CN114861345A - Design method and device of blade extension device and electronic equipment - Google Patents

Abstract

The application discloses a design method and a device of a blade extension device and electronic equipment, wherein the method and the device are applied to the electronic equipment; and (3) taking the annual energy generation capacity lifting amount as a target function, adopting a particle swarm multivariate parameter algorithm, and carrying out self-optimization calculation on a plurality of extension section parameters of each section position of the blade extension section based on the parameters in the CP-lambda corresponding relation curve, so as to obtain aerodynamic shape parameters such as chord length, torsion angle, relative thickness, airfoil model and the like of each section of the blade extension section. Through the scheme, the design of the blade extension device can be realized.

Description

Design method, device and electronic device of a blade extension device

technical field

The present application relates to the technical field of wind power, and more particularly, to a design method, device and electronic equipment for a blade extension device.

Background technique

As the main components of wind turbines to capture wind energy, the aerodynamic performance of blades directly determines the efficiency of wind energy conversion. In the subsonic flow field, the special design form of the blade airfoil makes the air flow form a complex three-dimensional effect at the trailing edge and blade tip position due to the pressure difference between the pressure surface and the suction surface during the rotation process, that is, a high-strength helical shape. The generated and diffused tip shedding vortices, along with the induced drag, increase the blade drag, resulting in loss of rotor torque and power.

In the development process of wind energy utilization and wind turbine design technology, early wind turbines have insufficient understanding of wind turbine design boundary conditions due to relatively backward technology. In order to avoid safety accidents, higher safety factors are often used in design. In addition, with the development and utilization of more and more wind farms, the early wind farms are affected by the shielding of surrounding wind farms, resulting in a downward trend in wind speed to varying degrees, so the benefits of wind farms also decrease.

In order to effectively solve the above-mentioned deficiencies due to the reduction of 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. The tip shedding vortex plays a role in reducing the induced resistance, thereby improving the power generation performance of the unit. However, there is no solution that can realize the design of the blade extension device.

SUMMARY OF THE INVENTION

In view of this, the present application provides a design method, device and electronic device of a blade extension device, which are used to realize the design of the blade extension device.

In order to achieve the above purpose, the proposed scheme is as follows:

A design method of a blade extension device, applied to electronic equipment, the blade extension device includes a blade extension section, and the design method includes the steps:

Using the modified BEM theory to calculate the CP～λ corresponding curve after adding the blade extension;

Taking the increase in annual power generation as the objective function, using the particle swarm multi-parameter algorithm, and based on the parameters in the CP~λ corresponding relationship curve, the parameters of each section of the blade extension section are automatically carried out. Optimization calculation.

Optionally, the plurality of extended section parameters include radius, chord length, twist angle and relative thickness.

Optionally, the calculation of the CP-λ corresponding relationship curve of the blade extension section by the modified BEM theoretical method includes the steps:

Select the same aerodynamic shape parameters as the specific blade model;

Using the modified BEM theory for each section of the blade extension section, iteratively calculate the inflow angle, tip loss, blade root loss, axial induction factor and tangential induction of each section at each tip speed ratio factor, and the corresponding functional relationships are:

In the formula: R is the blade radius; f_loss is the Prandtl tip correction coefficient with error coefficient; △r is the error coefficient; r _hub is the hub radius; H is the axial induction factor correction coefficient; F=F_loss·H_loss;

Integrate and calculate the inflow angle, tip loss, blade root loss, axial induction factor and tangential induction factor of each of the sections under each of the blade tip speed ratios, and construct the CP ~ λ according to the calculation results Correspondence curve.

Optionally, the error coefficient Δr ranges from 0.01 to 0.2.

Optionally, the annual power generation improvement is used as the objective function, the particle swarm multi-parameter algorithm is used, and based on the parameters in the CP-λ corresponding relationship curve, the multi-section position of each section position of the blade extension section is determined. A self-optimization calculation is performed on the parameters of the extended section, including the steps:

Selecting the starting position of the blade extension and the blade extension section, the design target length, and the design section step size;

Calculate the approximate optimal λ _ext-opt after extension of the blade extension

Calculate the theoretical optimal twist angle θ _theory of the blade extension section corresponding to each section position

α _start represents the average aerodynamic angle of attack α _start of X _start at the steady-state wind speed Vin (cut-in wind speed) ~ Vrate (the corresponding wind speed when the rated speed is reached) under the original blade length

