Yawed wind turbine wake analytical method considering cross-sectional deformation and related devices

Abstract

The present application belongs to the technical field of wind power generation, and particularly relates to the field of wind turbine wake analysis, and discloses a yaw wind turbine wake analysis method considering cross-section deformation and a related device; wherein the yaw wind turbine wake analysis method considering cross-section deformation comprises: obtaining basic parameters based on a yaw wind turbine to be analyzed; the basic parameters comprise set wind turbine parameters and atmospheric boundary layer inflow condition parameters; and performing wake analysis by using a pre-constructed yaw wake model based on the obtained basic parameters to obtain a wake velocity distribution. The technical scheme disclosed by the present application is suitable for predicting yaw wind turbine far-wake velocity deficit distribution, and is beneficial to accurately calculating the velocity distribution in the yaw wake, and can be used for predicting downstream wind turbine power generation power in the subsequent to ensure the effective operation of the active yaw strategy.

Description

Technical Field

[0001] This invention belongs to the field of wind power generation technology, and relates to the field of wind turbine wake analysis, specifically to a method and related apparatus for analyzing the wake of a yaw wind turbine that takes into account cross-sectional deformation. Background Technology

[0002] Generally speaking, in order to maximize the economic benefits of a wind farm within a limited area, as many wind turbines as possible need to be arranged within the wind farm. Some turbines will inevitably be located in the wake zone of other turbines. The wake effect has always been one of the most important influencing factors in wind turbine design and wind farm design. It will lead to a decrease in the output power of the wind turbine and an increase in fatigue load, which will in turn affect the economic benefits and safe operation of the entire wind farm.

[0003] In recent years, active yaw strategies have been proposed, which can effectively help downstream wind turbines escape the wake effects of upstream wind turbines. Specifically, when an upstream wind turbine is in a fixed yaw state, its wake is deflected in the crosswind direction due to lateral thrust, thus allowing the downstream wind turbine to escape part of the wake's influence and improving power generation efficiency. Furthermore, to operate the active yaw strategy efficiently, an analytical model that can accurately predict the yaw wake velocity distribution is needed.

[0004] Currently, most commercial software uses the Jensen and Frandsen models. These models employ a top-hat shape to represent the radial distribution of velocity loss. However, measured wake velocity loss, wind tunnel tests, and numerical simulations all indicate that the wake velocity loss exhibits a unimodal distribution. Using the top-hat shape to predict wake velocity will overestimate the velocity loss encountered by downstream wind turbines, resulting in a lower predicted power output than actual. Furthermore, yaw wakes exhibit significant cross-sectional deformation, which current commercial software cannot accurately predict. This affects the accurate prediction of downstream wind turbine power output. For example, assuming a uniform yaw angle within the wake cross-section will overestimate the lateral deformation of the yaw wake, thus failing to provide an accurate prediction of the incoming flow velocity for downstream wind turbines. Therefore, to address these existing problems, a new analytical model for yaw wind turbine wakes is urgently needed to ensure the efficient operation of active yaw strategies. Summary of the Invention

[0005] The purpose of this invention is to provide a method and related apparatus for analyzing the wake of a yaw wind turbine that considers cross-sectional deformation, in order to solve one or more of the aforementioned technical problems. The technical solution disclosed in this invention is applicable to predicting the velocity deficit distribution in the far wake of a yaw wind turbine, which is beneficial for accurately calculating the velocity distribution in the yaw wake. This can then be used to predict the power generation of downstream wind turbines to ensure the effective operation of the active yaw strategy.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for analyzing the wake of a yaw wind turbine considering cross-sectional deformation, comprising the following steps: Based on the yaw wind turbine to be analyzed in the wake, basic parameters are obtained; wherein, the basic parameters include the set wind turbine parameters and atmospheric boundary layer inflow condition parameters; Based on the aforementioned basic parameters, the wake is analyzed using the constructed yaw wake model to obtain the wake velocity distribution. In the yaw wake model, the calculation expression for the wake velocity distribution is as follows: ; In the formula, Represents any spatial point on the far wake section of a yaw wind turbine ( y , z The downwind speed, Indicates the crosswind coordinates. Represents the vertical coordinates; Indicates the incoming flow velocity; This indicates a speed deficit along the wake centerline; Wake deformation representing the maximum velocity deficit at different altitudes; The characteristic width of the lateral wake; Indicates the wheel hub height; The characteristic width of the wake in the vertical direction; ; In the formula, Indicates the thrust coefficient of a yaw wind turbine; This indicates the swept area of ​​the yaw wind turbine; Indicates the yaw angle; This represents the distance along the direction of the incoming flow.

