An optimization method for the aeroelastic stability of wind turbine blades

Abstract

The present invention provides a design optimization method for the aeroelastic stability of a wind turbine blade. First, a segmented model of a complete blade including the aerodynamic profile and the detailed structural ply is established; then, the overall physical parameter characteristics of the blade are calculated through the blade parameter model to obtain the corresponding mechanical properties of the blade, and the distributions of the torsional stiffness and the flapwise stiffness of the blade are output; at the same time, through the wind turbine whole machine model, the rated operation condition of the wind turbine is simulated and calculated to obtain the variation curves of the rotational speed and the pitch angle; then, the stability of the wind turbine rotor aeroelasticity is calculated, and according to the results, the distributions of the torsional stiffness and the flapwise stiffness are optimized and improved through different optimization curves to improve the rotor stability; finally, the above-mentioned cyclic optimization steps for the torsional stiffness distribution of the blade are repeated to coordinate the coupling relationships between various objectives and between constraints and objectives, and to promote the modification of its torsional stiffness and flapwise stiffness variables to converge to the optimal solution or the optimal solution set of the aeroelastic stability of the rotor.

Description

Technical Field

[0001] The present invention relates to a special aerodynamic elastic stability optimization method for wind turbine blades in new energy, and belongs to the field of blade design. Background Art

[0002] The problem of aerodynamic elastic stability of blades is the key to the design of large horizontal axis wind turbines. Especially for the current wind turbine blades, they are getting larger and more flexible, and the aeroelastic stability problem of wind turbines has become even more important. The non-linear aeroelastic coupling characteristics of flexible wind turbine blades make the coupling phenomenon of bending and torsion modes more prominent, and the critical speed of blade instability may decrease. Aeroelastic coupling mainly includes the coupling between the internal structural forces of the whole machine and the external aerodynamic forces. Conducting a structural modal analysis of wind turbines not only avoids structural damage caused by the operation of wind turbine units in the resonance area, but more importantly, conducts an aeroelastic stability analysis on them, because aeroelastic instability has greater potential destructiveness. To ensure that the blades can be safely and stably put into application, it is necessary to deeply study the influence of their aeroelastic stability. Studying the aerodynamic damping characteristics and their evolution laws corresponding to each order mode of flexible blades and wind turbines under various working conditions has always been a research topic that has received much attention in the field of wind turbine aeroelastic stability research. Nevertheless, the research on the optimization problem of wind turbine aeroelastic stability is still very lacking, and a considerable amount of research is needed to fill the gaps in this field, and the present method proposes an aeroelastic stability optimization method for large flexible wind turbine blades.

[0003] However, the optimization problem of wind turbine blades has always been a very complex design problem that requires coupling many disciplines, involving disciplines such as aerodynamics, aeroelasticity, structure, and aerodynamic noise. There are many variables, optimization objectives, and constraints, and there are often conflicts between optimization objectives, which is a quite complex multi-objective optimization design problem. Restricted by the complexity of the problem, the current optimization design of wind turbine blades mainly aims at maximizing a single aerodynamic performance parameter, and then uses various single-objective optimization algorithms to deal with it. The representative ones are: (1) The classical blade design method given based on the blade element momentum theory; (2) The genetic algorithm is introduced into the field of wind turbine blade optimization design and has been widely used; (3) In the multi-objective optimization design of wind turbine blades, the objective weighting method is used to simplify the multi-objective problem into a single-objective problem and solve it with the help of the classical genetic algorithm, and certain effects have been achieved. However, the above optimization methods are all single-objective design ideas and cannot solve complex multi-objective optimization design problems. Therefore, the multi-disciplinary optimization design of wind turbine blades requires new ideas and efficient multi-objective optimization algorithms. Summary of the Invention

[0004] The present invention provides a design optimization method for the aeroelastic stability of wind turbine blades, and adopts the following technical solutions:

