Method, device and equipment for optimizing long blade of wind turbine generator and medium

Abstract

The invention relates to the technical field of wind turbine generators, particularly provides a long blade optimization method and device for a wind turbine generator, equipment and a medium, and aims to solve the problems that long blades in the wind turbine generator can be obviously deformed in the actual operation process, only the shapes of the blades which are not deformed are optimized, and the working efficiency is low. And the technical problem of low power generation efficiency of the wind turbine generator is solved. In order to achieve the purpose, the method comprises the steps of obtaining blade shape data and blade deformation data; according to the blade shape data and the blade deformation data, blade non-deformation aerodynamic force and blade deformation aerodynamic force are obtained; according to the blade non-deformation aerodynamic force, the blade deformation aerodynamic force and the blade deformation data, an additional blade tip loss coefficient is obtained; according to the additional blade tip loss coefficient, corrected aerodynamic force is obtained; and adjusting the blade shape data of the long blade according to the corrected aerodynamic force.

Description

Technical Field

[0001] This application relates to the field of wind turbine technology, specifically providing a method, apparatus, equipment, and medium for optimizing long blades of wind turbines. Background Technology

[0002] With the development of wind power technology, the blade length of wind turbines is constantly increasing in order to improve power generation efficiency.

[0003] In existing technologies, simulation software is used to obtain the aerodynamic performance of wind turbine blades in their undeformed state, and the blade shape is then optimized based on this performance. However, for long blades in wind turbines, significant deformation occurs during actual operation, and optimizing only the shape of the undeformed blades can lead to low power generation efficiency in wind turbines.

[0004] Accordingly, there is a need in the field for a new method for optimizing the long blades of wind turbines to address the aforementioned problems. Summary of the Invention

[0005] In order to overcome the above-mentioned defects, this application is made to provide a solution or at least a partial solution to the technical problem in the prior art that for long blades in wind turbines, significant deformation will occur during actual operation, and optimizing only the shape of the undeformed blades will result in low power generation efficiency of the wind turbine.

[0006] In a first aspect, this application provides a method for optimizing the long blades of a wind turbine, comprising:

[0007] Acquire leaf shape data and leaf deformation data;

[0008] Based on the blade shape data and the blade deformation data, the aerodynamic forces of the blade without deformation and the aerodynamic forces of the blade with deformation are obtained;

[0009] Based on the undeformed aerodynamic force of the blade, the deformed aerodynamic force of the blade, and the blade deformation data, the additional tip loss coefficient is obtained;

[0010] Based on the additional tip loss coefficient, the corrected aerodynamic force is obtained;

[0011] Based on the modified aerodynamic force, the blade shape data of the long blade is adjusted.

[0012] In one technical solution of the aforementioned method for optimizing the long blades of a wind turbine, the step of obtaining an additional tip loss coefficient based on the undeformed aerodynamic force of the blade, the deformed aerodynamic force of the blade, and the blade deformation data includes:

[0013] Based on the ratio of the blade deformation aerodynamic force to the blade undeformed aerodynamic force, a first additional tip loss coefficient set corresponding to a portion of the blade deformation data is obtained.

[0014] Based on the blade deformation data and the first set of additional tip loss coefficients, a second set of additional tip loss coefficients is obtained;

[0015] The additional tip loss coefficients are obtained by combining the first set of additional tip loss coefficients and the second set of additional tip loss coefficients.

[0016] In one technical solution of the aforementioned method for optimizing the long blades of a wind turbine, the step of obtaining a second set of additional tip loss coefficients based on the blade deformation data and the first set of additional tip loss coefficients includes:

[0017] Obtain two adjacent deformation data points and the additional tip loss coefficient corresponding to the two adjacent deformation data points from the blade deformation data;

[0018] Interpolation is performed on the two adjacent deformation data to obtain interpolated deformation data;

[0019] Based on the additional tip loss coefficients corresponding to the two adjacent deformation data and the interpolated deformation data, a second set of additional tip loss coefficients is obtained.

[0020] In one technical solution of the aforementioned method for optimizing the long blades of a wind turbine, obtaining the corrected aerodynamic force based on the additional tip loss coefficient includes:

[0021] Obtain the incoming airflow speed, the rotor blade rotation speed, and the distance from the blade tip to the blade root;

[0022] The inflow angle is obtained based on the incoming wind speed, the rotational speed of the impeller blades, and the distance from the blade tip to the blade root.