[0007] A further improvement to the technical solution of this invention lies in the swept area of ​​the yaw wind turbine. The calculation expression is: A D = πD 2 / 4; In the formula, D The diameter is the wind turbine.

[0008] A further improvement to the technical solution of this invention lies in that the calculation expression for the wake deformation due to the maximum velocity deficit at different heights is as follows: ; In the formula, This indicates the wake deformation at the height of the wheel hub. This represents a semi-empirical expression; ; In the formula, The diameter of the wind turbine; Represents parameters related to the initial conditions of the far wake; , These are the wake expansion rates in the lateral and vertical directions, respectively; This is the starting position of the far wake; , These are the initial wake widths in the horizontal and vertical directions, respectively; For the initial deformation of the far wake; in, .

[0009] A further improvement to the technical solution of this invention lies in that the calculation expression for the initial deformation of the far wake is: ; In the formula, The turbulence intensity of the incoming flow.

[0010] A further improvement to the technical solution of this invention lies in that the semi-empirical expression is: .

[0011] A further improvement to the technical solution of the present invention lies in that, The expression for calculating the characteristic width of the transverse wake is: ; The expression for calculating the characteristic width of the vertical wake is: ; In the formula, , These are the wake expansion rates in the lateral and vertical directions, respectively; The parameters related to the initial characteristic width of the wake are... , D The diameter is the wind turbine.

[0012] In a second aspect, the present invention provides a wake analysis system for a yaw wind turbine that considers cross-sectional deformation, comprising: The parameter acquisition unit is used to acquire basic parameters based on the yaw wind turbine to be analyzed in the wake; wherein, the basic parameters include the set wind turbine parameters and atmospheric boundary layer inflow condition parameters; The wake analysis unit is used to analyze the wake based on the basic parameters and the constructed yaw wake model to obtain the wake velocity distribution. In the yaw wake model, the calculation expression for the wake velocity distribution is as follows: ; In the formula, Represents any spatial point on the far wake section of a yaw wind turbine ( y , z The downwind speed, Indicates the crosswind coordinates. Represents the vertical coordinates; Indicates the incoming flow velocity; This indicates a speed deficit along the wake centerline; Wake deformation representing the maximum velocity deficit at different altitudes; The characteristic width of the lateral wake; Indicates the wheel hub height; The characteristic width of the wake in the vertical direction; ; In the formula, Indicates the thrust coefficient of a yaw wind turbine; This indicates the swept area of ​​the yaw wind turbine; Indicates the yaw angle.

[0013] In a third aspect, the present invention provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the wake analysis method for a yaw wind turbine considering cross-sectional deformation as described in any one of the first aspects of the present invention.

[0014] In a fourth aspect, the present invention provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the wake analysis method for a yaw wind turbine considering cross-sectional deformation as described in any one of the first aspects of the present invention.

[0015] In a fifth aspect, the present invention provides a computer program product comprising computer instructions which, when executed by a processor, implement the steps of the yaw turbine wake analysis method considering cross-sectional deformation as described in any one of the first aspects of the present invention.

