A method and system for steady-state optimization of gas turbines

Abstract

This invention discloses a steady-state optimization method and system for gas turbines, relating to the field of gas turbine simulation technology. The method includes: randomly generating correction coefficients for various components of the gas turbine within a set range; selecting the optimal correction coefficients based on a differential evolution algorithm; calculating the degradation factor of each component of the gas turbine based on the optimal and original correction coefficients; and determining whether to perform maintenance on the gas turbine based on the degradation factor. This invention uses a differential evolution algorithm to determine the optimal correction coefficients and employs the Newton-Raphson algorithm to solve the objective function, thereby improving calculation speed and accuracy, enabling timely acquisition of the gas turbine degradation factor, and facilitating timely maintenance of the gas turbine, thus improving production safety and reducing operation and maintenance costs.

Description

Technical Field

[0001] This invention relates to the field of gas turbine simulation technology, and in particular to a gas turbine steady-state optimization method and system. Background Technology

[0002] During actual operation of a gas turbine, its components will degrade to varying degrees over time. At this point, the gas turbine simulation model will deviate significantly from the actual physical model. If the gas turbine degradation factor can be obtained in a timely manner, the gas turbine can be repaired promptly, thereby improving production safety and reducing operation and maintenance costs. Summary of the Invention

[0003] Based on this, the purpose of this invention is to provide a gas turbine steady-state optimization method and system to obtain the gas turbine degradation factor in a timely manner, thereby enabling timely maintenance of the gas turbine.

[0004] To achieve the above objectives, the present invention provides the following solution:

[0005] A gas turbine steady-state optimization method includes:

[0006] Correction coefficients for each component of the gas turbine are randomly generated within a set range; the components of the gas turbine include a high-pressure compressor, a high-pressure turbine, and a power turbine; the correction coefficients include a flow correction coefficient and an efficiency correction coefficient.

[0007] The optimal correction coefficients are obtained by filtering the correction coefficients using the differential evolution algorithm.

[0008] The degradation factor of each component of the gas turbine is calculated based on the optimal correction factor and the original correction factor;

[0009] The need for gas turbine maintenance is determined based on the aforementioned degradation factor.

[0010] To achieve the above objectives, the present invention also provides the following solution:

[0011] A gas turbine steady-state optimization system includes:

[0012] The correction coefficient random generation module is used to randomly generate correction coefficients for various components of the gas turbine within a set range; the gas turbine components include a high-pressure compressor, a high-pressure turbine, and a power turbine; the correction coefficients include a flow correction coefficient and an efficiency correction coefficient.

[0013] The optimal correction coefficient determination module is used to filter the correction coefficients based on the differential evolution algorithm to obtain the optimal correction coefficients;

[0014] The degradation factor calculation module is used to calculate the degradation factor of each component of the gas turbine based on the optimal correction coefficient and the original correction coefficient.

[0015] The maintenance determination module is used to determine whether the gas turbine needs maintenance based on the degradation factor.

[0016] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0017] This invention uses the differential evolution algorithm to determine the optimal correction coefficient and the Newton-Raphson algorithm to solve the objective function. This can improve the calculation speed and accuracy, obtain the gas turbine degradation factor in a timely manner, and carry out timely maintenance of the gas turbine, thereby improving production safety and reducing operation and maintenance costs. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart of the gas turbine steady-state optimization method provided by the present invention;

[0020] Figure 2 Flowchart for determining the optimal correction coefficient;

[0021] Figure 3 This is a schematic diagram illustrating how actual monitoring data is obtained.

[0022] Figure 4 Flowchart for solving the Newton-Rapson problem for a gas turbine. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] The purpose of this invention is to provide a gas turbine steady-state optimization method and system to obtain the gas turbine degradation factor in a timely manner, thereby enabling timely maintenance of the gas turbine.

[0025] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0026] Example 1

[0027] like Figure 1 As shown in the figure, this embodiment provides a gas turbine steady-state optimization method, which includes the following steps:

[0028] S1: Randomly generate correction coefficients for each component of the gas turbine within a set range; the components of the gas turbine include the high-pressure compressor, the high-pressure turbine, and the power turbine; the correction coefficients include flow correction coefficients and efficiency correction coefficients.

[0029] The range and population size of the flow and efficiency correction coefficients for the high-pressure compressor, high-pressure turbine, and power turbine components of the gas turbine are given by human intervention. Within this range, the above correction coefficients are randomly generated and used as the population for initialization.

