A method for calculating and optimizing unsteady aerodynamic forces of wind turbine blades

Abstract

This invention discloses a method for calculating and optimizing unsteady aerodynamic forces of wind turbine blades. Based on potential flow theory, this method establishes the Laplace governing equations and sets corresponding boundary conditions, importing them into a wind turbine geometric model composed of multiple airfoils. The boundary element method is used to discretize the blade surface into a vortex lattice composed of vortex lines. The vortex strength is obtained by allocating initial vortex intensities and solving linear matrices. The velocity and pressure fields are then iteratively calculated based on the Biot-Savart law. Furthermore, the blade aerodynamic forces and energy output coefficients are calculated based on the Kutta-Rukowski theorem, and nonlinear corrections are performed by comparing with experimental data to ensure calculation accuracy. This invention balances computational efficiency and accuracy, achieving higher accuracy than blade element momentum theory while consuming fewer computational resources than computational fluid dynamics methods. It is suitable for aerodynamic performance evaluation and optimization during the wind turbine design phase.

Description

Technical Field

[0001] This invention relates to wind turbine technology, and in particular to a method for calculating and optimizing unsteady aerodynamic forces on wind turbine blades. Background Technology

[0002] Wind energy, as a clean energy source with abundant reserves, has received widespread attention in recent years. Wind turbines are the direct devices that convert wind energy into electricity, and their blade shape is crucial to their energy capture performance and dynamic response. Accurate and efficient prediction of unsteady aerodynamic forces during the design phase can effectively improve design efficiency and reduce turbine costs. Simultaneously, unsteady aerodynamic forces also provide the data foundation for further exploration of aeroelastic effects such as flutter, stall, and vortex-induced resonance. Therefore, the accuracy and efficiency of unsteady aerodynamic modeling and calculation of wind turbine blades are of great significance to the development of the wind energy industry.

[0003] Generally, unsteady aerodynamic forces include time-domain unstable blade lift and drag, and the resulting wind turbine energy output coefficient. Traditional blade element momentum theory can quickly calculate these aerodynamic parameters. However, blade element momentum theory divides wind turbine blades into independent blade units along the spanwise direction, which geometrically oversimplifies the blades. Therefore, this method cannot consider some complex aerodynamic effects of the blades, such as dynamic stall. Furthermore, blade element momentum theory calculates aerodynamic responses based on the law of conservation of momentum, without simulating the wake field. Therefore, this method also cannot consider the interference problem of multiple wind turbines in a wind farm. Computational fluid dynamics based on viscous flow theory can comprehensively consider a series of unsteady aerodynamic problems. CN202410027095.X used this method to simulate the aerodynamic forces of a wind turbine and developed a fully coupled numerical simulation framework for floating wind turbines based on it. However, computational fluid dynamics requires a large amount of computational resources, which poses a significant challenge to controlling the cost of wind turbine design and research.

[0004] It should be noted that the information disclosed in the background section above is only for understanding the background of this application, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The main objective of this invention is to overcome the deficiencies in the aforementioned background technology and provide a method for calculating and optimizing unsteady aerodynamic forces of wind turbine blades.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] In a first aspect of the present invention, a method for calculating and optimizing unsteady aerodynamic forces on wind turbine blades includes the following steps:

[0008] A1. Establish the flow field control equation and set the boundary conditions, wherein the flow field is an inviscid, irrotational, and incompressible fluid, and the control equation is the Laplace equation. The boundary conditions include the fluid velocity at the edge of the wind turbine blade being perpendicular to the blade edge, and the far-field boundary conditions, so that the induced velocity has no effect on the far field.

[0009] A2. Import the wind turbine geometric model, which includes multiple airfoils. Each airfoil is composed of a two-dimensional curve determined by the horizontal and vertical coordinates. Modeling is performed by setting the torsion angle and chord length of each airfoil. The position of each airfoil is determined by the relative radius of the wind turbine blades.

[0010] A3. Divide the vortex grid. Use the boundary element method to discretize the surface of the blade geometric model to form a vortex grid. Each vortex line represents circulation, and multiple vortex lines make up the vortex grid of the entire wind turbine blade.

