Wind farm wake loss prediction method, device and medium considering flow turbulence

Abstract

The present invention relates to the technical field of wind farm planning and design, and specifically provides a method, device and medium for predicting the wake loss of a wind farm taking into account the flow turbulence, aiming to solve the problem of how to quickly, simply and accurately predict the wake loss of a wind farm. To this end, the present invention corrects the wake expansion coefficient of the wind turbine according to the flow turbulence in front of the wind turbine, and more accurately evaluates the wake effect of the wind turbine. The total output power of the wind turbine and the total output power without considering the wake effect are obtained according to the discrete actual wind conditions, and the total wake loss of the wind farm is obtained. Through the above-mentioned configuration, the present invention can fully consider the influence of the flow turbulence in the wind farm on the wake expansion coefficient of the wind turbine, so as to more accurately calculate the inflow wind speed of the wind turbine, and then make the total output power of the wind turbine calculated according to the inflow wind speed more accurate.

Description

Technical Field

[0001] The invention relates to the technical field of wind farm planning and design, and specifically provides a method, a device and a medium for predicting the wake loss of a wind farm taking into account the flow turbulence. Background Art

[0002] Accurately predicting the wake loss of a wind farm is of great significance for the micro-site selection of wind farms and the evaluation of wind farm power generation. With the advancement of wind farm base construction, the scale of wind farms has become larger and larger, which has also led to more serious wake effects in wind farms. According to research statistics, the Horns Rev wind farm in Denmark has suffered a power generation loss of up to 25% due to the wake effect. At present, some numerical simulation methods such as Large Eddy Simulation (LES) and Reynolds Average Navier-Stokes (RANS) can perform a more accurate calculation of wake losses, but these methods require the use of professional software or codes, which are complex to set up, take a long time to calculate, and are costly, and cannot achieve fast and accurate prediction of wakes.

[0003] Based on this, the art needs a more convenient solution for predicting the wake loss of wind farms to solve the above problems. Summary of the invention

[0004] In order to overcome the above-mentioned defects, the present invention is proposed to provide a solution or at least partially solve the problem of how to quickly, simply and accurately predict the wake loss of a wind farm.

[0005] In a first aspect, the present invention provides a method for predicting the wake loss of a wind farm taking into account the flow turbulence, the prediction method comprising:

[0006] For each wind turbine in the wind farm, according to the flow turbulence in front of the current wind turbine under each wind condition, the wake expansion coefficient of the current wind turbine is corrected to obtain the corrected wake expansion coefficient corresponding to each wind condition;

[0007] Using a preset wake model and according to the corrected wake expansion coefficient, the inflow wind speed in front of the hub of the current wind turbine generator set under each wind condition is obtained; and according to the inflow wind speed, the output power of the current wind turbine generator set under each wind condition is obtained respectively;

[0008] According to the output power corresponding to each wind condition and the probability of occurrence of each wind condition, the total output power of the current wind turbine generator set under all wind conditions is obtained;

[0009] According to the total output power of the current wind turbine generator set under all wind conditions and the total output power of the current wind turbine generator set without considering the wake effect, a relative loss of the total output power of the current wind turbine generator set is obtained, and the wake loss of the wind farm is predicted according to the relative loss;

[0010] The total output power without considering the wake effect refers to the total output power of the current wind turbine under all wind conditions when the inflow wind speed in front of the hub of the current wind turbine is the free inflow wind speed.

[0011] In a technical solution of the above-mentioned method for predicting the wake loss of a wind farm considering the flow turbulence, the step of "correcting the wake expansion coefficient of the current wind turbine according to the flow turbulence in front of the current wind turbine under each wind condition to obtain the corrected wake expansion coefficient corresponding to each wind condition" includes correcting the wake expansion coefficient according to the following formula to obtain the corrected wake expansion coefficient:

[0012] k wi =2×(0.3837×I i +0.003678)

[0013] Among them, k wi is the corrected wake expansion coefficient, I i is the flow turbulence in front of the current wind turbine i.

