Design method, device and electronic equipment of blade extension device

Abstract

The present application discloses a design method, device and electronic device for a blade extension device, which is applied to electronic devices. The blade extension device includes a blade extension section and a blade extension winglet. The design method and device specifically adopt the modified BEM theory to calculate the CP-λ correspondence curve of the blade extension section; taking the annual power generation increase as the objective function, adopting the particle swarm multivariate parameter algorithm, and based on the parameters in the CP-λ correspondence curve, a plurality of extension section parameters at each cross-sectional position of the blade extension section are self-optimized and calculated, thereby obtaining the aerodynamic shape parameters such as the chord length, twist angle, relative thickness, airfoil model, etc. of each cross-sectional position of the blade extension section. The above scheme can realize the design of the blade extension device.

Description

Technical Field

[0001] The present application relates to the field of wind power technology, and more specifically, to a design method, device and electronic equipment for a blade extension device. Background Art

[0002] As the main component of wind turbines to capture wind energy, the quality of their aerodynamic performance directly determines the efficiency of wind energy conversion. In the subsonic flow field, the special design of the blade airfoil makes it form a complex three-dimensional effect at the trailing edge and blade tip due to the pressure difference between the pressure surface and the suction surface during rotation, that is, the blade tip shedding vortex that occurs and diffuses in a high-intensity spiral shape, and the induced drag generated at the same time increases the blade resistance, resulting in the loss of wind rotor torque and power.

[0003] In the development of wind energy utilization and wind turbine design technology, early wind turbines were relatively backward in technology and lacked understanding of wind turbine design boundary conditions. In order to avoid safety accidents, a higher safety factor was often used in the design. In addition, with the development and utilization of more and more wind farms, early wind farms were affected by the shielding of surrounding wind farms, resulting in a trend of varying degrees of wind speed decline, so the income of wind farms also decreased.

[0004] In order to effectively solve the above-mentioned deficiencies caused by reduced wind speed and the mismatch between the power generation performance of the unit and the characteristics of wind resources, the purpose of improving quality and efficiency can be achieved by increasing the diameter of the wind rotor, that is, by extending the blade tip. In addition, blade extension can also improve the tip vortex shedding and reduce the induced drag, thereby achieving an improvement in the power generation performance of the unit. However, there is currently no solution that can realize the design of a blade extension device. Summary of the invention

[0005] In view of this, the present application provides a design method, device and electronic equipment for a blade extension device, which are used to implement the design of the blade extension device.

[0006] In order to achieve the above objectives, the proposed solution is as follows:

[0007] A design method for a blade extension device is applied to electronic equipment. The blade extension device includes a blade extension section. The design method includes the following steps:

[0008] The CP~λ corresponding relationship curve after adding leaf extension nodes was calculated by using modified BEM theory;

[0009] Taking the annual power generation increase as the objective function, a particle swarm multivariate parameter algorithm is adopted, and based on the parameters in the CP-λ corresponding relationship curve, multiple extension node parameters at each cross-sectional position of the blade extension node are self-optimized.

[0010] Optionally, the plurality of extension section parameters include radius, chord length, torsion angle and relative thickness.

[0011] Optionally, the calculation of the CP-λ corresponding relationship curve of the blade extension section by using the modified BEM theoretical method comprises the steps of:

[0012] Select the same aerodynamic shape parameters as the specific blade model;

[0013] The modified BEM theory is used for each section of the blade extension section to iteratively calculate the inflow angle, tip loss, root loss, axial induction factor and tangential induction factor of each section at each tip speed ratio. The corresponding functional relationships are:

[0014]

[0015]

[0016]

[0017]

[0018]

[0019] Where: R represents the blade radius; f_loss represents the Prandtl blade tip correction coefficient including the error coefficient; △r is the error coefficient; r hub represents the hub radius; H represents the axial induction factor correction coefficient; F = F_loss·H_loss;

[0020] The inflow angle, blade tip loss, blade root loss, axial induction factor and tangential induction factor of each cross section at each blade tip speed ratio are integrally calculated, and the CP-λ corresponding relationship curve is constructed according to the calculation results.

[0021] Optionally, the error coefficient △r ranges from 0.01 to 0.2.

[0022] Optionally, the annual power generation increase is used as the objective function, a particle swarm multivariate parameter algorithm is used, and based on the parameters in the CP-λ corresponding relationship curve, a plurality of extension node parameters at each cross-sectional position of the blade extension node are self-optimized and calculated, including the steps of:

[0023] Selecting the starting position, design target length, and design section step length of the blade extension and blade extension section;

[0024] Calculate the approximate optimal λ after the blade extension section is extended ext-opt

[0025]

[0026] Calculate the theoretical optimal twist angle θ of the blade extension section corresponding to each cross-sectional position theory

[0027]

[0028]

[0029] α start Indicates the original blade length X start The average aerodynamic angle of attack α at steady-state wind speed Vin (cut-in wind speed) ~ Vrate (corresponding wind speed when reaching rated speed) start

[0030] The polynomial fitting method is used to iteratively fit the curve of each chord length of the blade extension section

[0031] y=k1x n +k2x n-1 +...k n x+k0

[0032] Under different airfoil models, the chord length, twist angle, and relative thickness of the blade extension section are self-optimized by using the particle swarm optimization PSO algorithm.