[0016] Compared with the prior art, the present invention has the following beneficial effects: This invention specifically discloses a wake analysis method for yaw wind turbines that considers cross-sectional deformation. Addressing the issue of discrepancies between the top-hat shape and the measured single-peak distribution, it employs a double Gaussian distribution substitution technique. This approach closely aligns with the actual characteristics of the wake, where the core loss is greatest and the edge gradually decays, avoiding overestimation of velocity loss. Furthermore, addressing the problem of incomplete prediction of yaw wake cross-sectional deformation, it calculates the hub height wake offset using an integral formula, then corrects it with Gaussian correction to obtain the non-uniform deformation of the entire cross-section, correcting the erroneous assumption of a "uniform yaw angle distribution." Ultimately, this invention can accurately predict the far-wake velocity distribution, providing accurate incoming flow conditions for downstream wind turbines, effectively supporting the efficient operation of active yaw strategies, and improving wind farm power generation efficiency. Further specifically, the technical solution disclosed in this invention uses a Gaussian distribution to replace the top-hat shape, aligning with the measured single-peak distribution characteristics. Specifically, this invention introduces a double Gaussian distribution term (i.e., ...) into the wake velocity distribution formula. The peak value corresponds to the core region of the wake (where the velocity loss is greatest), and the distribution width is determined by the wake diffusion parameter ( , The decision was made to gradually reduce the velocity loss towards the edge of the cross section, perfectly matching the measured single-peak distribution pattern, thus fundamentally solving the problem of overestimation of velocity loss caused by the top-hat shape.

[0017] In a preferred embodiment of the present invention, a full-section deformation quantification model is further provided to accurately describe the yaw wake distortion characteristics. First, the lateral offset of the wake center at the hub height (i.e., the wake deformation at the hub height) is calculated using an integral formula as the deformation benchmark. Then, the deformation at any height of the full section is obtained using the Gaussian correction formula (i.e., the full-section wake deformation expression). This clearly presents the actual physical characteristics of "maximum deformation at the hub height and attenuation of deformation at the upper and lower edges," correcting the erroneous assumption of "uniform distribution of yaw angle" in the traditional model and avoiding the problem of overestimation of lateral deformation. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating a method for analyzing the wake of a yaw wind turbine that considers cross-sectional deformation, as described in an embodiment of the present invention. Figure 2 This is a schematic diagram of the yaw wake model in an embodiment of the present invention; Figure 3This is a schematic diagram of the yaw wake model calculation process in an embodiment of the present invention; Figure 4 This is a comparative wind tunnel test data comparison diagram of the predicted values ​​of the present invention under the conditions of a yaw angle of 10 degrees and a thrust coefficient of 0.78 in the comparative embodiment of the present invention; Figure 5 This is a comparative wind tunnel test data comparison diagram of the predicted values ​​of the present invention under the conditions of a yaw angle of 20 degrees and a thrust coefficient of 0.73 in the comparative embodiment of the present invention; Figure 6 This is a comparative wind tunnel test data comparison diagram of the predicted values ​​of the present invention under the conditions of a yaw angle of 30 degrees and a thrust coefficient of 0.66 in the comparative embodiment of the present invention; Figure 7 This is a wake section velocity distribution cloud map predicted by the present invention when the yaw angle is 10 degrees in an embodiment of the present invention; Figure 8 This is a wake section velocity distribution cloud map predicted by the present invention when the yaw angle is 20 degrees in an embodiment of the present invention; Figure 9 This is a wake velocity distribution cloud map predicted by the present invention when the yaw angle is 30 degrees in an embodiment of the present invention; Figure 10 This is a schematic diagram of a yaw turbine wake analysis system that takes into account cross-sectional deformation, according to an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention; obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0021] Based on the technical solutions disclosed in the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this invention. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices.

[0022] Please see Figure 1 The present invention provides a method for analyzing the wake of a yaw wind turbine considering cross-sectional deformation, comprising the following steps: Step 1: Based on the selected yaw wind turbine, obtain the wind turbine parameters and the incoming flow condition parameters of the atmospheric boundary layer; wherein, the wind turbine parameters may include the rotor diameter and thrust coefficient, and the incoming flow condition parameters may include the incoming wind speed and the incoming turbulence intensity at the hub height.