[0023] The normal force and tangential force are obtained based on the inflow angle and the additional tip loss coefficient;

[0024] The corrected aerodynamic force is obtained based on the normal force and the tangential force.

[0025] In one technical solution of the aforementioned method for optimizing the long blades of a wind turbine, after obtaining the corrected aerodynamic force based on the normal force and the tangential force, the method further includes:

[0026] Obtain the number of blades, rotor blade rotation speed, blade area, and incoming air velocity;

[0027] The total torque is obtained based on the number of blades and the inflow angle;

[0028] The wind turbine power is obtained based on the total torque and the wind turbine blade speed.

[0029] The power coefficient is obtained based on the wind turbine power, the blade area, and the incoming wind speed.

[0030] In one technical solution of the aforementioned method for optimizing the long blades of a wind turbine, the blade shape data of the long blades is adjusted based on the modified aerodynamic forces, including:

[0031] The corrected aerodynamic force is input into a preset neural network model to obtain updated blade shape data;

[0032] Based on the updated blade shape data, the blade shape data of the long blade is adjusted.

[0033] In one technical solution of the aforementioned method for optimizing the long blades of a wind turbine, the method further includes:

[0034] Obtain operating data of wind turbine units;

[0035] Based on the operational data, optimized blade shape data is obtained;

[0036] Based on the optimized blade shape data, the updated blade shape data is adjusted.

[0037] Secondly, this application provides a long blade optimization device, comprising:

[0038] The acquisition module is used to acquire blade shape data and blade deformation data;

[0039] The analysis module is used to obtain the aerodynamic forces of the blade without deformation and the aerodynamic forces of the blade with deformation based on the blade shape data and the blade deformation data.

[0040] The processing module is used to obtain the additional tip loss coefficient based on the undeformed aerodynamic force of the blade, the deformed aerodynamic force of the blade, and the blade deformation data;

[0041] The processing module is also used to obtain the corrected aerodynamic force based on the additional tip loss coefficient;

[0042] The adjustment module is used to adjust the blade shape data of the long blade according to the corrected aerodynamic force.

[0043] Thirdly, this application provides an electronic device including a processor and a storage device, the storage device being adapted to store a plurality of program codes, the program codes being adapted to be loaded and run by the processor to perform the method described in any one of the first aspects.

[0044] Fourthly, this application provides a computer-readable storage medium storing a plurality of program codes adapted to be loaded and run by a processor to perform the method described in any one of the first aspects.

[0045] This application provides a method, apparatus, equipment, and medium for optimizing long blades of wind turbines. The method specifically includes: acquiring blade shape data and blade deformation data; obtaining the undeformed aerodynamic force and the deformed aerodynamic force of the blade based on the blade shape data and blade deformation data; obtaining an additional tip loss coefficient based on the undeformed aerodynamic force, the deformed aerodynamic force, and the blade deformation data; obtaining a corrected aerodynamic force based on the additional tip loss coefficient; and adjusting the blade shape data of the long blade based on the corrected aerodynamic force, thereby improving the power generation efficiency of the wind turbine. Attached Figure Description

[0046] The disclosure of this application will become more readily understood with reference to the accompanying drawings. It will be readily understood by those skilled in the art that these drawings are for illustrative purposes only and are not intended to limit the scope of protection of this application. Furthermore, similar numbers in the drawings are used to denote similar components, wherein:

[0047] Figure 1 A flowchart illustrating an embodiment of a method for optimizing the long blades of a wind turbine provided in this application.

[0048] Figure 2 A flowchart illustrating a second embodiment of a method for optimizing the long blades of a wind turbine provided in this application.

[0049] Figure 3 A flowchart illustrating a third embodiment of a method for optimizing the long blades of a wind turbine provided in this application;

[0050] Figure 4 A flowchart illustrating a fourth embodiment of a method for optimizing the long blades of a wind turbine provided in this application;

[0051] Figure 5 A flowchart illustrating a fifth embodiment of a method for optimizing the long blades of a wind turbine provided in this application;

[0052] Figure 6 A flowchart illustrating a method for optimizing the long blades of a wind turbine, as provided in this application, is shown in Embodiment Six.

