Gas turbine performance evaluation method and device and gas turbine

Abstract

The invention relates to the technical field of equipment parameter monitoring, in particular to a gas turbine performance evaluation method and device and a gas turbine. The method comprises the following steps: establishing a gas compressor characteristic model, a turbine characteristic model, a combustion chamber flow and energy constraint model and a critical flow model based on characteristic data of a gas compressor and a turbine, and jointly constructing a multi-model evaluation network; performing inversion solution by taking the compressor pressure ratio as an independent variable through the multi-model evaluation network to obtain the compressor inlet flow, the compressor pressure ratio and the combustion chamber outlet flow, and obtaining the compressor efficiency through a compressor characteristic model based on the compressor pressure ratio; a pressure balance equation is established based on the compressor pressure ratio and the combustion chamber pressure loss coefficient, the turbine expansion ratio is obtained through the pressure balance equation, and the turbine expansion ratio is input into the turbine characteristic model to predict the turbine efficiency; and working characteristic parameters of the gas turbine are obtained according to the inlet flow of the gas compressor, the pressure ratio of the gas compressor, the efficiency of the gas compressor, the expansion ratio of the turbine and the efficiency of the turbine.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of equipment parameter monitoring, and particularly relates to a gas turbine performance evaluation method and device and a gas turbine. BACKGROUND

[0002] Traditional gas turbine performance calculation methods are usually based on characteristic curves of components such as compressors, combustors and turbines, and a coupled nonlinear equation set is established through basic thermodynamic relations such as equal flow rate, equal speed and energy conservation, and then the working point of the whole machine is solved by numerical iteration. Due to the need to simultaneously satisfy multiple coupling constraints, the model structure is complex and the nonlinearity is high, so in engineering applications, there are problems such as difficulty in converging the calculation process, sensitivity to initial values, and long iteration solving time. These deficiencies are particularly prominent in the scheme design stage of the whole machine, because at this stage, a large number of initial schemes need to be quickly matched and compared, and the solving efficiency of the traditional method is difficult to meet the demand for a large number of iterations.

[0003] To alleviate the above problems, in the prior art, a matching calculation method is usually used to simplify or approximately assume the characteristics of compressors and turbines, so as to reduce the number of equations and the calculation complexity. However, these methods do not accurately describe the real characteristics of the components, and there is a deviation from the actual component performance, which makes it difficult for the calculation results to accurately reflect the real thermodynamic state of the gas turbine, limiting its application value in scheme optimization and performance prediction. At the same time, the existing technology still continues the traditional theoretical framework and does not fully utilize the engineering characteristics of the turbine flow blockage at the critical condition, which can be used to reduce the size of the matching equation and weaken the degree of system coupling, thereby improving the stability and convergence of the whole machine performance calculation.

[0004] In summary, the solving difficulty of the traditional method leads to the fact that the prior art generally relies on simplification to reduce complexity, and the simplification of the prior art leads to insufficient accuracy, and the key physical characteristics such as turbine critical flow are not fully utilized to optimize the solving structure, so the calculation efficiency and accuracy cannot be considered. Therefore, it is urgent to construct a new technical scheme to solve at least one of the above technical problems. SUMMARY

[0005] The present application is directed to the technical problems existing in the prior art, and provides a gas turbine performance evaluation method and device and a gas turbine, which are used to realize online evaluation of the performance of the gas turbine, simplify the performance evaluation process of the gas turbine, improve the accuracy and evaluation efficiency of the performance parameters of the gas turbine, and guarantee the safe and stable operation and efficient regulation and control of the gas turbine.

[0006] In a first aspect, an embodiment of the present application provides a gas turbine performance evaluation method, which comprises:

[0007] The compressor characteristic model, the turbine characteristic model, the combustion chamber flow and energy constraint model, and the critical flow model are established based on characteristic data of the compressor and the turbine at a design rotating speed, and a multi-model evaluation network is constructed in combination to describe a coupling relationship among the compressor, the combustion chamber, and the turbine.

[0008] The compressor inlet flow, the compressor pressure ratio, and the combustion chamber outlet flow are obtained by inversion solving of the multi-model evaluation network with the compressor pressure ratio as an independent variable, and the compressor efficiency is obtained based on the compressor pressure ratio through the compressor characteristic model.

[0009] The turbine expansion ratio is obtained by solving a pressure balance equation based on the compressor pressure ratio and the combustion chamber pressure loss coefficient, and the turbine efficiency is predicted by inputting the turbine expansion ratio into the turbine characteristic model.

[0010] The working characteristic parameters of each component in the gas turbine are obtained according to the compressor inlet flow, the compressor pressure ratio, the compressor efficiency, the turbine expansion ratio, and the turbine efficiency, and the working characteristic parameters at least include power, efficiency, specific fuel consumption, and pressure and temperature parameters of each section.

[0011] In a second aspect, an embodiment of the present application provides a gas turbine performance evaluation device, which is applied to a gas turbine, and the device comprises the following units, wherein,

[0012] The construction unit is configured to establish a compressor characteristic model, a turbine characteristic model, a combustion chamber flow and energy constraint model, and a critical flow model based on characteristic data of the compressor and the turbine at a design rotating speed, and to construct a multi-model evaluation network in combination to describe a coupling relationship among the compressor, the combustion chamber, and the turbine.

[0013] The evaluation unit is configured to obtain the compressor inlet flow, the compressor pressure ratio, and the combustion chamber outlet flow by inversion solving of the multi-model evaluation network with the compressor pressure ratio as an independent variable, and to obtain the compressor efficiency based on the compressor pressure ratio through the compressor characteristic model; to obtain the turbine expansion ratio by solving a pressure balance equation based on the compressor pressure ratio and the combustion chamber pressure loss coefficient, and to predict the turbine efficiency by inputting the turbine expansion ratio into the turbine characteristic model; and to obtain working characteristic parameters of each component in the gas turbine according to the compressor inlet flow, the compressor pressure ratio, the compressor efficiency, the turbine expansion ratio, and the turbine efficiency, and the working characteristic parameters at least include power, efficiency, specific fuel consumption, and pressure and temperature parameters of each section.

[0014] In a third aspect, the embodiments of the present application provide a gas turbine, which is provided with a data monitoring system, the data monitoring system comprising at least one processor, a memory and an input and output unit;

[0015] The memory is configured to store a computer program, and the processor is configured to invoke the computer program stored in the memory to execute the gas turbine performance evaluation method of the first aspect.

[0016] In a fourth aspect, a computer readable storage medium is provided, which comprises instructions, when the instructions are executed on a computer, causing the computer to execute the gas turbine performance evaluation method of the first aspect.

[0017] The beneficial effects of the present application are: a gas turbine performance evaluation method and device, and a gas turbine are provided. In the technical solution, first, the compressor characteristic model, the turbine characteristic model, the combustion chamber flow and energy constraint model, and the critical flow model are established based on the characteristic data of the compressor and the turbine at the design speed, and a multi-model evaluation network is jointly constructed, which is used to describe the coupling relationship between the compressor, the combustion chamber and the turbine. Then, the compressor inlet flow, the compressor pressure ratio and the combustion chamber outlet flow are obtained by inversely solving the multi-model evaluation network with the compressor pressure ratio as the independent variable, and the compressor efficiency is obtained based on the compressor pressure ratio through the compressor characteristic model. Then, the pressure balance equation is established based on the compressor pressure ratio and the combustion chamber pressure loss coefficient, the turbine expansion ratio is obtained by solving the pressure balance equation, and the turbine efficiency is predicted by inputting the turbine expansion ratio into the turbine characteristic model. Finally, the working characteristic parameters of each component in the gas turbine are obtained according to the compressor inlet flow, the compressor pressure ratio, the compressor efficiency, the turbine expansion ratio and the turbine efficiency, which at least include power, efficiency, specific fuel consumption and pressure and temperature parameters of each section. The technical solution of the present application realizes unified modeling and adaptive inversion of the coupling relationship between the components of the gas turbine by constructing a multi-model evaluation network, greatly improves the accuracy, real-time performance and stability of the gas turbine performance evaluation, simplifies the evaluation process, and ensures the efficient and safe operation of the gas turbine. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is a flowchart of a gas turbine performance evaluation method according to an embodiment of the present application;

[0019] Figure 2 is a principle diagram of a gas turbine performance evaluation method according to an embodiment of the present application;

[0020] Figure 3 is a structure diagram of a gas turbine performance evaluation device according to an embodiment of the present application;

[0021] Figure 4 is a structural schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0023] To solve at least one technical problem in the prior art, the embodiments of the present application provide a gas turbine performance evaluation method and device and a gas turbine. The technical solutions of the present application construct a compressor characteristic model, a turbine characteristic model, a combustion chamber flow and energy constraint model, and a turbine critical flow model, and couple the above-mentioned multiple models in the form of a multi-model evaluation network, so that the strong coupling characteristics between the compressor, the combustion chamber and the turbine can be uniformly modeled in the form of mathematical logic and physical constraints, and the calculability and invertibility of the overall machine performance parameters are improved. The technical solutions of the present application take the compressor pressure ratio as the main solving variable, realize the inverse calculation of the compressor inlet flow, the combustion chamber outlet flow and the compressor efficiency through the multi-model evaluation network, and obtain the turbine expansion ratio by combining the pressure balance equation, and then obtain the turbine efficiency from the turbine characteristic model, so that the working point of the overall gas turbine can be quickly obtained without complex solving of large-scale coupled equations. In summary, by constructing a multi-model evaluation network to uniformly model and adaptively invert the coupling relationship between the components of the gas turbine, the accuracy, real-time performance and stability of the gas turbine performance evaluation are greatly improved, the evaluation process is simplified, and the efficient and safe operation of the gas turbine is ensured.

