Blade aeroelastic stability optimization method and system, electronic equipment and storage medium

Abstract

The invention provides a blade aeroelastic stability optimization method and system, electronic equipment and a storage medium. The blade aeroelastic stability optimization method comprises the steps of obtaining blade information of each long flexible blade of a wind turbine generator; according to the blade information of the long flexible blade, the flapping rigidity and shimmy rigidity of each blade section of the long flexible blade are determined; determining a modal shape matrix and a modal circular frequency of the long flexible blade by utilizing the flapping rigidity and the shimmy rigidity of each blade section; calculating an aerodynamic damping ratio corresponding to each order of modal shape of the long flexible blade under each working condition; based on the aerodynamic damping ratio corresponding to the modal shape of each order of the long flexible blade under each working condition, key design variables of the long flexible blade under each working condition are extracted from the blade layering design parameters; determining optimization parameters of the associated design variables of the long flexible blade under each working condition by utilizing a preset optimization target and a preset constraint condition; and optimizing the long flexible blade by utilizing the optimization parameters of the long flexible blade under each working condition to obtain the long flexible blade adapting to each working condition.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of blade aeroelastic optimization, more particularly, to a blade aeroelastic stability optimization method and system, an electronic device and a storage medium. BACKGROUND

[0002] With the continuous growth of installed capacity and single machine power, the rotor diameter of wind turbine is increasing. In order to adapt to this type of rotor, the large wind turbine blade is long and flexible due to its large aspect ratio and high structural flexibility. However, due to the coupling effect of aerodynamic force, elastic force and inertia force, the long and flexible blade is prone to aeroelastic instability phenomena such as flutter, which seriously affects the safe operation of the unit. Therefore, in order to ensure the safe operation of the unit, it is necessary to ensure the aeroelastic stability of the long and flexible blade.

[0003] At present, the stability optimization of the traditional long and flexible blade aeroelastic is mostly based on the blade mass, stiffness or natural frequency as the target for corresponding optimization. However, this optimization method not only fails to take into account the stability requirements under different working conditions, lacks analysis of the influence of blade layup design parameters on flutter characteristics, but also has the problem of insufficient stability. SUMMARY

[0004] Therefore, the present application provides a blade aeroelastic stability optimization method and system, an electronic device and a storage medium to solve the problem that the prior art fails to take into account the stability requirements under different working conditions, lacks analysis of the influence of blade layup design parameters on flutter characteristics and has insufficient stability.

[0005] The first aspect of the present application provides a blade aeroelastic stability optimization method, which comprises:

[0006] obtaining blade information of each long and flexible blade of a wind turbine;

[0007] determining the edgewise stiffness and the flapwise stiffness of each blade section of the long and flexible blade according to the blade information of the long and flexible blade;

[0008] determining the modal shape matrix and the modal circular frequency of the long and flexible blade by using the edgewise stiffness and the flapwise stiffness of each blade section, wherein the modal shape matrix comprises multiple order modal shapes;

[0009] calculating the corresponding aerodynamic damping ratio of each order modal shape of the long and flexible blade under each working condition;

[0010] extracting the key design variables of the long and flexible blade under each working condition from the blade layup design parameters based on the corresponding aerodynamic damping ratio of each order modal shape of the long and flexible blade under each working condition;

[0011] The optimization parameters of the associated design variables of the long flexible blade under each working condition are determined by using preset optimization objectives and preset constraints.

[0012] The long flexible blade is optimized using the optimized parameters of the blade under each working condition to obtain a long flexible blade that is adapted to each working condition.

[0013] Optionally, the mode shape matrix and modal circular frequencies of the long flexible blade are determined using the flapping stiffness and tessellation stiffness of each blade section, including:

[0014] The stiffness matrix and mass matrix of each blade section are constructed using the flapping stiffness and teeter stiffness of each blade section.

[0015] The stiffness matrix and mass matrix of each blade section are assembled to construct the Euler-Bernoulli beam model of the long flexible blade.

[0016] Modal analysis was performed on the long flexible blade based on the Euler-Bernoulli beam model to obtain the modal shape matrix and modal circular frequency of the long flexible blade.

[0017] Optionally, the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition is calculated, including:

[0018] Using the wind turbine's operating configuration information and wind condition information under each operating condition, an aerodynamic calculation model corresponding to each operating condition is constructed;

[0019] Using the aerodynamic calculation model corresponding to each working condition and the Euler-Bernoulli beam model of the long flexible blade, an aeroelastic coupling analysis model of the long flexible blade under each working condition is constructed.

[0020] The aeroelastic coupling analysis model of the long flexible blade under each working condition is solved to obtain the cross-sectional parameters of each blade section under each working condition.

[0021] Using the cross-sectional parameters of each blade section of the long flexible blade under each operating condition, the aerodynamic damping matrix of each blade section of the long flexible blade under each operating condition is calculated.

[0022] Based on the aerodynamic damping matrix and torsion angle of each blade section of the long flexible blade under each working condition, calculate the aerodynamic damping corresponding to each mode shape of the long flexible blade under each working condition.

[0023] Based on the aerodynamic damping and modal circular frequency corresponding to each mode of vibration of the long flexible blade under each operating condition, the aerodynamic damping ratio corresponding to each mode of vibration of the long flexible blade under each operating condition is calculated.

[0024] Optionally, based on the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition, key design variables for the long flexible blade under each operating condition are extracted from the blade layup design parameters, including:

[0025] Obtain blade layup design parameters and sample the blade layup design parameters to obtain a statistical sample; wherein, the blade layup design parameters include multiple influencing parameters;

[0026] The aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition is used as a reference parameter for the grey relational analysis method. The grey relational analysis method is then used to calculate the comparison sequence and reference sequence of the statistical sample under each operating condition. The reference sequence under each operating condition includes the aerodynamic damping ratio of each mode shape of the long flexible blade under each operating condition. The comparison sequence under each operating condition includes the target aerodynamic damping ratio of each mode shape of the long flexible blade under each operating condition under different influencing parameters.