A polynomial fitting method is used to iteratively fit and calculate the curve of each chord length of the blade extension section

y=k ₁ x ⁿ +k ₂ x ^n-1 +...k _n x+k ₀

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

v _i =ωv _i +ω ₁ rand()(pbest _i -x _i )+ω ₂ rand()(gbest _i -x _i )

x _i = x _i +v _i

In the formula: v _i represents the particle velocity, ω ₁ and ω ₂ represent the learning factor, ω ₁ =ω ₂ =1～2, rand() represents a random number from 0 to 1, i represents the total number of particle swarms, and _xi represents the current particle size. position, pbest _i and gbest _i represent the two extreme values in the particle iterative process, ω represents the inertia factor, ω=0.4～0.9;

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

selecting the starting position of the blade to extend the winglet;

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

Optionally, the aerodynamic shape parameters include leading edge sweep angle, trailing edge sweep angle, wing tip chord length, wing root chord length, tip root ratio, wing root chord direction starting position, and leading edge modified Bessel. Curve parameters, winglet span length, camber angle, bend radius and installation angle.

A design device for a blade extension device, applied to electronic equipment, the blade extension device includes a blade extension section, and the design device includes:

The first calculation module is used to calculate the corresponding relationship curve of CP to λ after the blade is extended by using the modified BEM theory;

The second calculation module is used for taking the increase in annual power generation as the objective function, adopting the particle swarm multi-parameter algorithm, and based on the parameters in the corresponding relationship curve of CP to λ, for each section position of the blade extension section. Self-optimization calculation is performed for multiple extension section parameters.

Optionally, the plurality of extended section parameters include radius, chord length, twist angle and relative thickness.

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

a position selection module for selecting the starting position of the blade extension winglet;

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

Optionally, the aerodynamic shape parameters include leading edge sweep angle, trailing edge sweep angle, wing tip chord length, wing root chord length, tip root ratio, wing root chord direction starting position, and leading edge modified Bessel. Curve parameters, winglet span length, camber angle, bend radius and installation angle.

An electronic device comprising 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 for executing the computer program or instructions, so that the electronic device implements the above-mentioned design method of the blade extension device.

As can be seen from the above technical solutions, the present application discloses a design method, device and electronic equipment for a blade extension device, the method and device are applied to electronic equipment, the blade extension device includes a blade extension section, the design method and device of the present invention Specifically, the modified BEM theory is used to calculate the CP ~ λ corresponding relationship curve of the blade extension; the annual power generation increase is used as the objective function, the particle swarm multi-parameter algorithm is used, and based on the parameters in the CP ~ λ corresponding relationship curve, the blade is extended. The self-optimization calculation is carried out for the parameters of multiple extension sections at each section position of the section, so as to obtain the aerodynamic shape parameters such as the chord length, twist angle, relative thickness, and airfoil type of each section of the blade extension section. Through the above solution, the design of the blade extension device can be realized.

Description of drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only These are some embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without any creative effort.

1 is a flowchart of a design method of a blade extension device according to an embodiment of the application;

2 is a flowchart of another design method of a blade extension device according to an embodiment of the application;

3a is a schematic diagram of a blade body and a blade extension section according to an embodiment of the application;

Fig. 3b is a schematic diagram of the connection part between the blade body and the blade extension section according to the embodiment of the application;

3c is a schematic diagram of a blade extension winglet according to an embodiment of the application;

4 is a block diagram of a design device of a blade extension device according to an embodiment of the application;

5 is a block diagram of another design method of a blade extension device according to an embodiment of the application;

FIG. 6 is a block diagram of an electronic device according to an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

Example 1

FIG. 1 is a flowchart of a design method of a blade extension device according to an embodiment of the present application.

As shown in FIG. 1 , the design method provided in this embodiment is applied to electronic equipment, which can be understood as a computer or server with data calculation and information processing capabilities, and the design method is used for the extension device of the blade of the wind turbine. Various parameters are calculated to obtain the manufacturing parameters of the blade extension device. The blade extension device includes a blade extension section. Specifically, the design method of the blade extension section includes the following steps:

S1. Use the modified BEM theory to calculate the CP ~ λ corresponding relationship curve after the blade is extended.

This method is used to calculate the corresponding relationship curve, so as to ensure that the calculated Cp value has an error of 1% with the calculation result of the commercial software GH Bladed, and to make the corresponding optimum tip speed ratio λ _opt equal. The technical steps are as follows:

First, the same aerodynamic shape parameters as those of 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 torsion angle θ, the relative thickness T, and the airfoil aerodynamic parameters (angle of attack). AOA corresponds to lift coefficient Cl, drag coefficient Cd and bending moment coefficient Cm);

Then, the modified BEM theory is used for each section to iteratively calculate the inflow angle φ, tip loss F_loss, blade root loss H_loss, axial induction factor a and tangential induction factor b under each λ, and the corresponding functional relationships are respectively for

In the formula: R represents the blade radius; f_loss represents the Prandtl tip correction coefficient with error coefficient; △r error coefficient is 0.01 to 0.2; r _hub represents the hub radius; H represents the axial induction factor correction factor;

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

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

2) Calculate the cross-section inflow angle φ according to formula (1);

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

4) If |a1-a|>allowable error △a or |b1-b|>allowable error △b, return to step 1) and continue to iterate until the allowable error requirements are met.