[0024] The gas turbine performance evaluation scheme provided by the embodiments of the present application can also be executed by an electronic device, which can be a server, a server cluster, a cloud server. The electronic device can also be a terminal device such as a mobile phone, a computer, a tablet computer, a wearable device, or a special-purpose device (such as a special-purpose terminal device with a gas turbine performance evaluation method system, etc.). The chips introduced in the above embodiments can also be carried in these electronic devices. Alternatively, these electronic devices can also install a service program for executing the gas turbine performance evaluation scheme.

[0025] Figure 1 A flowchart of a gas turbine performance evaluation method provided by an embodiment of the present application is shown in FIG. 1, which includes the following steps: Figure 1

[0026] ​101, based on the characteristic data of the compressor and the turbine at the design speed, a compressor characteristic model, a turbine characteristic model, a combustion chamber flow and energy constraint model, and a critical flow model are established, and a multi-model evaluation network is constructed;

[0027] 102, through the multi-model evaluation network, the compressor pressure ratio is taken as the independent variable to solve inversely, the compressor inlet flow, the compressor pressure ratio and the combustion chamber outlet flow are obtained, and the compressor efficiency is obtained based on the compressor pressure ratio through the compressor characteristic model;

[0028] 103, based on the compressor pressure ratio and the combustion chamber pressure loss coefficient, a pressure balance equation is established, the turbine expansion ratio is obtained by the pressure balance equation, and the turbine efficiency is obtained by inputting the turbine expansion ratio into the turbine characteristic model;

[0029] 104, according to the compressor inlet flow, the compressor pressure ratio, the compressor efficiency, the turbine expansion ratio and the turbine efficiency, the working characteristic parameters of each component matching in the gas turbine are obtained, and the working characteristic parameters at least include power, efficiency, specific fuel consumption and pressure and temperature parameters of each section.

[0030] Through the above steps 101 to 104, first, by modeling instead of the traditional way of directly solving high-coupling nonlinear equations, the performance evaluation process is changed from complex iterative solving to fast reasoning based on multi-model linkage, reducing the amount of calculation, supporting online or quasi-real-time performance evaluation. Secondly, by using real component characteristic curve fitting, energy and flow constraint model based on physical law, and turbine critical flow characteristics, the model prediction result is closer to the actual running state, and the calculation accuracy of key performance parameters such as compressor efficiency, turbine efficiency and flow is improved. Thirdly, taking the compressor pressure ratio as the main solving variable, and decoupling the coupling relationship between each component into multiple models that can be solved independently, the overall solving structure is more stable, and the convergence is stronger, avoiding the problem of slow convergence or non-convergence in traditional methods. Further, the present application realizes the coupling and decoupling of the compressor, the combustion chamber, the turbine and other components by constructing a unified multi-model evaluation network, so that the performance evaluation logic is clear, the process is simplified, and it is easier to deploy in the actual operation monitoring system. In addition, the present application obtains the working characteristic parameters (such as power, efficiency, specific fuel consumption, important section temperature and pressure) of each component of the gas turbine in time and accurately, which helps to realize dynamic regulation and control based on working condition, to identify the deviation working condition or abnormal state in advance, so as to improve the safe and stable operation ability of the gas turbine.

[0031] It is worth noting that all calculations involved in the embodiments of this application are based on the International System of Units (SI), with an enthalpy reference temperature of 15°C, ensuring data consistency. The technical solution provided by this application overcomes the limitations of traditional methods that require component characteristics and a large number of parameters, achieving real-time monitoring of the combustion chamber outlet temperature through only routine boundary tests, thus providing an effective means for gas turbine performance optimization and life assessment.

[0032] refer to Figure 2 As shown, this example graph is closely related to the critical flow model (optional embodiment in step 101) of the gas turbine performance evaluation method, and is a visual representation of the physical characteristics of the model. The horizontal axis represents the expansion ratio, corresponding to the turbine expansion ratio in the method, while the vertical axis represents the relative reduced flow rate, which can be correlated to the combustion chamber outlet flow rate. Different curves (e.g., n=0.7, n=0.8, etc.) reflect the relationship between the turbine expansion ratio and the combustion chamber outlet flow rate under different parameters (which can be understood as comprehensive parameters related to the compressor pressure ratio and combustion chamber outlet temperature). When the expansion ratio increases to a certain critical value ( Figure 2 When the "blockage" occurs (as indicated by the dashed line), the relative reduced flow rate tends to stabilize, which is the core physical basis of the critical flow model. At this point, the throat of the turbine's first-stage guide vane reaches the speed of sound, entering a critical flow state. The flow rate no longer changes with downstream pressure but is determined solely by upstream parameters (combustion chamber outlet temperature, pressure, turbine throat area, etc.). In the above evaluation method, the critical flow model constructed in step 101 is based on this characteristic, establishing a functional relationship between the combustion chamber outlet flow rate and the compressor pressure ratio (coupled through pressure balance). The inversion solution in step 102 and the turbine expansion ratio calculation in step 103 both rely on this model's constraint on "maintaining the critical state of turbine flow rate" to ensure the convergence and accuracy of the overall engine performance calculation. In short, Figure 2 This intuitively verifies the physical rationality of the critical flow model and provides visual support for the turbine flow constraint logic in the aforementioned evaluation method.

[0033] Step 101: Based on the characteristic data of the compressor and turbine at the design speed, establish the compressor characteristic model, turbine characteristic model, combustion chamber flow and energy constraint model, and critical flow model, and jointly construct a multi-model evaluation network.

[0034] In the embodiments of the present application, the multi-model evaluation network is used to describe the coupling relationship between the compressor, the combustion chamber and the turbine. It can be understood that the multi-model evaluation network is a comprehensive physical modeling framework for fast solving of performance parameters of the gas turbine. The multi-model evaluation network is composed of a compressor characteristic model, a turbine characteristic model, a combustion chamber flow and energy constraint model and a turbine critical flow model according to a preset data flow direction and solving logic, and is used to uniformly describe the flow matching relationship, the energy conservation relationship and the pressure balance relationship among the compressor, the combustion chamber and the turbine. Specifically, the multi-model evaluation network associates the input variables and the output variables of each sub-model, so that the key parameters such as the compressor pressure ratio, the combustion chamber outlet flow, the compressor inlet flow and the turbine expansion ratio can be inferred and solved step by step within the network, thereby avoiding the need to construct and solve highly coupled nonlinear equations in the traditional whole-machine performance calculation. Through the coupling relationship among the above models, the multi-model evaluation network can realize the collaborative inference of the working points of the compressor, the combustion chamber and the turbine by taking the compressor pressure ratio as the main solving variable, form a set of gas turbine component matching relationship expression forms with stronger convergence and higher solving efficiency, and is conducive to realizing the fast prediction and online evaluation of the performance of the gas turbine.

[0035] As an optional embodiment, in step 101, first, the compressor characteristic data of the compressor at the design speed is obtained, the compressor pressure ratio in the compressor characteristic data is taken as the input, the compressor inlet flow and the compressor efficiency are adaptively predicted by combining the fitting formula, and the compressor characteristic model is constructed. Then, the turbine characteristic data of the turbine at the design speed is obtained, the turbine expansion ratio in the turbine characteristic data is taken as the input, the turbine efficiency is predicted by combining the fitting formula, and the turbine characteristic model is constructed. Next, the compressor inlet flow, the air system bleed air ratio, the combustion efficiency, the low calorific value of the fuel, the combustion chamber inlet enthalpy value and the outlet enthalpy value are obtained, the correlation equation between the compressor inlet flow and the combustion chamber outlet flow is constructed by the flow conservation and energy conservation relationship, and the combustion chamber flow and energy constraint model is generated. Finally, under the condition that the combustion chamber outlet temperature is determined, the turbine first-stage guide vane throat area, the gas constant, the specific heat ratio of the gas and the compressor inlet pressure are taken as the input, and based on the physical characteristics that the turbine throat maintains the critical flow state, the functional relationship between the combustion chamber outlet flow and the compressor pressure ratio is constructed, and the critical flow model is formed.

[0036] In an optional embodiment of the present application, step 101 constructs respective characteristic models based on the physical correlation laws among the compressor, turbine and combustion chamber to form a multi-model evaluation structure capable of reflecting the coupling relationship among the three. The main principle of step 101 is to split the highly coupled nonlinear equation set difficult to be directly solved in the traditional gas turbine overall performance matching calculation into several sub-models that can be independently modeled, and establish the overall working constraint relationship of the compressor, combustion chamber and turbine through the input-output link among these models, thereby reducing the solving difficulty and improving the convergence and accuracy of the system.