[0027] For each operating condition, the correlation coefficient of each mode shape under the operating condition is calculated based on the aerodynamic damping ratio of each mode shape in the comparison sequence under the operating condition and the target aerodynamic damping of each mode shape in the reference sequence under the operating condition.

[0028] Based on the correlation coefficient of each mode shape under the aforementioned working condition, calculate the correlation degree of each mode shape under the aforementioned working condition.

[0029] Based on the correlation of each mode shape under the aforementioned operating conditions, the key design variables of the long flexible blade under the aforementioned operating conditions are extracted from the blade layup design parameters.

[0030] Optionally, the optimization parameters of the associated design variables of the long flexible blade under each working condition are determined using preset optimization objectives and preset constraints, including:

[0031] Using a non-dominated sorting genetic algorithm based on preset optimization objectives and preset constraints, the aerodynamic damping ratio of each mode of vibration of the long flexible blade under each operating condition is jointly optimized within the design range of the associated design variables of the long flexible blade under each operating condition to obtain the Pareto optimal solution; wherein, the Pareto optimal solution includes the optimization parameters of the associated design variables of the long flexible blade under each operating condition.

[0032] Optionally, the method further includes:

[0033] For each operating condition, the displacement response of each long flexible blade of the wind turbine under the operating condition is simulated to obtain the first simulation result;

[0034] The displacement response of each long flexible blade of the wind turbine after optimization under the above operating conditions is simulated to obtain the second simulation result;

[0035] If the second simulation result indicates that the displacement amplitude of the flexible blade of the wind turbine after optimization is not less than the displacement amplitude of the flexible blade of the wind turbine indicated by the first simulation result, a corresponding prompt message is output, so that the corresponding technician can adjust the design range of the associated design variables of the flexible blade under the operating condition based on the prompt message.

[0036] A second aspect of this application provides a blade aeroelastic stability optimization system, the system comprising:

[0037] The data acquisition module is used to acquire blade information for each long flexible blade of the wind turbine.

[0038] The aeroelastic calculation module is used to determine the flapping stiffness and oscillation stiffness of each blade section of the long flexible blade based on the blade information; and to determine the mode shape matrix and modal circular frequency of the long flexible blade using the flapping stiffness and oscillation stiffness of each blade section; wherein the mode shape matrix includes multiple mode shapes; and to calculate the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition.

[0039] The parameter analysis module is used to extract the key design variables of the long flexible blade under each working condition from the blade layup design parameters based on the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each working condition.

[0040] The optimization design module is used to determine the optimization parameters of the associated design variables of the long flexible blade under each working condition using preset optimization objectives and preset constraints; and to optimize the long flexible blade using the optimization parameters of the long flexible blade under each working condition to obtain a long flexible blade adapted to each working condition.

[0041] Optionally, the aeroelastic calculation module, which uses the flapping stiffness and oscillation stiffness of each blade section to determine the modal shape matrix and modal circular frequency of the long flexible blade, is specifically used for:

[0042] The stiffness matrix and mass matrix of each blade section are constructed using the flapping stiffness and teeter stiffness of each blade section.

[0043] The stiffness matrix and mass matrix of each blade section are assembled to construct the Euler-Bernoulli beam model of the long flexible blade.

[0044] Modal analysis was performed on the long flexible blade based on the Euler-Bernoulli beam model to obtain the modal shape matrix and modal circular frequency of the long flexible blade.

[0045] A third aspect of this application provides an electronic device, comprising: a processor and a memory, the processor and the memory being connected via a bus; wherein the processor is used to call and execute a program stored in the memory; the memory is used to store the program, the program being used to implement a blade aeroelastic stability optimization method as provided in the first aspect of this application.

[0046] The fourth aspect of this application provides a computer-readable storage medium storing computer-executable instructions for executing a blade aeroelastic stability optimization method provided in the first aspect of this application.

[0047] This application provides a method, system, electronic device, and storage medium for optimizing the aeroelastic stability of wind turbine blades. The method involves acquiring blade information for each long flexible blade of a wind turbine; determining the flapping stiffness and flaring stiffness of each blade section based on the blade information; determining the mode shape matrix and modal circular frequencies of the long flexible blade using the flapping and flaring stiffness of each blade section; wherein the mode shape matrix includes multiple mode shapes; calculating the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition; and extracting the aerodynamic damping ratio of each mode shape from the blade layup design parameters based on the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition. Key design variables of flexible blades under various operating conditions; optimization parameters of related design variables of flexible blades under each operating condition are determined by using preset optimization objectives and preset constraints; the flexible blades are optimized using the optimization parameters of flexible blades under each operating condition to obtain flexible blades adapted to each operating condition, realizing global optimization of the aerodynamic damping ratio of flexible blades under multiple operating conditions, thereby enhancing the aeroelastic stability of flexible blades, providing effective technical support for the safety design of flexible blades of wind turbines, and solving the problems in existing technologies that are difficult to take into account the stability requirements under different operating conditions, lack the influence analysis of blade layup design parameters on flutter characteristics, and have insufficient stability. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0049] Figure 1 A flowchart illustrating a method for optimizing the aeroelastic stability of a blade, provided in an embodiment of this application;

[0050] Figure 2 This is a schematic diagram of a blade aeroelastic stability optimization system provided in an embodiment of the present invention;

[0051] Figure 3 This is a schematic diagram of a blade aeroelastic stability optimization system provided in an embodiment of the present invention;

[0052] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0053] 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.

[0054] In this application, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0055] See Figure 1 The diagram shows a flowchart of a blade aeroelastic stability optimization method provided in an embodiment of this application. The blade aeroelastic stability optimization method specifically includes the following steps:

[0056] S101: Obtain blade information for each long flexible blade of the wind turbine.

[0057] In the embodiments of this application, when it is necessary to optimize the aeroelastic stability of the blades, the blade information of each long flexible blade of the wind turbine can be obtained first.