Finally, integrate the Cp-λ function relationship of each section to obtain Cp _max , to ensure that the error between Cp _max and the optimal Cp' calculated by GH Bladed or other commercial software is less than 1%, and the corresponding optimal tip speed Same as λ _opt . The calculation expression of Cp is shown in formula (6).

S2. Perform self-optimization calculation on a plurality of extension section parameters at each section position of the blade extension section.

Specifically, using the annual power generation AEP lift △AEP as the objective function, the particle swarm multi-parameter algorithm is used to calculate the section position radius r _ext of each extension section of the blade extension section, the chord length c _ext of each section position, and the torsion angle θ _ext . , The relative thickness _Text performs self-optimization calculation. The specific implementation steps are as follows:

Select the starting position X _start of the blade extension and blade extension section, the design target length X _end and the design section step size bin=0.2m～1m.

Calculate the approximate optimal λ _ext-opt for the blade extension

Calculate the theoretical optimal twist angle θ _theory corresponding to each section position of the blade extension

α _start represents the average aerodynamic angle of attack α _start of X _start at the steady-state wind speed Vin (cut-in wind speed) ~ Vrate (the corresponding wind speed when the rated speed is reached) under the original blade length

The curve of each chord length of the extended blade is calculated by iterative fitting using the polynomial fitting method

y=k ₁ x ⁿ +k ₂ x ^n-1 +...k _n x+k ₀ (10)

Iteration method:

1) Given X _end initial chord length c _end

2) The starting point of the fitted chord length curve is the maximum chord length c _max , and the end point is c _end

3) Use formula (10) for curve fitting, cycle n=1,2,3…

4) Calculate the correlation R _coeff between the fitted curve and the fitted curve for each n cycle

5) When R _coeff ≥ R ₁ , R ₁ =0.95～0.99, the corresponding n is used as the polynomial order of the lower boundary chord length curve of the particle swarm optimization chord length particle loop iteration

6) When R _coeff ≤ R ₂ , R ₁ =0.99～1, and the corresponding n is the polynomial order of the lower boundary chord length curve of the particle swarm optimization chord length particle loop iteration

7) If 6) the chord length of the extended blade calculated by the polynomial curve, the optimal Cp _ext-max calculated by the method in step 1 is less than the Cp _max of the blade before extension, increase the c _end value, and repeat the cycle until it is satisfied .

8) The cycle ends.

For different airfoil models, the particle swarm self-optimization PSO algorithm is used to perform self-optimization calculations on the chord length, twist angle and relative thickness of the blade extension section. The iteratively calculated chord length and torsion angle of each section of the blade extension section , relative thickness, and airfoil type are used as aerodynamic shape parameters for blade extension design.

v _i =ωv _i +ω ₁ rand()(pbest _i -x _i )+ω ₂ rand()(gbest _i -x _i ) (11)

x _i = x _i +v _i (12)

In the formula: v _i represents the particle velocity; ω ₁ and ω ₂ represent the learning factor, ω ₁ =ω ₂ =1～2; rand() represents a random number from 0 to 1; i represents the total number of particle swarms; x _i represents the current particle size position; pbest _i and gbest _i represent the two extreme values in the particle iterative process; ω represents the inertia factor, ω=0.4～0.9

The airfoil type selects the airfoils commonly used in wind turbines, DU series, RISO series, NACA series, FFA series, S series and their variants, with a relative thickness range of 16% to 18%.

The particle swarm scale particle_num=30～100, the iteration number iteration_num=10～50, and the optimization goal is the best AEP.

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

1) See 2-6 for the upper and lower boundaries of the chord length

2) The upper boundary of the twist angle is θ _theory ±Twist_Error, Twist_Error=1～2deg

3) The upper boundary of the relative thickness of the airfoil is the thickness corresponding to X _start , and the lower boundary is the smallest relative thickness in the airfoil model.

If the whole machine load after the blade is extended exceeds the design load or the power generation increase after the extension does not meet the requirements, adjust X _end and re-execute the subsequent calculation.