[0023] Step 2: Based on the wind turbine parameters and the incoming flow conditions of the atmospheric boundary layer, the wake is analyzed using the constructed yaw wake model to obtain the wake velocity distribution; in a specific exemplary technical solution, the wake centerline velocity deficit, the wake deformation at the hub height, and the wake deformation on the entire wake cross section can be calculated.

[0024] In a specific exemplary technical solution, the velocity deficit along the wake centerline is calculated using the following expression: ; In the formula, This indicates the velocity deficit along the wake centerline, i.e., the velocity in the core region after the velocity deficit. The incoming flow velocity is the wind speed at the hub height. The thrust coefficient of the yaw wind turbine; The swept area of ​​the yaw wind turbine ( A D =πD 2 / 4, D (This refers to the diameter of the wind turbine). Yaw angle is the angle between the plane of the wind turbine rotor and the direction of the incoming flow. , ; In the formula, The characteristic width of the lateral (y-direction) wake. The characteristic width of the wake in the vertical direction (z-direction); , These are the wake expansion rates in the lateral and vertical directions, respectively; x This represents the distance along the direction of the incoming flow, i.e., the coordinates of the downstream location; These are parameters related to the initial characteristic width of the wake.

[0025] In a specific exemplary technical solution, the calculation expressions for the wake deformation at the hub height and the wake deformation across the entire wake cross-section are as follows: ; In the formula, This indicates the wake deformation at the height of the wheel hub. This represents a semi-empirical expression; ; In the formula, The diameter of the wind turbine; Represents parameters related to the initial conditions of the far wake; , These are the wake expansion rates in the lateral and vertical directions, respectively; This is the starting position of the far wake; , These are the initial wake widths in the horizontal and vertical directions, respectively; For the initial deformation of the far wake; in, .

[0026] The formula for calculating the initial deformation of the far wake is: ; In the formula, The turbulence intensity of the incoming flow.

[0027] The semi-empirical expression is: .

[0028] In the technical solution of this invention embodiment, the final velocity distribution across the entire wake cross section is calculated as follows: .

[0029] This invention provides a novel wake analysis method for yaw wind turbines. The wake analysis process considers the three-dimensional spatial distribution of wake velocity and the deformation of the wake cross section. Based on the yaw wake velocity distribution in the wake analysis results, it serves as the inflow condition for downstream wind turbines, thereby obtaining the power generation efficiency of downstream wind turbines and ensuring the efficient operation of the active yaw strategy.

[0030] The Jensen and Frandsen models currently used by commercial software have two major problems: First, they describe the velocity distribution using a top-hat shape (uniformly distributed velocity deficit across the wake cross section), which is seriously inconsistent with the "single-peak distribution" characteristics verified by wake measurements, wind tunnel tests, and numerical simulations. This leads to an overestimation of the velocity deficit encountered by downstream wind turbines, resulting in a lower predicted power output than the actual value. Second, they cannot reasonably predict the cross-sectional deformation of the yaw wake. The incorrect assumption that "the yaw angle is uniformly distributed within the wake cross section" often overestimates the lateral deformation of the wake, failing to provide accurate incoming flow velocity data for downstream wind turbines and severely restricting the efficient operation of active yaw strategies. The novel solution provided by this invention effectively solves the above-mentioned problems. Based on the theory of momentum conservation and combined with the assumption of linear wake expansion, it forms a complete "input, calculation, and output" process: inputting wind turbine parameters, incoming flow conditions, and environmental parameters, first calculating the crosswind and vertical diffusion width of the wake, then obtaining the full cross-sectional deformation through integration and Gaussian correction, and finally substituting it into the velocity formula that integrates the double Gaussian distribution and deformation parameters, the downwind velocity at any point on the wake cross-section can be output. The method disclosed in this invention achieves two major breakthroughs: first, it can accurately calculate the wake velocity loss distribution, avoiding the deviation of "overestimating the loss and underestimating the power" in traditional models, making the downstream wind turbine incoming flow velocity prediction more realistic; second, it can accurately quantify the cross-sectional deformation of the yaw wake, providing clear spatial distribution data of incoming flow velocity for downstream units. These two major breakthroughs can provide reliable theoretical support for active yaw strategies, guiding upstream wind turbines to adjust their yaw angles to ensure that the core wake region avoids downstream units, reducing wake coupling losses. In summary, the method of this invention achieves the goal of "accurately predicting the velocity distribution of the wake of a yaw wind turbine," which can effectively ensure the efficient operation of the active yaw strategy, help wind farms improve overall power generation efficiency, meet the intelligent development needs of large wind farms from "passively adapting to the wake" to "actively managing the wake," and has broad application prospects and high practical value.