[0058] It should be noted that the blade information for long flexible blades includes the blade length, pre-bending distribution, pre-sweep distribution, torsion foot distribution, chord length distribution, airfoil aerodynamic characteristics, and interface parameter distribution of composite laminates, etc.

[0059] In this embodiment of the application, while obtaining the blade information of the long flexible blade, the wind condition information and operating configuration information of the wind turbine under each operating condition can also be obtained.

[0060] It should be noted that the operating conditions can be either the wind turbine's rated rotor operating condition or the high-wind shutdown operating condition. Specifically, the wind condition information for the wind turbine under the rated rotor operating condition includes at least: wind type, random number seed, wind plane size, wind shear, and duration. The wind condition operation information for the wind turbine under the high-wind shutdown condition includes at least: wind type, random number seed, wind plane size, wind shear, and duration. The operating configuration information for the wind turbine under the rated rotor operating condition includes: hub center height, rotor speed, rotor cone angle, and rotor elevation angle. The operating configuration information for the wind turbine under the high-wind shutdown condition includes: hub center height, rotor speed, rotor cone angle, and rotor elevation angle.

[0061] S102: Based on the blade information of the long flexible blade, determine the flapping stiffness and oscillation stiffness of each blade section of the long flexible blade.

[0062] In the specific execution step S102, for each long flexible blade of the wind turbine, after obtaining the blade information of the long flexible blade, the cross-sectional parameter distribution of the composite laminate can be extracted from the blade information, and the cross-sectional parameter distribution of the composite laminate can be calculated according to the composite laminate theory to obtain the bending stiffness matrix D of each blade cross section of the long flexible blade; for each blade cross section, the stiffness components corresponding to the flapping and swaying directions are extracted from the bending stiffness matrix D of the blade cross section to obtain the flapping stiffness and swaying stiffness of the blade cross section.

[0063] It should be noted that the bending stiffness matrix D of the blade section is composed of multiple stiffness components. The distribution of the cross-sectional parameters of the composite laminate is calculated according to the composite laminate theory. The method for calculating each stiffness component in the bending stiffness matrix D is shown in formula (1):

[0064] (1)

[0065] In formula (1), Let be the stiffness component in the i-th row and j-th column of the stiffness-bending matrix. The thickness of the k-th ply of the blade cross section; The vertical distance from the center of the k-th ply of the blade cross section to the mid-surface; This is the stiffness matrix in the blade section coordinate system; The calculation formula is: .

[0066] It should be noted that after obtaining the bending stiffness matrix D, the stiffness components corresponding to the flapping and oscillation directions can be extracted from the bending stiffness matrix to obtain the flapping stiffness. and oscillation stiffness .

[0067] S103: Determine the modal shape matrix and modal circular frequency of the long flexible blade using the flapping stiffness and oscillation stiffness of each blade section; wherein, the modal shape matrix includes multiple modal shapes.

[0068] In the specific execution step S103, for each long flexible blade, after obtaining the flapping stiffness and teeter stiffness of each blade section, an Euler-Bernoulli beam model of the long flexible blade can be constructed using the flapping stiffness and teeter stiffness of each blade section. Modal analysis is then performed on the long flexible blade based on the Euler-Bernoulli beam model to obtain the modal shape matrix and modal circular frequencies of the long flexible blade. The modal shape matrix includes multiple modal shapes.

[0069] Optionally, the process of determining the modal shape matrix and modal circular frequency of the long flexible blade using the flapping stiffness and tessellation stiffness of each blade section can be as follows: construct the stiffness matrix and mass matrix of each blade section using the flapping stiffness and tessellation stiffness of each blade section; assemble the stiffness matrix and mass matrix of each blade section to construct the Euler-Bernoulli beam model of the long flexible blade; perform modal analysis on the long flexible blade based on the Euler-Bernoulli beam model to obtain the modal shape matrix and modal circular frequency of the long flexible blade.

[0070] In some embodiments, for each blade section, the stiffness matrix and mass matrix of the blade section are constructed using the flapping stiffness and oscillation stiffness of the blade section, wherein the stiffness matrix is ​​as shown in formula (2) and the mass matrix is ​​as shown in formula (3).

[0071] (2)

[0072] In formula (2), For elastic modulus, For the unit (blade section) section along Moment of inertia of the shaft section For unit length, Here is the stiffness matrix.

[0073] (3)

[0074] In formula (3), For unit length, For the unit cross-sectional mass, This is the quality matrix.

[0075] In some embodiments, the stiffness matrix and mass matrix of each blade section of the long flexible blade are assembled to obtain the corresponding Euler-Bernoulli beam model. Modal analysis is then performed on the long flexible blade based on the blade structure dynamics equation and natural frequency formula within the Euler-Bernoulli beam model to obtain the mode shape matrix and modal circular frequency of the long flexible blade. The blade structure dynamics equation is shown in formula (4), and the natural frequency formula is shown in formula (5).

[0076] (4)

[0077] (5)

[0078] In formulas (4) and (5), M is the overall mass matrix, K is the overall stiffness matrix, F is the external force matrix, D is the mode shape matrix, and V is the eigenvalue matrix. Let x be the modal angular frequency and x be the length of the flexible blade. is the second derivative of the length of the long flexible blade.

[0079] It should be noted that the modal shape matrix D can also be normalized to obtain the normalized mode shape of the blade.

[0080] S104: Calculate the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition.

[0081] In the specific execution of step S104, for each operating condition, the operating configuration information and wind condition information of the wind turbine under that operating condition can be used to construct the corresponding aerodynamic calculation model. In order to use the corresponding aerodynamic calculation model and the Euler-Bernoulli beam model of the long flexible blade, the section parameters of each blade section of the long flexible blade under that operating condition can be determined. In order to use the section parameters and torsion angle of each blade section of the long flexible blade under that operating condition, the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under that operating condition can be calculated.