[0005] An optimization method for the aeroelastic stability of a wind turbine blade, comprising the following steps:

[0006] S1: Establish a complete blade model, construct a segmented blade model, calculate the overall mechanical properties of the blade model, and output the torsional stiffness and flapwise stiffness distributions of the blade;

[0007] S2: Use the blade model in S1 to establish a whole wind turbine model, conduct simulation on the whole wind turbine model, simulate and calculate the actual operating state of the wind turbine, obtain the variation relationships of the wind turbine's rotor speed and blade pitch angle with the wind speed, and output the operating simulation data of the whole wind turbine model;

[0008] S3: Calculate the aeroelastic stability of the wind turbine blade according to the operating simulation data of the whole wind turbine model in S2 (specifically whether it is the variation of the rotor speed and blade pitch angle with the wind speed), and calculate the aeroelastic stability of the wind turbine under the working conditions of wind speeds of plus and minus 5 m / s from the rated wind speed according to the simulation data;

[0009] S4: According to the aeroelastic damping ratio curve of the wind turbine blade calculated in S3, if all modes are positive damping, the blade stability can be considered; if negative damping appears in one or several of the modes, the blade is considered unstable;

[0010] S5: Conduct optimization calculation on the blade cross-section and calculate the optimization coefficient curve;

[0011] S6: Recalculate the torsional stiffness and flapwise stiffness distributions of the blade model according to the optimization results in S5, and repeat S2 to S4 to re-conduct the blade stability analysis;

[0012] S7: If the blade is stable, export the optimization coefficient curve of the blade stability and calculate the sum of the coefficients of the blade cross-section; if the blade is unstable, repeat S6 to conduct the blade cross-section optimization calculation;

[0013] S8: Cyclically conduct the blade cross-section optimization calculation, export the coefficient sum, and converge to the optimal solution or optimal solution set of the blade aeroelastic stability.

[0014] Furthermore, the parameters of the complete blade model in S1 include the aerodynamic shape and detailed structural ply, and the overall mechanical properties of the blade are calculated through the classical laminated plate theory. Specifically:

[0015] S11: Select the standard airfoil section of the blade for segmentation, and do not process other sections of the blade for the time being;

[0016] S12: Conduct segmented cross-sections on each standard airfoil section of the blade. The segments are longer near the blade root and the segmented cross-sections are sparser, while the segments are shorter near the blade tip and the segmented cross-sections are denser, so as to make the calculation of the blade tip part more accurate;

[0017] S13, the blade segment length is kept below 5 meters;

[0018] S14, the angle of attack change of each segmented blade does not exceed 5°;

[0019] S15, the twist angle change of each segmented web is less than 5°;

[0020] S16, when using the classical laminated plate theory for calculation, the data of the blade segmented cross-section that has been processed for the standard airfoil section of the blade is subjected to secondary average segmentation, ensuring that the segment length of the calculated segmented model is less than 0.5 meters, so that the calculation accuracy of the torsional stiffness and flapping stiffness distribution of the blade reaches more than 99.5%.

[0021] Furthermore, in S2, the actual rated operating condition of the wind turbine whole machine model is simulated, and the relationship between the wind turbine rotor speed and the blade pitch angle with the change of wind speed is calculated:

[0022] S21, the wind speed of the simulated condition slowly increases from 0 until it is greater than the rated wind speed of 10 m / s;

[0023] S22, after reaching the rated wind speed, ensure that the rotation speed of the wind turbine whole machine model is stable at the rated speed;

[0024] S23, export the relationship curve between the rotor speed and the blade pitch angle with the change of wind speed.

[0025] Furthermore, S3 is specifically as follows:

[0026] S31, calculate the natural frequencies of each order of the wind turbine, input for actual condition simulation in S2, adjust the blade pitch angle at the blade tip under different wind speeds, and ensure that the wind turbine is stable at the rated speed;

[0027] S32, calculate the aeroelastic frequency and aeroelastic damping ratio of the wind turbine under the working conditions of wind speeds of plus and minus 5 m / s of the rated wind speed.