[0031] This invention discloses a novel method for analyzing the wake of a yaw wind turbine, applicable to predicting the velocity distribution within the yaw wake and ensuring the efficient operation of active yaw strategies. Since downstream wind turbines are typically located in the far wake region of upstream wind turbines, this invention also addresses the far wake of yaw wind turbines. Further, in principle, when the wind turbine rotor and the incoming wind direction generate a fixed yaw angle, the rotor thrust will have not only a downwind component but also a crosswind component. The downwind thrust reduces the downwind speed, while the crosswind thrust imparts a crosswind speed to the wake, thus causing wake deflection. Therefore, establishing a yaw wake analytical model requires establishing momentum conservation equations in two directions, which differs from the non-yaw wake analytical model.

[0032] Please see Figure 2 , Figure 2 This is a schematic diagram of the control body of the yaw wake model in an embodiment of the present invention. The conditions on the left boundary characterize the incoming flow conditions of the wind turbine, and the right boundary is the exit boundary condition (i.e., the wake velocity distribution that the model needs to predict). The two sides of the control body can be regarded as boundary conditions at infinity.

[0033] In the derivation of the technical solution of this invention embodiment, the momentum conservation equation is first established based on the control volume of the yaw wake model. After neglecting the gravity term and the viscous force term, the following form can be obtained after simplification: (1); (2); In the formula, and These represent the components of the wind turbine thrust in the downwind and crosswind directions, respectively. air density; Indicates the incoming flow velocity; Indicates the tailwind speed of the wake; It is the deflection angle of the wake; y and z These are the crosswind direction and the vertical direction, respectively.

[0034] The model in this embodiment of the invention assumes that the wake center remains at hub height, which is the location of the maximum wake velocity loss at a specific downstream distance. According to existing literature, the yaw wake velocity loss distribution and yaw angle distribution exhibit self-similarity. The crosswind position of the wake center is located at... The maximum yaw angle is in phase with the wake center, that is... Therefore, the shape functions of the tailwind velocity and yaw angle of the yaw wake can be written as: (3); (4); In the formula, It is a speed loss along the wake centerline. This represents the wake deformation at different heights z where the maximum velocity deficit is located. It refers to the wheel hub height; and Characteristic widths of the wake in the lateral and vertical directions; D It is the diameter of the wind turbine. It is the maximum deflection angle of the wake at the height of the wheel hub.

[0035] Substituting equation (3) into equation (1) and integrating over the exit section of the control body, we get: (5) The thrust of the wind turbine is only affected by the velocity component perpendicular to the sweeping surface of the wind turbine, that is: (6) The projections of the wind turbine thrust in the downwind and crosswind directions are as follows: (7) (8) The downwind component of the thrust causes a loss in the downwind wake velocity.