[0037] Specifically, first, by acquiring the real characteristic data of the compressor at the design speed, the compressor pressure ratio is taken as the independent variable, and the function relationship between the compressor pressure ratio and the compressor inlet flow rate and the compressor efficiency is respectively constructed by using the fitting formula to form the compressor characteristic model. This way converts the discrete characteristic points into continuous mathematical expressions, solves the problem of small flow rate variation range of the compressor near the design speed and direct solution instability, and enables the flow rate and efficiency of the compressor side to be accurately predicted with the change of the pressure ratio. Second, the characteristic data of the turbine at the design speed is also acquired by the same method, and the continuous relationship between the turbine efficiency and the turbine expansion ratio is constructed by using the fitting model with the turbine expansion ratio as the input. The turbine characteristic model can express the change trend of the turbine efficiency with the expansion ratio by a smooth mathematical function, providing a basis for subsequent pressure balance solving of the turbine expansion ratio and further prediction of the turbine efficiency. Further, by the flow conservation and energy conservation relationship of the combustion chamber, the compressor inlet flow rate, air system bleed air ratio, combustion efficiency, fuel lower calorific value, combustion chamber inlet enthalpy value and outlet enthalpy value are taken as inputs to calculate the function relationship between the compressor inlet flow rate and the combustion chamber outlet flow rate. This part of the model reflects the influence of the energy increase in the combustion chamber on the outlet flow rate, so that the combustion chamber outlet flow rate is determined not only by the air quantity, but also by the fuel input and combustion efficiency, thereby ensuring the physical consistency of the combustion chamber. Finally, under the condition that the combustion chamber outlet temperature is determined, based on the physical characteristics that the throat of the turbine first-stage guide vane maintains a critical flow state, the critical flow model between the combustion chamber outlet flow rate and the compressor pressure ratio is constructed by using the throat area, gas constant, specific heat ratio of the combustion gas and compressor inlet pressure. Since the gas flow velocity at the throat of the turbine reaches the sound velocity in the critical state, the combustion chamber outlet flow rate no longer changes with the downstream pressure, so this model makes the combustion chamber outlet flow rate a determined function of the compressor pressure ratio, which fundamentally reduces the number of free variables in the overall calculation and enhances the convergence of the equation system.

[0038] Through the construction of the four types of models, the multi-model evaluation network formed in step 101 can more accurately construct the flow coupling, energy balance and pressure matching mechanism between the compressor, combustion chamber and turbine, and realize the decomposition of the originally jointly solved large-scale nonlinear equation set into a multi-model network structure that can be reasoned in a physical logic step by step. In this way, not only is the variable dimension of the overall solution reduced, making the calculation more stable and easier to converge, but also the fitting accuracy of the performance evaluation to the true component characteristics is improved, providing an accurate and low computational mathematical basis for subsequent engine operating point inversion solving, which helps to further improve the calculation efficiency and accuracy.

[0039] Further optionally, in an optional embodiment of step 101, the compressor pressure ratio in the compressor characteristic data is taken as input, and the compressor inlet flow and compressor efficiency are adaptively predicted by combining the fitting formula to construct the compressor characteristic model, including: preprocessing the characteristic data of the compressor at the design speed, wherein the preprocessing includes outlier elimination and smoothing processing; based on the preprocessed compressor characteristic points, the corresponding relationship between the compressor pressure ratio and the compressor inlet flow is fitted by a polynomial or interpolation fitting to obtain a continuous pressure ratio flow function; based on the preprocessed compressor characteristic points, the corresponding relationship between the compressor pressure ratio and the compressor efficiency is fitted by an independent fitting model to obtain a continuous pressure ratio efficiency function; and the pressure ratio flow function and the pressure ratio efficiency function are combined to form a compressor characteristic model for adaptively predicting the compressor inlet flow and the compressor efficiency under the condition of a given compressor pressure ratio.

[0040] It can be understood that, for the construction of the compressor characteristic model in step 101, the characteristic data of the compressor at the design speed is fitted and processed to form a continuous and invertible function relationship between the compressor pressure ratio, the compressor inlet flow and the compressor efficiency. The basic principle of the compressor characteristic model is to convert the actual performance curve of the compressor from discrete test points to a mathematical model to solve the problem that the traditional characteristic table cannot be directly used for engine inversion solving, and to provide stable calculation characteristic data support for the subsequent engine solving process with the compressor pressure ratio as the main variable.

[0041] Specifically, by preprocessing the compressor characteristic data, abnormal test points in the test process can be effectively removed, and numerical noise in the characteristic curve can be reduced by smoothing processing, so that the subsequent fitting model can more accurately reflect the real performance trend of the compressor. Subsequently, the corresponding relationship between the compressor pressure ratio and the compressor inlet flow is constructed as a continuous pressure ratio flow function by polynomial fitting or interpolation fitting, so that the compressor inlet flow can be predicted in a continuous and stable manner as the pressure ratio changes, not only improving the mathematical usability of the model, but also avoiding the instability problem of interpolation caused by discrete characteristic points.

[0042] Meanwhile, to further improve the accuracy of the model, the embodiment adopts an independent fitting model to model the relationship between the pressure ratio of the compressor and the efficiency of the compressor. Since the efficiency curve of the compressor usually has a segmented variation characteristic different from the flow curve, through independent modeling, the variation trend of the efficiency peak interval can be better captured, and a smooth and well-monotonic pressure ratio efficiency function can be obtained. Finally, the embodiment combines the pressure ratio flow function and the pressure ratio efficiency function to form the compressor characteristic model, so that the corresponding compressor inlet flow and compressor efficiency can be adaptively predicted under the condition of a given arbitrary pressure ratio.

[0043] Through the above modeling process, the compressor characteristic model first realizes continuous prediction of key performance variables with the change of the pressure ratio, enabling the working point of the compressor to be quickly solved by driving the pressure ratio as a single variable. Secondly, through the curve fitting modeling instead of the traditional discrete characteristic table, the stability and accuracy of the whole machine inverse solution are improved. Finally, the compressor characteristic model provides high-quality component input for the multi-model evaluation network, enabling the flow matching, energy balance and pressure balance process of the whole machine to be completed with smaller equation size and higher convergence, thereby improving the overall calculation efficiency and reliability of the gas turbine performance evaluation.

[0044] Exemplarily, assuming that the pressure ratio of the compressor is π c , the inlet flow of the compressor is m a , and the efficiency of the compressor is η c , based on this assumption, the compressor characteristic model can be expressed as the following formula: Wherein, a1, a2, …, a n , a n+1 are the fitting coefficients of the pressure ratio characteristic line of the compressor flow, b1, b2, …, b n , b n+1 are the fitting coefficients of the pressure ratio characteristic line of the compressor efficiency, and n is a constant.

[0045] Further optionally, in an optional embodiment of step 101, the turbine characteristic data of the turbine at the design speed is obtained, the turbine expansion ratio in the turbine characteristic data is taken as the input, the turbine efficiency is predicted by combining the fitting formula, and the turbine characteristic model is constructed, including:

[0046] The expansion ratio efficiency characteristic points of the turbine at the design speed are preprocessed to remove abnormal points and smooth the characteristic curve; based on the preprocessed turbine characteristic points, an interpolation method or a polynomial fitting method is used to establish a continuous function relationship between the turbine expansion ratio and the turbine efficiency; and the established continuous function relationship is constructed as a turbine characteristic model for predicting the turbine efficiency under the condition of a given turbine expansion ratio.

[0047] It can be explained that the principle used in constructing the turbine characteristic model in step 101 is to convert the actual performance curve of the turbine at the design speed into a mathematical function with continuity, differentiability, and predictability, so as to achieve rapid calculation and stable inference of turbine efficiency as a function of turbine expansion ratio. Since the performance characteristics of the turbine usually exhibit nonlinear changes with the expansion ratio, and the efficiency change trend in different expansion ratio regions may have inflection points or non-smooth segments, directly using the original test data for whole-machine solution is prone to problems such as oscillation or non-convergence. Therefore, it is necessary to perform fitting modeling of turbine characteristics.

[0048] Specifically, by preprocessing the turbine's expansion ratio efficiency characteristic points at the design speed, two things can be done: firstly, outlier data points caused by experimental errors, measurement noise, or unstable operating conditions can be eliminated; secondly, smoothing reduces the dispersion between characteristic points, resulting in a smoother and more continuous characteristic curve in the subsequent fitting process, ensuring the model's usability and stability. Subsequently, based on the preprocessed turbine characteristic points, interpolation or polynomial fitting methods are used to establish a continuous functional relationship between the turbine's expansion ratio and efficiency, allowing the turbine efficiency to be accurately expressed mathematically as the expansion ratio changes. This modeling approach captures the efficiency variation patterns of the turbine in the small, medium, and critical expansion ratio ranges, thus obtaining a more representative turbine efficiency curve than the original discrete characteristic points.

[0049] Finally, the continuous function obtained from the fitting is constructed into a turbine characteristic model. This allows the turbine expansion ratio, once obtained through the pressure balance equation, to be directly input into the turbine characteristic model during the overall performance calculation, thus quickly obtaining the corresponding turbine efficiency. This turbine characteristic model avoids the numerical discontinuities caused by frequent table lookups during bidirectional iterative solutions and significantly improves the smoothness, stability, and convergence of turbine efficiency calculations.