[0082] Optionally, the process of calculating the aerodynamic damping ratio corresponding to each mode shape of the flexible blade under each operating condition can be as follows: Using the wind turbine's operating configuration information and wind conditions under each operating condition, construct an aerodynamic calculation model corresponding to each operating condition; using the aerodynamic calculation model corresponding to each operating condition and the Euler-Bernoulli beam model of the flexible blade, construct an aeroelastic coupling analysis model of the flexible blade under each operating condition; solve the aeroelastic coupling analysis model of the flexible blade under each operating condition to obtain the values ​​for each blade under each operating condition. The section parameters of the cross section are calculated. Using the section parameters of each blade section of the long flexible blade under each operating condition, the aerodynamic damping matrix of each blade section of the long flexible blade under each operating condition is calculated. Based on the aerodynamic damping matrix and torsion angle of each blade section of the long flexible blade under each operating condition, the aerodynamic damping corresponding to each mode shape of the long flexible blade under each operating condition is calculated. Based on the aerodynamic damping and modal circular frequency corresponding to each mode shape of the long flexible blade under each operating condition, the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition is calculated.

[0083] In some embodiments, for each operating condition, parameters such as incoming wind, wind shear, rotor speed, rotor cone angle, and rotor elevation angle at the hub center height of the wind turbine under that operating condition can be extracted from the operating condition configuration information and wind condition information of the wind turbine under that operating condition. Then, the extracted parameters are used to construct an aerodynamic calculation model for that operating condition according to the blade element momentum theory.

[0084] In the embodiments of this application, after constructing the aerodynamic calculation model for each operating condition, the aerodynamic calculation model for each operating condition and the Euler-Bernoulli beam model of the long flexible blade can be further combined to construct the aeroelastic coupling analysis model of the long flexible blade for each operating condition, so as to solve the aeroelastic coupling analysis model of the long flexible blade for each operating condition and obtain the cross-sectional parameters of each blade section of the long flexible blade for each operating condition.

[0085] It should be noted that during the construction of the aeroelastic coupling analysis model, the time step of the aeroelastic coupling analysis model should not be too large in order to ensure the stability of the cross-sectional parameters of the obtained blade section.

[0086] It should also be noted that the coupling methods of the aeroelastic coupling analysis model include, but are not limited to, loose coupling and tight coupling.

[0087] For example, for various operating conditions including the rated operating condition of the wind turbine rotor and the high wind shutdown condition, the aeroelastic coupling analysis model of the long flexible blade under the rated operating condition of the wind turbine rotor is solved to obtain the cross-sectional parameters of each blade section of the long flexible blade under the rated operating condition of the wind turbine rotor; the aeroelastic coupling analysis model of the long flexible blade under the high wind shutdown condition is solved to obtain the cross-sectional parameters of each blade section of the long flexible blade under the high wind shutdown condition.

[0088] It should be noted that the cross-sectional parameters of the blade section can include the air density at the blade section, the chord length at the blade section, the rotor speed of the wind turbine, the length from the blade root to the blade section, the resultant velocity at the blade section, the airfoil drag coefficient at the blade section, the aerodynamic angle of attack at the blade section, and the airfoil lift coefficient at the blade section.

[0089] In some embodiments, for each blade section of a long flexible blade under operating conditions, the aerodynamic damping matrix of the blade section under that operating condition is calculated using the section parameters of that blade section. The method is shown in formula (6).

[0090] (6)

[0091] In formula (6), This indicates the air density at the blade cross-section; Indicates the chord length at the blade cross-section; This indicates the rotor speed of the wind turbine. Indicates the length from the leaf base to the cross-section of the leaf blade (via... It can be determined which blade section's aerodynamic damping matrix is ​​being calculated. This represents the resultant velocity at the blade cross-section; This represents the airfoil drag coefficient at the blade section; Indicates the aerodynamic angle of attack at the blade cross-section; This represents the airfoil lift coefficient at the blade section.

[0092] In some embodiments, since each blade section has a corresponding torsional angle, the aerodynamic damping matrix of the long flexible blade under each operating condition can be transformed using the torsional angle of each blade section under each operating condition. This allows the aerodynamic damping corresponding to each mode shape of the long flexible blade under each operating condition to be calculated using the aerodynamic damping matrix of each blade section under each operating condition after coordinate transformation. The calculation method for aerodynamic damping is shown in formula (7).

[0093] (7)

[0094] In formula (7), It is the sum of the pitch angle and the twist angle of the blade section. , The first blade section corresponding to r Blade cross section in blade root coordinate system under first mode vibration mode Directional coordinates The first blade section corresponding to r Blade cross section in blade root coordinate system under first mode vibration mode The coordinates of the direction are r, which is the length from the root of the long flexible blade to the blade cross section, and B represents the transformation from the blade cross section coordinate system to the blade root coordinate system.

[0095] In some embodiments, after obtaining the aerodynamic damping corresponding to each mode shape of the long flexible blade under each operating condition, the aerodynamic damping corresponding to each mode shape of the long flexible blade under each operating condition can be further stiffened to obtain the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition. The method of stiffening the aerodynamic damping corresponding to each mode shape of the long flexible blade is as shown in formula (8).

[0096] (8)

[0097] In formula (8), The first of the long and flexible leaves Modal mass corresponding to the first mode shape. The first of the long and flexible leaves First-order mode shape, The first of the long and flexible leaves The modal circular frequency corresponding to the first mode shape. Let be the aerodynamic damping ratio of the i-th mode of the long flexible blade, and M be the modal mass of the mode shape matrix of the long flexible blade.

[0098] S105: Based on the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition, extract the key design variables of the long flexible blade under each operating condition from the blade layup design parameters.

[0099] In the specific execution of step S105, for each operating condition, the corresponding blade layup design parameters of the long flexible blades can be selected from each long flexible blade of the wind turbine according to the current user experience and needs. In order to extract the key design variables of the long flexible blades under each operating condition from the blade layup design parameters based on the aerodynamic damping ratio corresponding to each mode shape of the long flexible blades under each operating condition.

