Pneumatic design method of wind power blade, electronic equipment and storage medium

Abstract

The invention relates to the technical field of wind power generation, particularly provides a pneumatic design method of a wind power blade, electronic equipment and a storage medium, and aims to solve the problems of how to reduce the weight of the blade and improve the power generation efficiency. In order to achieve the purpose, the aerodynamic design method of the wind power blade comprises the steps that basic design parameters are obtained; determining chord length distribution and torsional angle distribution of the blade based on the basic design parameters; determining the annual energy output of the wind turbine generator based on the chord length distribution and the torsional angle distribution; and performing twice optimization on the chord length distribution and the torsional angle distribution based on the annual energy output to obtain optimal solutions of the chord length distribution and the torsional angle distribution. Therefore, by optimizing chord length distribution and torsional angle distribution of the blade, the weight of the blade is remarkably reduced, the aerodynamic load is reduced, the working efficiency of a wind turbine generator is improved, and the stability and safety of the wind turbine blade are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation, and particularly provides a method for aerodynamic design of wind turbine blades, an electronic device, and a storage medium. Background Art

[0002] The blade is one of the most basic key components of a wind turbine. The aerodynamic performance of the blade determines the efficiency of the unit in extracting energy from the airflow. The aerodynamic load on the blade is the main load of the unit, which has an important impact on the fatigue characteristics and service life of the whole machine. Reasonable blade design is an important guarantee for the power generation efficiency and safety of wind turbines.

[0003] With the development of wind power technology, the unit capacity has been continuously improved, and ultra-large wind turbine blades have developed to more than one hundred meters. The increase in blade size is accompanied by a significant increase in blade weight, which poses severe challenges to blade structural safety and cost control. The lightweight design requirement for ultra-long flexible blades poses a challenge to blade aerodynamic design. How to reduce the blade weight, lower the load, and improve the power generation efficiency during the design process is a major difficulty in this field. Correspondingly, a new aerodynamic design method for wind turbine blades with high efficiency and low load characteristics is needed to solve the above problems. Summary of the Invention

[0004] In order to overcome the above defects, this application is proposed to provide a solution to solve or at least partially solve the above technical problems. This application provides a method for aerodynamic design of wind turbine blades, an electronic device, and a storage medium.

[0005] In a first aspect, this application provides a method for aerodynamic design of wind turbine blades, the method comprising:

[0006] Obtaining basic design parameters;

[0007] Determining the chord length distribution and twist angle distribution of the blade based on the basic design parameters;

[0008] Determining the annual power generation of the wind turbine based on the chord length distribution and the twist angle distribution;

[0009] Performing two optimizations on the chord length distribution and the twist angle distribution based on the annual power generation to obtain the optimal solutions of the chord length distribution and the twist angle distribution.

[0010] In an embodiment of this application, determining the chord length distribution and twist angle distribution of the blade based on the basic design parameters includes:

[0011] Determining a first mapping relationship between the chord length and the radial distance, and a second mapping relationship between the twist angle and the radial distance based on the basic design parameters, where the radial distance is the distance between each cross-section of the blade and the blade root;

[0012] Parametrize the first mapping relationship and the second mapping relationship to obtain the chord length distribution and the twist angle distribution.

[0013] In an embodiment of the present application, parametrizing the first mapping relationship and the second mapping relationship includes:

[0014] Obtain a first type of control points based on the first mapping relationship and the second mapping relationship;

[0015] Establish a Bezier curve based on the first type of control points;

[0016] Interpolate the Bezier curve to obtain a second type of control points.

[0017] In an embodiment of the present application, determining the annual power generation of a wind turbine based on the chord length distribution and the twist angle distribution includes:

[0018] Determine a third mapping relationship between the power coefficient and the tip speed ratio based on the chord length distribution and the twist angle distribution;

[0019] Determine the predicted power of the wind turbine based on the third mapping relationship;

[0020] Determine the annual power generation of the wind turbine based on the predicted power.

[0021] In an embodiment of the present application, performing a first optimization on the chord length distribution and the twist angle distribution includes:

[0022] Take maximizing the annual power generation and minimizing the root bending moment as the optimization objectives;

[0023] Establish an initial population, where the initial population includes multiple individuals;

[0024] Starting from the initial population, use the genetic algorithm to perform target optimization iteration to maximize the optimization objective;

[0025] When the optimization objective converges, obtain the Pareto front;

[0026] Obtain the preliminary solution of the chord length distribution and the preliminary solution of the twist angle distribution from the Pareto front.