It can be seen from the above technical solutions that this embodiment provides a design method for a blade extension device, which is applied to electronic equipment, and the blade extension device includes a blade extension section. The design method specifically uses the modified BEM theory to calculate the blade extension The CP~λ corresponding relationship curve of the blade section; the annual power generation improvement is used as the objective function, the particle swarm multi-parameter algorithm is used, and based on the parameters in the CP~λ corresponding relationship curve, the multi-section position of each section position of the blade extension section is calculated. The parameters of the extension section are self-optimized and calculated, so as to obtain the aerodynamic shape parameters such as the chord length, twist angle, relative thickness, and airfoil type of each section of the blade extension section. Through the above solution, the design of the blade extension device can be realized.

Since the blade extension device further includes a blade extension winglet, therefore, in a specific embodiment of the present application, the following steps are further included to realize the design of the blade extension winglet, as shown in FIG. 2 .

S3. Select the starting position of the blade to extend the winglet.

On the basis of the blade extension section calculated above, determine the starting position r _start of the blade tip winglet along the blade span. The selection of r _start is based on:

1) Through professional commercial software such as GH Bladed, Simpack, Ansys CFX/Fluent or open source software such as Fast, or based on modified BEM theory, lift line theory, actuation line model and other aerodynamic models, self-compiled iterative programs to calculate blade aerodynamics Performance calculation △AEP meets the design target requirements;

时，以此时的截面位置r_start为小翼的起始位置。2) Reduce the blade radius in step 2 according to the radius length bin given in 2-3, that is, reduce the design in reverse, and calculate the corresponding ΔAEP _i according to the method described above, when

, take the section position _rstart at this time as the starting position of the winglet.

翼根弦向起始位置x，前缘修型贝塞尔曲线参数s1、s2、小翼翼展长度Ltip，外倾角τ，折弯半径Rt₁、Rt₂、以及安装角A_set。分别如图3a、3b和3c所示。The key parameters of the aerodynamic profile of the blade extended winglet include the leading edge sweep angle γ ₁ , the trailing edge sweep angle γ ₂ , the tip chord length c ₂ , the wing root chord length c ₁ , the tip-to-root ratio

Root chordwise starting position x, leading edge modified Bezier curve parameters s1, s2, winglet span length Ltip, camber angle τ, bending radii Rt ₁ , Rt ₂ , and installation angle A _set . These are shown in Figures 3a, 3b and 3c, respectively.

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

Select the airfoil of the blade tip extended winglet, selection principle 1: the airfoil of the winglet is a series of airfoils with a flat upper surface and a certain camber on the trailing edge, and the thickness of the airfoil 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 trim, etc.

后缘后掠角γ₂∈(0°,γ₁)Winglet span length Ltip≥X _end -r _start , tip-to-root ratio y≥0.2, camber angle τ ∈ (0°, 90°), installation angle A _set ∈ (-2°, 5°), leading edge sweep angle

Trailing edge sweep angle γ ₂ ∈(0°,γ ₁ )

Determine the root chordwise starting positions x∈(x ₁ ,x ₂ ), x ₁ and x ₂ .

为边界条件时，r_start位置气流下洗起始位置，x₂为额定风速Vrate、额定转速

为边界条件时，r_start位置气流下洗起始位置。此时r_start为叶尖。Method 1: x ₁ =0, x ₂ = the maximum thickness of the airfoil used by r _start ; Method 2: Determine the values of x ₁ and x ₂ through CFD simulation, x ₁ is the cut-in wind speed Vin, the grid-connected speed

When it is the boundary condition, the r _start position is the starting position of the airflow downwash, and x ₂ is the rated wind speed Vrate and the rated speed.

When it is the boundary condition, the airflow downwash starting position at the r _start position. At this time, r _start is the tip of the blade.

Since Ltip, y, τ, and x are important parameters that determine the induced drag of the winglet among the aerodynamic shape parameters of the winglet, the above four parameters are determined first. After the determination, the leading edge sweep angle and the trailing edge sweep are optimized. Angle, installation angle, wing root bending radius, leading edge trim Bezier parameters.

The vortex lattice method VLM is used to calculate the aerodynamic force of the blade wing. The steps include:

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

2) Perform mesh division, and perform surface division on each section component of the blade winglet, the blade main body or the blade extension section;

3) Calculate the aerodynamic performance of the whole composed of the blade winglet and the blade main body or the blade extension section under the attack angle range of (-2°, 10°);

4) In the simulation results, the optimal lift-to-drag ratio is used as the judgment condition to determine the optimal combination of Ltip, y, τ, and x;

5) Based on the above combinations of Ltip, y, τ, and x, iteratively calculate the leading edge sweep angle, trailing edge sweep angle, installation angle, and leading edge modified Bessel parameters 90°<s1<180°, 90°< s2<180°.

Through the above scheme, the design of the winglet bending to the pressure surface and the suction surface can also be realized.

Through the following solutions, the design of all the components of the blade extension device can be realized.