[0033] v i =ωv i +ω1rand()(pbest i -x i )+ω2rand()(gbest i -x i )

[0034] x i =x i +v i

[0035] Where: v i represents the particle speed, ω1 and ω2 represent the learning factors, ω1=ω2=1~2, rand() represents a random number from 0 to 1, i represents the total number of particles, and x i Indicates the current position of the particle, pbest i and gbest i Represents the two extreme values ​​in the particle iteration process, ω represents the inertia factor, ω = 0.4 ~ 0.9;

[0036] Optionally, the blade extension device further includes a blade extension winglet, and the design method further includes the steps of:

[0037] Selecting a starting position of the blade extension winglet;

[0038] Based on the starting position, the aerodynamic shape parameters of the blade extension winglet are calculated.

[0039] Optionally, the aerodynamic shape parameters include leading edge sweep angle, trailing edge sweep angle, wingtip chord length, wing root chord length, tip-to-root ratio, wing root chord starting position, leading edge modification Bezier curve parameters, winglet span length, camber angle, bending radius and installation angle.

[0040] A design device for a blade extension device is applied to electronic equipment, wherein the blade extension device comprises a blade extension section, and the design device comprises:

[0041] The first calculation module is used to calculate the CP-λ corresponding relationship curve after the leaf extension node by using the modified BEM theory;

[0042] The second calculation module is used to perform self-optimization calculation on multiple extension node parameters of each cross-sectional position of the blade extension node based on the parameters in the CP-λ corresponding relationship curve, taking the annual power generation increase as the objective function, using a particle swarm multivariate parameter algorithm.

[0043] Optionally, the plurality of extension section parameters include radius, chord length, torsion angle and relative thickness.

[0044] Optionally, the blade extension device further includes a blade extension winglet, and the design device further includes:

[0045] A position selection module, used for selecting a starting position of the blade extension winglet;

[0046] The third calculation module is used to calculate the aerodynamic shape parameters of the blade extension winglet based on the starting position.

[0047] Optionally, the aerodynamic shape parameters include leading edge sweep angle, trailing edge sweep angle, wingtip chord length, wing root chord length, tip-to-root ratio, wing root chord starting position, leading edge modification Bezier curve parameters, winglet span length, camber angle, bending radius and installation angle.

[0048] An electronic device comprises at least one processor and a memory connected to the processor, wherein:

[0049] The memory is used to store computer programs or instructions;

[0050] The processor is used to execute the computer program or instruction so that the electronic device can implement the design method of the blade extension device as described above.

[0051] It can be seen from the above technical scheme that the present application discloses a design method, device and electronic device for a blade extension device, which is applied to electronic devices. The blade extension device includes a blade extension section. The present design method and device specifically adopt the modified BEM theory to calculate the CP-λ correspondence curve of the blade extension section; taking the annual power generation increase as the objective function, adopting the particle swarm multivariate parameter algorithm, and based on the parameters in the CP-λ correspondence curve, a plurality of extension section parameters at each cross-sectional position of the blade extension section are self-optimized and calculated, thereby obtaining the aerodynamic shape parameters such as the chord length, twist angle, relative thickness, airfoil model, etc. of each cross-sectional section of the blade extension section. The above scheme can realize the design of the blade extension device. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0053] Figure 1 A flow chart of a method for designing a blade extension device according to an embodiment of the present application;

[0054] Figure 2 A flow chart of another method for designing a blade extension device according to an embodiment of the present application;

[0055] Figure 3a A schematic diagram of a blade body and a blade extension section of an embodiment of the present application;

[0056] Figure 3b A schematic diagram of a connection portion between a blade body and a blade extension section according to an embodiment of the present application;

[0057] Figure 3c A schematic diagram of a blade extension winglet according to an embodiment of the present application;

[0058] Figure 4 A block diagram of a design device for a blade extension device according to an embodiment of the present application;

[0059] Figure 5 A block diagram of another method for designing a blade extension device according to an embodiment of the present application;

[0060] Figure 6 A block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0061] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0062] Embodiment 1

[0063] Figure 1 This is a flow chart of a method for designing a blade extension device according to an embodiment of the present application.

[0064] like Figure 1 As shown, the design method provided in this embodiment is applied to an electronic device, which can be understood as a computer or server with data calculation and information processing capabilities. The design method is used to calculate various parameters of the blade extension device of the wind turbine generator set to obtain the manufacturing parameters of the blade extension device. The blade extension device includes a blade extension section, and the design method of the blade extension section specifically includes the following steps:

[0065] S1. Use the modified BEM theory to calculate the CP~λ corresponding relationship curve after the leaf extension node.