[0011] A4. Flow field calculation and time step iteration: Based on the initial angle of attack and aerodynamic coefficient of the airfoil, assign an initial vortex intensity to each vortex of the discrete vortex grid, solve the linear matrix to obtain the vortex intensity of each vortex, and further obtain the velocity field and pressure field of the wind turbine blade according to the Biot-Savart law.

[0012] A6. Calculation of aerodynamic forces and energy output coefficients: According to the Kuta-Rukovsky theorem, the blade lift is obtained through vortex strength. The aerodynamic integral of each vortex grid unit is summed to obtain the lift and thrust of the entire wind turbine blade. Dimensionless coefficients CL and CD are calculated to represent the lift and drag characteristics, as well as coefficients reflecting the wind turbine's energy output capability.

[0013] A7. Nonlinear correction: Compare the calculation results of steps A4 to A6 with the experimental data to identify and quantify the deviation between model predictions and actual observations; based on the comparative analysis results, perform nonlinear correction on the aerodynamic parameters in the vortex lattice model, through an iterative process, until the error between model predictions and experimental data is lower than the set value.

[0014] In a second aspect of the invention, a computer-readable storage medium stores a computer program that, when executed by a processor, implements the method for calculating and optimizing unsteady aerodynamic forces of wind turbine blades.

[0015] In a third aspect of the invention, a computer program product includes a computer program that, when executed by a processor, implements the method for calculating and optimizing unsteady aerodynamic forces of wind turbine blades.

[0016] The present invention has the following beneficial effects:

[0017] This invention provides a method for calculating and optimizing unsteady aerodynamic forces of wind turbine blades, enabling efficient and accurate calculation and optimization design of unsteady aerodynamic forces in wind turbines. In terms of accuracy, this method divides the blade into meshes based on its original shape and simulates the real flow field using potential flow equations. Compared to blade element momentum theory, it offers higher accuracy and a wider range of applications. In terms of computational efficiency, by neglecting fluid viscosity, its governing equations exhibit linear characteristics, thus significantly saving computational resources compared to computational fluid dynamics methods.

[0018] As a method for calculating and optimizing unsteady aerodynamics of wind turbines based on potential flow theory, this invention achieves efficient and accurate numerical simulation of unsteady aerodynamic performance of wind turbines by dividing wind turbine blades into vortex elements to form a vortex grid, effectively solving the problem of difficulty in unifying accuracy and computational efficiency in existing calculation methods. Furthermore, to address the issue of neglecting fluid viscosity in existing unsteady aerodynamic calculation methods, nonlinear corrections are performed. By extracting the lift coefficient of a single airfoil and comparing it with experimental results, and then iterating to ensure that the error between the two is limited to a set range, the accuracy of the method is further verified by comparing it with the unsteady aerodynamic results calculated by blade element momentum theory.

[0019] The application of the technical solution of this invention also brings many advantages: simplifying the wind turbine blades into lifting surfaces and dividing them into vortex grids can accurately and efficiently describe the unsteady aerodynamic characteristics of the wind turbine; simulating the flow field with control equations can realize the simulation analysis of the wind turbine wake, thereby solving the problem of interference effects of multiple wind turbines in the wind field; and defining the physical field through vortex grids composed of vortex lines can effectively reduce the computational cost, making this method applicable to the simulation work in the design stage of wind turbines.

[0020] Other beneficial effects of the embodiments of the present invention will be further described below. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating the principle of the method for calculating and optimizing unsteady aerodynamic forces on wind turbine blades according to an embodiment of the present invention.

[0022] Figure 2 This is a schematic diagram illustrating the vortex grid division principle of the method of this invention. In the diagram, 1 represents the control point of the vortex grid, located at the center of 1 / 4 chord length. 2 represents the attached vortex, indicating a vortex attached longitudinally to the lifting surface. 3 represents the detached vortex, indicating a vortex detached chordally from the lifting surface into the wake. 4 represents the 1 / 4 chord line, on which the control points are distributed. 5 represents the formed wake, and 6 represents the wake vortex divided on the wake according to this invention.

[0023] Figure 3 This is a discrete vortex grid diagram of the blades used in the NREL 5MW wind turbine simulation based on the present invention.

[0024] Figure 4 The diagram shows the drag coefficient distribution of the NREL 5MW wind turbine along the blade radius direction calculated for an embodiment of the present invention and its comparison with the blade element momentum theory.