[0030] S2: The correction coefficients are selected based on the differential evolution algorithm to obtain the optimal correction coefficients.

[0031] S3: Calculate the degradation factor of each component of the gas turbine based on the optimal correction factor and the original correction factor. The calculation formula is as follows:

[0032]

[0033] Where factor is the degradation factor of each component of the gas turbine, cf optimization For the optimal correction coefficient, cf origin This is the original correction factor.

[0034] S4: Determine whether the gas turbine needs maintenance based on the degradation factor.

[0035] When the calculated degradation factor is greater than or equal to 30%, the gas turbine should be repaired.

[0036] Furthermore, such as Figure 2 As shown, step S2 specifically includes:

[0037] S21: Initialize the population; individuals in the population are correction coefficients.

[0038] S22: Perform mutation and hybridization operations on individuals.

[0039] Mutation operation: For each individual, if the mutation operator is F, then the following mutation formula holds:

[0040] v(i)=x(r0)+F*(x(r1)-x(r2)) (2)

[0041] In the formula, v(i) represents the mutated individual, i represents the mutated individual number, x represents the original population, and r0, r1, and r2 represent three random numbers of the original population. If the mutated individual exceeds the population range or is the same as the previous mutated individual, it will mutate again.

[0042] Crossover operation: If the crossover operator is CR, then the crossover of individuals in the population is calculated using the following formula:

[0043]

[0044] In the formula, rand is a random number, u(i) represents the i-th hybrid individual, v(i) represents the i-th mutated individual, and x(i) represents the i-th original individual.

[0045] S23: Calculate the fitness of an individual. Specifically, this includes:

[0046] S231: Obtain actual monitoring parameters of the gas turbine. Actual monitoring parameters of the gas turbine include: gas turbine inlet temperature, inlet pressure, fuel flow rate, power shaft speed, load, air flow rate, high-pressure shaft speed, and outlet temperature. The methods for obtaining each monitoring parameter are as follows: Figure 3 As shown

[0047] S231: Use the inlet temperature, inlet pressure, fuel flow rate, power shaft speed, and load from the actual monitored quantities as boundary conditions.

[0048] S231: Using the pressure ratio of the high-pressure compressor of the gas turbine, the expansion ratio of the high-pressure turbine and the power turbine, and the high-pressure shaft speed as initial values, the Newton-Raphson iteration method is used to solve for the steady-state value of the gas turbine.

[0049] The residual equations are constructed as follows:

[0050]

[0051]

[0052]

[0053]

[0054] Formulas (4) and (5) are the gas turbine flow balance residual equations, and formulas (6) and (7) are the gas turbine power balance residual equations. Here, e1, e2, e3, and e4 represent the high-pressure flow residual equation, low-pressure flow residual equation, high-pressure power residual equation, and power residual equation, respectively. The subscripts hpc represent the high-pressure compressor, hpt represent the high-pressure turbine, pt represent the power turbine, f represent fuel oil, w represent flow rate, Power represent power, and Load represent load.

[0055] Press during each iteration Figure 4 The equations for each engine component are calculated sequentially to obtain the gas flow rate and power of the high-pressure compressor, high-pressure turbine, and power turbine. These values ​​are then substituted into the selected residual equations to... Figure 4The given initial values ​​and corresponding variables are used to complete the steady-state calculation of the gas turbine according to the Newton-Raphson iteration method until the residuals are all less than 0.1%.

[0056] The formula for calculating the outlet pressure of a high-pressure compressor is:

[0057] P2 = P1 * π C (8)

[0058] In the formula, P1 and P2 represent the inlet and outlet pressures of the high-pressure compressor, respectively, and π C This refers to the pressure ratio of the high-pressure compressor.

[0059] The formula for calculating the outlet pressure of a high-pressure turbine is:

[0060] P4 = P3 / π T (9)

[0061] In the formula, P3 and P4 represent the inlet and outlet pressures of the high-pressure turbine, respectively, and π T This refers to the expansion ratio of the high-pressure turbine.

[0062] The formula for calculating the outlet pressure of the power turbine is:

[0063] P5 = P4 / π P (10)

[0064] In the formula, P4 and P5 represent the inlet and outlet pressures of the high-pressure compressor, respectively, and π P This refers to the expansion ratio of the power turbine.