[0066] This method is used to calculate the corresponding relationship curve to ensure that the calculated Cp value has an error of 1% with the calculation result of the commercial software GH Bladed, and the corresponding optimal tip speed ratio λ opt The specific technical steps are as follows:

[0067] First, the same aerodynamic shape parameters as the blade model of GH Bladed or other commercial software are used. The aerodynamic shape parameters here include the radius position r of each section, the chord length c, the twist angle θ, the relative thickness T, and the aerodynamic parameters of the airfoil (the corresponding relationship between the angle of attack AOA and the lift coefficient Cl, the drag coefficient Cd, and the bending moment coefficient Cm);

[0068] Then, the modified BEM theory is used for each section to iteratively calculate the inflow angle φ, blade tip loss F_loss, blade root loss H_loss, axial induction factor a and tangential induction factor b at each λ. The corresponding functional relationships are:

[0069]

[0070]

[0071]

[0072]

[0073]

[0074] Where: R represents the blade radius; f_loss represents the Prandtl blade tip correction coefficient including the error coefficient; △r error coefficient is 0.01~0.2; r hub represents the hub radius; H represents the axial induction factor correction coefficient; F=F_loss·H_loss.

[0075] The iterative process of the axial induction factor and tangential induction factor of each section at each tip speed ratio λ is as follows:

[0076] 1) Assume that the axial induction factor a=0 and the tangential induction factor b=0;

[0077] 2) Calculate the cross-sectional inflow angle φ according to formula (1);

[0078] 3) Calculate the axial induction factor a1 and the tangential induction factor b1 according to formulas (4) and (5):

[0079] 4) If |a1-a|>tolerance error △a or |b1-b|>tolerance error △b, return to step 1) and continue iterating until the tolerance error requirement is met.

[0080] Finally, integrate the Cp-λ function relationship for each section to find Cp max , to ensure Cp max The error of the best Cp' calculated by GH Bladed or other commercial software is less than 1%, and the corresponding best tip speed ratio λ opt The calculation expression of Cp is shown in formula (6).

[0081]

[0082] S2. Perform self-optimization calculation on multiple extension node parameters at each cross-sectional position of the blade extension node.

[0083] Specifically, taking the annual power generation AEP increase △AEP as the objective function, the particle swarm multivariate parameter algorithm is used to calculate the radius r of each extension section of the blade extension section. ext , chord length c at each cross section ext , torsion angle θ ext , relative thickness T ext Perform self-optimization calculation. The specific implementation steps are as follows:

[0084] Select the starting position X of the blade extension and blade extension section start , Design target length X end And the design section step bin = 0.2m~1m.

[0085] Calculate the approximate optimal λ for the blade extensionext-opt

[0086]

[0087] Calculate the theoretical optimal twist angle θ of the blade extension section corresponding to each cross-sectional position theory

[0088]

[0089]

[0090] α start Indicates the original blade length X start The average aerodynamic angle of attack α at steady-state wind speed Vin (cut-in wind speed) ~ Vrate (corresponding wind speed when reaching rated speed) start

[0091] The polynomial fitting method is used to iteratively fit the curve of each chord length of the extended blade

[0092] y=k1x n +k2x n-1 +...k n x+k0 (10)

[0093] Iterative method:

[0094] 1) Given X end Initial chord length c end

[0095] 2) The starting point of the fitted chord length curve is the maximum chord length c max , the end point is c end

[0096] 3) Use formula (10) to perform curve fitting, loop n = 1, 2, 3...

[0097] 4) Calculate the correlation R between the fitting curve and the fitted curve for each n cycles coeff

[0098] 5) When R coeff ≥R1, R1=0.95~0.99, and the corresponding n is used as the polynomial order of the lower boundary chord length curve of the particle swarm to find the optimal chord length particle loop iteration

[0099] 6) When R coeff ≤R2, R1=0.99~1, and the corresponding n is used as the polynomial order of the lower boundary chord length curve of the particle swarm to find the optimal chord length particle loop iteration

[0100] 7) If the chord lengths of the extended blades calculated by the polynomial curve in step 6 are the optimal Cp calculated by the method in step 1 ext-maxSmaller than the blade Cp before extension max , increase c end value, and repeat the cycle until it is satisfied.

[0101] 8)The loop ends.

[0102] For different airfoil models, the chord length, twist angle, and relative thickness of the blade extension section are self-optimized through the particle swarm optimization (PSO) algorithm. The chord length, twist angle, relative thickness, and airfoil model of each section of the blade extension section calculated iteratively are used as the aerodynamic shape parameters of the blade extension design.

[0103] v i =ωv i +ω1rand()(pbest i -x i )+ω2rand()(gbest i -x i ) (11)

[0104] x i =x i +v i (12)

[0105] Where: v i represents the particle speed; ω1 and ω2 represent learning factors, ω1=ω2=1~2; rand() represents a random number from 0 to 1; i represents the total number of particle swarms; x i Indicates the current position of the particle; pbest i and gbest i Represents the two extreme values ​​in the particle iteration process; ω represents the inertia factor, ω=0.4~0.9

[0106] The airfoil model is selected from commonly used airfoils for wind turbines, DU series, RISO series, NACA series, FFA series, S series and their variants, with a relative thickness range of 16% to 18%.