[0025] Figure 5 The image shows the lift coefficient distribution of the NREL 5MW wind turbine along the blade radius direction calculated for an embodiment of the present invention and its comparison with the blade element momentum theory.

[0026] Figure 6 The energy output curve of the NREL 5MW wind turbine is shown in this embodiment of the invention.

[0027] Figure 7 This is a flowchart illustrating the overall process of calculating and optimizing the unsteady aerodynamic forces of wind turbine blades according to the present invention.

[0028] Figure 8 This is a flowchart of a preferred embodiment of the present invention. Detailed Implementation

[0029] The embodiments of the present invention will be described in detail below. It should be emphasized that the following description is merely exemplary and not intended to limit the scope and application of the present invention.

[0030] It should be noted that when a component is referred to as "fixed to" or "set on" another component, it can be directly on or indirectly on that other component. When a component is referred to as "connected to" another component, it can be directly connected to or indirectly connected to that other component. Furthermore, a connection can be used for fixing, coupling, or communication.

[0031] It should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", and "outer" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the embodiments of the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the present invention.

[0032] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of embodiments of the present invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0033] This invention aims to solve the problem of balancing accuracy and computational efficiency in existing calculations of unsteady aerodynamic forces for wind turbine blades, achieving efficient and accurate calculations and optimization design of unsteady aerodynamic forces. It proposes a technical solution based on potential flow theory: by dividing the blade into vortex elements to form a vortex grid, combined with linear control equations that neglect fluid viscosity, computational efficiency is improved, while nonlinear corrections ensure accuracy. This solution offers superior accuracy compared to blade element momentum theory, consumes fewer computational resources than computational fluid dynamics, and can simulate flow fields to study wakes and the interactions between multiple wind turbines, making it suitable for simulations during the wind turbine design phase.

[0034] See Figure 7 This invention provides a method for calculating and optimizing unsteady aerodynamic forces on wind turbine blades, comprising the following steps:

[0035] Step A1: Establish the flow field control equation and set the boundary conditions, wherein the flow field is an inviscid, irrotational, and incompressible fluid, and the control equation is the Laplace equation. The boundary conditions include the fluid velocity at the edge of the wind turbine blade being perpendicular to the blade edge, and the far-field boundary conditions, so that the induced velocity has no effect on the far field.

[0036] Step A2: Import the wind turbine geometric model, which includes multiple airfoils. Each airfoil is composed of a two-dimensional curve determined by the horizontal and vertical coordinates. The model is created by setting the torsion angle and chord length of each airfoil. The position of each airfoil is determined by the relative radius of the wind turbine blades.

[0037] Step A3: Divide the vortex grid. Use the boundary element method to discretize the surface of the blade geometric model to form a vortex grid. Each vortex line represents circulation, and multiple vortex lines make up the vortex grid of the entire wind turbine blade.

[0038] Step A4: Flow field calculation and time step iteration. Based on the initial angle of attack and aerodynamic coefficients of the airfoil, assign an initial vortex intensity to each vortex of the discrete vortex grid, solve the linear matrix to obtain the vortex intensity of each vortex, and further obtain the velocity field and pressure field of the wind turbine blade according to the Biot-Savart law.

[0039] In some embodiments, step A4 specifically includes:

[0040] Step A4.1: Based on the initial angle of attack and aerodynamic coefficients of the airfoil, assign an initial vortex intensity to each vortex of the discrete vortex grid as the initial condition for the flow field calculation;

[0041] Step A4.2: Construct a linear matrix using the governing equations and vortex lattice discretization, and obtain the vortex intensity of each vortex by solving the matrix;

[0042] Step A4.3: Apply Biot-Savart law to calculate the velocity and pressure fields of the wind turbine blades at the initial moment;

[0043] Step A4.4: Based on the obtained velocity field, iteratively calculate the velocity field and pressure field for each step.

[0044] Step A6: Calculation of aerodynamic forces and energy output coefficients. According to the Kuta-Rukowski theorem, the blade lift is obtained through vortex strength. The aerodynamic force integral of each vortex grid unit is summed to obtain the lift and thrust of the entire wind turbine blade. Dimensionless coefficients CL and CD are calculated to represent the lift and drag characteristics, as well as coefficients reflecting the wind turbine's energy output capability.