[0065] In addition, the relevant calculation formulas for the component characteristics of high-pressure compressors, high-pressure turbines, and power turbines are as follows:

[0066]

[0067] In the formula, W and η represent the flow rate and efficiency of the component, and n and π represent the rotational speed and pressure ratio of the component, respectively. Map1 and Map2 are component characteristic diagram functions. This invention optimizes existing component characteristic diagrams, therefore these functions are known.

[0068] The thermodynamic calculation formula for a high-pressure compressor is as follows:

[0069] h in =f1(T in (12)

[0070] S out,s =S in +R g log(π) (13)

[0071] T out,s =f2(S out,s (14)

[0072] h out,s =f1(T out,s (15)

[0073] h out =(h out,s -h in ) / η+h in (16)

[0074] T out =f3(h out (17)

[0075] In the formula, h, T, and S represent enthalpy, temperature, and entropy, respectively. The subscript in represents the inlet, out represents the outlet, and other subscripts only serve to distinguish the contents. The functions f1, f2, and f3 are the enthalpy-temperature function, temperature-entropy function, and temperature-enthalpy function of air, respectively.

[0076] The power calculation formula for a high-pressure compressor is as follows:

[0077] Power = W(h) out -h in (18)

[0078] The thermodynamic calculation formulas for high-pressure turbines and power turbines are as follows:

[0079] H in =F1(t in ,yqb) (19)

[0080] s out,s =S in -R g log(π) (20)

[0081] t out,s =F2(s out,s ,yqb) (21)

[0082] H out,s =F1(t out,s ,yqb) (22)

[0083] H out =(H out,s -H in )*η+H in (twenty three)

[0084] t out =F3(H out ,yqb) (24)

[0085] In the formula, H, t, and s represent enthalpy, temperature, and entropy, respectively. The subscript in represents the inlet, out represents the outlet, and other subscripts only serve to distinguish the contents. yqb represents the turbine air-fuel ratio, and functions F1, F2, and F3 are the enthalpy-temperature function, temperature-entropy function, and temperature-enthalpy function of the gas, respectively.

[0086] The power calculation formulas for high-pressure turbines and power turbines are as follows:

[0087] Power = W(H) in -H out (25)

[0088] The relevant calculation formulas for combustion chamber components are as follows:

[0089] P bout =σ*P bin (26)

[0090] k(W bin h bin +W f H u η-W bout h bout ) = h bout (W bin +W f -W bout (27)

[0091]

[0092] h bin =f1(T bin (29)

[0093] h bout =F1(T bout ,yqb b (30)

[0094] In the formula, P, W, h, and T represent pressure, flow rate, enthalpy, and temperature, respectively. The subscripts bin, bout, and f represent the inlet, outlet, and fuel oil, respectively. Hu represents the lower heating value of the fuel oil, η represents the combustion chamber efficiency, and σ represents the combustion chamber pressure loss coefficient, all of which are known. The functions f1 and F1 are the same as the enthalpy-temperature functions of air in the high-pressure compressor and the enthalpy-temperature functions of gas in the high-pressure turbine, respectively. b This represents the air-fuel ratio in the combustion chamber. Furthermore, k represents the combustion chamber adiabatic coefficient, which can be calculated from the combustion chamber temperature using the following formula:

[0095]

[0096] In the formula, T represents the combustion chamber temperature, and the function f is the temperature-specific heat capacity function.

[0097] For the combustion chamber, the combustion chamber temperature needs to be solved iteratively using the bisection method until formula (27) is satisfied.

[0098] S231: Calculate the error between the actual monitored value and the steady-state value, and select the maximum error as the fitness.

[0099] The actual monitored values ​​and the corresponding steady-state values ​​calculated by the gas turbine were sequentially compared to calculate the error. The fitness was taken as the maximum value of all errors. The error calculation formula is as follows:

[0100]

[0101] In the formula, xr eal and x simulation These represent the actual monitored values ​​and the calculated steady-state values ​​of the gas turbine, respectively, with e representing the error.

[0102] The algorithm sequentially checks whether the calculated fitness is less than a given threshold (3% to 5%, where a lower threshold indicates a higher standard of optimization, and can be manually adjusted as needed). If it is less than the threshold, the algorithm exits and outputs the optimal correction coefficients for each component; otherwise, it proceeds to the next step.

[0103] Selection operation: Compare the target value corresponding to the current individual with that of the original individual, select the one with the smallest value, generate a new population, and return to step S21.