[0028] Furthermore, in S4:

[0029] S41, calculate the aeroelastic frequency and aeroelastic damping ratio of the wind turbine under different wind speeds when the tip speed ratio of the blade is certain. If the first ten modes of the blade are all positive damping, it indicates that the wind turbine blade is stable under this working condition. If one or several of the modes show negative damping, it indicates that the wind turbine blade may undergo aeroelastic instability under this working condition;

[0030] S42, the final optimization goal is to ensure that the aeroelastic damping ratio of the first ten modes is greater than 0.2% under all working conditions.

[0031] Furthermore, in S5:

[0032] S51. Optimize the torsional stiffness and flapping stiffness of each blade cross-section through a high-precision optimization algorithm according to the calculated stability of the wind turbine blade.

[0033] S52. Perform optimization calculations for each standard airfoil cross-section of the blade and perform interpolation processing for the remaining blade cross-sections.

[0034] S53. According to the optimization calculation results of each standard airfoil cross-section of the blade, use the rational quartic Heimite algorithm to fit the curve, let be each interpolation point, and set the function , where x n is the interpolation point, n is the number of standard airfoil cross-sections, the value range of i is 1~n, is the curve shape parameter, L is the fitted curve, and the shortest sum of L is the optimized fitted curve.

[0035] S54. The optimization coefficient value of each standard airfoil cross-section of the blade is between 0.7 and 1.4.

[0036] S55. The slope change of the fitted curve is within plus or minus 1.

[0037] Furthermore, in S6, according to the fitted curve in S5, recalculate the torsional stiffness and flapping stiffness distributions and perform stability optimization calculations again:

[0038] S61. The aeroelastic stability optimization is mainly based on torsional stiffness and supplemented by flapping stiffness, and the obtained objective function is

[0039] , where a is the optimization weight coefficient of torsional stiffness, b is the optimization weight coefficient of flapping stiffness, j is the torsional stiffness coefficient, k is the flapping stiffness coefficient, and n is the number of standard airfoil cross-sections.

[0040] S62. Substitute the standard airfoil cross-section of the blade into the fitted curve in S5 to calculate the new torsional stiffness and flapping stiffness distributions of the blade.

[0041] Furthermore, in S7, calculate the sum of the coefficients of the blade cross-section: , where, is the stiffness optimization coefficient of the nth blade cross-section, and n is the number of standard airfoil cross-sections.

[0042] Furthermore, in S8, perform cyclic optimization calculations for the blade cross-sections, record the sum of the coefficients of all stable blade cross-sections until the optimization converges to the optimal solution or optimal solution set of the blade aeroelastic stability. First, find the best optimization curve to make the blade as light as possible, that is, the corresponding sum of coefficients is the smallest; second, the convergence condition is that the reduction of the sum of coefficients obtained in each optimization is stable at one ten-thousandth.

[0043] The aerodynamic elastic stability optimization method for wind turbine blades provided by the present invention has the following beneficial effects:

[0044] 1. For the bending-torsion coupling mode, based on the high-precision stiffness distribution and the whole machine operation simulation data, a relatively simple and effective aerodynamic elastic stability optimization method is constructed, and a high-precision segmented model is used to provide a data basis for subsequent optimization calculations.

[0045] 2. The aerodynamic elastic stability optimization method starts from the structural angle to optimize the blade, and optimizes and improves the overall torsional stiffness and flapping stiffness distribution of the blade, which has little influence on the aerodynamic shape and is simple to optimize.

[0046] 3. The aerodynamic elastic stability optimization algorithm aims at aerodynamic elastic stability, takes into account the blade mass, coordinates the coupling relationship between various objectives and between constraints and objectives, and has a high cyclic iteration efficiency, which significantly improves the aerodynamic elastic damping ratio of the blade.