[0045] Step A7, Nonlinear Correction: Compare the calculation results from steps A4 to A6 with the experimental data to identify and quantify the deviation between model predictions and actual observations; based on the comparative analysis results, perform nonlinear correction on the aerodynamic parameters in the vortex lattice model, through an iterative process, until the error between model predictions and experimental data is lower than the set value.

[0046] In some embodiments, step A7, comparing the calculation results of steps A4 to A6 with the experimental data, includes: calculating and extracting the lift coefficient of a single airfoil and comparing it with the corresponding experimental data.

[0047] In some embodiments, in step A7, based on the comparative analysis results, the aerodynamic parameters in the vortex lattice model are nonlinearly corrected using a lookup table method, wherein the lookup table method uses a pre-calculated or experimentally obtained aerodynamic parameter data table.

[0048] See Figure 8 In some embodiments, the method further includes the following steps:

[0049] Step A5: Wake field calculation. Extend the vortex lattice into the wake field. Calculate the wake extension according to Kelvin's circulation theorem and the Kutta condition. The vortices on the blades will detach to form the wake, and the total vorticity remains unchanged.

[0050] In some embodiments, in step A5, the wake extension state is determined by combining the far-field velocity with the wind turbine flow field induced velocity.

[0051] In some embodiments, the method further includes: after the iterative process of nonlinear correction is completed, comparing the results with the unsteady aerodynamic forces calculated by leaf element momentum theory to further verify the accuracy of the method.

[0052] The main technical advantages of the unsteady aerodynamic calculation and optimization method for wind turbine blades proposed in this invention are as follows: By establishing the Laplace control equation based on potential flow theory and combining it with the boundary element method to discretize the blade surface using vortex lattice, the method effectively balances the contradiction between calculation accuracy and efficiency while preserving the original geometry of the blade. This method characterizes the circulation distribution through vortex lines, uses the Biot-Savart law to iteratively solve the unsteady velocity and pressure fields, and introduces a nonlinear correction mechanism to make the error between model prediction and experimental data controllable. Thus, while avoiding the limitations of traditional blade element momentum theory such as oversimplification of blades and inability to simulate wake and multi-machine interference, it significantly reduces the high computational resource consumption required by computational fluid dynamics methods based on viscous flow models. This provides a high-precision and engineering-applicable aerodynamic performance evaluation and optimization method for the wind turbine design stage.

[0053] The following further describes specific embodiments of the present invention, algorithm examples, and experimental verification.

[0054] A method for calculating unsteady aerodynamic forces of a wind turbine, the method comprising:

[0055] Step 1: Establish the flow field control equations and set the boundary conditions.

[0056] Specifically, this includes: considering the flow field as inviscid, irrotational, and incompressible, with the governing equations for the gas around the wind turbine being the Laplace equations. It also considers the boundary conditions at the wind turbine's surface and in the far field, namely: 1. The fluid velocity at the edge of the wind turbine blades is perpendicular to the blade edge; 2. The induced velocity has no effect on the far field. Since the governing equations and boundary equations of this method are linear, they can be solved directly through discretization.

[0057] Step 2: Import the wind turbine geometry model.

[0058] Wind turbine blades are composed of multiple airfoils, which are two-dimensional curves defined by the x and y coordinates. Typically, wind turbine airfoils utilize existing designs, but can also be custom-designed using software such as Xfoil. In this method, airfoils are imported, and the torsion angle and chord length of each airfoil are set for modeling. The position of each airfoil is determined by the relative radius of the wind turbine blade. Taking the classic DTU 10MW wind turbine blade as an example, its model creation requires importing data for six different airfoils. Additionally, the initial lift coefficient, drag coefficient, and moment coefficient for each airfoil must be input. These coefficients are typically obtained experimentally or through blade element momentum theory.

[0059] Step 3: Divide the vortex grid

[0060] The boundary element method is used to solve the flow field control equations, which requires discretization of the blade's geometric model surface. Compared to the traditional Eulerian mesh generation method, this method uses a vortex lattice formed by vortex lines for discretization to improve computational efficiency. Each vortex line represents circulation, and multiple vortex lines form the vortex lattice of the entire wind turbine blade.