[0100] Optionally, based on the aerodynamic damping ratios corresponding to the mode shapes of the long flexible blade under each operating condition, the process of extracting key design variables of the long flexible blade under each operating condition from the blade layup design parameters can be as follows: obtain the blade layup design parameters and sample them to obtain statistical samples; use the aerodynamic damping ratios corresponding to the mode shapes of the long flexible blade under each operating condition as reference parameters for the grey relational analysis method, and use the grey relational analysis method to calculate the comparison sequence and reference sequence of the statistical samples under each operating condition; wherein, the reference sequence under each operating condition includes the aerodynamic damping ratios corresponding to the mode shapes of the long flexible blade under each operating condition. Nibi; the comparison sequence for each operating condition includes the target aerodynamic damping ratio of each mode shape of the long flexible blade under different influencing parameters; for each operating condition, the correlation coefficient of each mode shape under the operating condition is calculated based on the aerodynamic damping ratio of each mode shape in the comparison sequence under the operating condition and the target aerodynamic damping of each mode shape in the reference sequence under the operating condition; based on the correlation coefficient of each mode shape under the operating condition, the correlation degree of each mode shape under the operating condition is calculated; based on the correlation degree of each mode shape under the operating condition, the key design variables of the long flexible blade under the operating condition are extracted from the blade layup design parameters.

[0101] In some embodiments, blade layup design parameters can be used as comparison parameters for correlation analysis. These parameters include multiple influencing parameters, such as, but not limited to, trailing edge foam thickness, carbon fiber parameters, web spacing, web foam thickness, glass fiber parameters, and leading edge foam thickness. Monte Carlo simulation is used to sample the reference parameters to obtain a certain number of statistical samples. The aerodynamic damping ratios corresponding to each mode shape of the long flexible blade under each operating condition are used as reference parameters for the grey relational analysis method. This allows the grey relational analysis method to calculate the statistical samples and obtain the reference sequence for each operating condition. and comparison sequences .

[0102] For each operating condition, the reference sequence for that operating condition is... In This indicates the first [blank] of the long flexible blade under this operating condition. The aerodynamic damping ratio of the first mode shape, where n represents the number of modes in the mode shape matrix of the long flexible blade; the comparison sequence under this operating condition. In This indicates the first [blank] of the long flexible blade under this operating condition. The first mode shape is subject to the first The target aerodynamic damping ratio under the influence of several parameters, where n represents the number of modes in the mode shape matrix of the long flexible blade, and m represents the number of influencing parameters.

[0103] It should be noted that before calculating the corresponding correlation coefficients, the comparison sequence and reference sequence under each working condition can be subjected to a quantity-free stiffness processing to eliminate the influence of different sequence index quantities.

[0104] In some embodiments, for each operating condition, the correlation coefficient of each mode shape of the long flexible blade under that operating condition is calculated based on the comparison sequence and reference sequence under that operating condition as shown in Equation (9).

[0105] (9)

[0106] In formula (9), The resolution coefficient, The smaller the value, the stronger the resolution; generally, 0.5 is used. The target aerodynamic damping ratio with the smallest value in the comparison sequence under all operating conditions; The target aerodynamic damping ratio with the smallest value in the comparison sequence under the current operating conditions; The target aerodynamic damping ratio that has the largest value in the comparison sequence under all operating conditions; The target aerodynamic damping ratio that is the largest in the comparison sequence under the current operating conditions; Let be the deviation sequence between the aerodynamic damping ratio of the k-th mode and the target aerodynamic damping ratio of the k-th mode under the influence of the i-th parameter. ; is the correlation coefficient between the aerodynamic damping ratio of the k-th mode and the target aerodynamic damping ratio of the k-th mode under the influence of the i-th parameter.

[0107] In some embodiments, for each operating condition, the correlation coefficient between the aerodynamic damping ratio of the k-th mode and the target aerodynamic damping ratio of the k-th mode under the influence of the i-th influence parameter can be used to calculate the correlation degree of the i-th influence parameter to the k-th mode of the long flexible blade under the current operating condition. The correlation degree is calculated as shown in formula (10).

[0108] (10)

[0109] In formula (10), r i Let represent the correlation degree between the i-th influencing parameter and the k-th mode shape of the long flexible blade under the current operating condition, where n is the order of the mode shape matrix.

[0110] As a preferred embodiment of this application, the various influencing parameters can be sorted from largest to smallest according to their degree of correlation, and multiple target influencing parameters can be selected from the various influencing parameters as key design variables according to certain selection criteria, that is, the corresponding key design variables can be extracted from the blade layup design parameters.

[0111] It should be noted that the selection criteria can be: select the influence parameters with a correlation degree greater than or equal to 0.8 as key design variables.

[0112] The above is a preferred selection criterion provided by the embodiments of this application. The corresponding selection criteria can be configured according to the actual application. This embodiment of the application does not limit the selection criteria.

[0113] S106: Determine the optimization parameters of the associated design variables of the long flexible blade under each working condition using preset optimization objectives and preset constraints.

[0114] In the specific execution step S106, after obtaining the associated design variables of the long flexible blade under each working condition, the non-dominated sorting genetic algorithm can be used to perform collaborative optimization of the aerodynamic damping ratio of each mode of the long flexible blade under each working condition within the design range of the associated design variables of the long flexible blade under each working condition, based on the preset optimization objective and preset constraints, to obtain the Pareto optimal solution; wherein, the Pareto optimal solution includes the optimization parameters of the associated design variables of the long flexible blade under each working condition.

[0115] In this embodiment, preset optimization targets and preset constraints for the aerodynamic damping ratios of each mode of vibration of the long flexible blade under each operating condition can be pre-configured. The preset optimization targets can be: maximizing the first-order flapping aerodynamic damping ratio of the long flexible blade under the rated operating condition of the wind turbine as the first target, or maximizing the first-order oscillation aerodynamic damping ratio of the long flexible blade under the high-wind shutdown condition as the second target. The preset constraints can be: under any operating condition, the aerodynamic damping ratios of other mode vibrations of the long flexible blade besides the first-order mode vibration are not lower than the original aerodynamic damping ratio of the long flexible blade (e.g., the second-order flapping aerodynamic damping ratio, the second-order oscillation aerodynamic damping ratio).