[0027] In an embodiment of the present application, performing a second optimization on the chord length distribution and the twist angle distribution includes:

[0028] Update the preliminary solution of the twist angle distribution to obtain the updated twist angle distribution;

[0029] Keep the updated twist angle distribution unchanged, and use the genetic algorithm to perform target optimization iteration to optimize the preliminary solution of the chord length distribution to maximize the optimization objective;

[0030] When the optimization objective converges, the Pareto front is obtained;

[0031] The optimal solution of the chord length distribution and the optimal solution of the twist angle distribution are obtained from the Pareto front.

[0032] In an embodiment of the present application, the obtaining the updated twist angle distribution includes: reducing a preset angle from the preliminary solution of the twist angle distribution to obtain the updated twist angle distribution; where when the radial distance is 0, the preset angle is 0, and when the radial distance is in the range of [R1 / 3, R1], R1 is the blade length, the preset angle θ is the value in the following formula, and a smooth transition is performed in the range of [0, R1 / 3], θ = min(2, α s -α - 3)

[0033] In the above formula, θ is the preset angle, and α s is the stall angle of attack of the blade section, and α is the working angle of attack of the blade section under the rated wind speed condition.

[0034] In an embodiment of the present application, the obtaining the preliminary solution of the chord length distribution and the preliminary solution of the twist angle distribution from the Pareto front includes: selecting the corresponding solution from the Pareto front according to the tip speed ratio corresponding to the maximum power coefficient as the preliminary solution of the chord length distribution and the preliminary solution of the twist angle distribution; and / or

[0035] The obtaining the optimal solution of the chord length distribution and the optimal solution of the twist angle distribution from the Pareto front includes: selecting the final solution from the Pareto front according to the tip speed ratio corresponding to the maximum power coefficient as the optimal solution of the chord length distribution and the optimal solution of the twist angle distribution.

[0036] In a second aspect, there is provided an electronic device, including:

[0037] At least one processor;

[0038] And a memory communicatively connected to the at least one processor;

[0039] Wherein, a computer program is stored in the memory, and when the computer program is executed by the at least one processor, the foregoing aerodynamic design method of the wind turbine blade is implemented.

[0040] In a third aspect, there is provided a computer-readable storage medium, which stores a plurality of program codes, and the program codes are adapted to be loaded and run by a processor to execute the aerodynamic design method of the wind turbine blade described in any one of the foregoing items.

[0041] One or more of the above technical solutions of the present application have at least one or more of the following Beneficial effects:

[0042] The aerodynamic design method of the wind turbine blade in this application includes: obtaining basic design parameters; determining the chord length distribution and twist angle distribution of the blade based on the basic design parameters; determining the annual power generation of the wind turbine based on the chord length distribution and twist angle distribution; and performing two optimizations on the chord length distribution and twist angle distribution based on the annual power generation to obtain the optimal solutions of the chord length distribution and twist angle distribution. By optimizing the chord length distribution and twist angle distribution of the blade, the blade weight can be significantly reduced, the aerodynamic load can be reduced, the working efficiency of the wind turbine can be improved, and the stability and safety of the wind turbine blade can be enhanced. Brief description of the drawings

[0043] Referring to the drawings, the disclosure of this application will become more understandable. It is easy for those skilled in the art to understand that these drawings are only for illustrative purposes and are not intended to limit the protection scope of this application. In addition, similar numbers in the drawings are used to represent similar components, where:

[0044] Figure 1 is a schematic diagram of the main process of the aerodynamic design method of the wind turbine blade in an embodiment of this application;

[0045] Figure 2 is a schematic diagram of the chord length distribution curve in an embodiment of this application;

[0046] Figure 3 is a schematic diagram of the curve of the twist angle distribution in an embodiment of this application;

[0047] Figure 4 is a schematic diagram of the predicted power curve of the blade in an embodiment of this application;

[0048] Figure 5 is a schematic diagram of the power coefficient curve in an embodiment of this application;

[0049] Figure 6 is a schematic diagram of the thrust coefficient curve in an embodiment of this application;

[0050] Figure 7 is a schematic diagram of the main structure of the aerodynamic design device of the wind turbine blade in an embodiment of this application;

[0051] Figure 8 is a schematic diagram of the structure of the electronic device in an embodiment of this application. Detailed implementation manners

[0052] Some implementation manners of this application will be described below with reference to the drawings. Those skilled in the art should understand that these implementation manners are only used to explain the technical principle of this application and are not intended to limit the protection scope of this application.