[0061] Figure 2 This demonstrates the vortex grid division principle of the present invention. In the diagram, 1 represents the control point of the vortex grid, located at the center of 1 / 4 chord length. 2 represents the attached vortex, indicating a vortex attached longitudinally to the lifting surface. 3 represents the detached vortex, indicating a vortex detached chordally from the lifting surface to the wake. 4 represents the 1 / 4 chord, upon which the control points are distributed. 5 represents the formed wake, and 6 represents the wake vortex divided on the wake according to the present invention. An example of discrete vortex grid division of the blades in the wind turbine simulation process of this embodiment is shown below. Figure 3 As shown.

[0062] Step 4: Flow field calculation and time step iteration

[0063] Based on the airfoil's initial angle of attack and aerodynamic coefficients, an initial vortex intensity is assigned to each vortex in the discrete vortex lattice as the initial condition for flow field calculation. After discretization of the above governing equations using the vortex lattice, a linear matrix is ​​obtained. Solving this matrix yields the vortex intensity of each vortex. Further, according to the Biot-Savart law, the velocity and pressure fields of the wind turbine blades are obtained, as shown in the following formulas:

[0064] In the formula, V ( r , t ) represents the induced velocity at position r at time t. s Represents the location of the control point, Ω ( s , t The value represents the discrete vortex intensity at time t. Subsequently, the velocity field is iteratively calculated for each step based on this velocity field. The pressure field is calculated using Bernoulli's equations, building upon the velocity field calculations.

[0065] Step 5: Wake Field Calculation

[0066] To further understand the characteristics of the wake and address interference issues among multiple wind turbines, the vortex lattice can be extended into the wake field. According to Kelvin's circulation theorem and the Kutta condition, vortices on the blades will detach to form a wake while the total vorticity remains constant. Mathematically, this can be expressed as: Therefore, wake spread can be expressed by the formula It indicates. Among them, x V represents the location of the wake extension. ∞ Indicates far-field velocity, This represents the induced velocity of the wind turbine's flow field.

[0067] Step 6: Calculation of aerodynamic forces and energy output coefficients

[0068] According to the Kutta-Rukowski theorem, blade lift can be obtained from vortex strength. Summing the aerodynamic integrals of each vortex lattice element yields the lift and thrust of the entire wind turbine blade. In the field of wind turbines, dimensionless coefficients are typically used. C L and C D The formula representing lift and drag characteristics is as follows: , Finally, the coefficient reflecting the energy output capacity of the wind turbine is expressed as: .

[0069] Step 7: Nonlinear correction and verification

[0070] The unsteady aerodynamic calculation method for wind turbines provided in this invention neglects the viscosity of the fluid, thus requiring a certain degree of correction. Nonlinear correction is achieved by extracting the lift coefficient of a single airfoil and comparing it with experimental results, followed by iteration to ensure that the error between the two is limited to a certain range. Finally, the accuracy of the method is verified by comparing it with the unsteady aerodynamic results calculated using blade element momentum theory.

[0071] Experimental verification

[0072] The unsteady aerodynamic calculation method for wind turbines provided by this invention can be applied to various wind turbines. To verify its accuracy, this invention provides an application example for the NREL 5MW wind turbine. The NREL 5MW wind turbine is a widely used wind turbine reference model with a blade radius of 63m. The twist angle of the wind turbine blade airfoil gradually changes from 13° at the root to 0° at the tip to optimize aerodynamic performance under different wind speeds. Based on the above steps, the lift coefficient and drag coefficient distributed along the radius of the wind turbine blade were calculated and compared with the results of the blade element momentum theory. In addition, energy output coefficient curves were obtained under different wind speeds.