[0036] Substituting equation (5) into equation (7), based on the general solution of the quadratic equation, we can obtain two equations related to... The analytical expression is given, but only one of them satisfies the physical condition that the velocity deficit is less than the incoming flow velocity. The expression is: (9) Similarly, we now consider the right-hand side of the integral equation (2). The crosswind velocity is smaller than the wake's downwind velocity, therefore the wake deflection angle is... It is relatively small. Therefore, according to the principle of equivalent infinitesimals, Approximately equal to Therefore, we have: (10) By combining the two, the maximum deflection angle can be obtained. for: (11) The reason for calculating the deflection angle is to obtain the deformation equation of the wake center through the equation of the deflection angle.

[0037] The deflection angle can be expressed as Equation (11) will be further rewritten as: (12) The offset of the wake center can be solved by integrating equation (12). Equation (12) also requires determining the expression for the wake characteristic width. Since the wake characteristic width varies with downstream distance, it is necessary to establish the relationship between the wake characteristic width and the downstream distance. If we assume that the wake width exhibits linear expansion, then the wake width can be expressed as: (13) (14) in, Indicates the wake expansion rate. It is a parameter related to the initial feature width.

[0038] By substituting equations (13) and (14) and performing a series of mathematical operations, the wake deflection can be obtained as follows: (15) in, (16) For the wake model, the initial position of the far wake is involved. The calculation is performed using a semi-empirical equation: (17) Initial deformation of the far wake Based on the potential core theory, we obtain: (18) The deformation on the wake section is obtained through a semi-empirical expression and the deformation at the hub height, specifically: (19) The semi-empirical expression is obtained by fitting the results of numerical simulation, and the expression is: (20) Please see Figures 3 to 9 In a specific embodiment of the present invention, to highlight the predictive capability of the model, wind tunnel test data from Bastankhah and Porté-Agel in 2016 were used for comparison. The specific calculation process is as follows: Figure 3 As shown, the process includes the following: The first step is to input the relevant parameters of the atmospheric boundary layer inflow conditions and the dimensions of the wind turbine, such as the rotor sweep diameter, hub height, inflow velocity at the hub height, and ground roughness. As can be seen from equation (9), to calculate the velocity deficit and distribution along the wake centerline, the characteristic width of the wake needs to be known, and this characteristic width is affected by the inflow conditions and thrust coefficient. This embodiment of the invention references the wind tunnel test conducted by Bastankhah and Porté-Agel. The model wind turbine has a diameter of 0.15m, a hub height of 0.125m, an inflow velocity of 4.88m / s at the hub height, a turbulence intensity of 0.08, and a roughness length of 0.00003m. This wind tunnel test examined three different yaw angles: 10 degrees, 20 degrees, and 30 degrees, with corresponding rotor thrust coefficients of 0.78, 0.73, and 0.66, respectively.

[0039] The second step is to calculate the characteristic width of the wake at a specific downstream location.

[0040] If we assume that the wake expands linearly with the downstream distance, then we can obtain the expression for the characteristic width of the wake at a specific location: ; ; in, The relevant parameters for the initial feature width are expressed as follows: .

[0041] The third step is to calculate the wake velocity distribution at the hub height at a specific downstream location.

[0042] Generally, in non-yaw wake models, the velocity distribution does not need to consider the yaw angle; however, in yaw models, the influence of the yaw angle needs to be considered. Therefore, using the momentum conservation equation, the velocity deficit along the wake centerline is obtained, as expressed below: .

[0043] The fourth step is to calculate the deformation formula for the wake center.

[0044] Variation of the wake center expression: ; in, An expression relating to the initial width: ; In the formula, physical quantities with a subscript of 0 represent the initial position of the far wake.

[0045] The initial deformation of the far wake is calculated using the following formula: ; For the initial width of the far wake, the predicted initial downstream position of the far wake can be substituted into the corresponding calculation formula above to obtain the wake deformation and wake velocity distribution at the hub height.