[0107] The particle swarm size particle_num = 30 to 100, the iteration number iteration_num = 10 to 50, and the optimization target is the best AEP.

[0108] In the particle swarm self-optimization PSO algorithm, the boundary conditions of each particle are set as follows:

[0109] 1) The upper and lower boundaries of the chord length are shown in 2-6

[0110] 2) The upper boundary of the torsion angle is θ theory ±Twist_Error,Twist_Error=1~2deg

[0111] 3) The upper boundary of the relative thickness of the airfoil is X start Corresponding to the thickness, the lower boundary is the minimum relative thickness in the airfoil model.

[0112] If the load of the whole machine after the blade extension exceeds the design load or the increase in power generation after the extension does not meet the requirements, adjust X end , and re-execute subsequent calculations.

[0113] It can be seen from the above technical scheme that this embodiment provides a design method for a blade extension device, which is applied to electronic equipment. The blade extension device includes a blade extension section. The design method specifically uses the modified BEM theory to calculate the CP-λ correspondence curve of the blade extension section; using the annual power generation increase as the objective function, using the particle swarm multivariate parameter algorithm, and based on the parameters in the CP-λ correspondence curve, a plurality of extension section parameters at each cross-sectional position of the blade extension section are self-optimized and calculated, thereby obtaining the aerodynamic shape parameters such as the chord length, twist angle, relative thickness, and airfoil model of each cross-sectional position of the blade extension section. The above scheme can realize the design of the blade extension device.

[0114] In view of the fact that the blade extension device also includes a blade extension winglet, therefore, in a specific embodiment of the present application, the following steps are also included to achieve the design of the blade extension winglet, such as Figure 2 shown.

[0115] S3. Select the starting position of the blade extension winglet.

[0116] Based on the blade extension calculated above, determine the starting position r of the blade tip winglet along the blade span direction. start , r start The selection is based on:

[0117] 1) Use professional commercial software such as GH Bladed, Simpack, Ansys CFX / Fluent or open source software such as Fast, or aerodynamic models such as modified BEM theory, lift line theory, and actuator line model to calculate the aerodynamic performance of the blade and calculate △AEP to meet the design target requirements;

[0118] 2) Reduce the blade radius in step 2 according to the radius length bin given in 2-3, that is, reverse the design, and calculate the corresponding △AEP as described above i ,when When the cross-sectional position r start is the starting position of the winglet.

[0119] The key parameters of the aerodynamic shape of the blade extension winglet include the leading edge sweep angle γ1, the trailing edge sweep angle γ2, the wingtip chord length c2, the wing root chord length c1, the tip-root ratio The chord-wise starting position x of the wing root, the leading edge modification Bezier curve parameters s1, s2, the winglet span length Ltip, the camber angle τ, the bending radius Rt1, Rt2, and the installation angle A set . Figure 3a , 3b and 3c.

[0120] S4. Calculate the aerodynamic shape parameters of the blade extension winglet based on the starting position.

[0121] Select the airfoil of the tip extended winglet, selection principle 1: the winglet airfoil is a series of airfoils with a flat upper surface and a certain curvature of the trailing edge. The airfoil thickness is less than 16%. The series of airfoils include but are not limited to DU series, S series, NACA 4 series, 5 series, 6 series, Wortmann FX series, FFA series and their variants, such as trailing edge modification.

[0122] Winglet span length Ltip ≥ X end -r start , tip-root ratio y ≥ 0.2, camber angle τ∈(0°,90°), installation angle A set ∈(-2°,5°), leading edge sweep angle Trailing edge sweep angle γ2∈(0°,γ1)

[0123] Determine the starting position x∈(x1,x2) of the wing root chord, x1 and x2.

[0124] Method 1: x1=0, x2=r start The maximum thickness of the airfoil used; Method 2: Determine the values ​​of x1 and x2 through CFD simulation, where x1 is the cut-in wind speed Vin and the grid-connected speed When r is the boundary condition, start Position: the starting position of the downwash airflow, x2: the rated wind speed Vrate, the rated speed When r is the boundary condition, start Position airflow downwash starting position. At this time r start For the leaf tip.

[0125] Among the aerodynamic shape parameters of the winglet, Ltip, y, τ, and x are important parameters that determine the induced drag of the winglet, so it is priority to determine the above four parameters. After determination, the leading edge sweep angle, trailing edge sweep angle, installation angle, wing root bending radius, and leading edge modification Bessel parameters are optimized.

[0126] The vortex lattice method (VLM) is used to calculate the aerodynamic force of the blade winglet. The steps include:

[0127] 1) For different combinations of Ltip, y, τ, and x, the aerodynamic shape of the winglet is given

[0128] 2) Meshing is performed to divide the surface of each cross-sectional component of the blade winglet and the blade body or the blade extension section;

[0129] 3) Calculate the aerodynamic performance of the whole composed of the blade winglet and the blade body or the blade extension section when the angle of attack falls within the range of (-2°, 10°);

[0130] 4) Taking the best lift-to-drag ratio in the simulation results as the judgment condition, determine the optimal combination of Ltip, y, τ, and x;

[0131] 5) Based on the above Ltip, y, τ, x combination, iteratively calculate the leading edge sweep angle, trailing edge sweep angle, installation angle, and leading edge modification Bessel parameter 90° <s1<180°、90°<s2<180°。

[0132] The above solution can also realize the design of the winglet bending towards the pressure side and the suction side.