[0104] S24: Determine the optimal individual based on fitness; the optimal individual is the one with the optimal correction coefficient.

[0105] This invention employs a differential evolution algorithm to determine the optimal correction coefficients and a Newton-Raphson algorithm to solve the objective function. Compared to traditional genetic algorithms, the differential evolution algorithm accelerates convergence and also offers the advantage of global applicability. The Newton-Raphson algorithm for calculating the objective function speeds up the solution of a single gas turbine steady-state model. This method has a large search range, good global applicability, fast single-cycle calculation speed, high accuracy, and versatility, making it valuable for optimizing gas turbine simulation models.

[0106] Example 2

[0107] In order to implement the method corresponding to Embodiment 1 above and achieve the corresponding functions and technical effects, a gas turbine steady-state optimization system is provided below.

[0108] The system includes:

[0109] The correction coefficient random generation module is used to randomly generate correction coefficients for various components of the gas turbine within a set range; the components of the gas turbine include the high-pressure compressor, the high-pressure turbine, and the power turbine; the correction coefficients include flow correction coefficients and efficiency correction coefficients.

[0110] The optimal correction coefficient determination module is used to filter correction coefficients based on the differential evolution algorithm to obtain the optimal correction coefficient.

[0111] The degradation factor calculation module is used to calculate the degradation factor of each component of the gas turbine based on the optimal correction factor and the original correction factor.

[0112] The maintenance determination module is used to determine whether the gas turbine needs maintenance based on the degradation factor.

[0113] Furthermore, the optimal correction coefficient determination module specifically includes:

[0114] The initialization submodule is used to initialize the population; the individuals in the population are correction coefficients.

[0115] The mutation and hybridization submodule is used to perform mutation and hybridization operations on individuals.

[0116] The fitness calculation submodule is used to calculate the fitness of an individual.

[0117] The optimal correction coefficient determination submodule is used to determine the optimal individual based on fitness; the optimal individual is determined by the optimal correction coefficient.

[0118] Furthermore, the fitness calculation submodule specifically includes:

[0119] The actual monitoring quantity acquisition unit is used to acquire the actual monitoring quantity of the gas turbine.

[0120] The boundary condition determination unit is used to take the inlet temperature, inlet pressure, fuel flow rate, power shaft speed and load from the actual monitored quantities as boundary conditions.

[0121] The solution unit is used to take the pressure ratio of the high-pressure compressor of the gas turbine, the expansion ratio of the high-pressure turbine and the power turbine, and the high-pressure shaft speed as initial values, and use the Newton-Raphson iteration method to solve for the steady-state values ​​of the gas turbine.

[0122] The fitness calculation unit is used to calculate the error between the actual monitored value and the steady-state value, and select the maximum error as the fitness.

[0123] Furthermore, the solution element specifically includes...

[0124] The residual equation construction sub-unit is used to construct the residual equations of the gas turbine; the residual equations include the flow balance residual equation and the power balance residual equation.

[0125] The flow and power calculation subunit is used to calculate the flow and power of each component of the gas turbine by taking the pressure ratio of the high-pressure compressor, the expansion ratio of the high-pressure turbine and the power turbine, and the high-pressure shaft speed as initial values.

[0126] The solution sub-element is used to input the flow rate and power of each component of the gas turbine into the residual equation, and the Newton-Raphson iteration method is used to solve it to obtain the steady-state value of the gas turbine.