Embodiment 2

FIG. 4 is a block diagram of a design device of a blade extension device according to an embodiment of the present application.

As shown in FIG. 4 , the design device provided in this embodiment is applied to electronic equipment, which can be understood as a computer or server with data computing and information processing capabilities, and the design device is used to extend the blade of the wind turbine. Various parameters are calculated to obtain the manufacturing parameters of the blade extension device. The blade extension device includes a blade extension section. Specifically, the design device for the blade extension section includes a first calculation module 10 and a second calculation module 20 .

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

This method is used to calculate the corresponding relationship curve, so as to ensure that the calculated Cp value has an error of 1% with the calculation result of the commercial software GH Bladed, and to make the corresponding optimum tip speed ratio λ _opt equal. The calculation process of this module is as follows:

First, the same aerodynamic shape parameters as those of 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 torsion angle θ, the relative thickness T, and the airfoil aerodynamic parameters (angle of attack). AOA corresponds to lift coefficient Cl, drag coefficient Cd and bending moment coefficient Cm);

Then, the modified BEM theory is used for each section to iteratively calculate the inflow angle φ, tip loss F_loss, blade root loss H_loss, axial induction factor a and tangential induction factor b under each λ, and the corresponding functional relationships are respectively for

In the formula: R represents the blade radius; f_loss represents the Prandtl tip correction coefficient with error coefficient; △r error coefficient is 0.01 to 0.2; r _hub represents the hub radius; H represents the axial induction factor correction factor;

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

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

6) Calculate the cross-section inflow angle φ according to formula (1);

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

8) If |a1-a|>allowable error △a or |b1-b|>allowable error △b, return to step 1) and continue to iterate until the allowable error requirements are met.

Finally, integrate the Cp-λ function relationship of each section to obtain Cp _max , to ensure that the error between Cp _max and the optimal Cp' calculated by GH Bladed or other commercial software is less than 1%, and the corresponding optimal tip speed Same as λ _opt . The calculation expression of Cp is shown in formula (6).

The second calculation module is used to perform self-optimization calculation on a plurality of extension node parameters of each section position of the blade extension node.

Specifically, using the annual power generation AEP lift △AEP as the objective function, the particle swarm multi-parameter algorithm is used to calculate the section position radius r _ext of each extension section of the blade extension section, the chord length c _ext of each section position, and the torsion angle θ _ext . , The relative thickness _Text performs self-optimization calculation. The calculation process of this module is as follows:

Select the starting position X _start of the blade extension and blade extension section, the design target length X _end and the design section step size bin=0.2m～1m.

Calculate the approximate optimal λ _ext-opt for the blade extension

Calculate the theoretical optimal twist angle θ _theory corresponding to each section position of the blade extension

α _start represents the average aerodynamic angle of attack α _start of X _start at the steady-state wind speed Vin (cut-in wind speed) ~ Vrate (the corresponding wind speed when the rated speed is reached) under the original blade length

The curve of each chord length of the extended blade is calculated by iterative fitting using the polynomial fitting method

y=k ₁ x ⁿ +k ₂ x ^n-1 +...k _n x+k ₀ (10)

Iteration method:

9) Given X _end initial chord length c _end

10) The starting point of the fitted chord length curve is the maximum chord length c _max , and the end point is c _end

11) Use formula (10) for curve fitting, loop n=1,2,3…

12) Calculate the correlation R _coeff between the fitted curve and the fitted curve for each n cycle

13) When R _coeff ≥ R ₁ , R ₁ =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 optimization chord-length particle loop iteration

14) When R _coeff ≤ R ₂ , R ₁ =0.99～1, and the corresponding n is the polynomial order of the lower boundary chord length curve of the particle swarm optimization chord length particle loop iteration

15) If 6) the chord length of the extended blade calculated by the polynomial curve, the optimal Cp _ext-max calculated by the method in step 1 is less than the Cp _max of the blade before extension, increase the c _end value, and repeat the cycle until it is satisfied .

16) The loop ends.

For different airfoil models, the particle swarm self-optimization PSO algorithm is used to perform self-optimization calculations on the chord length, twist angle and relative thickness of the blade extension section. The iteratively calculated chord length and torsion angle of each section of the blade extension section , relative thickness, and airfoil type are used as aerodynamic shape parameters for blade extension design.

v _i =ωv _i +ω ₁ rand()(pbest _i -x _i )+ω ₂ rand()(gbest _i -x _i ) (11)

x _i = x _i +v _i (12)

In the formula: v _i represents the particle velocity; ω ₁ and ω ₂ represent the learning factor, ω ₁ =ω ₂ =1～2; rand() represents a random number from 0 to 1; i represents the total number of particle swarms; x _i represents the current particle size position; pbest _i and gbest _i represent the two extreme values in the particle iterative process; ω represents the inertia factor, ω=0.4～0.9

The airfoil type selects the airfoils commonly used in wind turbines, DU series, RISO series, NACA series, FFA series, S series and their variants, with a relative thickness range of 16% to 18%.