[0014] In a technical solution of the above-mentioned method for predicting the wake loss of a wind farm considering the flow turbulence, the wake model is obtained according to the following formula:

[0015]

[0016] Where ΔU is the average speed loss of a single upstream wind turbine at a specified location in the wind farm, and U ∞ is the free inflow wind speed of the wind farm, C T is the thrust coefficient of the single upstream wind turbine, k is the wake expansion coefficient, d 1 is the flow distance between the specified position and the single upstream wind turbine, r 0 is the rotor radius of the single upstream wind turbine generator set, and r is the radial distance between the designated position and the rotor center of the single upstream wind turbine generator set;

[0017] The step of “using a preset wake model and according to the corrected wake expansion coefficient, obtaining the inflow wind speed in front of the hub of the current wind turbine under each wind condition; and obtaining the output power of the current wind turbine under each wind condition according to the inflow wind speed” includes:

[0018] Using the wake model and according to the corrected wake expansion coefficient, obtaining, when the designated position is the position of the current wind turbine generator set, an average speed loss of the upstream wind turbine generator set of the current wind turbine generator set at the position of the current wind turbine generator set;

[0019] According to the average speed loss and the method described in the following formula, the superimposed speed loss at the current location of the wind turbine generator set is obtained:

[0020]

[0021] Among them, ΔU i is the superposition velocity loss at the current location of wind turbine i; ΔU ij is the average speed loss of the jth upstream wind turbine at the current wind turbine i; q ij is a binary variable, q is valid if and only if the current wind turbine i is in the wake area generated by the jth upstream wind turbine ij =1, otherwise q ij =0; N p is the total number of wind turbines upstream of the current wind turbine in the wind farm;

[0022] According to the superposition velocity loss at the location of the current wind turbine generator set and the method described in the following formula, the inflow wind speed in front of the hub of the current wind turbine generator set under each wind condition is obtained:

[0023] U ip =U 0p -ΔU ip

[0024] Among them, U 0p is the free inflow wind speed in front of the hub of the current wind turbine under the pth wind condition; U ip is the inflow wind speed in front of the hub of wind turbine i under the pth wind condition; ΔU ip is the superposition velocity loss at the current location of wind turbine i under the pth wind condition;

[0025] According to the inflow wind speed in front of the hub of the current wind turbine set under each wind condition and a preset power curve of the current wind turbine set, the output power of the current wind turbine set under each wind condition is obtained respectively; wherein the power curve includes the corresponding relationship between the inflow wind speed in front of the hub and the output power under each wind condition.

[0026] In a technical solution of the above-mentioned method for predicting the wake loss of a wind farm considering the flow turbulence, the step of "obtaining the total output power of the current wind turbine under all wind conditions according to the output power corresponding to each wind condition and the probability of occurrence of each wind condition" includes obtaining the total output power of the current wind turbine under all wind conditions according to the method described in the following formula:

[0027]

[0028] Among them, P i is the total output power of wind turbine i under all wind conditions; f(u k ,θ l ) is the free inflow velocity u k And the wind direction angle is θ l The probability of the wind condition occurring at time u i1 The wind speed in the free inflow is u k And the wind direction angle is θ l The inflow wind speed in front of the hub of the current wind turbine i under the wind condition at time u i1 ≠u k ,Power(u i1 ) is based on the inflow wind speed u i1 The wind speed in the free inflow is u k And the wind direction angle is θ l The output power of wind turbine i at the current wind condition at time ; N θ is the total number of wind direction angles corresponding to all wind conditions; N u is the total number of free inflow wind speeds corresponding to all wind conditions, N t is the total number of wind turbines in the wind farm.

[0029] In a technical solution of the above-mentioned method for predicting the wake loss of a wind farm considering the flow turbulence, the step of "obtaining the relative loss of the total output power of the current wind turbine according to the total output power of the current wind turbine under all wind conditions and the total output power of the current wind turbine without considering the wake effect" includes obtaining the relative loss of the total output power of the current wind turbine according to the following formula:

[0030]

[0031] Where wakeloss(i) is the relative loss of the total output power of wind turbine i at present, P i is the total output power of wind turbine i under all wind conditions, P 0 is the total output power of wind turbine i without considering the wake effect, P 0 Obtained according to the following formula:

[0032]

[0033] u i2 The wind speed in the free inflow is u k And the wind direction angle is θ l The inflow wind speed in front of the hub of the current wind turbine i under the wind condition at time u i2 =u k ,Power(u i2 ) is based on the inflow wind speed u i2 The wind speed in the free inflow is u k And the wind direction angle is θ l The output power of the current wind turbine i under the wind conditions at time .