[0053] Figure 7 A flowchart illustrating Embodiment Seven of a method for optimizing the long blades of a wind turbine provided in this application;

[0054] Figure 8 This is a schematic diagram of a first embodiment of a long blade optimization device provided in this application.

[0055] Figure 9 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application.

[0056] List of reference numerals in the attached diagram:

[0057] 11: Acquisition module; 12: Analysis module; 13: Processing module; 14: Adjustment module; 21: Processor; 22: Memory. Detailed Implementation

[0058] Some embodiments of this application are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of this application and are not intended to limit the scope of protection of this application.

[0059] In the description of this application, "module" and "processor" can include hardware, software, or a combination of both. A module can include hardware circuitry, various suitable sensors, communication ports, memory, and can also include software components, such as program code, or a combination of software and hardware. A processor can be a central processing unit, microprocessor, image processor, digital signal processor, or any other suitable processor. The processor has data and / or signal processing capabilities. The processor can be implemented in software, in hardware, or a combination of both. Non-transitory computer-readable storage media includes any suitable medium capable of storing program code, such as magnetic disks, hard disks, optical disks, flash memory, read-only memory, random access memory, etc. The term "A and / or B" means all possible combinations of A and B, such as only A, only B, or A and B. The terms "at least one A or B" or "at least one of A and B" have a similar meaning to "A and / or B" and can include only A, only B, or A and B. The singular terms "a" or "this" can also include plural forms.

[0060] In the existing technology, during the design of long blades for wind turbines, the aerodynamic performance of the blades without deformation in a simulated environment is obtained through simulation software. Based on this aerodynamic performance, the shape parameters of the long blades are optimized. As a result, the long blades have low operating efficiency at both high and low wind speeds, and may even lead to fatigue of the blade structure.

[0061] Here we first explain some of the terms used in this application:

[0062] Tangential force: Tangential force is the force that acts on an object along the tangent to a curve. It changes the magnitude or direction of the object's velocity, causing it to accelerate or decelerate.

[0063] Normal force: The normal force is the force acting on an object perpendicular to the tangent of the curve. It is perpendicular to the object's trajectory and provides the source of the object's centripetal force.

[0064] Power factor: an important indicator for measuring the energy conversion efficiency of wind turbines.

[0065] Based on this, in order to solve the above-mentioned technical problems, this application provides a method for optimizing the shape of long blades of wind turbines, so as to optimize the shape of long blades and thereby improve the power generation efficiency of wind turbines.

[0066] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0067] Figure 1 This is a flowchart illustrating an embodiment of a method for optimizing the long blades of a wind turbine generator, as provided in this application. Figure 1 As shown, specifically, the method includes:

[0068] Step S101: Obtain blade shape data and blade deformation data.

[0069] In this embodiment, the blade shape data includes blade length, maximum chord length, maximum chord length position, root node diameter, hub diameter, and relative thickness distribution.

[0070] In this embodiment, the blade deformation data includes deformation data with multiple different deformation amplitudes.

[0071] In this embodiment, for example, the blade deformation data is {0%, 5%, 10%, 15%, 20%}.

[0072] Step S102: Based on the blade shape data and blade deformation data, obtain the aerodynamic forces of the blade without deformation and the aerodynamic forces of the blade with deformation.

[0073] In this embodiment, a three-dimensional geometric model of the blade is constructed based on the blade shape data, and the undeformed aerodynamic force and the blade deformed aerodynamic force of the three-dimensional geometric model of the blade are obtained based on different blade deformation data.

[0074] In this embodiment, for example, computational fluid dynamics simulation software is used to obtain the aerodynamic forces of the blade under different deformation amplitudes, both before and after deformation.

[0075] Step S103: Based on the undeformed aerodynamic force of the blade, the deformed aerodynamic force of the blade, and the blade deformation data, obtain the additional tip loss coefficient.

[0076] In this embodiment, based on the blade deformation data, the aerodynamic forces of the blade without deformation and the aerodynamic forces of the blade with deformation are obtained, and the additional tip loss coefficient is obtained based on the product of the aerodynamic forces of the blade without deformation and the aerodynamic forces of the blade with deformation.

[0077] Step S104: Obtain the corrected aerodynamic force based on the additional tip loss coefficient.

