry air component mole fraction benchmark can be calculated using not only the GPA 2145-2016 standard, but also the standard atmospheric component data specified in the ISO 2533 standard or Chinese national standards, to meet the application needs of different regions.

[0063] In a further embodiment, the mass fraction of each component of the humid air is determined as follows: Based on the mole fraction of each component of moist air By combining the known relative molecular masses of each component of moist air, the relative molecular mass of moist air is calculated, and then the mass fraction of each component of moist air is determined.

[0064] The mass fraction of each component in moist air, i.e.:

[0065] In the formula, Components of moist air The mass fraction, .

[0066] This step uses thermodynamic correlations to accurately calculate the mole fraction, mass fraction, and relative molecular mass of each component in the humid air under the current environmental conditions. By introducing the dry air composition benchmark determined by authoritative standards and specifications, and combining it with real-time environmental parameters for dynamic correction, it avoids the calculation errors caused by simply using the dry air approximation. Especially in high humidity environments, it can significantly improve the accuracy and reliability of subsequent energy balance and thermal efficiency calculations.

[0067] Step 3: Calculate the composition and mass flow rate of the combustion flue gas based on the fuel composition information and the thermophysical properties of the moist air.

[0068] In some embodiments, the composition and mass flow rate of the combustion flue gas are determined as follows: S3.1. Based on the mole fraction of fuel gas components and the real-time measured mass flow rate of fuel gas, combined with the combustion reaction coefficients of each component determined by the oxidation reaction equation, calculate the changes in molar flow rates of each component caused by fuel gas combustion. S3.2, Based on the change in oxygen molar flow rate, combined with the molar fraction of oxygen in dry air and the humidity ratio, calculate the molar flow rate of the humid air and its components during combustion. S3.3. Based on the changes in the molar flow rate of each component of the fuel gas combustion and the molar flow rate of each component of the humid air combustion, the molar flow rate of each component of the combustion flue gas is calculated by superposition, and then the total mass flow rate and mass fraction of each component of the combustion flue gas are determined.

[0069] In a further embodiment, the method for determining the changes in the molar flow rates of each component caused by the combustion of the fuel gas is as follows: Based on the molar fraction of fuel gas components obtained by online chromatography or offline analysis, combined with the real-time measured mass flow rate of fuel gas, and the combustion reaction coefficients of each component determined by the oxidation reaction equation, the changes in the molar flow rate of each component in the flue gas caused by the combustion of fuel gas are calculated.

[0070] As a concrete example, first, calculate the relative molecular mass of the fuel gas, that is:

[0071] In the formula, This represents the relative molecular mass of the fuel gas. fuel gas components The relative molecular mass. fuel gas components mole fraction, . , representing 21 common components in fuel gas, as shown in Table 3 above.

[0072] Table 3. 21 common components in fuel gas

[0073] Secondly, combined with real-time measured fuel gas mass flow rate Calculate the molar flow rate of the fuel gas. ,as follows:

[0074] In the formula, The molar flow rate of the fuel gas. . This refers to the mass flow rate of fuel gas. .

[0075] Then, the flue gas composition caused by fuel gas combustion is calculated. Molar flow rate variation ,as follows:

[0076] In the formula, fuel gas combustion components Molar flow rate variation, . fuel gas components of The combustion reaction coefficients are shown in Table 4.

[0077] Table 4. Fuel gas component i Combustion reaction coefficient

[0078] In a further embodiment, the method for determining the humid air used for combustion and the molar flow rates of its components is as follows: Based on the change in oxygen molar flow rate and the mole fraction of oxygen in dry air, the dry air flow rate for combustion is calculated; then, the humidity ratio is introduced to convert the dry air flow rate into the wet air flow rate for combustion; finally, the molar flow rate of each component of the wet air for combustion is calculated by combining the mole fraction of each component.

[0079] The dry air flow rate used for combustion is:

[0080] In the formula, The dry air flow rate used for combustion. .