[0050] The turbine characteristic model constructed in the above manner not only improves the accuracy of turbine efficiency prediction, but also provides stable mathematical support for the subsequent coupled calculation of multi-model evaluation networks. This enables the overall performance evaluation to achieve higher solution accuracy and overall stability under conditions of lower computational complexity, thereby effectively improving the reliability and engineering applicability of gas turbine performance evaluation.

[0051] For example, assume the turbine expansion ratio is π. c Based on this assumption, the turbine characteristic model can be expressed as the following formula: Where, η T For turbine efficiency, Let c1, c2, ..., c be the turbine expansion ratios. n c n+1wherein n is a constant, and wherein the expansion ratio is the ratio of the turbine inlet pressure to the turbine outlet pressure.

[0052] Further optionally, in one optional embodiment of step 101, the compressor inlet flow rate, the air system bleed air ratio, the combustion efficiency, the fuel lower heating value, the combustion chamber inlet enthalpy value, and the combustion chamber outlet enthalpy value are obtained, a correlation equation between the compressor inlet flow rate and the combustion chamber outlet flow rate is constructed based on the flow conservation and energy conservation relationship, and a combustion chamber flow and energy constraint model is generated, including:

[0053] The air flow rate entering the combustion chamber from the compressor outlet is corrected based on the air system bleed air ratio to obtain the actual air flow rate participating in combustion, the fuel input is converted into the effective energy increase in the combustion chamber based on the combustion efficiency and the fuel lower heating value, the combustion chamber energy conservation equation is established based on the relationship between the combustion chamber inlet enthalpy value and the outlet enthalpy value to obtain the correlation between the combustion product enthalpy value and the air flow rate, and the energy conservation equation is converted into a functional relationship between the compressor inlet flow rate and the combustion chamber outlet flow rate by combining the flow conservation relationship that the combustion chamber inlet flow rate is equal to the combustion chamber outlet flow rate, the correlation between the combustion product enthalpy value and the air flow rate, and the effective energy increase, to form the combustion chamber flow and energy constraint model.

[0054] It can be understood that the core principle of this step is to establish a quantitative correlation between the compressor inlet flow rate and the combustion chamber outlet flow rate based on the basic physical law of the combustion chamber operation, and to form a constraint model through the flow conservation and energy conservation relationship. From the flow conservation, the air at the compressor outlet will be partially discharged through the air system bleed air, and the actual air flow rate participating in combustion needs to be corrected according to the air system bleed air ratio, while the sum of the air flow rate participating in combustion at the combustion chamber inlet and the fuel flow rate is equal to the flow rate of the combustion products at the combustion chamber outlet, which is the core logic of flow balance. From the energy conservation, the effective energy produced by the fuel combustion is determined by the combustion efficiency and the fuel lower heating value, and this energy will increase the enthalpy value of the combustion products from the inlet level to the outlet level of the combustion chamber. By establishing the correlation between the inlet enthalpy value and the outlet enthalpy value, the corresponding relationship between the combustion product enthalpy value and the air flow rate participating in combustion can be determined. Combining these two conservation relationships, the energy conservation equation can be converted into a functional relationship containing only the compressor inlet flow rate and the combustion chamber outlet flow rate, and finally the combustion chamber flow and energy constraint model is formed.

[0055] Thus, on the one hand, the air system air bleeding ratio correction and the combustion efficiency quantification make the combustion chamber flow and energy constraint model accurately reflect the flow loss and energy conversion efficiency in the actual combustion process, thereby improving the authenticity of the constraint relationship. On the other hand, the complex combustion process is converted into an explicit functional relationship, avoiding the simplifying assumptions of the combustion process in traditional calculations and reducing the error of subsequent whole-machine performance matching calculations. At the same time, the combustion chamber flow and energy constraint model directly relates the compressor core parameter (inlet flow) and the combustion chamber key output (outlet flow), laying a foundation for subsequent solving of other component equations and simplifying the nonlinear equation set, thereby improving the convergence speed and calculation accuracy of whole-machine performance calculation and meeting the rapid calculation requirements of gas turbine iteration.

[0056] Exemplarily, assuming m a is the combustion chamber outlet flow, based on this assumption, the combustion chamber flow and energy constraint model can be expressed as the following formula: wherein, a is the air system air bleeding ratio, h 30 is the fuel inlet sensible heat, η is the combustion efficiency, LHV is the low heat value of fuel. h 31 is the combustion chamber inlet enthalpy, which can be calculated according to the combustion chamber inlet temperature. h4 is the combustion chamber outlet enthalpy, which can be calculated according to the combustion chamber outlet temperature.

[0057] Further optionally, in an optional embodiment of step 101, under the condition that the combustion chamber outlet temperature is determined, the function relationship between the combustion chamber outlet flow and the compressor pressure ratio is constructed based on the physical properties of the turbine throat maintaining critical flow state, taking the turbine first-stage guide vane throat area, the gas constant, the gas specific heat ratio and the compressor inlet pressure as inputs, to form a critical flow model, including:

[0058] The flow velocity of the turbine first-stage guide vane throat is set to the sound velocity to determine that the turbine throat is in a critical flow condition; the gas specific heat ratio and the gas constant under the critical state are calculated according to the combustion chamber outlet temperature; the maximum flow of the combustion chamber outlet under the critical state is calculated based on the critical flow mass flow formula, taking the gas specific heat ratio, the gas constant and the turbine throat area as inputs; the function relationship between the combustion chamber outlet flow and the compressor pressure ratio is constructed by coupling the changes of the compressor inlet pressure and the compressor pressure ratio to the critical mass flow calculation; the function relationship between the combustion chamber outlet flow and the compressor pressure ratio is constructed as a turbine critical flow model, which is used to constrain the turbine flow to maintain in a critical state in the whole-machine solving process.

[0059] It is worth mentioning that the core principle of building the turbine critical flow model is to establish a quantitative correlation between the combustor outlet flow and the compressor pressure ratio based on the physical characteristics of the turbine primary guide vane throat under critical flow conditions. From the physical nature of critical flow, when the turbine throat flow velocity reaches the speed of sound, the throat is in a critical state of flow blockage, at which point the flow is no longer determined by the downstream pressure but only by the upstream parameters. This characteristic provides a key basis for simplifying flow calculation. Under the premise that the combustor outlet temperature is determined, the thermodynamic properties of the gas (specific heat ratio, gas constant) can be accurately calculated through the corresponding relationship between temperature and gas composition, providing basic parameters for the application of the critical flow formula. Based on the critical flow mass flow formula of gas dynamics, the turbine throat area is a fixed geometric parameter, which, together with the specific heat ratio of the gas, the gas constant, and the combustor outlet temperature, determines the maximum flow under critical conditions; at the same time, the compressor pressure ratio directly affects the compressor outlet pressure, combined with the combustor pressure loss coefficient, the coupling relationship between the compressor inlet pressure and the compressor pressure ratio can be substituted into the flow calculation, and finally the functional relationship between the combustor outlet flow and the compressor pressure ratio is derived, forming a critical flow model that restricts the turbine flow to maintain a critical state.

[0060] Thus, first, by locking the critical flow state of the turbine throat, the complexity of the equation caused by the change of turbine flow with multiple parameters in traditional calculation is avoided, and the combustor outlet flow is directly related to the compressor pressure ratio, greatly simplifying the number of equations required for overall performance matching. Second, based on the calculation of the thermodynamic parameters of the gas under the determined combustor outlet temperature, combined with the geometric size of the turbine throat and the pressure parameters of the compressor, it is ensured that all model parameters are derived from the real characteristics of the components, avoiding errors caused by hypothetical parameters and improving the accuracy of flow calculation. Third, the critical flow model plays a role in flow restriction in the overall solution, ensuring that the turbine is always in a stable critical state, effectively solving the problem of easy divergence in traditional nonlinear equation iteration, providing a stable constraint condition for the subsequent fast solution of the overall parameters of the compressor and turbine characteristic equations, meeting the demand for calculation speed and convergence during the iteration of the overall scheme of the gas turbine.

[0061] For example, assume π c is the compressor pressure ratio, and assume m4 is the combustor outlet flow, based on this assumption, the critical flow model can be represented by the following formula: where k is the specific heat ratio of the gas, which can be obtained through the relationship between the gas composition and the specific heat ratio at the combustor outlet temperature, and the preliminary calculation can take 1.33. A is the throat area of the turbine primary guide vane, R is the gas constant of the gas. T3 is the combustor outlet temperature, which has been determined in the preliminary overall scheme design, and T3 is a given value. h 31 is the combustor inlet enthalpy, which can be calculated according to the combustor inlet temperature. β is the combustor pressure loss coefficient. P2 is the compressor inlet pressure.

[0062] At step 102, the multi-model evaluation network is used to inversely solve the compressor pressure ratio as an independent variable to obtain the compressor inlet flow, the compressor pressure ratio, and the combustor outlet flow, and the compressor efficiency is obtained based on the compressor pressure ratio through the compressor characteristic model.

[0063] As an optional embodiment, at step 102, the compressor pressure ratio to be solved is input into the compressor characteristic model to obtain the corresponding compressor inlet flow and initial compressor efficiency; the compressor inlet flow is substituted into the combustor flow and energy constraint model to obtain the combustor outlet flow corresponding to the compressor pressure ratio to be solved; the compressor inlet flow and the combustor outlet flow are substituted into the critical flow model, and the deviation of the combustor outlet flow is used as the iteration basis to adjust the compressor pressure ratio until the combustor outlet flow meets the critical flow condition; after the convergence of the compressor pressure ratio, the final compressor pressure ratio is input into the compressor characteristic model to obtain the corresponding compressor efficiency.