[0127] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0128] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A steady-state optimization method for a gas turbine, characterized in that, include: Correction coefficients for each component of the gas turbine are randomly generated within a set range; The gas turbine components include a high-pressure compressor, a high-pressure turbine, and a power turbine. The correction factors include flow correction factors and efficiency correction factors; The optimal correction coefficients are obtained by filtering the correction coefficients using the differential evolution algorithm. The degradation factor of each component of the gas turbine is calculated based on the optimal correction factor and the original correction factor; The gas turbine is deemed necessary for maintenance based on the aforementioned degradation factor. Specifically, the optimal correction coefficients are obtained by screening the correction coefficients using the differential evolution algorithm, which includes: Initialize the population; the individuals in the population are the correction coefficients; The individuals were subjected to mutation and hybridization operations; Calculate the fitness of the individual; The optimal individual is determined based on the fitness; the optimal individual is the optimal correction coefficient. The calculation of the fitness of the individual specifically includes: Obtain actual monitoring data of the gas turbine; The inlet temperature, inlet pressure, fuel flow rate, power shaft speed, and load in the actual monitored quantities are used as boundary conditions. The pressure ratio of the high-pressure compressor of the gas turbine, the expansion ratio of the high-pressure turbine and the power turbine, and the high-pressure shaft speed are used as initial values. The Newton-Raphson iteration method is used to solve for the steady-state values ​​of the gas turbine. Calculate the error between the actual monitored value and the steady-state value, and select the maximum error as the fitness. The pressure ratio of the high-pressure compressor, the expansion ratio of the high-pressure turbine and the power turbine, and the high-pressure shaft speed are used as initial values. The Newton-Raphson iteration method is employed to solve for the steady-state values ​​of the gas turbine, specifically including: Construct the residual equations for the gas turbine; the residual equations include the flow balance residual equation and the power balance residual equation; Using the pressure ratio of the high-pressure compressor of the gas turbine, the expansion ratio of the high-pressure turbine and the power turbine, and the high-pressure shaft speed as initial values, calculate the flow rate and power of each component of the gas turbine; The flow rate and power of each component of the gas turbine are substituted into the residual equation, and the Newton-Raphson iteration method is used to solve it to obtain the steady-state value of the gas turbine.

2. The gas turbine steady-state optimization method according to claim 1, characterized in that, The expression for the residual equation is as follows: Where e1, e2, e3, and e4 are the high-pressure flow residual equation, the low-pressure flow residual equation, the high-pressure power residual equation, and the dynamic power residual equation, respectively. This refers to the flow rate of the high-pressure compressor. For fuel flow rate, For high-pressure turbine flow, For power turbine flow, This refers to the power of the high-pressure compressor. For high-pressure turbine power, Where is the power of the turbine, and Load is the load.

3. The gas turbine steady-state optimization method according to claim 1, characterized in that, The formulas for calculating the degradation factors of each component of the gas turbine are as follows: Where factor is the degradation factor of each component of the gas turbine. The optimal correction coefficient is... This is the original correction factor.

4. A gas turbine steady-state optimization system, characterized in that, include: The correction coefficient random generation module is used to randomly generate correction coefficients for various components of the gas turbine within a set range; The gas turbine components include a high-pressure compressor, a high-pressure turbine, and a power turbine. The correction factors include flow correction factors and efficiency correction factors; The optimal correction coefficient determination module is used to filter the correction coefficients based on the differential evolution algorithm to obtain the optimal correction coefficients; The degradation factor calculation module is used to calculate the degradation factor of each component of the gas turbine based on the optimal correction coefficient and the original correction coefficient. The maintenance determination module is used to determine whether the gas turbine needs maintenance based on the degradation factor. Specifically, the optimal correction coefficient determination module includes: An initialization submodule is used to initialize the population; the individuals in the population are the correction coefficients. The mutation and hybridization submodule is used to perform mutation and hybridization operations on the individuals; The fitness calculation submodule is used to calculate the fitness of the individual. The optimal correction coefficient determination submodule is used to determine the optimal individual based on the fitness; the optimal individual is defined by the optimal correction coefficient. The fitness calculation submodule specifically includes: The actual monitoring quantity acquisition unit is used to acquire the actual monitoring quantity of the gas turbine; The boundary condition determination unit is used to take the inlet temperature, inlet pressure, fuel flow rate, power shaft speed and load in the actual monitored quantities as boundary conditions; The solution unit is used to take the pressure ratio of the high-pressure compressor of the gas turbine, the expansion ratio of the high-pressure turbine and the power turbine, and the high-pressure shaft speed as initial values, and use the Newton-Raphson iteration method to solve for the steady-state values ​​of the gas turbine. The fitness calculation unit is used to calculate the error between the actual monitored value and the steady-state value, and select the maximum error as the fitness. The solution unit specifically includes: A residual equation construction sub-unit is used to construct the residual equations of the gas turbine; the residual equations include the flow balance residual equation and the power balance residual equation. The flow and power calculation subunit is used to calculate the flow and power of each component of the gas turbine by taking the pressure ratio of the high-pressure compressor, the expansion ratio of the high-pressure turbine and the power turbine, and the high-pressure shaft speed as initial values. The solution sub-unit is used to input the flow rate and power of each component of the gas turbine into the residual equation and solve it using the Newton-Raphson iteration method to obtain the steady-state value of the gas turbine.

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