[0053] In the description of the present application, a "module" and a "processor" may include hardware, software, or a combination of both. A module may include a hardware circuit, various appropriate sensors, communication ports, a memory, and may also include a software part, such as program code, or may be a combination of software and hardware. A processor may be a central processing unit, a microprocessor, an image processor, a digital signal processor, or any other appropriate processor. The processor has data and / or signal processing functions. The processor may be implemented in software, in hardware, or in a combination of both. A non-transitory computer-readable storage medium includes any appropriate medium that can store program code, such as a magnetic disk, a hard disk, an optical disk, a flash memory, a read-only memory, a random access memory, and so on. The term "A and / or B" represents all possible combinations of A and B, such as only A, only B, or A and B. The term "at least one of A or B" or "at least one of A and B" has a meaning similar to "A and / or B" and may include only A, only B, or A and B. The singular terms "a" and "the" may also include the plural form.

[0054] Currently, the increase in the size of traditional blades is accompanied by a significant increase in blade weight, which poses a severe challenge to blade structural safety and cost control. The lightweight design requirement for ultra-long flexible blades poses a challenge to blade aerodynamic design. How to reduce blade weight, lower loads, and improve power generation efficiency during the design process is a major difficulty in this field.

[0055] To this end, the present application proposes an aerodynamic design method, an electronic device, and a storage medium for a wind turbine blade.

[0056] Refer to the attached Figure 1 , Figure 1 which is a schematic diagram of the main step flow of an aerodynamic design method for a wind turbine blade according to an embodiment of the present application.

[0057] As Figure 1 shown, the aerodynamic design method for a wind turbine blade in the embodiment of the present application mainly includes the following steps S10 - step S40.

[0058] Step S10: Obtain basic design parameters.

[0059] Step S20: Determine the chord length distribution and the twist angle distribution of the blade based on the basic design parameters.

[0060] Step S30: Determine the annual power generation of the wind turbine based on the chord length distribution and the twist angle distribution.

[0061] Step S40: Optimize the chord length distribution and the twist angle distribution twice based on the annual power generation to obtain the optimal solutions of the chord length distribution and the twist angle distribution.

[0062] Based on the above steps S10 - S40, first obtain the basic design parameters; determine the chord length distribution and twist angle distribution of the blade based on the basic design parameters; determine the annual power generation of the wind turbine based on the chord length distribution and twist angle distribution; optimize the chord length distribution and twist angle distribution twice based on the annual power generation to obtain the optimal solutions of the chord length distribution and twist angle distribution. By optimizing the chord length distribution and twist angle distribution of the blade, the blade weight can be significantly reduced, the aerodynamic load can be reduced, the working efficiency of the wind turbine can be improved, and the stability and safety of the wind turbine blade can be enhanced.

[0063] The above steps S10 to S40 will be further described below.

[0064] Specifically for the above step S10, the basic design parameters may include the airfoil of the blade to be used, blade length, maximum chord length and its position, root pitch diameter, hub diameter, maximum and minimum rotational speeds, cut-in and cut-out wind speeds, rated power of the wind turbine, relative thickness distribution, tip speed ratio corresponding to the maximum power coefficient of the wind turbine, etc.

[0065] The above is the further description of step S10. Next, the further description of step S20 will be continued.

[0066] The above step S20 can be implemented through the following steps S201 to S202.

[0067] Step S201: Determine the first mapping relationship between the chord length and the radial distance, and the second mapping relationship between the twist angle and the radial distance based on the basic design parameters, where the radial distance is the distance between each section of the blade and the root.

[0068] The first mapping relationship is the mapping relationship between the chord length of the blade and the distance from each section of the blade to the root. The second mapping relationship is the mapping relationship between the twist angle of the blade and the distance from each section of the blade to the root. Exemplarily, a curve can be used as an example of the mapping relationship, and no specific limitation is made thereto.

[0069] Specifically, determine the tip speed ratio λ0 according to the rotational speed of the wind turbine:

[0070] In the above formula, λ0 is the tip speed ratio, ω is the angular velocity of the blade rotation, R is the radius of the wind turbine, v is the incoming flow wind speed, R1 is the blade length, and R hub is the hub radius.