[0064] It can be understood that the core principle of achieving multi-model collaborative solving by iteratively adjusting the compressor pressure ratio is to gradually approach the optimal solution of the whole machine performance matching based on the parameter coupling relationship among the compressor, the combustor, and the turbine, and to take the flow constraint of the critical flow model as the iteration target. From the perspective of parameter association logic, the compressor characteristic model has established a quantitative relationship between the compressor pressure ratio and the inlet flow and efficiency (the pressure ratio is the independent variable, and the flow and efficiency are the dependent variables) through the fitting formula, so the corresponding inlet flow and initial efficiency can be directly obtained by inputting the compressor pressure ratio to be solved. The combustor flow and energy constraint model has established a functional relationship between the compressor inlet flow and the combustor outlet flow based on the conservation of mass and energy, so the theoretical combustor outlet flow under the above inlet flow can be inversely calculated. However, the outlet flow needs to meet the constraint of the turbine critical flow model. That is, the outlet flow needs to meet the critical flow condition with the compressor pressure ratio, so the deviation between the theoretical outlet flow and the target outlet flow calculated by the critical flow model needs to be compared. If the deviation exceeds the allowed range, the compressor pressure ratio needs to be adjusted and the above process needs to be repeated. Specifically, the new compressor pressure ratio obtains a new inlet flow through the compressor characteristic model, the new inlet flow obtains a new outlet flow through the combustor model, and the new outlet flow is compared with the target outlet flow calculated by the critical model until the deviation converges. At this time, the compressor pressure ratio is the optimal value that meets the whole machine component matching, and finally the accurate compressor efficiency can be obtained by substituting the compressor pressure ratio into the compressor characteristic model.

[0065] Thus, by deep cooperation of the compressor characteristic model, the turbine characteristic model, the combustion chamber flow and energy constraint model, and the turbine critical flow model, the parameter mismatch problem caused by isolated solving of each component model in the traditional method is avoided. The deviation of the combustion chamber outlet flow is taken as the iteration basis to convert the abstract whole-machine performance matching problem into a specific flow deviation control problem, the iteration target is clear and the convergence direction is clear, effectively solving the technical problem of ambiguous convergence path and easy divergence in the traditional nonlinear equation iteration solving, greatly improving the solving stability. Finally, the compressor efficiency is obtained based on the converged compressor pressure ratio, and the pressure ratio has met the turbine critical flow and the combustion chamber energy or flow constraint, ensuring that the efficiency value can truly reflect the compressor performance under the whole-machine matching state, avoiding the precision deviation caused by assuming the pressure ratio to obtain the efficiency in the traditional method, providing a component performance basis for subsequent calculation of core parameters such as gas turbine whole-machine power and specific fuel consumption, and meeting the dual needs of fast iteration and high-precision calculation of the gas turbine whole-machine scheme.

[0066] In step 103, a pressure balance equation is established based on the compressor pressure ratio and the combustion chamber pressure loss coefficient, the turbine expansion ratio is obtained by the pressure balance equation, and the turbine efficiency is predicted by inputting the turbine expansion ratio into the turbine characteristic model.

[0067] As an optional embodiment, in step 103, the compressor outlet pressure and the combustion chamber outlet pressure are calculated according to the compressor pressure ratio and the combustion chamber pressure loss coefficient; a turbine pressure balance equation is constructed based on the combustion chamber outlet pressure and a preset turbine outlet pressure, and the turbine expansion ratio is obtained by solving; and the turbine efficiency is predicted by inputting the turbine expansion ratio into the turbine characteristic model through the fitting relationship between the turbine expansion ratio and the efficiency.

[0068] It can be understood that the core principle of solving the turbine expansion ratio and predicting the turbine efficiency is based on the correlation of the pressure balance law of the gas turbine whole machine and the characteristics of the turbine component, realizing the transformation of the pressure parameter to the efficiency parameter. From the pressure balance logic, the compressor pressure ratio is defined as the ratio of the compressor outlet pressure to the inlet pressure, and the compressor outlet pressure can be calculated combined with the known compressor inlet pressure. The combustor has a fixed pressure loss, and the combustor outlet pressure is equal to the compressor outlet pressure multiplied by the corresponding coefficient, which is derived from the physical nature of the combustor pressure loss. That is, the pressure decay caused by the air flow resistance in the combustion process. The core physical definition of the turbine expansion ratio is the ratio of the turbine inlet pressure (i.e. the combustor outlet pressure) to the turbine outlet pressure. Under the premise of preset turbine outlet pressure (usually atmospheric pressure or system given back pressure), the turbine expansion ratio can be solved by calculating the turbine inlet pressure or turbine outlet pressure to construct the pressure balance equation. At the same time, the turbine characteristic model has established the quantitative relationship between the turbine expansion ratio and the efficiency (expansion ratio as independent variable, efficiency as dependent variable) through fitting formula, so that the turbine efficiency under the corresponding working condition can be directly predicted by substituting the solved turbine expansion ratio into the model.

[0069] Therefore, the parameter chain of the compressor pressure ratio, the combustor outlet pressure, and the turbine expansion ratio is connected through the pressure balance equation, and the pressure relationship of the compressor, the combustor, and the turbine is transformed into explicit mathematical calculation, avoiding the empirical assumption of the turbine expansion ratio in the traditional method, ensuring that the expansion ratio can truly reflect the whole machine pressure transmission process, and providing accurate basic parameters for subsequent efficiency calculation. The fitting relationship based on the real characteristics of the turbine predicts the efficiency, replacing the simplified idea of assuming efficiency to calculate performance in the traditional method, making the matching of turbine efficiency and expansion ratio consistent with the actual working characteristics of the turbine, and greatly improving the accuracy of efficiency prediction. In addition, this step combines pressure balance calculation with characteristic model application, the process is clear and the parameter transmission is seamless, which not only ensures the rigor of the calculation logic, but also avoids the complexity of solving caused by the coupling of multiple component parameters, providing reliable turbine performance data for the calculation of subsequent whole machine power, specific fuel consumption and other core performance parameters, further meeting the needs of fast and high-precision calculation of gas turbine whole machine performance.

[0070] Exemplarily, according to the pressure balance, the compressor pressure ratio π c The turbine expansion ratio π T is obtained, i.e. π T = π c (1-β), where β is the combustor pressure loss coefficient. Substituting the obtained turbine expansion ratio π T into the above turbine characteristic model can obtain the turbine efficiency η T .

[0071] At step 104, the working characteristic parameters of each component in the gas turbine are obtained according to the compressor inlet flow, the compressor pressure ratio, the compressor efficiency, the turbine expansion ratio and the turbine efficiency. It can be understood that the working characteristic parameters at least include power, efficiency, specific fuel consumption and pressure and temperature parameters of each section.

[0072] As an optional embodiment, at step 104, firstly, the power consumption and the outlet state parameters of the compressor are calculated based on the compressor inlet flow, the compressor pressure ratio and the compressor efficiency. Then, the turbine output power and the turbine outlet state parameters are calculated based on the combustor outlet state parameters and the turbine expansion ratio. Then, the net power output of the gas turbine is calculated by the difference between the turbine output power and the compressor power consumption. Next, the thermal efficiency and the specific fuel consumption of the gas turbine are calculated based on the fuel flow and the net power output. Finally, the pressure and temperature of multiple sections of the gas turbine are calculated according to the state equations of the compressor, the combustor and the turbine, wherein the pressure and temperature of multiple sections include the pressure and temperature parameters of the compressor outlet, the combustor outlet, the turbine inlet and the turbine outlet.

[0073] The core principle of obtaining the component matching work characteristic parameters is based on the energy transfer law and thermodynamic process equation of each component of the gas turbine. The key characteristic parameters of the whole machine and each section are gradually derived based on the core performance parameters of the compressor and turbine. From the energy balance and thermodynamic calculation logic, the power consumption of the compressor can be calculated by the inlet flow, pressure ratio and efficiency combined with the energy consumption formula of the compression process in gas thermodynamics. The pressure ratio determines the energy demand of the compression process, the efficiency reflects the energy conversion loss, and the inlet flow quantifies the energy consumption scale in unit time. The outlet pressure can be calculated by the compressor inlet state parameters (temperature, pressure) and pressure ratio, and the outlet enthalpy can be calculated by the efficiency and inlet enthalpy to obtain the outlet temperature. The calculation of turbine output power follows the energy release law of expansion process, and the turbine expansion ratio and efficiency are inputted. The expansion ratio determines the energy release potential, and the efficiency reflects the energy conversion efficiency. The outlet state parameters (temperature, pressure) can be derived by the expansion ratio, inlet pressure, inlet enthalpy and efficiency, respectively. The net power of the gas turbine is the turbine output power minus the power consumption of the compressor, which is derived from the nature of the whole machine energy balance. The energy generated by the turbine needs to meet the operation demand of the compressor first, and the remaining part is the effective output. The thermal efficiency is calculated by the ratio of net power to total input heat of fuel (fuel flow and low heat value), and the specific fuel consumption is the ratio of fuel flow to net power. Both of them reflect the conversion efficiency of fuel energy to effective power. The pressure and temperature parameters of each section are derived by the state equation of each component. The outlet pressure of the compressor is obtained by the inlet pressure and pressure ratio, and the outlet temperature is calculated by the inlet temperature and enthalpy rise in the compression process. The outlet pressure of the combustor is obtained by the outlet pressure of the compressor and the pressure loss coefficient, and the outlet temperature is given by the whole machine scheme design. The turbine inlet parameters are the outlet parameters of the combustor, and the outlet pressure is obtained by the inlet pressure and expansion ratio, and the outlet temperature is calculated by the inlet temperature and enthalpy drop in the expansion process, finally forming the thermodynamic parameter system covering the key sections of the whole machine.