[0081] The flow rate of moist air used for combustion is:

[0082] In the formula, The flow rate of moist air used for combustion. .

[0083] The molar flow rates of each component of the moist air used for combustion are as follows:

[0084] In the formula, Moist air components for combustion Mole flow rate, .

[0085] The required dry air volume is calculated by working backward from the oxygen consumption of fuel combustion, and then converted into a humid air volume containing water vapor using the humidity ratio. This calculation method avoids the complex process of directly measuring flue gas flow rate or iteratively solving for the excess air coefficient.

[0086] In a further embodiment, the method for determining the molar flow rate and mass flow rate of each component of the combustion flue gas is as follows: The changes in molar flow rates of each component of the fuel gas combustion calculated in S3.1 are superimposed with the molar flow rates of each component of the humid air used for combustion calculated in S3.2 to calculate the molar flow rates of each component of the combustion flue gas. Then, combined with the relative molecular mass of each component, the total mass flow rate and the mass fraction of each component of the combustion flue gas are calculated.

[0087] Specifically, as a concrete example, firstly, calculate the molar flow rates of the combustion flue gas components.

[0088]

[0089] In the formula, Combustion flue gas components Mole flow rate, .

[0090] Secondly, calculate the total mass flow rate of the combustion flue gas. ,Right now:

[0091] In the formula, For the flow rate of combustion flue gas, , flue gas components j The relative molecular mass.

[0092] Then, calculate the mass fraction of each component in the combustion flue gas, i.e.:

[0093] In the formula, Combustion flue gas components The mass fraction, .

[0094] Using known fuel flow and composition information, the amount of combustion products and oxygen consumption are accurately calculated through chemical reaction stoichiometry. Then, based on the oxygen consumption and the oxygen content in the air, the theoretical dry air volume required for combustion is deduced, and the humidity ratio (HR) is introduced. HR This is then converted into a more realistic theoretical amount of moist air; finally, the moist air is superimposed with the combustion products to obtain complete combustion flue gas composition and flow rate data.

[0095] Step 4: Based on the mass fractions of each component of the humid air and the mass fractions of each component of the combustion flue gas, and combined with the inlet and outlet temperatures of the waste heat boiler under steady-state conditions, calculate the gas enthalpy values ​​and determine the specific enthalpy of the humid air and the specific enthalpy of the combustion flue gas at the inlet and outlet of the waste heat boiler, respectively.

[0096] In some embodiments, the method for determining the enthalpy ratio of humid air to combustion flue gas at the inlet and outlet of the waste heat boiler is as follows: First, based on the inlet and outlet temperatures of the waste heat boiler under steady-state operating conditions, and combined with the mass fractions of each component of the humid air, the specific enthalpy of the humid air at the inlet and outlet of the waste heat boiler is calculated according to the standard of gas thermodynamic properties. Then, based on the inlet and outlet temperatures of the waste heat boiler under steady-state conditions, and combined with the mass fraction of each component of the combustion flue gas, the specific enthalpy of the combustion flue gas at the inlet and outlet of the waste heat boiler is calculated.

[0097] Specifically, the method for calculating the specific enthalpy of each gas component at a given temperature is as follows:

[0098] In the formula, For a given temperature, the gas composition enthalpy, . , For a given temperature, . gaseous components The specific enthalpy calculation constants are shown in Table 5.

[0099] Table 5 Gas Components Enthalpy calculation constant

[0100] The calculation method for the specific enthalpy of the moist air at the inlet and outlet of the waste heat boiler is as follows:

[0101] in, The inlet and outlet temperatures of the waste heat boiler Specific enthalpy of moist air .

[0102] The calculation method for the specific enthalpy of the flue gas at the inlet and outlet of the waste heat boiler is as follows:

[0103] In the formula, The inlet and outlet temperatures of the waste heat boiler Enthalpy of combustion flue gas .