[0047] 4. For the constructed aerodynamic elastic stability optimization algorithm, the flapping stiffness and torsional stiffness distribution at the typical cross-sections of the blade are selected as the optimization basis, and the rational quartic Heimite algorithm is used for curve fitting and data interpolation, which greatly reduces the number of optimization iterations, reduces the optimization calculation amount, and improves the optimization speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a schematic flow chart of the optimization method of the present invention;

[0049] Figure 2 is the original torsional stiffness distribution along the span of the reference blade and the torsional stiffness distribution after stability optimization;

[0050] Figure 3 is the original flapping stiffness distribution along the span of the reference blade and the flapping stiffness distribution after stability optimization;

[0051] Figure 4 is the torsional stiffness optimization coefficient obtained after aerodynamic elastic stability optimization for six selected cross-sections of the reference blade, and the fitted curve;

[0052] Figure 5 is the flapping stiffness optimization coefficient obtained after aerodynamic elastic stability optimization for six selected cross-sections of the reference blade, and the fitted curve;

[0053] Figure 6 is the curve of the first-order damping ratio varying with the wind speed calculated after the reference blade is optimized;

[0054] Figure 7 is the curve of the second-order damping ratio varying with the wind speed calculated after the reference blade is optimized. DETAILED DESCRIPTION OF THE INVENTION

[0055] In order to make the technical means, creative features, achieved purposes and effects realized by the present invention easy to understand, the following specifically describes the optimization design method of the wind turbine blade considering aerodynamic efficiency and aerodynamic load in combination with embodiments and drawings.

[0056] Step 1 of the present invention is to establish a complete parametric model of the blade, construct a segmented model of the blade, preferably select to segment at the standard airfoil section of the blade, and divide the blade into 7-8 segments with longer lengths; secondly, randomly select segmented sections between different standard airfoils, and divide each longer segment into shorter and more stable small segments, ensuring that the segmented length of the blade remains below 5 meters, the angle of attack change of each segmented blade does not exceed 5°, and the twist angle change of each segmented web remains less than 5°. Then, based on the detailed aerodynamic structure model of the blade, calculate the overall torsional stiffness and flapping stiffness distribution data of the blade. Before finally calculating the overall physical properties of the blade, perform average interpolation on each segment of the original segmented model to further subdivide the blade and control the segment length to below 0.5 meters.

[0057] Step 2 is to establish a whole wind turbine model, simulate and simulate the whole wind turbine model, calculate the actual operating state of the wind turbine by simulation, and obtain the relationship between the wind turbine speed and the pitch angle with the wind speed. The wind speed slowly increases from 0 until it is greater than the rated wind speed of 10 m / s. After reaching a certain wind speed, it is necessary to ensure that the wind turbine speed can be stabilized at the rated speed.

[0058] In step 3, first calculate the natural frequencies of each order of the wind turbine structure, and then, according to the previous wind turbine simulation data, adjust the blade pitch angles at different wind speeds to ensure that the wind turbine operates stably at the rated speed, analyze and calculate the stability of the wind turbine rotor aeroelasticity, and calculate the aeroelastic frequencies and aeroelastic damping ratios under the working conditions of wind speeds of plus and minus 5 m / s of the rated wind speed of the wind turbine.

[0059] In step 4, calculate the aeroelastic frequencies and aeroelastic damping ratios at different wind speeds when the tip speed ratio of the wind turbine is certain. If the first ten modes of the rotor are all positive damping, it indicates that the rotor is stable. If one or several of these modes have negative damping, it indicates that the wind turbine may undergo aeroelastic instability under this working condition. Finally, the optimization goal of this method is to ensure that the aeroelastic damping ratios of the first ten modes in all working conditions are greater than 0.2%.