[0074] Therefore, these steps achieve systematic conversion from component performance parameters to whole machine characteristic parameters. Through energy balance and thermodynamic equations, the basic parameters of the compressor and turbine, such as efficiency and pressure ratio, are gradually derived into whole machine indexes with engineering application value, such as net power, thermal efficiency, and specific fuel consumption, avoiding the roughness of directly assuming whole machine performance in traditional calculation and ensuring the logical consistency between parameters. Secondly, the recursive calculation of the pressure and temperature parameters of each section provides accurate working condition data for the design and strength checking of the hot end components of the gas turbine (such as the combustion chamber and turbine blades), solving the problem of component design redundancy or insufficient performance caused by large estimation error of section parameters in traditional methods. Thirdly, the entire calculation process is based on the International System of Units and standardized thermodynamic formulas, and all input parameters (such as compressor efficiency and turbine expansion ratio) come from the convergence results of the previous steps, ensuring the calculation accuracy of core indexes such as net power and specific fuel consumption, providing reliable data support for performance evaluation and optimization iteration of the whole machine scheme of the gas turbine, while meeting the demand for traceability and verification of performance parameters in engineering practice, further improving the practicality and reliability of whole machine performance calculation.

[0075] It is worth understanding that after obtaining core parameters such as compressor inlet flow, compressor pressure ratio, compressor efficiency, turbine expansion ratio, and turbine efficiency, the whole machine power, efficiency, specific fuel consumption, and section thermodynamic parameters can be obtained by following the conventional logic of gas turbine thermodynamic calculation. Specifically, first, calculate the power consumption and outlet state parameters of the compressor. The power consumption calculation of the compressor needs to combine the inlet flow, pressure ratio, and efficiency. The inlet flow determines the total amount of compressed air per unit time. The greater the flow, the more air needs to be processed, and the higher the basic power consumption. The pressure ratio reflects the degree of air compression. The greater the pressure ratio, the more energy is required to compress per unit mass of air, further increasing the power demand. The compressor efficiency is used to correct energy loss. That is, the lower the efficiency, the more power is consumed in reality than in the ideal lossless state, and the efficiency needs to be converted from ideal compression power to actual power consumption. In the outlet state parameters of the compressor, the outlet pressure is directly obtained from the inlet pressure (usually atmospheric pressure) and the pressure ratio. The inlet pressure multiplied by the pressure ratio is the outlet pressure. The outlet temperature needs to be calculated first according to the inlet temperature (reference 15℃) and the pressure ratio. Then, combined with the compressor efficiency correction, the lower the efficiency, the higher the actual outlet temperature due to the conversion of energy loss into heat.

[0076] Then, the turbine output power and the outlet state parameters are calculated. The turbine output power calculation is based on the combustion chamber outlet state parameters (outlet pressure, outlet temperature, wherein the outlet temperature is a given value in the design of the whole machine, and the outlet pressure is obtained by deducting the combustion chamber pressure loss from the compressor outlet pressure) and the turbine expansion ratio. The combustion chamber outlet flow can be approximately calculated according to the compressor inlet flow (after deducting the air system bleed air). The greater the flow, the more the amount of fuel gas participating in expansion and doing work per unit time, and the higher the basic value of the output power. The turbine expansion ratio reflects the degree of expansion of the fuel gas. The greater the expansion ratio, the more energy released per unit mass of fuel gas. The turbine efficiency corrects the energy conversion effect. The higher the efficiency, the closer the actual output power is to the power under ideal expansion conditions. In the turbine outlet state parameters, the outlet pressure is obtained by correlating the combustion chamber outlet pressure and the turbine expansion ratio. The outlet pressure is the combustion chamber outlet pressure divided by the expansion ratio. The outlet temperature needs to be calculated according to the combustion chamber outlet temperature and the expansion ratio first, and then corrected according to the turbine efficiency. The higher the efficiency, the lower the actual outlet temperature due to effective energy conversion.

[0077] Subsequently, the net power output of the gas turbine is calculated. When the gas turbine is running, the power generated by the turbine needs to meet the demand of the compressor for compressing air first, so the net power output is the difference between the turbine output power and the power consumption of the compressor. This difference is the effective power that can be output externally by the whole machine. If the turbine output power is less than the power consumption of the compressor, the whole machine cannot run normally and needs to be adjusted and matched again.

[0078] The thermal efficiency and the specific fuel consumption of the gas turbine are calculated. The determination of the fuel flow is a prerequisite, which is based on the combustion chamber energy balance. The effective energy released by the fuel per unit time (fuel flow multiplied by fuel lower calorific value, and then multiplied by combustion efficiency to deduct the combustion loss) needs to be equal to the energy increment of the air in the combustion chamber per unit time (air flow multiplied by the enthalpy difference between the inlet and outlet, which can be converted from the temperature difference between the inlet and outlet). The fuel flow is obtained by inversely deducing the fuel flow through this balance relationship. The thermal efficiency is the proportion of fuel energy converted into effective power. The calculation logic is the ratio of net power to total fuel input energy. The total fuel input energy is the fuel flow multiplied by the fuel lower calorific value. The percentage of net power to this value is the thermal efficiency. The higher the thermal efficiency, the better the energy conversion effect. The specific fuel consumption is the amount of fuel consumed per unit net power. The calculation logic is the ratio of fuel flow to net power. The lower the specific fuel consumption, the better the fuel economy of the whole machine.

[0079] Finally, the pressure and temperature of multiple sections of the gas turbine are calculated. The pressure and temperature at the outlet of the compressor are calculated in the previous stage. The pressure at the outlet of the combustion chamber is the pressure at the outlet of the compressor minus the pressure loss (the pressure at the outlet of the compressor multiplied by (1-combustion chamber pressure loss coefficient)), and the outlet temperature is a given value, and the outlet section of the combustion chamber is the inlet section of the turbine, so the inlet pressure and temperature of the turbine are equal to the outlet pressure and temperature of the combustion chamber. The outlet pressure and temperature of the turbine are calculated in the turbine parameter calculation stage. Through this recursive logic, the pressure and temperature parameters of the three key sections of the compressor outlet, the combustion chamber outlet (turbine inlet), and the turbine outlet can be completely obtained, which provides core thermodynamic data for component design and working condition evaluation of the gas turbine.

[0080] In the embodiments of the application, the coupling relationship between the components of the gas turbine is uniformly modeled and adaptively inverted by constructing a multi-model evaluation network, which greatly improves the accuracy, real-time performance and stability of the performance evaluation of the gas turbine, simplifies the evaluation process, and ensures the efficient and safe operation of the gas turbine.

[0081] In another embodiment of the application, a gas turbine performance evaluation device is also provided. Referring to Figure 3 As described above, the device is applied to a gas turbine, and the device comprises the following units:

[0082] The construction unit is configured to establish a compressor characteristic model, a turbine characteristic model, a combustion chamber flow and energy constraint model, and a critical flow model based on the characteristic data of the compressor and the turbine at the design speed, and jointly construct a multi-model evaluation network for describing the coupling relationship between the compressor, the combustion chamber and the turbine;

[0083] The evaluation unit is configured to perform inversion and solving by taking the compressor pressure ratio as the independent variable through the multi-model evaluation network to obtain the compressor inlet flow, the compressor pressure ratio and the combustion chamber outlet flow, and obtain the compressor efficiency based on the compressor pressure ratio through the compressor characteristic model; a pressure balance equation is established based on the compressor pressure ratio and the combustion chamber pressure loss coefficient, and the turbine expansion ratio is obtained by the pressure balance equation, and the turbine efficiency is predicted by inputting the turbine expansion ratio into the turbine characteristic model; the working characteristic parameters of each component in the gas turbine are obtained according to the compressor inlet flow, the compressor pressure ratio, the compressor efficiency, the turbine expansion ratio and the turbine efficiency, and the working characteristic parameters at least include power, efficiency, specific fuel consumption and pressure and temperature parameters of each section.