[0046] Then, the deformation on the wake section is calculated and expressed as: ; ; Substituting the predicted data into the wake velocity distribution, we can obtain the velocity distribution across the entire wake cross section, as follows: ; Figures 4 to 6 A comparison chart of the predicted values ​​of the model disclosed in the technical solution of this invention and wind tunnel test data is provided. It can be seen from the chart that the wake velocity predicted by the model of this invention is more consistent with the test results, while the errors of other analytical models are more obvious. Figures 7 to 9Cross-wind profiles of the wake at different downstream locations and yaw angles predicted by this invention are presented. It can be seen that the model of this invention can predict the velocity distribution of the wake at different altitudes well, and can also reproduce the bending phenomenon on the wake cross section.

[0047] This invention provides a novel technical solution and specific calculation expressions, which can predict the velocity distribution on the cross-section of the yaw turbine wake at different yaw angles, predict the lateral displacement of the yaw wake center as the downstream distance changes, and predict the deformation of the yaw wake on the cross-section, thereby ensuring the effective operation of the active yaw strategy. Further, to ensure the effective operation of the active yaw strategy, this invention discloses a newly constructed analytical model. It utilizes the Reynolds-averaged Navier-Stokes equations to establish momentum conservation equations for the velocity and yaw angle distributions of the yaw turbine wake. It also assumes that the wake width expands linearly along the downstream distance, and that the velocity deficit and yaw angle distribution within the wake exhibit a standard Gaussian distribution. Finally, through a series of mathematical solutions, the yaw wake model proposed in this invention is constructed. The yaw wake model constructed by the improved technical means of this invention has high accuracy and is more efficient and convenient than numerical simulation and wind tunnel testing methods, which is beneficial for the application of the active yaw strategy in actual wind farms. In summary, based on the theory of momentum conservation, this invention proposes an analytical model that can predict the deformation of the wake section of a yaw wind turbine. This analytical model can effectively predict the velocity distribution of the yaw wake, thereby ensuring accurate prediction of the power generation of the downstream wind turbine. Furthermore, through data fitting, a semi-empirical expression for predicting the deformation of the wind turbine wake section is derived.

[0048] The following are embodiments of the apparatus of the present invention, which can be used to execute embodiments of the method of the present invention. For details not disclosed in the apparatus embodiments, please refer to the embodiments of the method of the present invention.

[0049] Please see Figure 10 In this embodiment of the invention, a wake analysis system for a yaw wind turbine considering cross-sectional deformation is provided, comprising: The parameter acquisition unit is used to acquire basic parameters based on the yaw wind turbine to be analyzed in the wake; wherein, the basic parameters include the set wind turbine parameters and atmospheric boundary layer inflow condition parameters; The wake analysis unit is used to analyze the wake based on the basic parameters and the constructed yaw wake model to obtain the wake velocity distribution. In the yaw wake model, the calculation expression for the wake velocity distribution is as follows: ; In the formula, Represents any spatial point on the far wake section of a yaw wind turbine ( y ,z The downwind speed, Indicates the crosswind coordinates. Represents the vertical coordinates; Indicates the incoming flow velocity; This indicates a speed deficit along the wake centerline; Wake deformation representing the maximum velocity deficit at different altitudes; The characteristic width of the lateral wake; Indicates the wheel hub height; The characteristic width of the wake in the vertical direction; ; In the formula, Indicates the thrust coefficient of a yaw wind turbine; This indicates the swept area of ​​the yaw wind turbine; Indicates the yaw angle.

[0050] In one embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used to execute the operation of a yaw turbine wake analysis method considering cross-sectional deformation.

[0051] In one embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the operating system of the terminal. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor, which can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM (Random Access Memory) or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the yaw turbine wake analysis method considering cross-sectional deformation in the above embodiments.

[0052] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, etc.) containing computer-usable program code.