[0060] In step 5, according to the calculated rotor stability, the computer optimizes the torsional stiffness and flapping stiffness of each cross-section of the blade through a high-precision optimization algorithm. Considering the efficiency of the calculation method, the computer optimizes the calculation of each standard airfoil cross-section of the blade, and performs interpolation processing on the remaining cross-sections. According to the optimization results of each standard airfoil cross-section, use the rational quartic Heimite algorithm for curve fitting:

[0061] Let be each interpolation point, and set the function

[0062]

[0063] where x n is the interpolation point, n is the number of standard airfoil sections, and the value range of i is from 1 to n. is the curve shape parameter. Taking the shortest sum as the closest optimized fitting curve. In addition, the optimized coefficient of each section takes values between 0.7 and 1.4, and the slope change of the fitting curve cannot be too large, and it needs to be ensured to be within plus or minus 1.

[0064] Step 6 According to the optimization calculation of the computer, substitute the obtained coefficient curve, modify the torsion and flapping stiffness distributions, and conduct a stability analysis again.

[0065] Step 7 Export the optimized curves of all blades passing the stability analysis, and calculate the sum of the corresponding section coefficients of the exported curves: is the stiffness optimization coefficient of the nth blade section, and n is the number of standard airfoil sections.

[0066] Step 8 Conduct cyclic optimization for the blades, record the sum of the coefficients of all stable blades, find the best optimized curve to make the blades as light as possible, that is, the corresponding sum of coefficients is the smallest, and the convergence condition is that the reduction amount of the sum of coefficients obtained from each optimization is stable at one ten-thousandth.

[0067] In the embodiment of the present invention, taking an actual wind turbine rotor blade with a design length of 90 m as the original reference blade, the optimization of the original reference blade is specifically described by optimizing the torsion stiffness and flapping stiffness distributions of the wind turbine blade.

[0068] First, establish a complete blade parametric model, construct a blade segmented model, preferably select to segment at the standard airfoil sections of the blade, and conduct normalization processing for the blade along the span. Therefore, six standard airfoil sections at 9.5%, 25.5%, 47.7%, 63.8%, 79.8%, and 95.7% are selected; secondly, randomly select segmented sections between different standard airfoils to ensure that the segmented length of the blade remains less than 5 m, the angle of attack change of each segmented blade does not exceed 5°, and the torsion angle change of each segmented web remains less than 5°. Based on the aerodynamic and structural integrated segmented model of the blade, calculate the torsion stiffness and flapping stiffness distribution data of the whole blade. Before calculating the overall physical properties of the blade, average interpolation should be performed for each segment of the original segmented model to further subdivide the blade and ensure that the non-linear calculation accuracy of the blade reaches more than 99.5% to obtain the torsion stiffness and flapping stiffness curves of the reference blade.

[0069] A wind turbine whole machine model including a reference blade is established, and the operating state of the wind turbine is simulated at wind speeds from 0 m / s to 20 m / s to obtain the curves of rotational speed and pitch angle changes.

[0070] After obtaining the overall physical parameter characteristics of the blade, it is necessary to calculate the aeroelastic stability of the corresponding wind turbine rotor. First, calculate the natural frequencies of each order of the wind turbine structure, solve the aeroelastic coupling characteristic equations of the wind turbine by the eigenvalue method, and calculate the aeroelastic frequencies and aeroelastic damping ratios of the rotor at wind speeds of 10 m / s, 11 m / s, 12 m / s, 13 m / s, 14 m / s, and 15 m / s according to the simulation data.

[0071] According to the calculated rotor stability, the computer optimizes the torsional stiffness and flapping stiffness of the six standard airfoil sections of the blade through the genetic algorithm, and performs curve fitting based on the optimization results. The optimization fitting curve for the torsional stiffness is:

[0072] Y = -11.337m 4 +21.482m 3 -15.025m 2 +5.4685m + 0.2424, where m represents the section position.