[0078] Step S105: Adjust the blade shape data of the long blades according to the corrected aerodynamic force.

[0079] In this embodiment, blade shape optimization data corresponding to the modified aerodynamic force is obtained based on the magnitude of the modified aerodynamic force, and the blade shape data of long blades is adjusted based on the blade shape optimization data.

[0080] In this embodiment, blade shape data and blade deformation data are acquired; based on the blade shape data and blade deformation data, the undeformed aerodynamic force and the deformed aerodynamic force of the blade are obtained; based on the undeformed aerodynamic force, the deformed aerodynamic force, and the blade deformation data, an additional tip loss coefficient is obtained; based on the additional tip loss coefficient, a corrected aerodynamic force is obtained; based on the corrected aerodynamic force, the blade shape data of the long blade is adjusted. Compared with the prior art, which optimizes the shape of the blade based on the aerodynamic performance of the undeformed long blade, resulting in low power generation efficiency of wind turbines with long blades in actual operation, this application obtains the undeformed aerodynamic force and the deformed aerodynamic force of the blade based on the blade shape data and blade deformation data, and obtains the additional tip loss coefficient based on the undeformed aerodynamic force, the deformed aerodynamic force, and the blade deformation data, and then obtains the corrected aerodynamic force based on the additional tip loss coefficient, and adjusts the blade shape data of the long blade based on the corrected aerodynamic force, thereby obtaining the optimal shape design parameters of the long blade and improving the power generation efficiency of wind turbines with long blades.

[0081] Figure 2 This is a flowchart illustrating a second embodiment of a method for optimizing the long blades of a wind turbine, as provided in this application. Based on the above embodiments, as follows... Figure 2 As shown, specifically, one embodiment of step S103 includes:

[0082] Step S201: Based on the ratio of blade deformation aerodynamic force to blade undeformed aerodynamic force, obtain the first set of additional tip loss coefficients corresponding to a portion of the blade deformation data.

[0083] In this embodiment, there is a large amount of blade deformation data. A portion of the deformation data is taken from this portion, and the additional tip loss coefficient corresponding to each deformation data in this portion is calculated as the ratio of the blade deformation aerodynamic force to the blade undeformed aerodynamic force. Among them, multiple additional tip loss coefficients form a first set of additional tip loss coefficients.

[0084] Step S202: Based on the blade deformation data and the first set of additional tip loss coefficients, obtain the second set of additional tip loss coefficients.

[0085] In this embodiment, interpolation processing is performed on the blade deformation data to obtain interpolated data, and a second additional blade tip loss coefficient set is obtained based on the interpolated data and the first additional blade tip loss coefficient set.

[0086] Step S203: Combine the first set of additional tip loss coefficients and the second set of additional tip loss coefficients to obtain additional tip loss coefficients.

[0087] In this embodiment, the first set of additional tip loss coefficients and the second set of additional tip loss coefficients are spliced ​​together to obtain the additional tip loss coefficients.

[0088] In this embodiment, a first set of additional tip loss coefficients corresponding to a portion of the blade deformation data is obtained based on the ratio of the blade deformation aerodynamic force to the blade undeformed aerodynamic force; a second set of additional tip loss coefficients is obtained based on the blade deformation data and the first set of additional tip loss coefficients; and the first set of additional tip loss coefficients and the second set of additional tip loss coefficients are combined to obtain additional tip loss coefficients.

[0089] Figure 3 This is a flowchart illustrating a third embodiment of a method for optimizing the long blades of a wind turbine, as provided in this application. Based on the above embodiments, as follows... Figure 3 As shown, one specific implementation of step S202 is as follows:

[0090] Step S301: Obtain the additional tip loss coefficient corresponding to two adjacent deformation data points and two adjacent deformation data points in the blade deformation data.

[0091] Step S302: Perform interpolation on two adjacent deformation data to obtain interpolated deformation data.

[0092] In this embodiment, interpolation is performed on any value from two adjacent deformation data to obtain deformation data, which is interpolated deformation data.

[0093] Step S303: Based on the additional tip loss coefficients corresponding to two adjacent deformation data and the interpolated deformation data, obtain the second set of additional tip loss coefficients.