[0034] In a technical solution of the above-mentioned method for predicting the wake loss of a wind farm taking into account the flow turbulence, the method further comprises calculating the flow turbulence in front of the current wind turbine according to the following steps:

[0035] According to the additional flow turbulence generated by the upstream wind turbine at any position of the wind farm and the method described in the following formula, the additional flow turbulence at any position of the wind farm is obtained:

[0036]

[0037] in, The wind direction angle is θ l When , the additional streamwise turbulence at the position (x, y, z) in the wind farm; ΔIu m (x, y, z) is the additional flow turbulence generated by the mth upstream wind turbine at the position (x, y, z); N is the total number of upstream wind turbines at the position (x, y, z) in the wind farm;

[0038] According to the additional flow turbulence at the location of the current wind turbine and any location of the wind farm and in accordance with the method described below, the point flow turbulence at multiple points in front of the hub of the current wind turbine is obtained:

[0039]

[0040] in, The wind direction angle is θ l When the current wind turbine i hub front (x i ,y i ,z i ) point flow turbulence at point I 0 is the atmospheric turbulence in front of the hub of the current wind turbine;

[0041] According to the point flow turbulence degrees at multiple points in front of the hub of the current wind turbine generator set, the maximum value of the point flow turbulence degrees among the multiple point flow turbulence degrees is obtained as the flow turbulence degree in front of the current wind turbine generator set.

[0042] In a second aspect, a control device is provided, which includes a processor and a storage device, wherein the storage device is suitable for storing multiple program codes, and the program codes are suitable for being loaded and run by the processor to execute the method for predicting wake losses in a wind farm considering flow turbulence as described in any of the technical solutions of the above-mentioned method for predicting wake losses in a wind farm considering flow turbulence.

[0043] In a third aspect, a computer-readable storage medium is provided, which stores a plurality of program codes, wherein the program codes are suitable for being loaded and run by a processor to execute the method for predicting wake losses in a wind farm considering flow turbulence as described in any of the technical solutions of the method for predicting wake losses in a wind farm considering flow turbulence.

[0044] The above one or more technical solutions of the present invention have at least one or more of the following beneficial effects:

[0045] In the technical solution for implementing the present invention, the wake expansion coefficient of the current wind turbine is corrected according to the flow turbulence in front of the current wind turbine under each wind condition, and the inflow wind speed in front of the hub of the current wind turbine is obtained by using a preset wake model and based on the corrected wake expansion coefficient. The output power of the current wind turbine under each wind condition is obtained according to the inflow wind speed, and the total output power of the current wind turbine under all wind conditions is obtained according to the output power under each wind condition and the probability of occurrence of each wind condition. The wake loss of the current wind turbine is obtained according to the total output power of the current wind turbine under all wind conditions and the total output power of the current wind turbine without considering the wake effect, so as to realize the prediction of the wake loss of the wind farm. Through the above configuration, the present invention can correct the wake expansion coefficient according to the flow turbulence before calculating the inflow wind speed in front of the hub of the wind turbine, and further use the corrected wake expansion coefficient to calculate the inflow wind speed in front of the hub of the wind turbine, fully considering the influence of the flow turbulence in the wind farm on the wake expansion coefficient of the wind turbine, and calculating the inflow wind speed according to the wake expansion coefficient, so that the total output power of the wind turbine calculated according to the inflow wind speed is more accurate. At the same time, because the present invention does not require the use of professional software and codes, and does not require a complicated setting process to be implemented, it also makes the prediction process of the wind farm wake loss simpler and faster, reduces the calculation cost, and provides an effective reference for the planning and design of large wind farms. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The disclosure of the present invention will become more easily understood with reference to the accompanying drawings. It is easy for those skilled in the art to understand that these drawings are only for illustrative purposes and are not intended to limit the scope of protection of the present invention. Among them:

[0047] Figure 1 This is a schematic flow chart of the main steps of a method for predicting wind farm wake losses considering flow turbulence according to an embodiment of the present invention;