[0104] This method uses NASA-standard high-order polynomials to calculate the specific enthalpy of each gas component. Compared with the simplified algorithm that uses a fixed specific heat capacity, it has a significant accuracy advantage: the temperature of the flue gas at the inlet of the waste heat boiler is usually as high as several hundred degrees. Within this wide temperature range, the specific heat capacity of the gas exhibits obvious nonlinear characteristics as temperature and composition change. The high-order polynomial can accurately capture this change pattern, thereby accurately calculating the enthalpy value of the gas at different temperatures.

[0105] In one possible implementation, the standard or method used to calculate the specific enthalpy of gas components, in addition to the 9-coefficient polynomial provided in NASATP 2002 211556, can also employ JANAF thermochemical tables, the database of the National Institute of Standards and Technology (NIST), or other standard material thermodynamic property calculation models recommended by the International Union of Pure and Applied Chemistry (IUPAC).

[0106] Step 5: Based on the combustion flue gas flow rate and various specific enthalpy parameters, the excess air flow rate is calculated according to the energy balance of the gas turbine, and then the thermal efficiency of the waste heat boiler is determined in real time through the energy inverse balance calculation of the waste heat boiler.

[0107] In some embodiments, the method for determining the thermal efficiency of the waste heat boiler is as follows: S5.1. Based on the fuel gas mass flow rate, fuel gas lower heating value, and gas turbine power generation under steady-state conditions, combined with the combustion flue gas flow rate and various specific enthalpy parameters, calculate the excess air flow rate under combustion according to the gas turbine energy balance equation. S5.2. Based on the excess air flow rate and flue gas flow rate, combined with the enthalpy of the humid air at the inlet and outlet of the waste heat boiler and the enthalpy of the flue gas, the thermal efficiency of the waste heat boiler is calculated according to the energy rebalancing principle of the waste heat boiler.

[0108] In a further embodiment, the method for determining the excess combustion air flow rate is as follows: Based on the fuel gas mass flow rate, fuel gas lower heating value, and gas turbine power generation under steady-state conditions determined in step 1, and combined with the combustion flue gas flow rate, gas turbine inlet humid air enthalpy, gas turbine outlet humid air enthalpy, and gas turbine outlet combustion flue gas enthalpy, the excess combustion air flow rate is calculated in real time according to the gas turbine energy balance equation, without considering energy loss.

[0109] The physical meaning of the gas turbine energy balance equation is: the sum of fuel input energy and intake energy equals the sum of gas turbine power generation and exhaust energy. From this, the excess air flow rate can be derived as follows:

[0110] In the formula, To burn excess air flow, . The lower heating value of fuel gas, . For gas turbine power generation, . For gas turbine inlet temperature Specific enthalpy of moist air , . Gas turbine outlet temperature Specific enthalpy of moist air ,because ,so . Gas turbine outlet temperature Enthalpy of combustion flue gas ,because ,so .

[0111] In a further embodiment, the method for determining the thermal efficiency of the waste heat boiler is as follows: Based on the excess air flow and flue gas flow calculated by S5.1, and combined with the enthalpy of the wet air at the inlet of the waste heat boiler, the enthalpy of the wet air at the outlet of the waste heat boiler, the enthalpy of the flue gas at the inlet of the waste heat boiler, and the enthalpy of the flue gas at the outlet of the waste heat boiler, the thermal efficiency of the waste heat boiler is calculated according to the principle of energy rebalancing of the waste heat boiler.

[0112] As a concrete example, the physical meaning of energy imbalance in a waste heat boiler is: thermal efficiency equals the total energy input to the waste heat boiler minus the energy lost in flue gas, divided by the total input energy. Without considering heat dissipation and other losses, the thermal efficiency of the waste heat boiler can be calculated in real time using the following formula. (unit:%):

[0113] Example 1 This embodiment uses the historical operating data of Unit #3 of a gas turbine power plant on March 25, 2025 as the research object to provide a detailed description of the specific implementation of the present invention.