[0133] Through subsequent solutions, the design of all components of the blade extension device can be realized.

[0134] Embodiment 2

[0135] Figure 4 This is a block diagram of a design device for a blade extension device according to an embodiment of the present application.

[0136] like Figure 4 As shown, the design device provided in this embodiment is applied to an electronic device, which can be understood as a computer or server with data calculation and information processing capabilities. The design device is used to calculate various parameters of the extension device of the blade of the wind turbine generator set to obtain the manufacturing parameters of the blade extension device. The blade extension device includes a blade extension section, and the design device of the blade extension section specifically includes a first calculation module 10 and a second calculation module 20.

[0137] The first calculation module is used to calculate the CP-λ corresponding relationship curve after adding the blade extension node by using the modified BEM theory.

[0138] This method is used to calculate the corresponding relationship curve to ensure that the calculated Cp value has an error of 1% with the calculation result of the commercial software GH Bladed, and the corresponding optimal tip speed ratio λ opt The calculation process of this module is as follows:

[0139] First, the same aerodynamic shape parameters as the blade model of GH Bladed or other commercial software are used. The aerodynamic shape parameters here include the radius position r of each section, the chord length c, the twist angle θ, the relative thickness T, and the aerodynamic parameters of the airfoil (the corresponding relationship between the angle of attack AOA and the lift coefficient Cl, the drag coefficient Cd, and the bending moment coefficient Cm);

[0140] Then, the modified BEM theory is used for each section to iteratively calculate the inflow angle φ, blade tip loss F_loss, blade root loss H_loss, axial induction factor a and tangential induction factor b at each λ. The corresponding functional relationships are:

[0141]

[0142]

[0143]

[0144]

[0145]

[0146] Where: R represents the blade radius; f_loss represents the Prandtl blade tip correction coefficient including the error coefficient; △r error coefficient is 0.01~0.2; r hub represents the hub radius; H represents the axial induction factor correction coefficient; F=F_loss·H_loss.

[0147] The iterative process of the axial induction factor and tangential induction factor of each section at each tip speed ratio λ is as follows:

[0148] 5) Assume that the axial induction factor a=0 and the tangential induction factor b=0;

[0149] 6) Calculate the cross-sectional inflow angle φ according to formula (1);

[0150] 7) Calculate the axial induction factor a1 and the tangential induction factor b1 according to formulas (4) and (5):

[0151] 8) If |a1-a|>tolerance error △a or |b1-b|>tolerance error △b, return to step 1) and continue iterating until the tolerance error requirement is met.

[0152] Finally, integrate the Cp-λ function relationship for each section to find Cp max , to ensure Cp max The error of the best Cp' calculated by GH Bladed or other commercial software is less than 1%, and the corresponding best tip speed ratio λ opt The calculation expression of Cp is shown in formula (6).

[0153]

[0154] The second calculation module is used to perform self-optimization calculation on multiple extension node parameters at each cross-sectional position of the blade extension node.

[0155] Specifically, taking the annual power generation AEP increase △AEP as the objective function, the particle swarm multivariate parameter algorithm is used to calculate the radius r of each extension section of the blade extension section. ext , chord length c at each cross section ext , torsion angle θ ext , relative thickness T ext Perform self-optimization calculation. The calculation process of this module is as follows:

[0156] Select the starting position X of the blade extension and blade extension section start , Design target length X end And the design section step bin = 0.2m~1m.

[0157] Calculate the approximate optimal λ for the blade extension ext-opt

[0158]

[0159] Calculate the theoretical optimal twist angle θ of the blade extension section corresponding to each cross-sectional position theory

[0160]

[0161]

[0162] α start Indicates the original blade length X start The average aerodynamic angle of attack α at steady-state wind speed Vin (cut-in wind speed) ~ Vrate (corresponding wind speed when reaching rated speed) start

[0163] The polynomial fitting method is used to iteratively fit the curve of each chord length of the extended blade

[0164] y=k1x n +k2x n-1 +...k n x+k0 (10)

[0165] Iterative method:

[0166] 9) Given X end Initial chord length c end

[0167] 10) The starting point of the fitted chord length curve is the maximum chord length c max , the end point is c end

[0168] 11) Use formula (10) to perform curve fitting, loop n = 1, 2, 3...

[0169] 12) Calculate the correlation R between the fitting curve and the fitted curve for each n cycles coeff

[0170] 13) When R coeff ≥R1, R1=0.95~0.99, and the corresponding n is used as the polynomial order of the lower boundary chord length curve of the particle swarm to find the optimal chord length particle loop iteration

[0171] 14) When R coeff ≤R2, R1=0.99~1, and the corresponding n is used as the polynomial order of the lower boundary chord length curve of the particle swarm to find the optimal chord length particle loop iteration

[0172] 15) If the chord lengths of the extended blades calculated by the polynomial curve in step 6 are the optimal Cp calculated by the method in step 1 ext-max Smaller than the blade Cp before extension max , increase c end value, and repeat the cycle until it is satisfied.