[0048] Figure 2 This is a schematic diagram of the Horns Rev wind farm layout;

[0049] Figure 3 is a thrust curve schematic diagram and a power curve schematic diagram of a Vestas-V80 wind turbine according to an implementation of an embodiment of the present invention;

[0050] Figure 4 This is a schematic diagram of the flow turbulence cloud diagram in front of the hub at 270 degrees wind down at Horns Rev wind farm based on LES results;

[0051] Figure 5 It is a schematic diagram of a flow turbulence cloud diagram in front of a hub at 270 degrees wind down in a Horns Rev wind farm according to an implementation of an embodiment of the present invention;

[0052] Figure 6 It is a schematic diagram comparing the turbulence prediction result in the front flow direction of each row of wind turbines in the Horns Rev wind farm at a wind direction of 270 degrees with the LES result according to an implementation of an embodiment of the present invention;

[0053] Figure 7 is a schematic diagram of the arrangement of wind turbines in a wind farm according to an implementation of an embodiment of the present invention;

[0054] Figure 8 It is a schematic diagram comparing actual observed data within a wind direction range of 270°±1° according to an implementation of an embodiment of the present invention and normalized output power obtained by a Jensen wake model, a BP wake model, and an embodiment of the present invention;

[0055] Fig. 9 It is a schematic diagram comparing actual observed data within a wind direction range of 270°±5° according to an implementation of an embodiment of the present invention and normalized output power obtained by a Jensen wake model, a BP wake model, and an embodiment of the present invention;

[0056] Fig.10It is a schematic diagram comparing actual observed data within a wind direction range of 222°±1° according to an implementation of an embodiment of the present invention and normalized output power obtained by a Jensen wake model, a BP wake model, and an embodiment of the present invention;

[0057] Fig.11 It is a schematic diagram comparing actual observed data within a wind direction range of 222°±5° according to an implementation of an embodiment of the present invention and normalized output power obtained by the Jensen wake model, the BP wake model, and the embodiment of the present invention. DETAILED DESCRIPTION

[0058] Some embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0059] In the description of the present invention, "module" and "processor" may include hardware, software or a combination of the two. A module may include hardware circuits, various suitable sensors, communication ports, and memory, and may also include software parts, such as program code, or a combination of software and hardware. The processor may be a central processing unit, a microprocessor, a digital signal processor, or any other suitable processor. The processor has data and / or signal processing functions. The processor may be implemented in software, hardware, or a combination of the two. Non-temporary computer-readable storage media include any suitable medium that can store program code, such as a disk, a hard disk, an optical disk, a flash memory, a read-only memory, a random access memory, and the like. 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 term "at least one A or B" or "at least one of A and B" has a similar meaning to "A and / or B", and may include only A, only B, or A and B. The singular terms "one" and "the" may also include plural forms.

[0060] See attached Figure 1 , Figure 1 FIG. 1 is a schematic flow chart of the main steps of a method for predicting the wake loss of a wind farm considering the flow turbulence according to an embodiment of the present invention. Figure 1 As shown, the method for predicting the wind farm wake loss considering the flow turbulence in the embodiment of the present invention mainly includes the following steps S101 to S104.

[0061] Step S101: for each wind turbine in the wind farm, the wake expansion coefficient of the current wind turbine is corrected according to the flow turbulence in front of the current wind turbine under each wind condition, so as to obtain the corrected wake expansion coefficient corresponding to each wind condition.

[0062] In this embodiment, for each wind turbine in the wind farm, the wake expansion coefficient of the current wind turbine can be corrected according to the flow turbulence in front of the current wind turbine under each wind condition, so as to obtain the corrected wake expansion coefficient corresponding to each wind condition. Flow turbulence is a characteristic quantity that describes the degree to which wind speed changes with time and space. In a wind farm, the flow turbulence has an important influence on the speed of the wind farm wake recovery. Specifically, a stronger flow turbulence helps the wake to expand, so that the wake and the surrounding free flow undergo convection transformation, so that the speed loss caused by the wake can be quickly recovered; while a smaller flow turbulence has a smaller effect on the wake expansion, so that the speed loss caused by the wake can be recovered more slowly. In view of the above-mentioned influence mechanism of flow turbulence on the wake characteristics, it can be considered to correct the wake expansion coefficient of the current wind turbine according to the flow turbulence in front of the wind turbine. The wake expansion coefficient is a coefficient that represents the linear law of wake expansion. Free flow refers to the inflow that is not affected by the wake.