[0114] Step 1: Perform anomaly detection and correction on the multi-source heterogeneous raw operating data of each monitoring system of the combined cycle unit to obtain steady-state correction data. Based on the operating characteristics of the combined cycle unit, perform steady-state identification on the steady-state correction data to determine the steady-state operating condition.

[0115] S1.1, following the rule of "data time alignment," interpolation and matching are performed on the multi-source heterogeneous raw operating data collected from the gas turbine control system, gas turbine combustion monitoring system, and unit distributed control system to obtain preprocessed basic data. Table 6 shows some of the preprocessed basic data after matching and integration for Unit #3 of a gas turbine power plant.

[0116] Table 6. Basic Pre-processing Data of Unit #3 Combined Cycle Unit in a Gas Turbine Power Plant

[0117] S1.2, using the improved Grubbs criterion method, dynamic anomaly detection and correction are performed on each item of the preprocessed basic data. Taking the fuel gas flow rate of Unit #3 combined cycle as an example, the anomaly detection results for this parameter are obtained through Python programming calculation, such as... Figure 2 As shown. The test results indicate that the fuel gas flow signal sensor of Unit #3 combined cycle unit malfunctioned at 15:33:00 on 03 / 25 / 2025. The abnormal value was replaced and corrected using the windowed middle value to obtain the abnormal correction data.

[0118] S1.3, based on the operating characteristics of the combined cycle unit, multiple relevant parameters such as gas turbine power, fuel gas flow rate, compressor inlet flow rate, and compressor inlet temperature are selected as the criteria for determining steady-state operation. The deviation of each parameter's data from its mean value within each identification window period is dynamically assessed to determine whether it falls within the threshold range specified for steady-state operation. Taking the load parameters of the #3 combined cycle unit as an example, the steady-state data of these parameters is obtained through Python programming. The selected parameters are then collaboratively assessed within the same identification window period. When all selected parameters are determined to be steady-state data, the unit is confirmed to be in steady-state operation within that window period.

[0119] Step 2: Based on the environmental parameters of steady-state operating conditions and combined with the standard dry air composition benchmark, determine the thermophysical properties of humid air under the current environmental conditions.

[0120] S2.1, based on environmental parameters such as atmospheric pressure, dry-bulb temperature, and relative humidity under steady-state conditions, calculates the saturated vapor pressure of water at dry-bulb temperature and the actual partial pressure of water vapor in the gas through thermodynamic correlations, and then calculates the mass fraction and humidity ratio of dry air.

[0121] S2.2, based on the dry air mass fraction calculated in S2.1, and combined with the mole fraction of each component of dry air as determined by the standard specification GPA 2145-2016, calculate the mole fraction of each component of the actual humid air.

[0122] S2.3: Based on the mole fraction of each component of the actual moist air calculated in S2.2, and combined with the known relative molecular mass of each component, calculate the relative molecular mass of the moist air, and then determine the mass fraction of each component of the moist air.

[0123] Taking the #3 combined cycle unit of a gas turbine power plant as an example, Table 7 shows the results of the air composition calculation unit.

[0124] Table 7 Results of Air Component Calculation for Unit #3 Combined Cycle Unit in a Gas Turbine Power Plant

[0125]

[0126] Step 3: Based on the fuel composition information and the thermophysical properties of the moist air determined in Step 2, calculate the composition and mass flow rate of the combustion flue gas.

[0127] Step S3.1: Based on the mole fraction of fuel gas components obtained by the online chromatograph, and combined with the relative molecular mass of each component of the fuel gas, calculate the relative molecular mass of the fuel gas; then, combined with the real-time measured mass flow rate of the fuel gas, calculate the molar flow rate of the fuel gas; and finally, combined with the combustion reaction coefficients of each component determined by the general oxidation reaction equation, calculate the change in molar flow rate of each component caused by the combustion of the fuel gas.

[0128] S3.2, Based on the change in oxygen molar flow rate calculated in S3.1, and combined with the molar fraction of oxygen in the dry air, calculate the dry air flow rate for combustion; introduce the humidity ratio determined in step 2, and convert the dry air flow rate into the wet air flow rate for combustion; then, combined with the molar fraction of each component of the wet air determined in step 2, calculate the molar flow rate of each component of the wet air for combustion.