[0173] 16) The loop ends.

[0174] For different airfoil models, the chord length, twist angle, and relative thickness of the blade extension section are self-optimized through the particle swarm optimization (PSO) algorithm. The chord length, twist angle, relative thickness, and airfoil model of each section of the blade extension section calculated iteratively are used as the aerodynamic shape parameters of the blade extension design.

[0175] v i =ωv i +ω1rand()(pbest i -x i )+ω2rand()(gbest i -x i ) (11)

[0176] x i =x i +v i (12)

[0177] Where: v i represents the particle speed; ω1 and ω2 represent learning factors, ω1=ω2=1~2; rand() represents a random number from 0 to 1; i represents the total number of particle swarms; x i Indicates the current position of the particle; pbest i and gbest i Represents the two extreme values ​​in the particle iteration process; ω represents the inertia factor, ω=0.4~0.9

[0178] The airfoil model is selected from commonly used airfoils for wind turbines, DU series, RISO series, NACA series, FFA series, S series and their variants, with a relative thickness range of 16% to 18%.

[0179] The particle swarm size particle_num = 30 to 100, the iteration number iteration_num = 10 to 50, and the optimization target is the best AEP.

[0180] In the particle swarm self-optimization PSO algorithm, the boundary conditions of each particle are set as follows:

[0181] 4) The upper and lower boundaries of the chord length are shown in 2-6

[0182] 5) The upper boundary of the torsion angle is θ theory ±Twist_Error,Twist_Error=1~2deg

[0183] 6) The upper boundary of the relative thickness of the airfoil is X start Corresponding to the thickness, the lower boundary is the minimum relative thickness in the airfoil model.

[0184] If the load of the whole machine after the blade extension exceeds the design load or the increase in power generation after the extension does not meet the requirements, adjust X end , and re-execute subsequent calculations.

[0185] It can be seen from the above technical scheme that this embodiment provides a design device for a blade extension device, which is applied to electronic equipment. The blade extension device includes a blade extension section. The design method specifically adopts the modified BEM theory to calculate the CP-λ correspondence curve of the blade extension section; taking the annual power generation increase as the objective function, the particle swarm multivariate parameter algorithm is adopted, and based on the parameters in the CP-λ correspondence curve, multiple extension section parameters at each cross-sectional position of the blade extension section are self-optimized and calculated, thereby obtaining the aerodynamic shape parameters such as the chord length, twist angle, relative thickness, and airfoil model of each cross-sectional position of the blade extension section. The above scheme can realize the design of the blade extension device.

[0186] In view of the fact that the blade extension device also includes a blade extension winglet, therefore, in a specific embodiment of the present application, it also includes a position selection module 30 and a third calculation module 40 to implement the design of the blade extension winglet, such as Figure 2 shown.

[0187] The position selection module is used to select the starting position of the blade extension winglet.

[0188] Based on the blade extension calculated above, determine the starting position r of the blade tip winglet along the blade span direction. start , r start The selection is based on:

[0189] 3) Use professional commercial software such as GH Bladed, Simpack, Ansys CFX / Fluent or open source software such as Fast, or aerodynamic models such as modified BEM theory, lift line theory, and actuator line model to calculate the aerodynamic performance of the blade and calculate △AEP to meet the design target requirements;

[0190] 4) Reduce the blade radius in step 2 according to the radius length bin given in 2-3, that is, reverse the design, and calculate the corresponding △AEP as described above i ,when When the cross-sectional position r start is the starting position of the winglet.

[0191] The key parameters of the aerodynamic shape of the blade extension winglet include the leading edge sweep angle γ1, the trailing edge sweep angle γ2, the wingtip chord length c2, the wing root chord length c1, the tip-root ratio The chord-wise starting position x of the wing root, the leading edge modification Bezier curve parameters s1, s2, the winglet span length Ltip, the camber angle τ, the bending radius Rt1, Rt2, and the installation angle A set . Figure 3a , 3b and 3c.

[0192] The third calculation module is used to calculate the aerodynamic shape parameters of the blade extension winglet based on the starting position.

[0193] Select the airfoil of the tip extended winglet, selection principle 1: the winglet airfoil is a series of airfoils with a flat upper surface and a certain curvature of the trailing edge. The airfoil thickness is less than 16%. The series of airfoils include but are not limited to NACA 4 series, 5 series, 6 series, Wortmann FX series, FFA series and their variants, such as trailing edge modification.

[0194] Winglet span length Ltip ≥ X end -r start , tip-root ratio y ≥ 0.2, camber angle τ∈(0°,90°), installation angle A set ∈(-2°,5°), leading edge sweep angle Trailing edge sweep angle γ2∈(0°,γ1)

[0195] Determine the starting position x∈(x1,x2) of the wing root chord, x1 and x2.