[0063] Step S102: using a preset wake model and according to the corrected wake expansion coefficient, obtaining the inflow wind speed in front of the hub of the current wind turbine under each wind condition; and obtaining the output power of the current wind turbine under each wind condition according to the inflow wind speed.

[0064] In this embodiment, a preset wake model can be used to obtain the output power of the current wind turbine under each wind condition according to the corrected wake expansion coefficient obtained in step S101. The wake model refers to a mathematical analytical model developed based on the aerodynamic principle of the wind turbine, and the wake model can include the relationship between the inflow wind speed in front of the wind turbine hub and the wake expansion coefficient.

[0065] Step S103: According to the output power corresponding to each wind condition and the probability of occurrence of each wind condition, the total output power of the current wind turbine generator set under all wind conditions is obtained.

[0066] In this implementation, the total output power of the current wind turbine generator set under all wind conditions may be obtained according to the output power corresponding to each wind condition and the probability of occurrence of each wind condition.

[0067] In one embodiment, the probability of occurrence of each wind condition may be used as the weight of the output power corresponding to each wind condition, and the output power corresponding to each wind condition may be weighted and calculated to obtain the total output power of the current wind turbine under all wind conditions.

[0068] Step S104: According to the total output power of the current wind turbine under all wind conditions and the total output power of the current wind turbine without considering the wake effect, the relative loss of the total output power of the current wind turbine is obtained, and the wake loss of the wind farm is predicted according to the relative loss; wherein, the total output power without considering the wake effect refers to the total output power of the current wind turbine under all wind conditions when the inflow wind speed in front of the hub of the current wind turbine is the free inflow wind speed.

[0069] In this embodiment, it can be assumed that the inflow wind speed in front of the hub of the current wind turbine is the free inflow wind speed, and the total output power of the current wind turbine under all wind conditions is calculated as the total output power without considering the wake effect. The relative loss of the total output power of the current wind turbine can be obtained according to the total output power of the current wind turbine under all wind conditions and the total output power without considering the wake effect, so as to predict the wake loss of the wind farm. Among them, the free inflow wind speed refers to the inflow wind speed in front of the hub that is not affected by the wake.

[0070] In one embodiment, the relative loss of the total output power of the current wind turbines may be defined as the wake loss of the wind farm.

[0071] In one embodiment, the relative loss of total output power may be the difference between the total output power of the current wind turbine without considering the wake effect and the total output power of the current wind turbine under all wind conditions, or may be the result obtained by numerically transforming the difference.

[0072] Based on the above steps S101 to S104, the present invention can correct the wake expansion coefficient of the current wind turbine according to the flow turbulence in front of the current wind turbine under each wind condition, adopt a preset wake model and obtain the inflow wind speed in front of the hub of the current wind turbine according to the corrected wake expansion coefficient, obtain the output power of the current wind turbine under each wind condition according to the inflow wind speed, and obtain the total output power of the current wind turbine under all wind conditions according to the output power under each wind condition and the probability of occurrence of each wind condition, and obtain the wake loss of the current wind turbine according to the total output power of the current wind turbine under all wind conditions and the total output power of the current wind turbine without considering the wake effect, so as to realize the prediction of the wake loss of the wind farm. Through the above configuration, the present invention can correct the wake expansion coefficient according to the flow turbulence before calculating the inflow wind speed in front of the hub of the wind turbine, and further use the corrected wake expansion coefficient to calculate the inflow wind speed in front of the hub of the wind turbine, fully considering the influence of the flow turbulence in the wind farm on the wake expansion coefficient of the wind turbine, and calculating the inflow wind speed according to the wake expansion coefficient, so that the total output power of the wind turbine calculated according to the inflow wind speed is more accurate. At the same time, because the present invention does not require the use of professional software and codes, and does not require a complicated setting process to be implemented, it also makes the prediction process of the wind farm wake loss simpler and faster, reduces the calculation cost, and provides an effective reference for the planning and design of large wind farms.