[0116] It should be noted that the non-dominated sorting genetic algorithm can be NSGA-II.

[0117] It should also be noted that the first wave is a specific mode shape, and the aerodynamic damping ratio of the first wave is the aerodynamic damping ratio of a specific mode shape; the first oscillation is also a specific mode shape, the second wave is also a specific mode shape, and the second oscillation is also a specific mode shape. The corresponding first wave, first oscillation, second wave, and second oscillation can be configured according to the actual application. This application does not limit these configurations in the embodiments.

[0118] S107: Optimize the long flexible blade using the optimized parameters for each working condition to obtain a long flexible blade that adapts to each working condition.

[0119] In the specific execution of step S107, under each operating condition, after obtaining the optimized parameters of each long flexible blade under that operating condition, the optimized parameters of each long flexible blade under that operating condition can be used to optimize each long flexible blade of the wind turbine to obtain a wind turbine adapted to that operating condition.

[0120] Furthermore, in this embodiment, for each operating condition, after optimizing each long flexible blade of the wind turbine under that operating condition, the displacement response of each long flexible blade of the wind turbine under that operating condition can be simulated to obtain a first simulation result; the displacement response of each long flexible blade of the wind turbine after optimization under that operating condition can be simulated to obtain a second simulation result; if the second simulation result indicates that the displacement amplitude of the long flexible blade of the wind turbine after optimization is not less than the displacement amplitude of the long flexible blade of the wind turbine indicated by the first simulation result, a corresponding prompt message is output, so that the corresponding technician can adjust the design range of the associated design variables of the long flexible blade under that operating condition based on the prompt message. Once the technicians have completed the corresponding adjustments, the algorithm can return to the point where a non-dominated sorting genetic algorithm is used to collaboratively optimize the aerodynamic damping ratio of each mode of the long flexible blade under each operating condition within the design range of the associated design variables of the long flexible blade under each operating condition, based on the preset optimization objectives and preset constraints, until the second simulation result indicates that the displacement amplitude of the long flexible blade of the wind turbine after optimization is less than the displacement amplitude of the long flexible blade of the wind turbine indicated by the first simulation result.

[0121] In some embodiments, third-party gas bullet simulation software (such as Bladed or OpenFast) can be invoked to perform the corresponding simulation operations.

[0122] It should be noted that the displacement amplitude of the flexible blades in the optimized wind turbine is smaller than that in the unoptimized wind turbine. This indicates that the effectiveness of the optimized wind turbine is higher than that of the unoptimized wind turbine, which in turn shows that the aeroelastic stability of the optimized flexible blade is improved.

[0123] This application provides a method for optimizing the aeroelastic stability of a wind turbine blade. The method involves acquiring blade information for each long flexible blade of a wind turbine; determining the flapping stiffness and yaw stiffness of each blade section based on the blade information; determining the mode shape matrix and modal circular frequency of the long flexible blade using the flapping and yaw stiffness of each blade section; wherein the mode shape matrix includes multiple mode shapes; calculating the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition; extracting key design variables for each operating condition from the blade layup design parameters based on the aerodynamic damping ratios corresponding to each mode shape of the long flexible blade under each operating condition; determining the optimization parameters of the associated design variables of the long flexible blade under each operating condition using preset optimization objectives and preset constraints; and optimizing the long flexible blade using the optimization parameters for each operating condition to obtain a long flexible blade adapted to each operating condition. Therefore, this application determines the aerodynamic damping ratio of each mode of the long flexible blade under each operating condition, and uses the aerodynamic damping of each mode of the long flexible blade under each operating condition as a reference parameter for the grey relational analysis. This allows for parameter correlation analysis under multiple operating conditions using the grey relational analysis method, quantifying the influence of blade layup design parameters on the aerodynamic damping ratio of each mode of the long flexible blade under each operating condition, and extracting the key design variables of the long flexible blade under each operating condition from the blade layup design parameters. Furthermore, it utilizes preset optimization objectives and preset constraints to determine the aerodynamic damping ratio of each mode of the long flexible blade under each operating condition. The optimization parameters of the associated design variables of the flexible blade under various operating conditions are obtained. Finally, the flexible blade is optimized using the optimization parameters of the flexible blade under each operating condition to obtain a flexible blade that adapts to each operating condition. This achieves global optimization of the aerodynamic damping ratio of the flexible blade under multiple operating conditions, thereby enhancing the aeroelastic stability of the flexible blade. This provides effective technical support for the safe design of flexible blades for wind turbines, thus solving the problems in the existing technology that it is difficult to take into account the stability requirements under different operating conditions, lack the influence analysis of blade layup design parameters on flutter characteristics, and have insufficient stability.

[0124] Based on the blade aeroelastic stability optimization method provided in the above embodiments of this application, correspondingly, the embodiments of this application provide a blade aeroelastic stability optimization system, such as... Figure 2 As shown, the blade aeroelastic stability optimization system includes:

[0125] The data acquisition module 201 is used to acquire the blade information of each long flexible blade of the wind turbine.

[0126] The aeroelastic calculation module 202 is used to determine the flapping stiffness and teeter stiffness of each blade section of the long flexible blade based on the blade information; and to determine the mode shape matrix and modal circular frequency of the long flexible blade using the flapping stiffness and teeter stiffness of each blade section; wherein the mode shape matrix includes multiple mode shapes; and to calculate the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition.

[0127] The parameter analysis module 203 is used to extract the key design variables of the long flexible blade under each working condition from the blade layup design parameters based on the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each working condition.

[0128] The optimization design module 204 is used to determine the optimization parameters of the associated design variables of the long flexible blade under each working condition using preset optimization objectives and preset constraints; and to optimize the long flexible blade using the optimization parameters of the long flexible blade under each working condition to obtain a long flexible blade that adapts to each working condition.