[0129] S3.3, based on the changes in the molar flow rate of each component of the fuel gas combustion calculated in S3.1, is superimposed with the molar flow rate of each component of the humid air used for combustion calculated in S3.2 to calculate the molar flow rate of each component of the combustion flue gas; combined with the relative molecular mass of each component, the total mass flow rate of the combustion flue gas is calculated, and then the mass fraction of each component of the combustion flue gas is determined.

[0130] Taking the #3 combined cycle unit of a gas turbine power plant as an example, Table 8 shows the results of the combustion flue gas calculation unit.

[0131] Table 8 Results of Flue Gas Calculation Unit for Unit #3 Combined Cycle Unit of a Gas Turbine Power Plant

[0132]

[0133] Step 4: Based on the mass fractions of each component of the humid air determined in Step 2 and the mass fractions of each component of the combustion flue gas determined in Step 3, and combined with the inlet and outlet temperatures of the waste heat boiler under steady-state conditions determined in Step 1, calculate the gas enthalpy values ​​and determine the specific enthalpy of the humid air and the specific enthalpy of the combustion flue gas at the inlet and outlet of the waste heat boiler, respectively.

[0134] S4.1 Based on the inlet and outlet temperatures of the waste heat boiler under steady-state conditions determined in step 1, and combined with the mass fractions of each component of the humid air determined in step 2, calculate the humid air specific enthalpy at the inlet and outlet of the waste heat boiler according to the gas component specific enthalpy calculation polynomial given in standard NASA TP 2002 211556.

[0135] S4.2 Based on the inlet and outlet temperatures of the waste heat boiler under steady-state conditions determined in step 1, and combined with the mass fractions of each component of the combustion flue gas determined in step 3, the specific enthalpy of the combustion flue gas at the inlet and outlet of the waste heat boiler is calculated according to the gas component specific enthalpy calculation polynomial given in standard NASA TP 2002 211556.

[0136] Taking the #3 combined cycle unit of a gas turbine power plant as an example, Table 9 shows the results of the gas enthalpy calculation unit.

[0137] Table 9 Results of Gas Enthalpy Calculation for Unit #3 of a Gas Turbine Power Plant

[0138] Step 5: Based on the combustion flue gas flow rate determined in Step 3 and the specific enthalpy parameters determined in Step 4, the excess air flow rate is calculated according to the energy balance of the gas turbine, and then the thermal efficiency of the waste heat boiler is determined in real time through the energy inverse balance calculation of the waste heat boiler.

[0139] S5.1 Based on the fuel gas mass flow rate, fuel gas lower heating value, and gas turbine power generation under steady-state conditions determined in step 1, and combined with the combustion flue gas flow rate determined in step 3 and the specific enthalpy parameters determined in step 4, calculate the excess combustion air flow rate according to the gas turbine energy balance equation.

[0140] S5.2, based on the excess air flow rate of combustion calculated in S5.1 and the flue gas flow rate of combustion determined in step 3, combined with the enthalpy of the wet air at the inlet and outlet of the waste heat boiler and the enthalpy of the flue gas of combustion determined in step 4, the thermal efficiency of the waste heat boiler is calculated according to the energy reverse balance principle of the waste heat boiler.

[0141] Taking the #3 combined cycle unit of a gas turbine power plant as an example, Table 10 shows the results of the energy balance calculation unit.

[0142] Table 10 Results of Energy Balance Calculation for Unit #3 Combined Cycle Unit of a Gas Turbine Power Plant

[0143] The above specific embodiments demonstrate that the method provided by this invention for real-time monitoring of the thermal efficiency of waste heat boilers in combined cycle power units improves the quality and reliability of multi-source heterogeneous data from the field through a data processing unit. It simplifies the complex iterative solution process in traditional methods through three units: air composition calculation, combustion flue gas calculation, and gas enthalpy calculation. Furthermore, it achieves direct calculation of excess combustion air flow and online inverse balance calculation of waste heat boiler thermal efficiency through an energy balance calculation unit. The entire method has clear logic and low computational complexity, enabling online monitoring of the thermal efficiency of waste heat boilers in combined cycle power units and providing strong technical support for real-time economic analysis of combined cycle power units.