[0071] Exemplarily, the first mapping relationship can be a linear relationship between the chord length of the blade and the distance (radial distance) from each cross-section of the blade to the blade root, and the second mapping relationship can be a linear relationship between the twist angle of the blade and the distance (radial distance) from each cross-section of the blade to the blade root. The specific linear relationship can be obtained by manual setting and can be adaptively adjusted according to the actual scenario, and no specific limitation is made thereto.

[0072] Step S202: Parameterize the first mapping relationship and the second mapping relationship to obtain the chord length distribution and the twist angle distribution.

[0073] Specifically, the above step S202 can be implemented through the following steps S2021 to S2023.

[0074] Step S2021: Obtain the first type of control points based on the first mapping relationship and the second mapping relationship.

[0075] The first type of control points are the key control points of the chord length distribution and the twist angle distribution.

[0076] To ensure the continuity of the geometric aerodynamic shape, the Bezier curve is used to parameterize the first mapping relationship and the second mapping relationship.

[0077] Exemplarily, in a specific embodiment of the present application, it is assumed that the coordinates of n control points of the chord length and the twist angle distributed along the radial direction are [X C , Y C and [X β , Y C : X C = [x c1 , x c2 , x c3 , …, x cn ; Y C = [y c1 , y c2 , y c3 , …, y cn ; X β = [x β1 , x β2 , x β3 , …, y βn ; Y β = [y β1 , y β2 , y β3 , …, y βn ;

[0078] Where X C , Y C , X β , Y βThey respectively represent the distance of the chord length control point from the blade root, the chord length value of the chord length control point, the distance of the twist angle control point from the blade root, and the twist angle value of the twist angle control point.

[0079] The Bezier Curve is used to represent the parametric scheme. The connection line of the control points is the boundary of the obtained curve. The key control points (the first type of control points) of the distribution curve can be:

[0080] For the chord length curve: the starting control point is [0, D root , the maximum chord length control point is [X Cmax , C max , and the tip control point is [1, 0];

[0081] For the twist angle curve: the starting control point is [0, β root , the maximum twist angle control point is [X βmax , β max , and the tip control point is [1, β tip .

[0082] Among them, D root is the root diameter, X Cmax is the coordinate when obtaining the maximum chord length C max ; β root is the twist angle at the root, X βmax is the coordinate when obtaining the maximum twist angle β max , and β tip is the twist angle at the tip.

[0083] Step S2022: Establish a Bezier curve based on the first type of control points.

[0084] Specifically, according to the above control points, the relationship between the Bezier curve and the key control points can be established as B = g(X, Y).

[0085] Step S2023: Interpolate the Bezier curve to obtain the second type of control points.

[0086] The second type of control points are the control points obtained by interpolation.

[0087] Specifically, interpolating the Bezier curve can obtain the second type of control points, that is, the corresponding chord length distribution and twist angle distribution C = B(X C ), β = B(X β ).

[0088] That is to say, two segments of curves can be adopted to ensure that the positions of the starting point and the maximum point of the curve remain unchanged. The first segment of the Bezier curve is from the blade root to the maximum value of the chord length or the twist angle, and the second segment of the Bezier curve is from the maximum value to the blade tip. Exemplarily, the control points of the first segment of the curve can be 4, and the second segment can be freely selected. Since the description range is relatively large, it can be 5 or more. Exemplarily, the following curves can be used as examples of the two segments of the Bezier curve:

[0089] The first segment:

[0090] X: 0 → X Cmax or X βmax X C = [0, x c2 , x c3 , 0.2]; Y C = [D root , y c2 , y c3 , C max ; X β = [0, x β2 , x β3 , 0.08]; Y β = [y β1 , y β2 , y β3 , β max ;

[0091] The second segment:

[0092] X: X Cmax or X βmax → 1 X C = [0.2, x c6 , x c7 , …, 1]; Y C = [C max , y c6 , y c7 , …, 0]; X β = [0.08, x β6 , x β7 , …, 1]; Y β = [β max , y β6 , y β7 , …, y βn ;

[0093] The chord length distribution curve and the twist angle distribution curve can be obtained through the above steps.

[0094] The above is a further description of step S20. Next, step S30 will be further described.

[0095] The above-mentioned step S30 can be implemented through the following steps S301 to S303.

[0096] Step S301: Determine the third mapping relationship between the power coefficient and the tip speed ratio based on the chord length distribution and the twist angle distribution.

[0097] Specifically, according to the chord length distribution and the twist angle distribution curves, the third mapping relationship between the power coefficient and the tip speed ratio can be obtained by using the blade element momentum theory (BEM).