[0094] In this embodiment, according to formula 1:

[0095] (1)

[0096] Obtain the additional tip loss coefficient F corresponding to the interpolated deformation data ω. extra (ω). Where F extra(i) The preceding adjacent deformation data ω of the interpolated deformation data i The corresponding additional tip loss coefficient; F extra(i+1) The next adjacent deformation data ω of the interpolated deformation data i+1 The corresponding additional tip loss coefficient.

[0097] In this embodiment, the additional tip loss coefficients corresponding to all interpolated deformation data are the second set of additional tip loss coefficients.

[0098] In this embodiment, two adjacent deformation data and the additional tip loss coefficients corresponding to the two adjacent deformation data are obtained from the blade deformation data; interpolation deformation data is obtained by performing difference processing on the two adjacent deformation data; and a second set of additional tip loss coefficients is obtained based on the additional tip loss coefficients corresponding to the two adjacent deformation data and the interpolation deformation data.

[0099] Figure 4 This is a flowchart illustrating a fourth embodiment of a method for optimizing the long blades of a wind turbine, as provided in this application. Based on the above embodiments, as follows... Figure 4 As shown, one specific implementation of step S104 is as follows:

[0100] Step S401: Obtain the incoming wind speed, the rotor blade rotation speed, and the distance from the blade tip to the blade root.

[0101] Step S402: Obtain the inflow angle based on the incoming wind speed, the rotor blade rotation speed, and the distance from the blade tip to the blade root.

[0102] In this embodiment, assuming the initial values ​​of axial induction factor a and axial induction factor b are 0, then according to formula 2:

[0103] (2)

[0104] The inflow angle Φ is obtained. Where V is the incoming wind speed; Ω is the rotor blade rotation speed; and r is the distance from the blade tip to the blade root.

[0105] In this embodiment, according to formula 3:

[0106] (3)

[0107] The angle of attack α is obtained. Where β is the angle between the blade chord length and the horizontal plane.

[0108] Step S403: Obtain the normal force and tangential force based on the inflow angle and the additional tip loss coefficient.

[0109] In this embodiment, according to formula 4:

[0110] (4)

[0111] Obtain the normal force coefficient C n Where C1 is the lift coefficient; C d Φ is the drag coefficient; Φ is the inflow angle.

[0112] In this embodiment, the lift coefficient and drag coefficient of the blade element are obtained based on the airfoil aerodynamic characteristic curve.

[0113] In this embodiment, according to formula 5:

[0114] (5)

[0115] The tangential force coefficient C is obtained. t Where C1 is the lift coefficient; C d Φ is the drag coefficient; Φ is the inflow angle.

[0116] In this embodiment, according to formulas 6 and 7:

[0117] (6)

[0118] (7)

[0119] The updated axial induction factors a and b are obtained. Among them, F(r) is the additional tip loss coefficient of long leaves at r.

[0120] In this embodiment, the iteration stops when the difference between the updated axial induction factor a and the original axial induction factor a is less than a preset error value, and the difference between the updated axial induction factor b and the original axial induction factor b is less than a preset error value.

[0121] In this embodiment, the final inflow angle is obtained after stopping the iteration.

[0122] In this embodiment, according to formula 8:

[0123] (8)

[0124] Obtain the normal force dF n Where ρ is the flow field density; c is the blade chord length; V0 is the inflow velocity; Φ ’γ is the final inflow angle; γ is the angle between the blade tangent and the original blade.

[0125] In this embodiment, according to formula 9:

[0126] (9)

[0127] The tangential force dF is obtained t Where ρ is the flow field density; c is the blade chord length; V0 is the inflow velocity; Φ ’ γ is the final inflow angle; γ is the angle between the blade tangent and the original blade.

[0128] Step S404: Obtain the corrected aerodynamic force based on the normal force and tangential force.

[0129] In this embodiment, the normal force and the tangential force are perpendicular to each other, and a rectangle is formed by the values ​​of the normal force and the tangential force. The diagonal of this rectangle is the corrected aerodynamic force.

[0130] In this embodiment, the incoming wind speed, the rotor blade rotation speed, and the distance from the blade tip to the blade root are obtained; the inflow angle is obtained based on the incoming wind speed, the rotor blade rotation speed, and the distance from the blade tip to the blade root; the normal force and the tangential force are obtained based on the inflow angle and the additional blade tip loss coefficient; and the corrected aerodynamic force is obtained based on the normal force and the tangential force.