[0144] This application discloses a method and system for real-time monitoring of the thermal efficiency of waste heat boilers in combined cycle power units, comprising five units: data processing, air composition calculation, combustion flue gas calculation, gas enthalpy calculation, and energy balance calculation. By improving data processing accuracy and simplifying calculation complexity, online monitoring of the thermal efficiency of waste heat boilers in combined cycle power units is achieved, providing strong technical support for conducting real-time economic analysis of combined cycle power units.

[0145] Example 2 A system for real-time monitoring of the thermal efficiency of a waste heat boiler in a combined cycle unit, comprising: The data processing unit is used to perform anomaly detection and correction on the multi-source heterogeneous raw operating data of each monitoring system of the combined cycle unit to obtain steady-state correction data, and to perform steady-state identification on the steady-state correction data according to the operating characteristics of the combined cycle unit to determine the steady-state operating condition. An air composition calculation unit is used to determine the thermophysical properties of humid air under the current environmental conditions based on the environmental parameters under the steady-state operating conditions and in conjunction with the standard dry air composition benchmark. The combustion flue gas calculation unit is used to perform combustion flue gas calculations based on fuel composition information and the thermophysical properties of the humid air, and to determine the composition and mass flow rate of the combustion flue gas. The gas enthalpy calculation unit is used to calculate the gas enthalpy based on the thermophysical properties of the humid air and the composition of the combustion flue gas, combined with the temperature parameters under the steady-state operating conditions, and to determine the specific enthalpy of the gas at the inlet and outlet of the waste heat boiler. The energy balance calculation unit is used to determine the thermal efficiency of the waste heat boiler through energy balance calculation based on the mass flow rate of the combustion flue gas and the specific enthalpy of the gas at the inlet and outlet of the waste heat boiler.

[0146] It should be noted that, in the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another device, or some features may be ignored or not executed. The modules described as separate components may or may not be physically separated. The components shown as modules may be one or more physical units, that is, they may be located in one place or distributed in multiple different places. Some or all of the modules can be selected to achieve the purpose of the solution in this embodiment according to actual needs.

[0147] Furthermore, in the various embodiments of the present invention, the modules can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The integrated unit described above can be implemented in hardware or as a software functional unit.

[0148] An electronic device provided in this application includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the steps of the method for real-time monitoring of the thermal efficiency of a combined cycle unit waste heat boiler as described in any of the above embodiments.

[0149] Another electronic device provided in this application embodiment may further include: an input port connected to a processor for transmitting multimodal data collected by an external acquisition device to the processor; a display unit connected to the processor for displaying the processor's processing results to the outside world; and a communication module connected to the processor for enabling communication between the electronic device and the outside world. The display unit may be a display panel, a laser scanning display, etc.; the communication method adopted by the communication module includes, but is not limited to, Mobile High Definition Link (HML), Universal Serial Bus (USB), High Definition Multimedia Interface (HDMI), and wireless connection (including Wi-Fi, Bluetooth, Bluetooth Low Energy, and IEEE 802.11s-based communication technology).

[0150] This application provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the steps of the method for real-time monitoring of the thermal efficiency of a combined cycle unit waste heat boiler as described in any of the above embodiments.

[0151] For descriptions of the system, electronic equipment, and computer-readable storage medium for real-time monitoring of the thermal efficiency of a combined cycle unit's waste heat boiler provided in this application's embodiments, please refer to the detailed descriptions of the corresponding parts in the method for real-time monitoring of the thermal efficiency of a combined cycle unit's waste heat boiler provided in this application's embodiments; they will not be repeated here. Furthermore, parts of the technical solutions provided in this application that are consistent with the implementation principles of corresponding technical solutions in the prior art have not been described in detail to avoid excessive elaboration.