[0098] In an embodiment of the present application, the expression of the power coefficient can be:

[0099] where C P is the power coefficient, ω is the angular velocity of the blade rotation, V is the oncoming wind speed, R is the wind turbine radius, a is the axial induction factor, b is the tangential induction factor, r is the distance of the blade section from the root of the blade, σ is the local solidity, C n is the axial force coefficient, C t is the tangential force coefficient, B is the number of blades, c is the chord length of the blade element profile, is the oncoming flow angle at the blade element (related to β(r)).

[0100] Step S302: Determine the predicted power of the wind turbine based on the third mapping relationship.

[0101] Specifically, the expression of the predicted power P(v) is:

[0102] where ρ is the air density, η is the mechanical loss and electrical loss coefficient, C P is the power coefficient, and v is the oncoming wind speed.

[0103] Step S303: Determine the annual power generation of the wind turbine based on the predicted power.

[0104] Specifically, the calculation formula for determining the annual power generation according to the predicted power is: P t = 8760·P(v)·w(v)

[0105] where P t is the annual power generation, P(v) is the predicted power, w(v) is the Weibull distribution probability density function, u is the annual average wind speed, and v s is the wind speed value interval.

[0106] The above is a further description of step S30. Next, a further description of step S40 will be continued.

[0107] The above step S40 can be implemented through the following steps S401 to S403.

[0108] Step S401: Take maximizing the annual power generation and minimizing the blade root bending moment as the optimization objectives.

[0109] Specifically, maximizing the annual power generation and minimizing the blade root bending moment can be taken as the optimization objectives.

[0110] Step S402: Establish an initial population, where the initial population includes multiple individuals, and each individual is the coordinate values of the control points in the first and second Bessel curves, specifically including the chord lengths and twist angles of the control points distributed along the radial direction.

[0111] Specifically, establish an initial population and set the population size and the maximum number of genetic generations. Exemplarily, the population size can be set to 200, and the maximum number of genetic generations can be set to 250.

[0112] Step S403: Starting from the initial population, use the genetic algorithm to perform target optimization iteration to maximize the optimization objectives.

[0113] Specifically, the genetic algorithm function "ga" in MATLAB can be used for single-objective optimization, which means finding the minimum value of the objective function through the genetic algorithm. At the initial stage of the optimization, the numerical stability of the function will be tested. If an error is reported, the objective function needs to be modified according to the prompt. During the optimization process, there may be situations where the BEM calculation returns null values, infinite values, complex numbers, etc. The calculation program needs to be optimized to enhance the robustness of the optimization process.

[0114] Step S404: When the optimization objectives converge, obtain the Pareto front, and further select the corresponding solutions from the Pareto front as the preliminary solutions of the chord length distribution and the twist angle distribution according to the tip speed ratio corresponding to the maximum power coefficient.

[0115] The Pareto front, also known as the Pareto optimal boundary or non-dominated solution set, is an important concept in multi-objective optimization problems.

[0116] Specifically, when the optimization objectives converge, the Pareto front can be obtained. Further, obtain the tip speed ratio corresponding to the maximum power coefficient, and take the chord length and twist angle corresponding to this tip speed ratio as the preliminary solutions of the chord length distribution and the twist angle distribution respectively.

[0117] Step S405: Update the preliminary solution of the twist angle distribution to obtain the updated twist angle distribution.

[0118] Specifically, the update of the preliminary solution of the twist angle distribution can be achieved by increasing or decreasing a preset value for the preliminary solution of the twist angle distribution.

[0119] In a specific embodiment of the present application, obtaining the updated twist angle distribution includes: reducing a preset angle from the preliminary solution of the twist angle distribution to obtain the updated twist angle distribution; where when the radial distance is 0, the preset angle is 0, and when the radial distance is within the range of [R1 / 3, R1], R1 is the blade length, the preset angle θ is the value in the following formula, and a smooth transition is performed in the range of [0, R1 / 3]. θ = min(2, α s -α - 3)

[0120] In the above formula, θ is the preset angle, and α s is the stall angle of attack of the blade section, and α is the working angle of attack of the blade section under the rated wind speed condition.