[0053] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0054] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0055] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0056] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for analyzing the wake of a yaw wind turbine considering cross-sectional deformation, characterized in that, Includes the following steps: Based on the yaw wind turbine to be analyzed in the wake, basic parameters are obtained; wherein, the basic parameters include the set wind turbine parameters and atmospheric boundary layer inflow condition parameters; Based on the aforementioned basic parameters, the wake is analyzed using the constructed yaw wake model to obtain the wake velocity distribution. In the yaw wake model, the calculation expression for the wake velocity distribution is as follows: ； In the formula, Represents any spatial point on the far wake section of a yaw wind turbine ( y , z The downwind speed, Indicates the crosswind coordinates. Represents the vertical coordinates; Indicates the incoming flow velocity; This indicates a speed deficit along the wake centerline; Wake deformation representing the maximum velocity deficit at different altitudes; The characteristic width of the lateral wake; Indicates the wheel hub height; The characteristic width of the wake in the vertical direction; ； In the formula, Indicates the thrust coefficient of a yaw wind turbine; This indicates the swept area of ​​the yaw wind turbine; Indicates the yaw angle; This represents the distance along the direction of the incoming flow.

2. The method for analyzing the wake of a yaw wind turbine considering cross-sectional deformation according to claim 1, characterized in that, swept area of ​​yaw wind turbine The calculation expression is: A D = πD 2 / 4； In the formula, D The diameter is the wind turbine.

3. The method for analyzing the wake of a yaw wind turbine considering cross-sectional deformation according to claim 1, characterized in that, The formula for calculating the wake deformation at different altitudes due to the maximum velocity deficit of the wake is as follows: ； In the formula, This indicates the wake deformation at the height of the wheel hub. This represents a semi-empirical expression; ； In the formula, The diameter of the wind turbine; Represents parameters related to the initial conditions of the far wake; , These are the wake expansion rates in the lateral and vertical directions, respectively; This is the starting position of the far wake; , These are the initial wake widths in the horizontal and vertical directions, respectively; For the initial deformation of the far wake; in, .

4. The method for analyzing the wake of a yaw wind turbine considering cross-sectional deformation according to claim 3, characterized in that, The formula for calculating the initial deformation of the far wake is: ； In the formula, The turbulence intensity of the incoming flow.

5. The method for analyzing the wake of a yaw wind turbine considering cross-sectional deformation according to claim 3, characterized in that, The semi-empirical expression is: 。 6. The method for analyzing the wake of a yaw wind turbine considering cross-sectional deformation according to claim 1, characterized in that, The expression for calculating the characteristic width of the transverse wake is: ; The expression for calculating the characteristic width of the vertical wake is: ; In the formula, , These are the wake expansion rates in the lateral and vertical directions, respectively; The parameters related to the initial characteristic width of the wake are... , D The diameter is the wind turbine.

7. A wake analysis system for a yaw wind turbine considering cross-sectional deformation, characterized in that, include: The parameter acquisition unit is used to acquire basic parameters based on the yaw wind turbine to be analyzed in the wake; wherein, the basic parameters include the set wind turbine parameters and atmospheric boundary layer inflow condition parameters; The wake analysis unit is used to analyze the wake based on the basic parameters and the constructed yaw wake model to obtain the wake velocity distribution. In the yaw wake model, the calculation expression for the wake velocity distribution is as follows: ； In the formula, Represents any spatial point on the far wake section of a yaw wind turbine ( y , z The downwind speed, Indicates the crosswind coordinates. Represents the vertical coordinates; Indicates the incoming flow velocity; This indicates a speed deficit along the wake centerline; Wake deformation representing the maximum velocity deficit at different altitudes; The characteristic width of the lateral wake; Indicates the wheel hub height; The characteristic width of the wake in the vertical direction; ； In the formula, Indicates the thrust coefficient of a yaw wind turbine; This indicates the swept area of ​​the yaw wind turbine; Indicates the yaw angle.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the wake analysis method for yaw wind turbines that considers cross-sectional deformation as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the wake analysis method for yaw wind turbines that takes into account cross-sectional deformation as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, It includes computer instructions that, when executed by a processor, implement the steps of the wake analysis method for a yaw wind turbine considering cross-sectional deformation as described in any one of claims 1 to 6.

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