[0152] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A method for real-time monitoring of the thermal efficiency of a waste heat boiler in a combined cycle unit, characterized in that, Includes the following steps: Step 1: Perform anomaly detection and correction on the multi-source heterogeneous raw operating data of each monitoring system of the combined cycle unit to obtain steady-state correction data, and perform steady-state identification on the steady-state correction data according to the operating characteristics of the combined cycle unit to determine the steady-state operating condition. Step 2: Based on the environmental parameters under the steady-state operating conditions and in conjunction with the standard dry air composition benchmark, determine the thermophysical properties of the humid air under the current environmental conditions; Step 3: Based on the fuel composition information and the thermophysical properties of the humid air, perform combustion flue gas calculations to determine the composition and mass flow rate of the combustion flue gas; Step 4: Based on the thermophysical properties of the humid air and the composition of the combustion flue gas, and combined with the temperature parameters under the steady-state operating conditions, calculate the gas enthalpy and determine the specific enthalpy of the gas at the inlet and outlet of the waste heat boiler. Step 5: Based on the mass flow rate of the combustion flue gas and the specific enthalpy of the gas at the inlet and outlet of the waste heat boiler, determine the thermal efficiency of the waste heat boiler through energy balance calculation.

2. The method for real-time monitoring of the thermal efficiency of a waste heat boiler in a combined cycle unit according to claim 1, characterized in that, The process of detecting and correcting anomalies in the multi-source heterogeneous raw operating data of each monitoring system of the combined cycle unit to obtain steady-state correction data includes: Based on the data time alignment rules, the multi-source heterogeneous original running data is interpolated, matched and integrated to obtain preprocessed basic data; An improved Grubbs criterion is used to perform dynamic anomaly detection on the preprocessed basic data point by point. The identified outliers are replaced and corrected using the window midpoint to obtain the steady-state corrected data without any abnormal jumps throughout the time period.

3. The method for real-time monitoring of the thermal efficiency of a waste heat boiler in a combined cycle unit according to claim 2, characterized in that, The improved Grubbs criterion is used to perform dynamic anomaly detection on the preprocessed basic data point by point, and the identified outliers are replaced and corrected using the window value, including: Sort the data within the dynamic sliding detection window by numerical value and calculate the median of the window data; Calculate the absolute value of the residuals between each data point and the median, and the median difference of all residuals; Calculate the Grubbs statistic for each data point and compare it with the Grubbs critical value for the corresponding window length. If the statistic is greater than or equal to the critical value, the data point is determined to be an outlier. Outliers are replaced by the middle value in the window. The detection is iterated until there are no outliers in the current window. The sliding window traverses all time period data to complete the anomaly correction of all parameters.

4. A method for real-time monitoring of the thermal efficiency of a waste heat boiler in a combined cycle unit according to claim 1, characterized in that, The determination of steady-state operating conditions includes: Several operating parameters that significantly affect thermal efficiency are selected as steady-state judgment indicators. Multi-parameter collaborative steady-state identification is performed on the steady-state correction data to determine the unit's steady-state operating condition.

5. A method for real-time monitoring of the thermal efficiency of a waste heat boiler in a combined cycle unit according to claim 1, characterized in that, Step 2, determining the thermophysical properties of moist air under the current environmental conditions, includes: Based on the environmental parameters under the aforementioned steady-state operating conditions, the mass fraction and humidity ratio of dry air are calculated using thermodynamic correlations. Based on the dry air mass fraction and the mole fraction of each component of dry air, calculate the mole fraction of each component of actual humid air; Based on the mole fraction and relative molecular mass of each component of the actual humid air, the relative molecular mass of the humid air is calculated, and then the mass fraction of each component of the humid air is determined.