[0073] Steps S101 to S104 are further described below.

[0074] In one implementation of the embodiment of the present invention, step S101 may further include correcting the wake expansion coefficient according to the following formula (1) to obtain a corrected wake expansion coefficient:

[0075] k wi =2×(0.3837×I i +0.003678) (1)

[0076] Among them, k wi is the corrected wake expansion coefficient, I i is the flow turbulence in front of the current wind turbine i.

[0077] In this embodiment, the corrected wake expansion coefficient can be calculated and obtained according to the method shown in formula (1).

[0078] In one embodiment, the three-dimensional wake additional flow turbulence model of a wind turbine disclosed in a patent application with the invention name “A method for calculating the flow turbulence of a far-field wake of a wind turbine”, application number CN202011102957.9, and publication number CN112347611A can be used to calculate the flow turbulence of the wind turbine. The three-dimensional wake additional flow turbulence model of a wind turbine is determined according to the following formulas (2)-(9):

[0079]

[0080]

[0081]

[0082] σ y =k×x+eD (5)

[0083]

[0084]

[0085]

[0086]

[0087] Among them, ΔI u is the additional streamwise turbulence; is the maximum additional flow turbulence; r is the straight-line distance from the coordinate of any position in the wake section to the centerline of the hub; is the radial distance between the maximum position of the additional flow turbulence and the centerline of the hub; δ(r) is the correction function, which corrects the asymmetry of the additional flow turbulence in the vertical direction; σ T is the standard deviation of the Gaussian distribution of the additional flow outside the turbulence peak; C T is the thrust coefficient of the wind turbine; I a I is the ambient turbulence at the hub height of the wind turbine; 0 is the atmospheric turbulence in front of the hub of the current wind turbine; x is the distance between the upstream and downstream wind turbines; D is the diameter of the wind turbine rotor; σ y is the standard deviation of the wake velocity loss profile in the horizontal plane; k is the wake expansion coefficient; ε is the standard deviation of the wake velocity loss profile at the wind rotor position; I 0 h is the atmospheric turbulence intensity at the hub height h of the wind turbine; α is the azimuth angle corresponding to the radial peak position of the correction value (the y direction represents 0 degrees); z is the vertical distance from the ground; h is the hub height of the wind turbine; k 1is the weight distribution, which indicates the weight change of the correction function at different positions in the wake section. The streamwise distance refers to the distance between adjacent wind turbines in the direction corresponding to the inflow wind direction. The radial distance refers to the distance between adjacent wind turbines in the direction perpendicular to the inflow wind direction.

[0088] In this embodiment, the flow turbulence degree in front of the current wind turbine can be calculated according to the following steps S1011 to S1013:

[0089] Step S1011: According to the additional flow turbulence generated by the upstream wind turbine at any position of the wind farm and in accordance with the method described in formula (10), the additional flow turbulence at any position of the wind farm is obtained:

[0090]

[0091] in, The wind direction angle is θ l When , the additional streamwise turbulence at the position (x, y, z) in the wind farm; ΔIu m (x, y, z) is the additional flow turbulence generated by the mth upstream wind turbine at the position (x, y, z); N is the total number of upstream wind turbines at the position (x, y, z) in the wind farm.

[0092] In this embodiment, the additional flow turbulence at any position of the wind farm can be obtained according to formula (10). Specifically, studies have shown that when predicting the flow turbulence in the wake of a given wind turbine, the adjacent upstream wind turbine has the greatest impact on the flow turbulence. Therefore, for the flow turbulence at any position in the wind farm, only the influence of the maximum additional flow turbulence generated by the nearest upstream wind turbine is considered, and the additional flow turbulence at any position of the wind farm is obtained according to formula (10).

[0093] Step S1012: According to the additional flow turbulence at the current wind turbine location and any location of the wind farm and according to formula (11), the point flow turbulence at multiple points in front of the hub of the current wind turbine is obtained:

[0094]

[0095] in, The wind direction angle is θ l When the current wind turbine i hub front (x i ,y i , z i ) point flow turbulence at point I 0 is the atmospheric turbulence in front of the hub of the current wind turbine.