[0131] Figure 5 This is a flowchart illustrating a fifth embodiment of a method for optimizing the long blades of a wind turbine, as provided in this application. Based on the above embodiments, as follows... Figure 5 As shown, after step S403, the method further includes:

[0132] Step S501: Obtain the number of blades, the rotor blade rotation speed, the blade area, and the incoming wind speed.

[0133] Step S502: Obtain the total torque based on the number of blades and the inflow angle.

[0134] In this embodiment, according to formula 10:

[0135] (10)

[0136] The total torque M is obtained. Where R is the length from the distal end of the deformed blade section to the blade root; r h ρ is the length from the proximal end of the deformed part of the blade to the blade root; B is the number of blades; ρ is the flow field density; c is the blade chord length; V0 is the inflow velocity; r is the distance from the blade tip to the blade root; Φ is the inflow angle; γ is the angle between the blade tangent and the original blade.

[0137] In this embodiment, according to formula 11:

[0138] (11)

[0139] The total thrust T of the wind turbine is obtained. Where R is the length from the distal end of the deformed blade to the blade root; r h ρ is the length from the proximal end of the deformed part of the blade to the blade root; B is the number of blades; ρ is the flow field density; c is the blade chord length; V0 is the inflow velocity; r is the distance from the blade tip to the blade root; Φ is the inflow angle; γ is the angle between the blade tangent and the original blade.

[0140] Step S503: Obtain the wind turbine power based on the total torque and the wind turbine blade speed.

[0141] In this embodiment, according to formula 12:

[0142] (12)

[0143] The wind turbine power P is obtained. Where M is the total torque and Ω is the wind turbine blade speed.

[0144] Step S504: Obtain the power coefficient based on the wind turbine power, blade area, and incoming wind speed.

[0145] In this embodiment, according to formula 13:

[0146] (13)

[0147] The power coefficient C is obtained. p Where P is the wind turbine power, ρ is the flow field density, V is the incoming wind speed, and A is the blade area.

[0148] In this embodiment, optionally, according to formula 14:

[0149] (14)

[0150] The annual power generation AEP of the wind turbine generator is obtained. Where P is the power of the wind turbine.

[0151] In this embodiment, the number of blades, the rotor blade speed, the blade area, and the incoming wind speed are obtained; the total torque is obtained based on the number of blades and the inflow angle; the rotor power is obtained based on the total torque and the rotor blade speed; and the power coefficient is obtained based on the rotor power, the blade area, and the incoming wind speed. The energy conversion efficiency of the wind turbine generator set can then be evaluated based on the power coefficient.

[0152] Figure 6 This is a flowchart illustrating a sixth embodiment of a method for optimizing the long blades of a wind turbine, as provided in this application. Based on the above embodiments, as follows... Figure 6 As shown, a specific implementation of step S105 includes:

[0153] Step S601: Input the corrected aerodynamic force into the preset neural network model to obtain updated blade shape data.

[0154] In this embodiment, a preset neural network model is obtained by acquiring a large amount of aerodynamic data and blade shape data, and by training a preset neural network with the objective functions of maximizing the power coefficient and minimizing the tip loss.

[0155] Step S602: Adjust the blade shape data of long blades based on the updated blade shape data.

[0156] In this embodiment, each value in the blade shape data of the long blade is updated based on the updated blade shape data.

[0157] In this embodiment, the modified aerodynamic force is input into a preset neural network model to obtain updated blade shape data; based on the updated blade shape data, the blade shape data of the long blade is adjusted and processed, thereby optimizing the shape of the long blade.

[0158] Figure 7 This is a flowchart illustrating a method for optimizing the long blades of a wind turbine, as provided in Embodiment Seven of this application. Based on the above embodiments, as follows... Figure 7 As shown, after step S602, the method further includes:

[0159] Step S701: Obtain the operating data of the wind turbine.

[0160] In this embodiment, after adjusting the blade shape data of the long blades based on the updated blade shape data, the blades are installed on the wind turbine, and the power generation and power coefficient of the wind turbine are obtained when the wind turbine is running.

[0161] Step S702: Obtain optimized blade shape data based on the running data.

[0162] In this embodiment, the running data is input into a preset blade optimization model to obtain optimized blade shape data.