[0084] Further optionally, the constructing unit is configured to: obtain compressor characteristic data of the compressor at the design rotating speed, take compressor pressure ratio in the compressor characteristic data as input, and combine a fitting formula to adaptively predict compressor inlet flow rate and compressor efficiency, thereby constructing a compressor characteristic model; obtain turbine characteristic data of the turbine at the design rotating speed, take turbine expansion ratio in the turbine characteristic data as input, and combine a fitting formula to predict turbine efficiency, thereby constructing a turbine characteristic model; obtain compressor inlet flow rate, air system bleed air ratio, combustion efficiency, fuel low heat value, combustion chamber inlet enthalpy value, and combustion chamber outlet enthalpy value, and construct a correlation equation between the compressor inlet flow rate and the combustion chamber outlet flow rate through flow conservation and energy conservation, thereby generating a combustion chamber flow and energy constraint model; and under the condition that the combustion chamber outlet temperature is determined, take turbine first-stage guide vane throat area, gas constant, specific heat ratio of the gas, and compressor inlet pressure as input, and construct a functional relationship between the combustion chamber outlet flow rate and the compressor pressure ratio based on the physical characteristics of the turbine throat keeping in a critical flow state, thereby forming a critical flow model.

[0085] Further optionally, the constructing unit is configured to: preprocess the characteristic data of the compressor at the design rotating speed, wherein the preprocessing includes outlier elimination and smoothing processing; based on the preprocessed compressor characteristic points, perform polynomial fitting or interpolation fitting on the corresponding relationship between the compressor pressure ratio and the compressor inlet flow rate to obtain a continuous pressure ratio flow function; based on the preprocessed compressor characteristic points, perform fitting on the corresponding relationship between the compressor pressure ratio and the compressor efficiency using an independent fitting model to obtain a continuous pressure ratio efficiency function; and combine the pressure ratio flow function and the pressure ratio efficiency function to form the compressor characteristic model, which is used to adaptively predict the compressor inlet flow rate and the compressor efficiency under the condition that the compressor pressure ratio is given.

[0086] Further optionally, the constructing unit is configured to: preprocess the turbine expansion ratio efficiency characteristic points of the turbine at the design rotating speed, remove abnormal points, and smooth the characteristic curve; based on the preprocessed turbine characteristic points, establish a continuous functional relationship between the turbine expansion ratio and the turbine efficiency through an interpolation method or a polynomial fitting method; and construct the established continuous functional relationship as the turbine characteristic model, which is used to predict the turbine efficiency under the condition that the turbine expansion ratio is given.

[0087] Further optionally, the constructing unit obtains the compressor inlet flow, the air system bleed air ratio, the combustion efficiency, the fuel low heat value, the combustion chamber inlet enthalpy value and the outlet enthalpy value, and constructs a correlation equation between the compressor inlet flow and the combustion chamber outlet flow through the flow conservation and energy conservation relationship to generate a combustion chamber flow and energy constraint model, which is configured to: correct the air flow entering the combustion chamber from the compressor outlet based on the air system bleed air ratio to obtain the actual air flow participating in combustion; convert the fuel input into the effective energy increase in the combustion chamber based on the combustion efficiency and the fuel low heat value; establish a combustion chamber energy conservation equation according to the relationship between the combustion chamber inlet enthalpy value and the outlet enthalpy value to obtain the correlation between the combustion product enthalpy value and the air flow; combine the flow conservation relationship that the combustion chamber inlet flow is equal to the combustion chamber outlet flow, and convert the energy conservation equation into a functional relationship between the compressor inlet flow and the combustion chamber outlet flow through the correlation between the combustion product enthalpy value and the air flow and the effective energy increase, to form the combustion chamber flow and energy constraint model.

[0088] Further optionally, the constructing unit, under the condition that the combustion chamber outlet temperature is determined, takes the turbine first-stage guide vane throat area, the gas constant, the gas specific heat ratio and the compressor inlet pressure as inputs, and constructs a functional relationship between the combustion chamber outlet flow and the compressor pressure ratio based on the physical characteristics that the turbine throat maintains a critical flow state, to form a critical flow model, which is configured to: set the flow velocity of the turbine first-stage guide vane throat to the speed of sound to determine that the turbine throat is in a critical flow condition; calculate the gas specific heat ratio and the gas constant under the critical state according to the combustion chamber outlet temperature; calculate the maximum flow of the combustion chamber outlet under the critical state based on the critical flow mass flow formula, taking the gas specific heat ratio, the gas constant and the turbine throat area as inputs; couple the changes of the compressor inlet pressure and the compressor pressure ratio into the critical mass flow calculation to construct the functional relationship between the combustion chamber outlet flow and the compressor pressure ratio; construct the functional relationship between the combustion chamber outlet flow and the compressor pressure ratio into the turbine critical flow model, which is used to constrain the turbine flow to maintain in the critical state in the whole machine solving process.

[0089] Further optionally, the evaluation unit, by the multi-model evaluation network, inversely solves the compressor pressure ratio to obtain the compressor inlet flow, the compressor pressure ratio and the combustor outlet flow, and obtains the compressor efficiency based on the compressor pressure ratio through the compressor characteristic model, is configured to: input the to-be-solved compressor pressure ratio into the compressor characteristic model to obtain the corresponding compressor inlet flow and initial compressor efficiency; substitute the compressor inlet flow into the combustor flow and energy constraint model to obtain the combustor outlet flow corresponding to the to-be-solved compressor pressure ratio; substitute the compressor inlet flow and the combustor outlet flow into the critical flow model, and take the deviation of the combustor outlet flow as the iteration basis to adjust the compressor pressure ratio through iteration until the combustor outlet flow meets the critical flow condition; after the convergence of the compressor pressure ratio, input the final compressor pressure ratio into the compressor characteristic model to obtain the corresponding compressor efficiency.

[0090] Further optionally, the evaluation unit, based on the compressor pressure ratio and the combustor pressure loss coefficient, establishes a pressure balance equation, obtains the turbine expansion ratio by the pressure balance equation, and inputs the turbine expansion ratio into the turbine characteristic model to predict the turbine efficiency, and is configured to: calculate the compressor outlet pressure and the combustor outlet pressure according to the compressor pressure ratio and the combustor pressure loss coefficient; based on the combustor outlet pressure and the preset turbine outlet pressure, construct a turbine pressure balance equation to obtain the turbine expansion ratio; input the turbine expansion ratio into the turbine characteristic model to predict the turbine efficiency through the fitting relationship between the turbine expansion ratio and the efficiency.

[0091] Further optionally, the evaluation unit, according to the compressor inlet flow, the compressor pressure ratio, the compressor efficiency, the turbine expansion ratio and the turbine efficiency, obtains the working characteristic parameters of each component matched in the gas turbine, and is configured to: calculate the power consumption and outlet state parameters of the compressor based on the compressor inlet flow, the compressor pressure ratio and the compressor efficiency; calculate the turbine output power and turbine outlet state parameters based on the combustor outlet state parameters and the turbine expansion ratio; calculate the net power output of the gas turbine through the difference between the turbine output power and the compressor power consumption; calculate the thermal efficiency and specific fuel consumption of the gas turbine based on the fuel flow and the net power output; calculate the pressure and temperature of multiple cross sections of the gas turbine according to the state equations of the compressor, the combustor and the turbine, wherein the pressure and temperature of multiple cross sections include the pressure and temperature parameters of the compressor outlet, the combustor outlet, the turbine inlet and the turbine outlet.

[0092] The apparatus can implement various steps in the above method embodiments, which will not be described here.

[0093] In the embodiment of the present application, the gas turbine performance evaluation device is adopted, the coupling relationship between the components of the gas turbine can be uniformly modeled and adaptively inverted by constructing a multi-model evaluation network, the accuracy, real-time performance and stability of the gas turbine performance evaluation are greatly improved, the evaluation process is simplified, and the efficient and safe operation of the gas turbine is ensured.

[0094] The embodiment of the present application provides a gas turbine, the gas turbine is provided with a data monitoring system, the data monitoring system comprises at least one processor, a memory and an input and output unit. Wherein, the memory is used for storing a computer program, and the processor is used for calling the computer program stored in the memory to execute the gas turbine performance evaluation method introduced in the above method embodiment. For example, the data monitoring system can be realized as an electronic device. Please refer to Figure 4 , Figure 4 The embodiment of the electronic device provided by the embodiment of the present application is shown. As shown in Figure 4 The embodiment of the present application provides an electronic device 500, which comprises a memory 510, a processor 520 and a software program 511 stored in the memory 510 and executable on the processor 520, and the processor 520 executes the software program 511 to realize each step in the above embodiment.

[0095] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can adopt a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can adopt a computer program product embodied on one or more computer usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer usable program code. Although the preferred embodiments of the present application have been described, those skilled in the art can make further changes and modifications to the embodiments once they know the basic inventive concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0096] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these modifications and variations.

Claims

1. A method for evaluating the performance of a gas turbine, characterized in that, The method includes: Based on the characteristic data of the compressor and turbine at the design speed, a compressor characteristic model, a turbine characteristic model, a combustion chamber flow and energy constraint model, and a critical flow model are established, and a multi-model evaluation network is jointly constructed. The multi-model evaluation network is used to describe the coupling relationship between the compressor, combustion chamber and turbine. The compressor inlet flow rate, compressor pressure ratio, and combustion chamber outlet flow rate are obtained by inversion solution using the multi-model evaluation network with compressor pressure ratio as independent variable. The compressor efficiency is obtained by compressor characteristic model based on compressor pressure ratio. A pressure balance equation is established based on the compressor pressure ratio and the combustion chamber pressure loss coefficient. The turbine expansion ratio is obtained from the pressure balance equation, and the turbine expansion ratio is input into the turbine characteristic model to predict the turbine efficiency. Based on the compressor inlet flow rate, compressor pressure ratio, compressor efficiency, turbine expansion ratio, and turbine efficiency, the matching operating characteristic parameters of each component in the gas turbine are obtained. The operating characteristic parameters include at least power, efficiency, fuel consumption rate, and pressure and temperature parameters of each section.