[0129] Optionally, an aeroelastic calculation module is provided to determine the modal shape matrix and modal circular frequencies of long flexible blades using the flapping stiffness and tessellation stiffness of each blade section. Specifically, this module is used for:

[0130] The stiffness matrix and mass matrix of each blade section are constructed using the flapping stiffness and teeter stiffness of each blade section.

[0131] The stiffness matrix and mass matrix of each blade section are assembled to construct an Euler-Bernoulli beam model of a long, flexible blade.

[0132] Modal analysis of the long flexible blade was performed based on the Euler-Bernoulli beam model to obtain the modal shape matrix and modal circular frequency of the long flexible blade.

[0133] Optionally, an aeroelastic calculation module is provided to calculate the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition. Specifically, this module is used for:

[0134] Using the wind turbine's operating configuration information and wind condition information under each operating condition, an aerodynamic calculation model corresponding to each operating condition is constructed;

[0135] Using the aerodynamic calculation model corresponding to each working condition and the Euler-Bernoulli beam model of the long flexible blade, an aeroelastic coupling analysis model of the long flexible blade under each working condition is constructed.

[0136] The aeroelastic coupling analysis model of the long flexible blade under each working condition is solved to obtain the cross-sectional parameters of each blade section under each working condition.

[0137] Using the cross-sectional parameters of each blade section of the long flexible blade under each operating condition, the aerodynamic damping matrix of each blade section of the long flexible blade under each operating condition is calculated.

[0138] Based on the aerodynamic damping matrix and torsion angle of each blade section of the long flexible blade under each working condition, calculate the aerodynamic damping corresponding to each mode shape of the long flexible blade under each working condition.

[0139] Based on the aerodynamic damping and modal circle corresponding to each mode shape of the long flexible blade under each operating condition.

[0140] Optionally, a parameter analysis module is provided to extract key design variables of the long flexible blade under each operating condition from the blade layup design parameters, based on the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition. Specifically, this module is used for:

[0141] Obtain the blade layup design parameters and sample the blade layup design parameters to obtain a statistical sample;

[0142] The aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition is used as the reference parameter of the grey relational analysis method to calculate the comparison sequence and reference sequence of the statistical sample under each operating condition. The reference sequence under each operating condition includes the aerodynamic damping ratio of each mode shape of the long flexible blade under each operating condition. The comparison sequence under each operating condition includes the target aerodynamic damping ratio of each mode shape of the long flexible blade under each operating condition under different influencing parameters.

[0143] For each operating condition, the correlation coefficient of each mode shape under the operating condition is calculated based on the aerodynamic damping ratio of each mode shape in the comparison sequence under the operating condition and the target aerodynamic damping of each mode shape in the reference sequence under the operating condition.

[0144] The correlation degree of each mode shape under the working condition is calculated based on the correlation coefficient of each mode shape under the working condition.

[0145] Based on the correlation of each mode shape under operating conditions, the key design variables of long flexible blades under operating conditions are extracted from the blade layup design parameters.

[0146] Optionally, an optimization design module is used to determine the optimization parameters of the associated design variables of the long flexible blade under each working condition using preset optimization objectives and preset constraints. Specifically, this module is used for:

[0147] Using a non-dominated sorting genetic algorithm based on preset optimization objectives and constraints, the aerodynamic damping ratio of each mode of the long flexible blade under each operating condition is co-optimized within the design range of the associated design variables of the long flexible blade under each operating condition, to obtain the Pareto optimal solution; wherein, the Pareto optimal solution includes the optimization parameters of the associated design variables of the long flexible blade under each operating condition.

[0148] Optional, see Figure 3 The embodiments of this application provide a blade aeroelastic stability optimization system, which also includes a verification and analysis unit 25;

[0149] The verification and analysis unit is used to simulate the displacement response of each long flexible blade of the wind turbine under each operating condition, and obtain the first simulation result; to simulate the displacement response of each long flexible blade of the wind turbine after optimization under the operating condition, and obtain the second simulation result; if the second simulation result indicates that the displacement amplitude of the long flexible blade of the wind turbine after optimization is not less than the displacement amplitude of the long flexible blade of the wind turbine indicated by the first simulation result, the corresponding prompt information is output, so that the corresponding technicians can adjust the design range of the associated design variables of the long flexible blade under the operating condition based on the prompt information.

[0150] This application also provides a storage medium storing program instructions, which, when loaded and executed by a processor, implement any of the above-described embodiments of the blade aeroelastic stability optimization method.

[0151] This application also provides an electronic device, such as Figure 4 As shown, the device includes a processor 401 and a memory 402, which are connected via a bus; the memory stores program instructions; the processor calls the program instructions in the memory to execute any of the above-described embodiments of the blade aeroelastic stability optimization method.

[0152] The processor mentioned in this article can be the terminal's CPU, an integrated MCU within the terminal, or a combination of a CPU and an MCU. Furthermore, the processor contains a kernel that retrieves the corresponding program from memory; one or more kernels can be configured.

[0153] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0154] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the descriptions in the method embodiments. The systems and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0155] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0156] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0157] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for optimizing the aeroelastic stability of blades, characterized in that, The method includes: Obtain blade information for each long flexible blade of the wind turbine; Based on the blade information of the long flexible blade, determine the flapping stiffness and oscillation stiffness of each blade section of the long flexible blade; The mode shape matrix and modal circular frequency of the long flexible blade are determined by using the flapping stiffness and oscillation stiffness of each blade section; wherein, the mode shape matrix includes multiple mode shapes; Calculate the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition; Based on the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each working condition, the key design variables of the long flexible blade under each working condition are extracted from the blade layup design parameters. The optimization parameters of the associated design variables of the long flexible blade under each working condition are determined by using preset optimization objectives and preset constraints. The long flexible blade is optimized using the optimized parameters of the blade under each working condition to obtain a long flexible blade that is adapted to each working condition.