[0163] Step S703: Adjust the updated blade shape data based on the optimized blade shape data.

[0164] In this embodiment, the operating data of the wind turbine is acquired; based on the operating data, optimized blade shape data is obtained; based on the optimized blade shape data, the updated blade shape data is adjusted to obtain the optimal shape of the long blade, thereby improving the efficiency and stability of the wind turbine.

[0165] It should be noted that although the steps in the above embodiments are described in a specific order, those skilled in the art will understand that in order to achieve the effect of this application, different steps do not necessarily have to be executed in such an order. They can be executed simultaneously (in parallel) or in other orders, and these variations are all within the scope of protection of this application.

[0166] Furthermore, this application also provides a long blade optimization device.

[0167] Figure 8 This is a schematic diagram of a first embodiment of a long blade optimization device provided in this application. Figure 8 As shown, the apparatus in this embodiment mainly includes an acquisition module 11, an analysis module 12, a processing module 13, and an adjustment module 14. In some embodiments, one or more of the acquisition module 11, analysis module 12, processing module 13, and adjustment module 14 can be combined into a single module. In some embodiments, the acquisition module 11 can be configured to acquire blade shape data and blade deformation data. The analysis module 12 can be configured to obtain the undeformed aerodynamic force and the deformed aerodynamic force of the blade based on the blade shape data and blade deformation data. The processing module 13 can be configured to obtain an additional tip loss coefficient based on the undeformed aerodynamic force, the deformed aerodynamic force, and the blade deformation data. The processing module 13 can also be configured to obtain a corrected aerodynamic force based on the additional tip loss coefficient. The adjustment module 14 can be configured to adjust the blade shape data of long blades based on the corrected aerodynamic force.

[0168] The above-mentioned device is used for performing Figures 1 to 7 The embodiment of the method for optimizing long blades of a wind turbine shown is similar in technical principle, the technical problem solved and the technical effect produced. Those skilled in the art can clearly understand that, for the sake of convenience and brevity, the specific working process of the device and related descriptions can be found in the description of the embodiment of the method for optimizing long blades of a wind turbine, which will not be repeated here.

[0169] Those skilled in the art will understand that all or part of the processes in the method of the above-described embodiment can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable storage medium can include any entity or device capable of carrying the computer program code, a medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory, a random access memory, an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the content included in the computer-readable storage medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable storage medium does not include electrical carrier signals and telecommunication signals.

[0170] Furthermore, this application also provides an electronic device.

[0171] Figure 9 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Figure 9 As shown, the electronic device includes at least one processor 21 and a memory 22, the memory 22 being configured to store data executed as described above. Figures 1 to 7 The program for the long blade optimization method of the wind turbine in the illustrated embodiment is such that the processor 21 can be configured to execute the program stored in the memory 22. This program includes, but is not limited to, a program for executing a long blade optimization method for a wind turbine according to the above-described method embodiment. For ease of explanation, only the parts related to the embodiments of this application are shown; for specific technical details not disclosed, please refer to the method section of the embodiments of this application. The electronic device can be a control device comprising various electronic devices.

[0172] Furthermore, this application also provides a computer-readable storage medium. In one embodiment of the computer-readable storage medium according to this application, the computer-readable storage medium can be configured to store a program that executes a long blade optimization method for a wind turbine generator according to the above-described method embodiments. This program can be loaded and run by a processor to implement the above-described long blade optimization method for a wind turbine generator. For ease of explanation, only the parts related to the embodiments of this application are shown; for specific technical details not disclosed, please refer to the method section of the embodiments of this application. The computer-readable storage medium can be a storage device device comprising various electronic devices. Optionally, in the embodiments of this application, the computer-readable storage medium is a non-transitory computer-readable storage medium.

[0173] Furthermore, it should be understood that since the various modules are only provided to illustrate the functional units of the device described in this application, the physical devices corresponding to these modules may be the processor itself, or a part of the processor's software, hardware, or a combination of both. Therefore, the number of modules shown in the figures is merely illustrative.

[0174] Those skilled in the art will understand that the various modules in the device can be adaptively split or combined. Such splitting or combining of specific modules will not cause the technical solution to deviate from the principles of this application; therefore, the technical solutions after splitting or combining will fall within the protection scope of this application.