[0073] For the optimization fitting curve of the flapping stiffness:

[0074] Y = -2.1429m 4 +1.098m 3 +0.1928m 2 +1.1202m - 0.6203, where m represents the section position.

[0075] The remaining sections are interpolated. Through automatic repeated iteration by the computer, the optimal optimization curves of the blade torsional stiffness and flapping stiffness coefficients are found.

[0076] The above is only the preferred implementation mode of the present invention. The protection scope of the present invention is not limited to the above embodiments. All technical solutions within the idea of the present invention belong to the protection scope of the present invention. It should be pointed out that for those of ordinary skill in the art in this technical field, several improvements and refinements made without departing from the principle of the present invention should be regarded as within the protection scope of the present invention.

Claims

1. An optimization method for the aeroelastic stability of a wind turbine blade, characterized in that It includes the following steps: S1: Establish a complete blade model, construct a segmented blade model, calculate the overall mechanical properties of the blade model, and output the torsional stiffness and flapping stiffness distribution of the blade; S2: Use the blade model described in S1 to establish a whole wind turbine model, conduct simulation on the whole wind turbine model, simulate and calculate the actual operating state of the wind turbine, obtain the relationship between the wind turbine rotor speed and the blade pitch angle changing with the wind speed, and output the operation simulation data of the whole wind turbine model; S3: According to the operation simulation data of the whole wind turbine model in S2, calculate the stability of the blade aeroelasticity of the wind turbine, and calculate the aeroelastic stability of the wind turbine under the working conditions of wind speeds of plus and minus 5 m / s from the rated wind speed according to the simulation data; S4: According to the wind turbine blade aeroelastic damping ratio curve calculated in S3, if all modes are positive damping, the blade stability can be considered. If negative damping appears in one or several of these modes, the blade is considered unstable; S5: Conduct optimization calculation on the blade cross-section and calculate the optimization coefficient curve; S6: Recalculate the torsional stiffness and flapping stiffness distribution of the blade model according to the optimization result in S5, and repeat S2 to S4 to conduct blade stability analysis again; S7: If the blade is stable, export the optimization coefficient curve of the blade stability and calculate the sum of the coefficients of the blade cross-section; If the blade is unstable, repeat S6 to conduct optimization calculation on the blade cross-section; S8: Conduct cyclic optimization calculation on the blade cross-section, export the sum of coefficients, and converge to the optimal solution or optimal solution set of the blade aeroelastic stability.

2. The optimization method for the aeroelastic stability of a wind turbine blade according to claim 1, characterized in that, In the above-mentioned S1, the parameters of the complete blade model include the aerodynamic shape and detailed structure ply. The overall mechanical properties of the blade are calculated through the classical laminated plate theory. Specifically: S11: Select the standard airfoil section segments of the blade, and do not process other sections of the blade for the time being; S12: Conduct segmented cross-sections on each standard airfoil section of the blade. The segments near the blade root are longer and the segmented cross-sections are sparser. The segments near the blade tip are shorter and the segmented cross-sections are denser, making the calculation of the blade tip part more accurate; S13: The length of the blade segments is kept below 5 meters; S14: The angle of attack change of each segmented blade does not exceed 5°; S15: The twist angle change of the web of each segmented blade is less than 5°; S16: When using the classical laminated plate theory for calculation, conduct secondary average segmentation on the data of the blade segmented cross-sections that have been processed for the standard airfoil section of the blade, ensuring that the segment length of the calculated segmented model is less than 0.5 meters, and making the calculation accuracy of the torsional stiffness and flapping stiffness distribution of the blade reach more than 99.5%.

3. An optimization method for the aeroelastic stability of a wind turbine blade according to claim 2, characterized in that, In the above-mentioned S2, conduct simulation on the actual rated operating conditions of the whole wind turbine model and calculate the relationship between the wind turbine rotor speed and the blade pitch angle changing with the wind speed: S21: The wind speed of the simulation condition slowly increases from 0 until it is greater than the rated wind speed of 10 m / s; S22: After reaching the rated wind speed, ensure that the rotation speed of the whole wind turbine model is stable at the rated rotation speed; S23: Export the curve of the relationship between the rotor speed and the blade pitch angle changing with the wind speed.