[0121] Specifically, for the twist angle distribution of the preliminary solution, the twist angle is appropriately reduced to obtain a new twist angle distribution. For example, the twist angle in the main power output area of the blade can be reduced by a preset angle θ, the root of the blade remains unchanged, and a smooth transition is made in the middle section. The smooth transition means that the twist angle needs to smoothly transition from 0 to θ when in the range of [0, R1 / 3]. In a specific embodiment, the main power output area of the blade is set as the part from the 60% blade length radial position to the blade tip.

[0122] Step S406: Keep the updated twist angle distribution unchanged, and use the genetic algorithm to perform target optimization iteration to optimize the preliminary solution of the chord length distribution to maximize the optimization target and minimize the root bending moment.

[0123] Specifically, the twist angle distribution adopts the result obtained in step S405 and remains unchanged, only the chord length distribution is optimized, and other settings remain unchanged, and the multi-objective optimization process is performed again.

[0124] Exemplarily, a multi-objective genetic algorithm is selected for optimization calculation. Taking the position of the maximum chord length as the boundary, two Bezier curves are used to control the chord length distribution, and one Bezier curve is used to control the twist angle distribution. To ensure that the root pitch diameter, the maximum chord length, the maximum twist angle, etc. are design values and the curve change rate is reasonable, the coordinates of some control points are set as fixed values.

[0125] Exemplarily, the annual average wind speed is 8.5 m / s, the cut-in wind speed is 3 m / s, the cut-out wind speed is 25 m / s, and a series of values with the value range of the incoming flow wind speed v from 3 to 25 and an interval of 0.1 are set, that is, vs = 0.1. Among the series of solutions, the solution with the tip speed ratio corresponding to the maximum power coefficient being 11.5 is selected as the preliminary solution.

[0126] Step S407: When the optimization target converges, obtain the Pareto front.

[0127] The Pareto front, also known as the Pareto optimal boundary or non-dominated solution set, is an important concept in multi-objective optimization problems.

[0128] Specifically, when the optimization objectives converge, the Pareto front can be obtained.

[0129] Step S408: Obtain the optimal solution of the chord length distribution and the optimal solution of the twist angle distribution from the Pareto front.

[0130] In a specific embodiment of the present application, the obtaining of the optimal solution of the chord length distribution and the optimal solution of the twist angle distribution from the Pareto front includes: selecting the final solution from the Pareto front as the optimal solution of the chord length distribution and the optimal solution of the twist angle distribution according to the tip speed ratio corresponding to the maximum power coefficient.

[0131] Specifically, the tip speed ratio corresponding to the maximum power coefficient can be obtained, and finally the chord length and twist angle corresponding to this tip speed ratio are respectively used as the optimal solution of the chord length distribution and the optimal solution of the twist angle distribution.

[0132] In a specific embodiment, an aerodynamic design is carried out on a wind turbine blade with a length of 123 meters. Figure 2 It can be a schematic diagram of the chord length distribution curve; Figure 3 It can be a curve schematic diagram of the twist angle distribution; Figure 4 It can be a schematic diagram of the predicted power curve of the blade; Figure 5 It can be a schematic diagram of the power coefficient curve; Figure 6 It can be a schematic diagram of the thrust coefficient curve. Among them Figures 2 to 6 Curve 1 in the figure represents the blade obtained by the existing method, and curve 2 represents the blade obtained by the method of the present application. The annual power generation of the blade obtained by the general method is 82.20 GW, and the maximum bending moment at the blade root is 44.30 MNm; the annual power generation of the blade obtained by the method of the present application is 81.96 GW, and the maximum bending moment at the blade root is 43.25 MNm. It can be seen that the present application effectively reduces the chord length of the blade by reducing the twist angle, with little change in the blade output and power performance, which is beneficial to reducing the blade weight, reducing the aerodynamic load, and improving the operation efficiency.

[0133] Through the multi-objective optimization method, the aerodynamic design results of the blade with high annual power generation and small blade aerodynamic load can be obtained conveniently and simply, and the overall optimal result can be obtained. At the same time, a series of optimal solutions are obtained, and the designer can select a suitable blade design scheme according to needs. Compared with the conventional method, the blade designed by the present application has a smaller chord length, a lighter blade weight and a lower aerodynamic load, greatly improving the working efficiency of the blade, and can effectively improve the design efficiency and accuracy of the wind turbine blade, and enhance the performance and safety of the wind turbine blade.

[0134] It should be noted that although the above embodiments describe the various steps in a specific order, those skilled in the art can understand that in order to achieve the effects of the present application, different steps do not necessarily have to be executed in such an order. They can be executed simultaneously (in parallel) or in other orders, and these variations are within the protection scope of the present application.