[0073] Figure 3 This invention demonstrates the discrete vortex grid partitioning of blades implemented in the NREL 5MW wind turbine simulation. Figure 4 This paper presents the drag coefficient distribution of the NREL 5MW wind turbine along the blade radius calculated by this invention and compares it with the blade element momentum theory. Figure 4 As can be seen, the drag coefficients predicted by the two methods are basically consistent in the spanwise variation trend. The simulation results of this method are slightly higher than those of the blade element momentum theory. The flow field at the root and tip is strongly affected by three-dimensional disturbances, which cannot be fully described by the two-dimensional assumptions of the blade element momentum theory, resulting in a deviation between the two methods. This shows that this method can capture the overall aerodynamic characteristics of the blade better. Figure 5This paper presents the lift coefficient distribution of the NREL 5MW wind turbine along the blade radius calculated by this invention and compares it with the blade element momentum theory. Figure 5 As can be seen, the simulation results of this method and the results of the blade element momentum theory have a high degree of overlap in the mid-section region. The largest relative error occurs at a relative radius of 0.87, which is about 8%, and is within the acceptable error range. In the tip region (relative radius between 0.9 and 1), the two methods are in high agreement, which fully demonstrates that the aerodynamic model of this method has high fidelity and can effectively reflect the tip effect. Figure 6 The energy output curve of the NREL 5MW wind turbine presented in this invention is shown. The energy coefficient Cp is a core indicator for measuring the wind energy utilization efficiency of a wind turbine, and its theoretical maximum value is the Betz limit (approximately 0.593). Figure 6 As can be seen, when the wind speed is between 2 and 8 m / s, Cp rises rapidly from near 0; in the range of 8 to 12 m / s, Cp remains around 0.577, close to the Bates limit, which is the efficient operating range of the wind turbine; after the wind speed exceeds 12 m / s, Cp gradually decreases, approaching 0 at 25 m / s, which is the wind turbine actively reducing its wind energy capture efficiency to avoid overload. This curve reflects the wind energy utilization efficiency of the wind turbine at different wind speeds, indicating that its aerodynamic design is highly optimized, enabling it to start generating electricity in low wind speed areas and safely shut down in high wind speed areas, with excellent wind energy utilization efficiency in the range close to the rated wind speed of 11.4 m / s.

[0074] In summary, this invention provides a method for calculating and optimizing unsteady aerodynamic forces of wind turbine blades. Based on potential flow theory, it establishes the Laplace governing equations for an inviscid, irrotational, and incompressible flow field and sets corresponding boundary conditions. It then imports a geometric model of a wind turbine with multiple airfoil parameters, uses the boundary element method to divide the vortex grid (with vortex lines representing circulation), and combines the Biot-Savart law to calculate the flow field and aerodynamic forces. The vortex grid can also be extended to the wake field to study the interference of multiple wind turbines as needed. At the same time, nonlinear correction (comparing the airfoil lift coefficient with experimental results iteratively) ensures accuracy, effectively solving the problem of inconsistent accuracy and computational efficiency in existing methods. Moreover, its accuracy is better than that of blade element momentum theory, and its computational resource consumption is less than that of computational fluid dynamics. By applying the technical solution of this invention, the unsteady aerodynamic characteristics of wind turbines can be accurately and efficiently described by simplifying wind turbine blades into lifting surfaces and dividing them into vortex grids. By simulating the flow field through control equations, the simulation and analysis of wind turbine wakes can be achieved, thereby solving the problem of mutual influence among multiple wind turbines in a wind field. By defining the physical field through vortex grids composed of vortex lines, the computational cost can also be effectively reduced, making it suitable for simulation in the design stage of wind turbines.

[0075] This invention also provides a storage medium for storing a computer program, which, when executed, performs at least the methods described above.

[0076] This invention also provides a control device, including a processor and a storage medium for storing a computer program; wherein the processor executes the computer program by performing at least the method described above.

[0077] This invention also provides a processor that executes a computer program, at least performing the methods described above.

[0078] The storage medium can be implemented by any type of non-volatile storage device, or a combination thereof. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk drive or magnetic tape drive. The storage media described in the embodiments of this invention are intended to include, but are not limited to, these and any other suitable types of memory.

[0079] In the several embodiments provided by this invention, it should be understood that the disclosed systems and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0080] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0081] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0082] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0083] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0084] The methods disclosed in the several method embodiments provided by this invention can be arbitrarily combined without conflict to obtain new method embodiments.

[0085] The features disclosed in the several product embodiments provided by this invention can be arbitrarily combined without conflict to obtain new product embodiments.

[0086] The features disclosed in the several method or device embodiments provided by the present invention can be arbitrarily combined without conflict to obtain new method or device embodiments.

[0087] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various equivalent substitutions or obvious modifications can be made without departing from the concept of the present invention, and all such modifications, achieving the same performance or application, should be considered within the scope of protection of the present invention.