[0175] The technical solutions of this application have been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of this application is obviously not limited to these specific embodiments. Without departing from the principles of this application, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of this application.

Claims

1. A method for optimizing the long blades of a wind turbine, characterized in that, include: Acquire leaf shape data and leaf deformation data; Based on the blade shape data and the blade deformation data, the aerodynamic forces of the blade without deformation and the aerodynamic forces of the blade with deformation are obtained; Based on the undeformed aerodynamic force of the blade, the deformed aerodynamic force of the blade, and the blade deformation data, the additional tip loss coefficient is obtained; Based on the additional tip loss coefficient, the corrected aerodynamic force is obtained; Based on the modified aerodynamic force, the blade shape data of the long blade is adjusted.

2. The method according to claim 1, characterized in that, The step of obtaining the additional tip loss coefficient based on the undeformed aerodynamic force of the blade, the deformed aerodynamic force of the blade, and the blade deformation data includes: Based on the ratio of the blade deformation aerodynamic force to the blade undeformed aerodynamic force, a first additional tip loss coefficient set corresponding to a portion of the blade deformation data is obtained. Based on the blade deformation data and the first set of additional tip loss coefficients, a second set of additional tip loss coefficients is obtained; The additional tip loss coefficients are obtained by combining the first set of additional tip loss coefficients and the second set of additional tip loss coefficients.

3. The method according to claim 2, characterized in that, The step of obtaining a second additional tip loss coefficient set based on the blade deformation data and the first additional tip loss coefficient set includes: Obtain two adjacent deformation data points and the additional tip loss coefficient corresponding to the two adjacent deformation data points from the blade deformation data; Interpolation is performed on the two adjacent deformation data to obtain interpolated deformation data; Based on the additional tip loss coefficients corresponding to the two adjacent deformation data and the interpolated deformation data, a second set of additional tip loss coefficients is obtained.

4. The method according to claim 1, characterized in that, The process of obtaining the corrected aerodynamic force based on the additional tip loss coefficient includes: Obtain the incoming airflow speed, the rotor blade rotation speed, and the distance from the blade tip to the blade root; The inflow angle is obtained based on the incoming wind speed, the rotational speed of the impeller blades, and the distance from the blade tip to the blade root. The normal force and tangential force are obtained based on the inflow angle and the additional tip loss coefficient; The corrected aerodynamic force is obtained based on the normal force and the tangential force.

5. The method according to claim 4, characterized in that, After obtaining the corrected aerodynamic force based on the normal force and the tangential force, the method further includes: Obtain the number of blades, rotor blade rotation speed, blade area, and incoming air velocity; The total torque is obtained based on the number of blades and the inflow angle; The wind turbine power is obtained based on the total torque and the wind turbine blade speed. The power coefficient is obtained based on the wind turbine power, the blade area, and the incoming wind speed.

6. The method according to claim 1, characterized in that, Based on the corrected aerodynamic forces, the blade shape data of the long blade is adjusted, including: The corrected aerodynamic force is input into a preset neural network model to obtain updated blade shape data; Based on the updated blade shape data, the blade shape data of the long blade is adjusted.

7. The method according to claim 6, characterized in that, The method further includes: Obtain operating data of wind turbine units; Based on the operational data, optimized blade shape data is obtained; Based on the optimized blade shape data, the updated blade shape data is adjusted.

8. A long blade optimization device, characterized in that, include: The acquisition module is used to acquire blade shape data and blade deformation data; The analysis module is used to obtain the aerodynamic forces of the blade without deformation and the aerodynamic forces of the blade with deformation based on the blade shape data and the blade deformation data. The processing module is used to obtain the additional tip loss coefficient based on the undeformed aerodynamic force of the blade, the deformed aerodynamic force of the blade, and the blade deformation data; The processing module is also used to obtain the corrected aerodynamic force based on the additional tip loss coefficient; The adjustment module is used to adjust the blade shape data of the long blade according to the corrected aerodynamic force.

9. An electronic device comprising a processor and a storage device, said storage device being adapted to store a plurality of program codes, characterized in that, The program code is adapted to be loaded and run by the processor to perform the method of any one of claims 1 to 7.

10. A computer-readable storage medium storing a plurality of program codes, characterized in that, The program code is adapted to be loaded and run by a processor to perform the method of any one of claims 1 to 7.

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