[0135] Furthermore, the present application also provides an aerodynamic design device for a wind turbine blade.

[0136] Refer to the attached Figure 7 , Figure 7 which is the main structural block diagram of the aerodynamic design device for a wind turbine blade according to an embodiment of the present application.

[0137] As Figure 7 shown, the aerodynamic design device for a wind turbine blade in the embodiments of the present application mainly includes an acquisition module 11, a first determination module 12, a second determination module 13, and an optimization module 14. In some embodiments, one or more of the acquisition module 11, the first determination module 12, the second determination module 13, and the optimization module 14 can be combined into one module.

[0138] In some embodiments, the acquisition module 11 can be configured to acquire basic design parameters.

[0139] The first determination module 12 can be configured to determine the chord length distribution and twist angle distribution of the blade based on the basic design parameters.

[0140] The second determination module 13 can be configured to determine the annual power generation of the wind turbine based on the chord length distribution and the twist angle distribution.

[0141] The optimization module 14 can be configured to perform two optimizations on the chord length distribution and the twist angle distribution based on the annual power generation to obtain the optimal solutions of the chord length distribution and the twist angle distribution.

[0142] In one implementation manner, the description of the specific implementation functions can be referred to the steps S10 - S40.

[0143] The above - mentioned aerodynamic design device for a wind turbine blade is used to execute Figure 1 the embodiments of the aerodynamic design method for a wind turbine blade shown. The technical principles, the technical problems solved, and the technical effects produced by the two are similar. Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working process and related descriptions of the aerodynamic design device for a wind turbine blade can refer to the content described in the embodiments of the aerodynamic design method for a wind turbine blade, and will not be elaborated here.

[0144] Furthermore, it should be understood that since the settings of the respective modules are only for illustrating the functional units of the device of the present application, the physical devices corresponding to these modules can be the processor itself, or a part of the software in the processor, a part of the hardware, or a part of the combination of software and hardware. Therefore, the number of each module in the figure is only illustrative.

[0145] Those skilled in the art can understand that the respective modules in the device can be adaptively split or combined. Such splitting or combining of specific modules will not cause the technical solution to deviate from the principle of the present application. Therefore, the technical solutions after splitting or combining will all fall within the protection scope of the present application.

[0146] Those skilled in the art can understand that all or part of the processes in the method of the above-mentioned embodiment of the present application can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable storage medium can include: any entity or device, medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal, and software distribution medium, etc., that can carry the computer program code.

[0147] Furthermore, the present application also provides an electronic device, which may include at least one processor; and a memory communicatively connected to the at least one processor; wherein, a computer program is stored in the memory, and when the computer program is executed by the at least one processor, the aerodynamic design method of the wind turbine blade described in any of the above embodiments is implemented. See Figure 8 as shown Figure 8 The structure of the electronic device is exemplarily shown in, which includes a processor 100 and a memory 200.

[0148] In some embodiments of the present application, the electronic device further includes at least one sensor for sensing information. The sensor is communicatively connected to any type of processor mentioned in the present application. Optionally, the electronic device further includes an autonomous driving system for guiding the electronic device to drive itself or assist in driving. The processor communicates with the sensor and / or the autonomous driving system to implement the aerodynamic design method of the wind turbine blade described in any of the above embodiments.

[0149] Furthermore, the present application also provides a computer-readable storage medium. In an embodiment of the computer-readable storage medium according to the present application, the computer-readable storage medium may be configured to store a program for executing the aerodynamic design method of the wind turbine blade in the above method embodiment. This program can be loaded and run by a processor to implement the aerodynamic design method of the wind turbine blade. For ease of explanation, only the parts related to the embodiments of the present application are shown. For the specific technical details not disclosed, please refer to the method part of the embodiments of the present application. The computer-readable storage medium may be a memory device formed by various electronic devices. Optionally, the computer-readable storage medium in the embodiments of the present application is a non-transitory computer-readable storage medium.

[0150] So far, the technical solutions of the present application have been described in conjunction with the specific embodiments shown in the drawings. However, those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Without departing from the principle of the present application, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the protection scope of the present application.

Claims

1. An aerodynamic design method for a wind turbine blade, characterized in that: The method comprises: Obtain basic design parameters; Determining the chord length distribution and the twist angle distribution of the blade based on the basic design parameters; Determine the annual power generation of the wind turbine generator set based on the chord length distribution and the torsion angle distribution; The chord length distribution and the torsion angle distribution are optimized twice based on the annual power generation to obtain optimal solutions of the chord length distribution and the torsion angle distribution.