[0196] Method 1: x1=0, x2=r start The maximum thickness of the airfoil used; Method 2: Determine the values ​​of x1 and x2 through CFD simulation, where x1 is the cut-in wind speed Vin and the grid-connected speed When r is the boundary condition, startPosition: the starting position of the downwash airflow, x2: the rated wind speed Vrate, the rated speed When r is the boundary condition, start Position airflow downwash starting position. At this time r start For the leaf tip.

[0197] Among the aerodynamic shape parameters of the winglet, Ltip, y, τ, and x are important parameters that determine the induced drag of the winglet, so it is priority to determine the above four parameters. After determination, the leading edge sweep angle, trailing edge sweep angle, installation angle, wing root bending radius, and leading edge modification Bessel parameters are optimized.

[0198] The vortex lattice method (VLM) is used to calculate the aerodynamic force of the blade winglet. The steps include:

[0199] 1) For different combinations of Ltip, y, τ, and x, the aerodynamic shape of the winglet is given

[0200] 2) Meshing is performed to divide the surface of each cross-sectional component of the blade winglet and the blade body or the blade extension section;

[0201] 3) Calculate the aerodynamic performance of the whole composed of the blade winglet and the blade body or the blade extension section when the angle of attack falls within the range of (-2°, 10°);

[0202] 4) Taking the best lift-to-drag ratio in the simulation results as the judgment condition, determine the optimal combination of Ltip, y, τ, and x;

[0203] 5) Based on the above Ltip, y, τ, x combination, iteratively calculate the leading edge sweep angle, trailing edge sweep angle, installation angle, and leading edge modification Bessel parameter 90° <s1<180°、90°<s2<180°。

[0204] The above solution can also realize the design of the winglet bending towards the pressure side and the suction side.

[0205] Through subsequent solutions, the design of all components of the blade extension device can be realized.

[0206] Embodiment 3

[0207] This embodiment provides an electronic device, which can be understood as a computer or server with data calculation and information processing capabilities. The electronic device includes at least one processor 101 and a memory 102, which are connected via a data bus 103. The memory is used to store computer programs or instructions, and the processor is used to execute corresponding computer programs or instructions so that the electronic device can implement the design method of the blade extension device provided in an embodiment.

[0208] The blade extension device includes a blade extension section. The design method specifically adopts the modified BEM theory to calculate the CP-λ correspondence curve of the blade extension section; taking the annual power generation increase as the objective function, the particle swarm multivariate parameter algorithm is adopted, and based on the parameters in the CP-λ correspondence curve, multiple extension section parameters at each cross-sectional position of the blade extension section are self-optimized and calculated, thereby obtaining the aerodynamic shape parameters such as the chord length, twist angle, relative thickness, airfoil model, etc. of each cross-sectional position of the blade extension section. The above scheme can realize the design of the blade extension device.

[0209] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0210] It will be appreciated by those skilled in the art that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0211] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0212] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0213] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0214] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0215] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0216] The technical solution provided by the present invention is introduced in detail above. Specific examples are used in this article to illustrate the principle and implementation mode of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation mode and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A design method for a blade extension device, applied to electronic equipment, characterized in that: The blade extension device includes a blade extension section, and the design method includes the steps of: The modified BEM theory is used to calculate the CP~λ corresponding relationship curve after adding the leaf extension node, including: Select the same aerodynamic shape parameters as the specific blade model; The modified BEM theory is used for each section of the blade extension section to iteratively calculate the inflow angle, tip loss, root loss, axial induction factor and tangential induction factor of each section at each tip speed ratio. The corresponding functional relationships are: Where: R represents the blade radius; f_loss represents the Prandtl blade tip correction coefficient including the error coefficient; Δr is the error coefficient; r hub represents the hub radius; H represents the axial induction factor correction coefficient; F = F_loss·H_loss; r represents the cross-sectional radius position; F_loss represents the tip loss; H_loss represents the root loss; c represents the chord length; C1 represents the lift coefficient; C d represents the drag coefficient; Integrating the inflow angle, blade tip loss, blade root loss, axial induction factor and tangential induction factor of each cross section at each blade tip speed ratio, and constructing the CP-λ corresponding relationship curve according to the calculation results; Taking the annual power generation increase as the objective function, a particle swarm multivariate parameter algorithm is used, and based on the parameters in the CP-λ corresponding relationship curve, multiple extension node parameters at each cross-sectional position of the blade extension node are self-optimized and calculated, specifically including: Selecting the starting position, design target length, and design section step length of the blade extension and blade extension section; Calculate the approximate optimal λ after the blade extension section is extended ext-opt Calculate the theoretical optimal twist angle θ of the blade extension section corresponding to each cross-sectional position theory α start Indicates the original blade length X start The average aerodynamic angle of attack α at steady-state wind speed Vin (cut-in wind speed) ~ Vrate (corresponding wind speed when reaching rated speed) start ; r ext Indicates the radius of the section position of the blade extension section; The polynomial fitting method is used to iteratively fit the curve of each chord length of the blade extension section y=k1x n +k2x n-1 +...k n x+k0 Under different airfoil models, the chord length, twist angle, and relative thickness of the blade extension section are self-optimized by using the particle swarm optimization PSO algorithm. v i =ωv i +ω1rand()(pbest i -x i )+ω2rand()(gbest i -x i ) (11) x i =x i +v i (12) Where: v i represents the particle speed, ω1 and ω2 represent the learning factors, ω1=ω2=1~2, rand() represents a random number from 0 to 1, i represents the total number of particles, and x i Indicates the current position of the particle, pbest i and gbest i Represents the two extreme values ​​in the particle iteration process, ω represents the inertia factor, ω = 0.4 ~ 0.