6. A method for real-time monitoring of the thermal efficiency of a waste heat boiler in a combined cycle unit according to claim 1, characterized in that, Step 3, calculating the total mass flow rate and mass fraction of each component of the combustion flue gas, includes: Based on the mole fraction of fuel gas components and real-time mass flow rate, the molar flow rate of fuel gas is calculated. Combined with the oxidation and combustion reaction coefficients of each component, the change in molar flow rate of each component of flue gas caused by fuel combustion is calculated. Based on the oxygen molar flow rate consumption, the theoretical dry air flow rate is calculated by combining the molar fraction of oxygen in the dry air, and then converted into the total flow rate of humid air for combustion and the molar flow rate of each component by the humidity ratio. The changes in the molar flow rates of the combustion products are superimposed with the molar flow rates of the humid air used for combustion to obtain the molar flow rates of each component of the combustion flue gas, and then the total mass flow rate and mass fraction of each component of the combustion flue gas are calculated.

7. A method for real-time monitoring of the thermal efficiency of a waste heat boiler in a combined cycle unit according to claim 1, characterized in that, Step 4, determining the specific enthalpy of the gas at the inlet and outlet of the waste heat boiler, includes: Based on the inlet and outlet temperatures of the waste heat boiler under the aforementioned steady-state operating conditions, and in conjunction with the mass fractions of each component of the humid air, the enthalpy of the humid air at the inlet and outlet of the waste heat boiler is calculated. Based on the inlet and outlet temperatures of the waste heat boiler under the aforementioned steady-state operating conditions, and in conjunction with the mass fractions of each component of the combustion flue gas, the specific enthalpy of the combustion flue gas at the inlet and outlet of the waste heat boiler is calculated.

8. A method for real-time monitoring of the thermal efficiency of a waste heat boiler in a combined cycle unit according to claim 1, characterized in that, Step 5, determining the thermal efficiency of the waste heat boiler, includes: Based on the fuel gas mass flow rate, fuel gas lower heating value, and gas turbine power generation under the steady-state operating conditions, combined with the combustion flue gas mass flow rate, the enthalpy of moist air at the inlet of the waste heat boiler, and the enthalpy of combustion flue gas, the excess combustion air flow rate is calculated according to the gas turbine energy balance equation. Based on the excess air flow rate and the mass flow rate of the combustion flue gas, combined with the enthalpy of the moist air and the enthalpy of the combustion flue gas at the inlet and outlet of the waste heat boiler, the thermal efficiency of the waste heat boiler is calculated according to the energy reverse balance principle of the waste heat boiler.

9. A system for real-time monitoring of the thermal efficiency of a waste heat boiler in a combined cycle unit, characterized in that, include: The data processing unit is used to perform anomaly detection and correction on the multi-source heterogeneous raw operating data of each monitoring system of the combined cycle unit to obtain steady-state correction data, and to perform steady-state identification on the steady-state correction data according to the operating characteristics of the combined cycle unit to determine the steady-state operating condition. An air composition calculation unit is used to determine the thermophysical properties of humid air under the current environmental conditions based on the environmental parameters under the steady-state operating conditions and in conjunction with the standard dry air composition benchmark. The combustion flue gas calculation unit is used to perform combustion flue gas calculations based on fuel composition information and the thermophysical properties of the humid air, and to determine the composition and mass flow rate of the combustion flue gas. The gas enthalpy calculation unit is used to calculate the gas enthalpy based on the thermophysical properties of the humid air and the composition of the combustion flue gas, combined with the temperature parameters under the steady-state operating conditions, and to determine the specific enthalpy of the gas at the inlet and outlet of the waste heat boiler. The energy balance calculation unit is used to determine the thermal efficiency of the waste heat boiler through energy balance calculation based on the mass flow rate of the combustion flue gas and the specific enthalpy of the gas at the inlet and outlet of the waste heat boiler.

10. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, connected to the memory, is configured to execute the computer program to implement the steps of the method for real-time monitoring of the thermal efficiency of a combined cycle unit waste heat boiler as described in any one of claims 1 to 8.

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