Claims

1. A method for the calculation and optimization of the unsteady aerodynamic forces of a wind turbine blade, characterized in that, The method comprises the following steps: A1, establishing a flow field control equation and setting boundary conditions, wherein the flow field is a viscous, irrotational, incompressible fluid, and the control equation is Laplace equation, and the boundary conditions include the fluid velocity of the wind turbine blade edge and the vertical of the blade edge, and the far field boundary condition, so that the induced velocity has no effect on the far field; A2, importing the wind turbine geometric model, including a plurality of airfoils, each airfoil being composed of a two-dimensional curve determined by the horizontal and vertical coordinates, and the modeling being performed by setting the twist angle and chord length of each airfoil, and the position of each airfoil being determined by the relative radius of the wind turbine blade; A3, dividing vortex lattice, and discretizing the surface of the blade geometric model by using the boundary element method to form a vortex lattice, wherein each vortex line represents a circulation, and a plurality of vortex lines form the vortex lattice of the entire wind turbine blade; A4, flow field calculation and time step iteration, wherein the initial attack angle and the aerodynamic force coefficient of the airfoil are used to assign an initial vortex intensity to each vortex of the discrete vortex lattice, a linear matrix is solved to obtain the vortex intensity of each vortex, and the velocity field and pressure field of the wind turbine blade are further obtained according to the Biot-Savart law; step A4 specifically comprises: A4.1, assigning an initial vortex intensity to each vortex of the discrete vortex lattice according to the initial attack angle and the aerodynamic force coefficient of the airfoil, as the initial condition for flow field calculation; A4.2, constructing a linear matrix by using the control equation and the discrete vortex lattice, and obtaining the vortex intensity of each vortex by solving the matrix; A4.3, applying the Biot-Savart law to calculate the velocity field and pressure field of the wind turbine blade at the initial time; A4.4, iteratively calculating the velocity field and pressure field of each step based on the obtained velocity field; A6, aerodynamic force and energy output coefficient calculation, wherein the lift of the blade is obtained from the vortex intensity according to the Kutta-Joukowski theorem, the aerodynamic force of each vortex lattice unit is integrated and summed to obtain the lift and thrust of the entire wind turbine blade, the dimensionless coefficients CL and CD representing the lift and drag characteristics are calculated, and the coefficient reflecting the energy output capacity of the wind turbine is calculated; A7, nonlinear correction, wherein the calculation results of steps A4 to A6 are compared with experimental data to identify and quantify the deviation between the model prediction and the actual observation; based on the comparison analysis result, the aerodynamic force parameters in the vortex lattice model are nonlinearly corrected, and through an iterative process, the error between the model prediction and the experimental data is lower than a set value.

2. The wind turbine blade unsteady aerodynamic force calculation and optimization method of claim 1, wherein, Further comprising the following steps: A5, wake field calculation, wherein the vortex lattice is extended into the wake field, and the wake extension is calculated according to the Kelvin circulation theorem and the Kutta condition, wherein the vortex on the blade will fall off to form a wake and the total vortex quantity remains unchanged.

3. The wind turbine blade unsteady aerodynamic force calculation and optimization method of claim 2, wherein, In step A5, the extension state of the wake is determined by combining the far field velocity with the induced velocity of the wind turbine flow field.

4. The wind turbine blade unsteady aerodynamic force calculation and optimization method of claim 1, wherein, In step A7, the comparison of the calculation results of steps A4 to A6 with the experimental data comprises: comparing the lift coefficient of a single airfoil extracted by calculation with the corresponding experimental data.

5. The wind turbine blade unsteady aerodynamic force calculation and optimization method of claim 1, wherein, In step A7, based on the comparison analysis result, the aerodynamic force parameters in the vortex lattice model are nonlinearly corrected by using a lookup table method, and the lookup table method uses a pre-calculated or experimentally obtained aerodynamic force parameter data table.

6. The wind turbine blade unsteady aerodynamic force calculation and optimization method of claim 1, wherein, Further comprising: After the iteration of the nonlinear correction is completed, the accuracy of the method is further verified by comparing with the unsteady aerodynamic force results calculated by the blade element momentum theory.

7. A computer-readable storage medium storing a computer program, characterized in that, The computer program, when executed by a processor, implements the wind turbine blade unsteady aerodynamic force calculation and optimization method according to any one of claims 1 to 6.

8. A computer program product comprising a computer program, characterized in that, The computer program, when executed by a processor, implements the wind turbine blade unsteady aerodynamic force calculation and optimization method according to any one of claims 1 to 6.

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