9.

2. The design method according to claim 1, characterized in that: The plurality of extension section parameters include radius, chord length, twist angle and relative thickness.

3. The design method according to claim 1, characterized in that: The error coefficient Δr ranges from 0.01 to 0.

2.

4. The design method according to any one of claims 1 to 3, characterized in that: The blade extension device also includes a blade extension winglet, and the design method also includes the steps of: Selecting a starting position of the blade extension winglet; Based on the starting position, the aerodynamic shape parameters of the blade extension winglet are calculated.

5. The design method according to claim 4, characterized in that: The aerodynamic shape parameters include leading edge sweep angle, trailing edge sweep angle, wingtip chord length, wing root chord length, tip-to-root ratio, wing root chord starting position, leading edge modification Bezier curve parameters, winglet span length, camber angle, bending radius and installation angle.

6. A design device for a blade extension device, applied to electronic equipment, characterized in that: The blade extension device includes a blade extension section, and the design device includes: The first calculation module is used to calculate the CP-λ corresponding relationship curve after adding the leaf extension node by using the modified BEM theory, and specifically includes: Select the same aerodynamic shape parameters as the specific blade model; The modified BEM theory is used for each section of the blade extension section to iteratively calculate the inflow angle, tip loss, root loss, axial induction factor and tangential induction factor of each section at each tip speed ratio. The corresponding functional relationships are: Where: R represents the blade radius; f_loss represents the Prandtl blade tip correction coefficient including the error coefficient; Δr is the error coefficient; r hub represents the hub radius; H represents the axial induction factor correction coefficient; F = F_loss·H_loss; r represents the cross-sectional radius position; F_loss represents the tip loss; H_loss represents the root loss; c represents the chord length; C1 represents the lift coefficient; C d represents the drag coefficient; Integrating the inflow angle, blade tip loss, blade root loss, axial induction factor and tangential induction factor of each cross section at each blade tip speed ratio, and constructing the CP-λ corresponding relationship curve according to the calculation results; The second calculation module is used to use the annual power generation increase as the objective function, adopt the particle swarm multivariate parameter algorithm, and based on the parameters in the CP-λ corresponding relationship curve, perform self-optimization calculation on multiple extension node parameters at each cross-sectional position of the blade extension node, specifically including: Selecting the starting position, design target length, and design section step length of the blade extension and blade extension section; Calculate the approximate optimal λ after the blade extension section is extended ext-opt Calculate the theoretical optimal twist angle θ of the blade extension section corresponding to each cross-sectional position theory α start Indicates the original blade length X start The average aerodynamic angle of attack α at steady-state wind speed Vin (cut-in wind speed) ~ Vrate (corresponding wind speed when reaching rated speed) start ; r ext Indicates the radius of the section position of the blade extension section; The polynomial fitting method is used to iteratively fit the curve of each chord length of the blade extension section y=k1x n +k2x n-1 +...k n x+k0 Under different airfoil models, the chord length, twist angle, and relative thickness of the blade extension section are self-optimized by using the particle swarm optimization PSO algorithm. v i =ωv i +ω1rand()(pbest i -x i )+ω2rand()(gbest i -x i ) (11) x i =x i +v i (12) Where: v i represents the particle speed, ω1 and ω2 represent the learning factors, ω1=ω2=1~2, rand() represents a random number from 0 to 1, i represents the total number of particles, and x i Indicates the current position of the particle, pbest i and gbest i Represents the two extreme values ​​in the particle iteration process, ω represents the inertia factor, ω = 0.4 ~ 0.

9.

7. The design device according to claim 6, characterized in that The plurality of extension section parameters include radius, chord length, twist angle and relative thickness.

8. The design device according to claim 6 or 7, characterized in that The blade extension device also includes a blade extension winglet, and the design device also includes: A position selection module, used for selecting a starting position of the blade extension winglet; The third calculation module is used to calculate the aerodynamic shape parameters of the blade extension winglet based on the starting position.

9. The design device according to claim 8, characterized in that The aerodynamic shape parameters include leading edge sweep angle, trailing edge sweep angle, wingtip chord length, wing root chord length, tip-to-root ratio, wing root chord starting position, leading edge modification Bezier curve parameters, winglet span length, camber angle, bending radius and installation angle.

10. An electronic device, characterized in that: The method comprises at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs or instructions; The processor is used to execute the computer program or instruction so that the electronic device can implement the method for designing a blade extension device according to any one of claims 1 to 5.

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