2. The gas turbine performance evaluation method according to claim 1, characterized in that, The establishment of compressor characteristic models, turbine characteristic models, combustion chamber flow and energy constraint models, and critical flow models based on the characteristic data of the compressor and turbine at design speeds includes: Compressor characteristic data at the design speed is obtained. The compressor pressure ratio in the compressor characteristic data is used as input. The compressor inlet flow rate and compressor efficiency are obtained by adaptive prediction using the fitting formula, and a compressor characteristic model is constructed. Turbine characteristic data at the design speed is obtained. The turbine expansion ratio in the turbine characteristic data is used as input. The turbine efficiency is predicted by combining the fitting formula, and a turbine characteristic model is constructed. The compressor inlet flow rate, air system bleed ratio, combustion efficiency, fuel lower heating value, combustion chamber inlet enthalpy and outlet enthalpy are obtained. By constructing the correlation equation between the compressor inlet flow rate and the combustion chamber outlet flow rate through the flow conservation and energy conservation relationship, a combustion chamber flow and energy constraint model is generated. Under the condition of a fixed combustion chamber outlet temperature, the throat area of ​​the turbine first-stage guide vane, the gas constant of the combustion gas, the specific heat ratio of the combustion gas, and the compressor inlet pressure are used as inputs. Based on the physical characteristics of the turbine throat maintaining a critical flow state, a functional relationship between the combustion chamber outlet flow rate and the compressor pressure ratio is constructed, forming a critical flow model.

3. The gas turbine performance evaluation method according to claim 2, characterized in that, The compressor characteristic model is constructed by using the compressor pressure ratio from the compressor characteristic data as input, combining it with a fitting formula to adaptively predict the compressor inlet flow rate and compressor efficiency, and then constructing the compressor characteristic model, including: The characteristic data of the compressor at the design speed are preprocessed, including outlier removal and smoothing. Based on the pre-processed compressor characteristic points, polynomial fitting or interpolation fitting is performed on the correspondence between compressor pressure ratio and compressor inlet flow rate to obtain a continuous pressure ratio-flow rate function. Based on the pre-processed compressor characteristic points, an independent fitting model is used to fit the correspondence between compressor pressure ratio and compressor efficiency to obtain a continuous pressure ratio efficiency function. The pressure ratio flow rate function and the pressure ratio efficiency function are combined to form a compressor characteristic model.

4. The gas turbine performance evaluation method according to claim 2, characterized in that, The process of obtaining turbine characteristic data at the design speed, using the turbine expansion ratio from the turbine characteristic data as input, and combining it with a fitting formula to predict the turbine efficiency, thereby constructing a turbine characteristic model, includes: The expansion ratio efficiency characteristic points of the turbine at the design speed are preprocessed to remove outliers and smooth the characteristic curves. Based on the preprocessed turbine characteristic points, a continuous functional relationship between turbine expansion ratio and turbine efficiency is established by interpolation or polynomial fitting methods. The obtained continuous function relationship is used to construct a turbine characteristic model.

5. The gas turbine performance evaluation method according to claim 2, characterized in that, The process involves acquiring the compressor inlet flow rate, air system bleed ratio, combustion efficiency, fuel lower heating value, combustion chamber inlet enthalpy, and combustion chamber outlet enthalpy. By constructing a correlation equation between the compressor inlet flow rate and the combustion chamber outlet flow rate through the flow conservation and energy conservation relationships, a combustion chamber flow and energy constraint model is generated, including: The actual air flow rate participating in combustion is obtained by correcting the air flow rate from the compressor outlet to the combustion chamber based on the air system bleed ratio. Based on combustion efficiency and the lower heating value of fuel, the fuel input is converted into an effective increase in energy in the combustion chamber; Based on the relationship between the inlet and outlet enthalpy of the combustion chamber, an energy conservation equation for the combustion chamber is established, and the correlation between the enthalpy of combustion products and air flow rate is obtained. By combining the flow conservation relationship that the inlet flow rate and the outlet flow rate of the combustion chamber are equal, and by using the correlation between the enthalpy of combustion products and the air flow rate, as well as the increase in effective energy, the energy conservation equation is transformed into a functional relationship between the compressor inlet flow rate and the outlet flow rate of the combustion chamber, thus forming a combustion chamber flow and energy constraint model.

6. The gas turbine performance evaluation method according to claim 2, characterized in that, Under the condition of a fixed combustion chamber outlet temperature, using the turbine first-stage guide vane throat area, gas constant, gas specific heat ratio, and compressor inlet pressure as inputs, and based on the physical characteristics of maintaining a critical flow state at the turbine throat, a functional relationship between the combustion chamber outlet flow rate and the compressor pressure ratio is constructed to form a critical flow model, including: The flow velocity at the throat of the first-stage guide vane of the turbine is set to the speed of sound in order to determine that the turbine throat is under critical flow conditions. Calculate the specific heat ratio and gas constant of the gas under critical conditions based on the combustion chamber outlet temperature; Based on the critical flow mass flow formula, the maximum flow rate at the combustion chamber outlet under critical conditions is calculated using the specific heat ratio of the fuel gas, the fuel gas constant, and the turbine throat area as inputs. The changes in compressor inlet pressure and compressor pressure ratio are coupled into the calculation of critical mass flow rate to construct a functional relationship between combustion chamber outlet flow rate and compressor pressure ratio; A functional relationship between the combustion chamber outlet flow rate and the compressor pressure ratio is constructed as a turbine critical flow model to constrain the turbine flow rate to maintain a critical state during the overall engine solution process.

7. The gas turbine performance evaluation method according to claim 1, characterized in that, The process involves using the multi-model evaluation network, with the compressor pressure ratio as the independent variable, to perform inversion and solve for the compressor inlet flow rate, compressor pressure ratio, and combustion chamber outlet flow rate. Based on the compressor pressure ratio, the compressor efficiency is then obtained through a compressor characteristic model. This includes: Input the compressor pressure ratio to be solved into the compressor characteristic model to obtain the corresponding compressor inlet flow rate and initial compressor efficiency; Substitute the compressor inlet flow rate into the combustion chamber flow rate and energy constraint model to obtain the combustion chamber outlet flow rate corresponding to the compressor pressure ratio to be solved; Substitute the compressor inlet flow rate and the combustion chamber outlet flow rate into the critical flow model, and use the deviation of the combustion chamber outlet flow rate as the basis for iteration. Adjust the compressor pressure ratio iteratively until the combustion chamber outlet flow rate meets the critical flow condition. After the compressor pressure ratio converges, the final compressor pressure ratio is input into the compressor characteristic model to obtain the corresponding compressor efficiency.

8. The gas turbine performance evaluation method according to claim 1, characterized in that, The process of establishing a pressure balance equation based on the compressor pressure ratio and the combustion chamber pressure loss coefficient, obtaining the turbine expansion ratio using the pressure balance equation, and inputting the turbine expansion ratio into the turbine characteristic model to predict the turbine efficiency includes: Calculate the compressor outlet pressure and the combustion chamber outlet pressure based on the compressor pressure ratio and the combustion chamber pressure loss coefficient; Based on the combustion chamber outlet pressure and the preset turbine outlet pressure, a turbine pressure balance equation is constructed, and the turbine expansion ratio is obtained by solving it. The turbine expansion ratio is input into the turbine characteristic model, and the turbine efficiency is predicted by fitting the relationship between the turbine expansion ratio and efficiency.

9. A gas turbine performance evaluation device, characterized in that, The device is applied to a gas turbine, and the device includes the following units, wherein... The building unit is configured to establish compressor characteristic model, turbine characteristic model, combustion chamber flow and energy constraint model and critical flow model based on the characteristic data of compressor and turbine at design speed, and jointly build a multi-model evaluation network, which is used to describe the coupling relationship between compressor, combustion chamber and turbine. The evaluation unit is configured to perform inversion solving using the compressor pressure ratio as the independent variable through the multi-model evaluation network to obtain the compressor inlet flow rate, compressor pressure ratio, and combustion chamber outlet flow rate. Based on the compressor pressure ratio, the compressor efficiency is obtained through the compressor characteristic model. A pressure balance equation is established based on the compressor pressure ratio and combustion chamber pressure loss coefficient. The turbine expansion ratio is obtained using the pressure balance equation, and the turbine expansion ratio is input into the turbine characteristic model to predict the turbine efficiency. Based on the compressor inlet flow rate, compressor pressure ratio, compressor efficiency, turbine expansion ratio, and turbine efficiency, the matching operating characteristic parameters of each component in the gas turbine are obtained. The operating characteristic parameters include at least power, efficiency, fuel consumption rate, and pressure and temperature parameters of each section.

10. A gas turbine, characterized in that, The gas turbine is equipped with a data monitoring system, which includes: a memory for storing computer software programs; and a processor for reading and executing the computer software programs, thereby implementing the gas turbine performance evaluation method according to any one of claims 1-8.

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