2. The method according to claim 1, characterized in that, Using the flapping stiffness and teeter stiffness of each blade section, the modal shape matrix and modal circular frequencies of the long flexible blade are determined, including: The stiffness matrix and mass matrix of each blade section are constructed using the flapping stiffness and teeter stiffness of each blade section. The stiffness matrix and mass matrix of each blade section are assembled to construct the Euler-Bernoulli beam model of the long flexible blade. Modal analysis was performed on the long flexible blade based on the Euler-Bernoulli beam model to obtain the modal shape matrix and modal circular frequency of the long flexible blade.

3. The method according to claim 2, characterized in that, Calculate the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition, including: Using the wind turbine's operating configuration information and wind condition information under each operating condition, an aerodynamic calculation model corresponding to each operating condition is constructed; Using the aerodynamic calculation model corresponding to each working condition and the Euler-Bernoulli beam model of the long flexible blade, an aeroelastic coupling analysis model of the long flexible blade under each working condition is constructed. The aeroelastic coupling analysis model of the long flexible blade under each working condition is solved to obtain the cross-sectional parameters of each blade section under each working condition. Using the cross-sectional parameters of each blade section of the long flexible blade under each operating condition, the aerodynamic damping matrix of each blade section of the long flexible blade under each operating condition is calculated. Based on the aerodynamic damping matrix and torsion angle of each blade section of the long flexible blade under each working condition, calculate the aerodynamic damping corresponding to each mode shape of the long flexible blade under each working condition. Based on the aerodynamic damping and modal circular frequency corresponding to each mode of vibration of the long flexible blade under each operating condition, the aerodynamic damping ratio corresponding to each mode of vibration of the long flexible blade under each operating condition is calculated.

4. The method according to claim 1, characterized in that, Based on the aerodynamic damping ratios corresponding to the mode shapes of the long flexible blade under each operating condition, key design variables for the long flexible blade under each operating condition are extracted from the blade layup design parameters, including: Obtain blade layup design parameters and sample the blade layup design parameters to obtain a statistical sample; wherein, the blade layup design parameters include multiple influencing parameters; The aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition is used as a reference parameter for the grey relational analysis method. The grey relational analysis method is then used to calculate the comparison sequence and reference sequence of the statistical sample under each operating condition. The reference sequence under each operating condition includes the aerodynamic damping ratio of each mode shape of the long flexible blade under each operating condition. The comparison sequence under each operating condition includes the target aerodynamic damping ratio of each mode shape of the long flexible blade under each operating condition under different influencing parameters. For each operating condition, the correlation coefficient of each mode shape under the operating condition is calculated based on the aerodynamic damping ratio of each mode shape in the comparison sequence under the operating condition and the target aerodynamic damping of each mode shape in the reference sequence under the operating condition. Based on the correlation coefficient of each mode shape under the aforementioned working condition, calculate the correlation degree of each mode shape under the aforementioned working condition. Based on the correlation of each mode shape under the aforementioned operating conditions, the key design variables of the long flexible blade under the aforementioned operating conditions are extracted from the blade layup design parameters.

5. The method according to claim 1, characterized in that, The optimization parameters of the associated design variables of the long flexible blade under each working condition are determined using preset optimization objectives and preset constraints, including: Using a non-dominated sorting genetic algorithm based on preset optimization objectives and preset constraints, the aerodynamic damping ratio of each mode of vibration of the long flexible blade under each operating condition is jointly optimized within the design range of the associated design variables of the long flexible blade under each operating condition to obtain the Pareto optimal solution; wherein, the Pareto optimal solution includes the optimization parameters of the associated design variables of the long flexible blade under each operating condition.

6. The method according to claim 5, characterized in that, The method further includes: For each operating condition, the displacement response of each long flexible blade of the wind turbine under the operating condition is simulated to obtain the first simulation result; The displacement response of each long flexible blade of the wind turbine after optimization under the above operating conditions is simulated to obtain the second simulation result; If the second simulation result indicates that the displacement amplitude of the flexible blade of the wind turbine after optimization is not less than the displacement amplitude of the flexible blade of the wind turbine indicated by the first simulation result, a corresponding prompt message is output, so that the corresponding technician can adjust the design range of the associated design variables of the flexible blade under the operating condition based on the prompt message.

7. A blade aeroelastic stability optimization system, characterized in that, The system includes: The data acquisition module is used to acquire blade information for each long flexible blade of the wind turbine. The aeroelastic calculation module is used to determine the flapping stiffness and oscillation stiffness of each blade section of the long flexible blade based on the blade information; and to determine the mode shape matrix and modal circular frequency of the long flexible blade using the flapping stiffness and oscillation stiffness of each blade section; wherein the mode shape matrix includes multiple mode shapes; and to calculate the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each operating condition. The parameter analysis module is used to extract the key design variables of the long flexible blade under each working condition from the blade layup design parameters based on the aerodynamic damping ratio corresponding to each mode shape of the long flexible blade under each working condition. The optimization design module is used to determine the optimization parameters of the associated design variables of the long flexible blade under each working condition using preset optimization objectives and preset constraints; and to optimize the long flexible blade using the optimization parameters of the long flexible blade under each working condition to obtain a long flexible blade adapted to each working condition.

8. The system according to claim 7, characterized in that, The aeroelastic calculation module, which determines the modal shape matrix and modal circular frequency of the long flexible blade using the flapping stiffness and oscillation stiffness of each blade section, is specifically used for: The stiffness matrix and mass matrix of each blade section are constructed using the flapping stiffness and teeter stiffness of each blade section. The stiffness matrix and mass matrix of each blade section are assembled to construct the Euler-Bernoulli beam model of the long flexible blade. Modal analysis was performed on the long flexible blade based on the Euler-Bernoulli beam model to obtain the modal shape matrix and modal circular frequency of the long flexible blade.

9. An electronic device, characterized in that, include: A processor and a memory are connected via a bus; wherein the processor is used to call and execute a program stored in the memory; The memory is used to store a program for implementing a blade aeroelastic stability optimization method as described in any one of claims 1-6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions for performing a blade aeroelastic stability optimization method as described in any one of claims 1-6.

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