The particle swarm scale particle_num=30～100, the iteration number iteration_num=10～50, and the optimization goal is the best AEP.

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

4) See 2-6 for the upper and lower boundaries of the chord length

5) The upper boundary of the twist angle is θ _theory ±Twist_Error, Twist_Error=1～2deg

6) The upper boundary of the relative thickness of the airfoil is the thickness corresponding to X _start , and the lower boundary is the smallest relative thickness in the airfoil model.

If the whole machine load after the blade is extended exceeds the design load or the power generation increase after the extension does not meet the requirements, adjust X _end and re-execute the subsequent calculation.

It can be seen from the above technical solutions that this embodiment provides a design device for a blade extension device, which is applied to electronic equipment, and the blade extension device includes a blade extension section. The CP~λ corresponding relationship curve of the blade section; the annual power generation improvement is used as the objective function, the particle swarm multi-parameter algorithm is used, and based on the parameters in the CP~λ corresponding relationship curve, the multi-section position of each section position of the blade extension section is calculated. The parameters of the extension section are self-optimized and calculated, so as to obtain the aerodynamic shape parameters such as the chord length, twist angle, relative thickness, and airfoil type of each section of the blade extension section. Through the above solution, the design of the blade extension device can be realized.

Since the blade extension device also includes a blade extension winglet, in a specific embodiment of the present application, it also includes a position selection module 30 and a third calculation module 40, so as to realize the design of the blade extension winglet, as shown in Fig. 2 shown.

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

On the basis of the blade extension section calculated above, determine the starting position r _start of the blade tip winglet along the blade span. The selection of r _start is based on:

3) Through professional commercial software such as GH Bladed, Simpack, Ansys CFX/Fluent or open source software such as Fast, or based on modified BEM theory, lift line theory, actuation line model and other aerodynamic models, self-compiled iterative programs to calculate blade aerodynamics Performance calculation △AEP meets the design target requirements;

时，以此时的截面位置r_start为小翼的起始位置。4) Reduce the blade radius in step 2 according to the radius length bin given in 2-3, that is, reduce the design in reverse, and calculate the corresponding ΔAEP _i according to the method described above, when

, take the section position _rstart at this time as the starting position of the winglet.

翼根弦向起始位置x，前缘修型贝塞尔曲线参数s1、s2、小翼翼展长度Ltip，外倾角τ，折弯半径Rt₁、Rt₂、以及安装角A_set。分别如图3a、3b和3c所示。The key parameters of the aerodynamic profile of the blade extended winglet include the leading edge sweep angle γ ₁ , the trailing edge sweep angle γ ₂ , the tip chord length c ₂ , the wing root chord length c ₁ , the tip-to-root ratio

Root chordwise starting position x, leading edge modified Bezier curve parameters s1, s2, winglet span length Ltip, camber angle τ, bending radii Rt ₁ , Rt ₂ , and installation angle A _set . These are shown in Figures 3a, 3b and 3c, respectively.

The third calculation module is used for calculating the aerodynamic shape parameters of the blade extension winglet based on the starting position.

Select the airfoil of the blade tip extended winglet, selection principle 1: the airfoil of the winglet is a series of airfoils with a flat upper surface and a certain camber on the trailing edge, and the thickness of the airfoil is less than 16%. The series of airfoils include but are not limited to NACA 4 series, 5 series, 6 series, WortmannFX series, FFA series and their variants, such as trailing edge trim, etc.

后缘后掠角γ₂∈(0°,γ₁)Winglet span length Ltip≥X _end -r _start , tip-to-root ratio y≥0.2, camber angle τ ∈ (0°, 90°), installation angle A _set ∈ (-2°, 5°), leading edge sweep angle

Trailing edge sweep angle γ ₂ ∈(0°,γ ₁ )

Determine the root chordwise starting positions x∈(x ₁ ,x ₂ ), x ₁ and x ₂ .

为边界条件时，r_start位置气流下洗起始位置，x₂为额定风速Vrate、额定转速

为边界条件时，r_start位置气流下洗起始位置。此时r_start为叶尖。Method 1: x ₁ =0, x ₂ = the maximum thickness of the airfoil used by r _start ; Method 2: Determine the values of x ₁ and x ₂ through CFD simulation, x ₁ is the cut-in wind speed Vin, the grid-connected speed

When it is the boundary condition, the r _start position is the starting position of the airflow downwash, and x ₂ is the rated wind speed Vrate and the rated speed.