4. An optimization method for the aeroelastic stability of a wind turbine blade according to claim 3, characterized in that, The above-mentioned S3 is specifically: S31. Calculate the natural frequencies of each order of the wind turbine modes, input them into the actual working condition simulation in S2, adjust the blade pitch angles at different wind speeds, and ensure that the wind turbine operates stably at the rated speed. S32. Calculate the aeroelastic frequencies and aeroelastic damping ratios of the wind turbine under the working conditions of wind speeds of plus and minus 5 m / s from the rated wind speed.

5. The optimization method for the aeroelastic stability of a wind turbine blade according to claim 4, wherein In the said S4: S41. Calculate the aeroelastic frequencies and aeroelastic damping ratios of the wind turbine at different wind speeds when the tip speed ratio is constant. If the first ten modes of the blade are all positive damping, it indicates that the wind turbine blade is stable under this working condition. If one or several of these modes show negative damping, it indicates that the wind turbine blade may undergo aeroelastic instability under this working condition. S42. The final optimization goal is to ensure that the aeroelastic damping ratios of the first ten modes are greater than 0.2% under all working conditions.

6. The optimization method for the aeroelastic stability of a wind turbine blade according to claim 5, characterized in that, In the said S5: S51. According to the calculated stability of the wind turbine blade, optimize the torsional stiffness and flapping stiffness of each section of the blade through a high-precision optimization algorithm. S52. Conduct optimization calculations for each standard airfoil section of each blade, and perform interpolation processing for the remaining blade sections. S53. According to the optimization calculation results of each blade standard airfoil section, the rational quartic Heimite algorithm is used to fit the curve, and let be each interpolation point, and set the function , L= dx where x n is the interpolation point, n is the number of standard airfoil sections, and the value range of i is from 1 to n. is the curve shape parameter, L is the fitting curve, and the shortest total L is the optimized fitting curve. S54. The optimization coefficient values for each standard airfoil section of each blade are between 0.7 and 1.

4. S55. The change in the slope of the fitted curve is within plus or minus 1.

7. An optimization method for the aeroelastic stability of a wind turbine blade according to claim 6, characterized in that, In the said S6, according to the fitted curve in S5, recalculate the distribution of torsional stiffness and flapping stiffness, and perform stability optimization calculations again: S61. The aeroelastic stability optimization is mainly based on torsional stiffness and supplemented by flapping stiffness. The obtained objective function is , where a is the optimization weight coefficient of the torsional stiffness, b is the optimization weight coefficient of the flapping stiffness, j is the torsional stiffness coefficient, k is the flapping stiffness coefficient, and n is the number of standard airfoil sections; S62. Substitute the standard airfoil section of the blade into the fitted curve in S5 to calculate the new distribution of the torsional stiffness and flapping stiffness of the blade.

8. An optimization method for the aeroelastic stability of a wind turbine blade according to claim 7, characterized in that, In the aforementioned S7, calculate the sum of the coefficients of the blade cross-sections: , where is the stiffness optimization coefficient of the nth blade cross-section, and n is the number of standard airfoil cross-sections.

9. The optimization method for the aeroelastic stability of a wind turbine blade according to claim 8, characterized in that In the said S8, perform cyclic blade section optimization calculations, record the sum of the coefficients of all stable blade sections until the optimization converges to the optimal solution or the set of optimal solutions for the aeroelastic stability of the blade. First, find the best optimization curve to make the blade as light as possible, that is, the corresponding sum of coefficients is the smallest. Second, the convergence condition is that the reduction in the sum of coefficients obtained from each optimization is stable at one ten-thousandth.

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