2. The aerodynamic design method of a wind turbine blade according to claim 1, characterized in that: Determining the chord length distribution and the twist angle distribution of the blade based on the basic design parameters includes: Determine a first mapping relationship between chord length and radial distance and a second mapping relationship between twist angle and radial distance based on the basic design parameters, wherein the radial distance is the distance between each section of the blade and the blade root; The first mapping relationship and the second mapping relationship are parameterized to obtain the chord length distribution and the torsion angle distribution.

3. The aerodynamic design method of a wind turbine blade according to claim 2, characterized in that: Parameterizing the first mapping relationship and the second mapping relationship includes: Acquire a first type of control point based on the first mapping relationship and the second mapping relationship; Establishing a Bezier curve based on the first type of control points; The Bezier curve is interpolated to obtain the second type of control points.

4. The aerodynamic design method of a wind turbine blade according to claim 1, characterized in that: Determining the annual power generation of the wind turbine generator set based on the chord length distribution and the torsion angle distribution includes: Determine a third mapping relationship between power coefficient and tip speed ratio based on the chord length distribution and the twist angle distribution; Determine the predicted power of the wind turbine generator set based on the third mapping relationship; The annual power generation of the wind turbine is determined based on the predicted power.

5. The aerodynamic design method of a wind turbine blade according to claim 1, characterized in that: The chord length distribution and the torsion angle distribution are optimized for the first time, including: Taking maximizing the annual power generation and minimizing the blade root bending moment as optimization objectives; establishing an initial population, wherein the initial population includes a plurality of individuals; Starting from the initial population, using a genetic algorithm to perform target optimization iterations to maximize the optimization target; When the optimization objective converges, the Pareto front is obtained; A preliminary solution for the chord length distribution and a preliminary solution for the torsion angle distribution are obtained from the Pareto front.

6. The aerodynamic design method of a wind turbine blade according to claim 5, characterized in that: The chord length distribution and the torsion angle distribution are optimized for the second time, including: updating the preliminary solution of the torsion angle distribution to obtain an updated torsion angle distribution; Keeping the updated torsion angle distribution unchanged, using a genetic algorithm to perform target optimization iterations to optimize the preliminary solution of the chord length distribution to maximize the optimization target; When the optimization objective converges, the Pareto front is obtained; The optimal solution of the chord length distribution and the optimal solution of the torsion angle distribution are obtained from the Pareto front.

7. The aerodynamic design method of a wind turbine blade according to claim 6, characterized in that: The obtaining of the updated torsion angle distribution includes: reducing the preset angle of the preliminary solution of the torsion angle distribution to obtain the updated torsion angle distribution; wherein when the radial distance is 0, the preset angle is 0, when the radial distance is within the range of [R1 / 3, R1], R1 is the blade length, the preset angle θ is the value in the following formula, and [0, R1 / 3] is smoothly transitioned, in θ=min(2,a s -a-3) In the above formula, θ is the preset angle, α s is the stall angle of attack of the blade section, and α is the working angle of attack of the blade section under rated wind speed conditions.

8. The aerodynamic design method of a wind turbine blade according to claim 6, characterized in that: The obtaining of the preliminary solution of the chord length distribution and the preliminary solution of the torsion angle distribution from the Pareto front comprises: selecting corresponding solutions from the Pareto front as the preliminary solutions of the chord length distribution and the preliminary solutions of the torsion angle distribution according to the tip speed ratio corresponding to the maximum power coefficient; and / or The obtaining of the optimal solution of the chord length distribution and the optimal solution of the torsion angle distribution from the Pareto front includes: selecting a final solution from the Pareto front as the optimal solution of the chord length distribution and the optimal solution of the torsion angle distribution according to the tip speed ratio corresponding to the maximum power coefficient.

9. An electronic device, characterized in that: include: at least one processor; and, a memory communicatively coupled to the at least one processor; Wherein, a computer program is stored in the memory, and when the computer program is executed by the at least one processor, the aerodynamic design method for a wind turbine blade according to any one of claims 1 to 8 is implemented.

10. A computer-readable storage medium storing a plurality of program codes, characterized in that: The program code is suitable for being loaded and run by a processor to execute the aerodynamic design method for a wind turbine blade according to any one of claims 1 to 8.

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