When it is the boundary condition, the airflow downwash starting position at the r _start position. At this time, r _start is the tip of the blade.

Since Ltip, y, τ, and x are important parameters that determine the induced drag of the winglet among the aerodynamic shape parameters of the winglet, the above four parameters are determined first. After the determination, the leading edge sweep angle and the trailing edge sweep are optimized. Angle, installation angle, wing root bending radius, leading edge trim Bezier parameters.

The vortex lattice method VLM is used to calculate the aerodynamic force of the blade wing. The steps include:

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

2) Perform mesh division, and perform surface division on each section component of the blade winglet, the blade main body or the blade extension section;

3) Calculate the aerodynamic performance of the whole composed of the blade winglet and the blade main body or the blade extension section under the attack angle range of (-2°, 10°);

4) In the simulation results, the optimal lift-to-drag ratio is used as the judgment condition to determine the optimal combination of Ltip, y, τ, and x;

5) Based on the above combinations of Ltip, y, τ, and x, iteratively calculate the leading edge sweep angle, trailing edge sweep angle, installation angle, and leading edge modified Bessel parameters 90°<s1<180°, 90°< s2<180°.

Through the above scheme, the design of the winglet bending to the pressure surface and the suction surface can also be realized.

Through the following solutions, the design of all the components of the blade extension device can be realized.

Embodiment 3

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

The blade extension device includes a blade extension section. The design method is to use the modified BEM theory to calculate the CP-λ corresponding relationship curve of the blade extension section; take the annual power generation increase as the objective function, adopt the particle swarm multi-parameter algorithm, and based on CP ～λ corresponds to the parameters in the relationship curve, and performs self-optimization calculation on the parameters of multiple extension sections at each section position of the blade extension section, so as to obtain the chord length, twist angle, relative thickness, airfoil type, etc. of each section of the blade extension section. Aerodynamic shape parameters. Through the above solution, the design of the blade extension device can be realized.

The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the various embodiments may be referred to each other.

It should be understood by those skilled in the art that the embodiments of the embodiments of the present invention may be provided as a method, an apparatus, or a computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media having computer-usable program code embodied therein, including but not limited to disk storage, CD-ROM, optical storage, and the like.

Embodiments of the present invention are described with reference to flowcharts and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the present invention. It will be understood that each flow and/or block in the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing terminal equipment to produce a machine that causes the instructions to be executed by the processor of the computer or other programmable data processing terminal equipment Means are created for implementing the functions specified in the flow or flows of the flowcharts and/or the blocks or blocks of the block diagrams.

These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing terminal equipment to operate in a particular manner, such that the instructions stored in the computer readable memory result in an article of manufacture comprising instruction means, the The instruction means implement the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

These computer program instructions can also be loaded on a computer or other programmable data processing terminal equipment, so that a series of operational steps are performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby executing on the computer or other programmable terminal equipment The instructions executed on the above provide steps for implementing the functions specified in the flowchart or blocks and/or the block or blocks of the block diagrams.

While preferred embodiments of the embodiments of the present invention have been described, additional changes and modifications to these embodiments may be made by those skilled in the art once the basic inventive concepts are known. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications that fall within the scope of the embodiments of the present invention.

Finally, it should also be noted that in this document, relational terms such as first and second are used only to distinguish one entity or operation from another, and do not necessarily require or imply these entities or there is any such actual relationship or sequence between operations. Moreover, the terms "comprising", "comprising" or any other variation thereof are intended to encompass non-exclusive inclusion such that a process, method, article or terminal device that includes a list of elements includes not only those elements, but also a non-exclusive list of elements. other elements, or also include elements inherent to such a process, method, article or terminal equipment. Without further limitation, an element defined by the phrase "comprises a..." does not preclude the presence of additional identical elements in the process, method, article, or terminal device that includes the element.

The technical solutions provided by the present invention have been described in detail above, and specific examples are used to illustrate the principles and implementations of the present invention. The descriptions of the above embodiments are only used to help understand the methods and core ideas of the present invention; 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 embodiments and application scope. To sum up, the content of this specification should not be construed as a limitation of the present invention.

Claims (12)

1. A design method of a blade extension device, applied to electronic equipment, is characterized in that, the blade extension device comprises a blade extension section, and the design method comprises the steps: Using the modified BEM theory to calculate the CP～λ corresponding relationship curve after adding the blade extension; Taking the increase in annual power generation as the objective function, using the particle swarm multi-parameter algorithm, and based on the parameters in the CP ~ λ corresponding relationship curve, the parameters of each section of the blade extension section are automatically carried out. Optimization calculation. 2. The design method of claim 1, wherein the plurality of elongation parameters include radius, chord length, twist angle, and relative thickness. 3. The design method according to claim 1, wherein the calculation of the CP-λ corresponding relationship curve of the blade extension section by the modified BEM theory method comprises the steps of: Select the same aerodynamic shape parameters as the specific blade model; Using the modified BEM theory for each section of the blade extension section, iteratively calculate the inflow angle, tip loss, blade root loss, axial induction factor and tangential induction of each section at each tip speed ratio factor, and the corresponding functional relationships are:

In the formula: R is the blade radius; f_loss is the Prandtl tip correction coefficient with error coefficient; △r is the error coefficient; r _hub is the hub radius; H is the axial induction factor correction coefficient; F=F_loss·H_loss; Integrate and calculate the inflow angle, tip loss, blade root loss, axial induction factor and tangential induction factor of each of the sections under each of the blade tip speed ratios, and construct the CP~λ according to the calculation results Correspondence curve. 4 . The design method according to claim 3 , wherein the error coefficient Δr ranges from 0.01 to 0.2. 5 . 5 . The design method according to claim 1 , wherein the improvement in annual power generation is taken as the objective function, the particle swarm multi-parameter algorithm is used, and based on the parameters in the CP-λ corresponding relationship curve, the The self-optimization calculation is performed on a plurality of extension section parameters of each section position of the blade extension section, including the steps: Selecting the starting position of the blade extension and the blade extension section, the design target length, and the design section step size; Calculate the approximate optimal λ _ext-opt after the extension of the blade extension

Calculate the theoretical optimal twist angle θ _theory of the blade extension section corresponding to each section position

α _start represents the average aerodynamic angle of attack α _start of X _start at the steady-state wind speed Vin (cut-in wind speed) ~ Vrate (corresponding wind speed when the rated speed is reached) under the original blade length A polynomial fitting method is used to iteratively fit and calculate the curve of each chord length of the blade extension section y=k ₁ x ⁿ +k ₂ x ^n-1 +...k _n x+k ₀ Under different airfoil models, the chord length, twist angle and relative thickness of the airfoil of the blade extension section are self-optimized by the particle swarm self-optimization PSO algorithm. v _i =ωv _i +ω ₁ rand()(pbest _i -x _i )+ω ₂ rand()(gbest _i -x _i ) x _i = x _i +v _i In the formula: v _i represents the particle velocity, ω ₁ and ω ₂ represent the learning factor, ω ₁ =ω ₂ =1～2, rand() represents a random number from 0 to 1, i represents the total number of particle swarms, and _xi represents the current particle size. position, pbest _i and gbest _i represent the two extreme values in the particle iterative process, ω represents the inertia factor, ω=0.4～0.9. 6. The design method according to any one of claims 1 to 5, wherein the blade extension device further comprises a blade extension winglet, and the design method further comprises the steps of: selecting the starting position of the blade to extend the winglet; Based on the starting position, the aerodynamic shape parameters of the blade extension winglet are calculated. 7. The design method according to claim 6, wherein the aerodynamic shape parameters include leading edge sweep angle, trailing edge sweep angle, wing tip chord length, wing root chord length, tip root ratio, wing root Chordal starting position, leading edge modified Bezier curve parameters, winglet span length, camber angle, bend radius and installation angle. 8. A design device for a blade extension device, which is applied to electronic equipment, wherein the blade extension device comprises a blade extension section, and the design device comprises: The first calculation module is used to calculate the CP-λ corresponding relationship curve after adding the blade extension section by using the modified BEM theory; The second calculation module is used for taking the increase in annual power generation as the objective function, using the particle swarm multi-parameter algorithm, and based on the parameters in the corresponding relationship curve of CP to λ, to determine the position of each section of the blade extension section. Self-optimization calculation is performed for multiple extension section parameters. 9. The design apparatus of claim 8, wherein the plurality of elongation parameters include radius, chord length, twist angle, and relative thickness. 10. The design device according to claim 8 or 9, wherein the blade extension device further comprises a blade extension winglet, and the design device further comprises: a position selection module for selecting the starting position of the blade extension winglet; The third calculation module is configured to calculate the aerodynamic shape parameters of the blade extension winglet based on the starting position. 11. The design device according to claim 10, wherein the aerodynamic shape parameters include leading edge sweep angle, trailing edge sweep angle, wing tip chord, wing root chord, tip root ratio, wing root Chordal starting position, leading edge modified Bezier curve parameters, winglet span length, camber angle, bend radius and installation angle. 12. An electronic device, comprising 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 configured to execute the computer program or instructions, so that the electronic device implements the design method of the blade extension device according to any one of claims 1 to 7 .

Images