[0096] In this embodiment, the flow turbulence at multiple points in front of the hub of the current wind turbine can be calculated according to the location of the wind turbine and the flow turbulence at any location in the wind farm according to formula (11).

[0097] Step S1013: according to the point flow turbulence at multiple points in front of the hub of the current wind turbine, the maximum value of the point flow turbulence among the point flow turbulence at multiple points is obtained as the flow turbulence in front of the current wind turbine.

[0098] In this embodiment, the maximum value of the point flow turbulence at multiple points in front of the hub of the current wind turbine can be obtained, and the maximum value can be used as the flow turbulence in front of the current wind turbine.

[0099] In one implementation of the present invention, the wake model may be obtained according to the following formula (12):

[0100]

[0101] Where ΔU is the average speed loss of a single upstream wind turbine at a specified location in the wind farm, and U ∞ is the free inflow wind speed of the wind farm, C T is the thrust coefficient of a single upstream wind turbine, k is the wake expansion coefficient, d 1 is the flow distance between the specified location and a single upstream wind turbine, r 0 is the rotor radius of a single upstream wind turbine, and r is the radial distance between the specified position and the rotor center of a single upstream wind turbine.

[0102] In this embodiment, step S102 may further include the following steps:

[0103] Step S1021: using the wake model and according to the corrected wake expansion coefficient, obtaining the average speed loss of the upstream wind turbine of the current wind turbine at the location of the current wind turbine.

[0104] In this embodiment, the wake model described in formula (12) can be used to obtain the average speed loss of the upstream wind turbine of the current wind turbine at the location of the current wind turbine according to the corrected wake expansion coefficient obtained in step S101.

[0105] Step S1022: According to the average speed loss and formula (13), the superimposed speed loss at the current location of the wind turbine is obtained:

[0106]

[0107] Among them, ΔU iis the superposition velocity loss at the current location of wind turbine i; ΔU ij is the average speed loss of the jth upstream wind turbine at the current wind turbine i; q ij is a binary variable, q is valid if and only if the current wind turbine i is in the wake area generated by the jth upstream wind turbine ij =1, otherwise q ij =0; N p is the total number of wind turbines upstream of the current wind turbine in the wind farm.

[0108] In this embodiment, the superimposed speed loss at the current location of the wind turbine generator system can be obtained by applying the average speed loss obtained in step S1021 according to formula (13).

[0109] Step S1023: According to the superposition velocity loss at the current wind turbine location and in accordance with formula (14), the inflow wind speed in front of the hub of the current wind turbine under each wind condition is obtained:

[0110] U ip =U 0p -ΔU ip (14)

[0111] Among them, U 0p is the free inflow wind speed in front of the hub of the current wind turbine under the pth wind condition; U ip is the inflow wind speed in front of the hub of wind turbine i under the pth wind condition; ΔU ip is the superimposed velocity loss at the current location of wind turbine i under the pth wind condition.

[0112] In this embodiment, according to formula (14), the superposition velocity loss at the location of the front wind turbine obtained in step S1022 can be applied to obtain the inflow wind speed in front of the hub of the current wind turbine under each wind condition.

[0113] Step S1024: According to the inflow wind speed in front of the hub of the current wind turbine generator set under each wind condition and the preset power curve of the current wind turbine generator set, the output power of the current wind turbine generator set under each wind condition is obtained respectively; wherein the power curve includes the corresponding relationship between the inflow wind speed in front of the hub and the output power under each wind condition.

[0114] In this embodiment, the output power of the current wind turbine set under each wind condition may be obtained according to the inflow wind speed in front of the hub of the current wind turbine set under each wind condition and a preset power curve of the current wind turbine set.

[0115] In one implementation of the embodiment of the present invention, step S103 may further include calculating the total output power of the current wind turbine generator system under all wind conditions according to the following formula (15);

[0116]

[0117] Among them, P i is the total output power of wind turbine i under all wind conditions; f(u k ,θ l ) is the free inflow velocity u k And the wind direction angle is θ l The probability of the wind condition occurring at time u i1 The wind speed in the free inflow is u k And the wind direction angle is θ l The inflow wind speed in front of the hub of the current wind turbine i under the wind condition at time u i1 ≠u k ,Power(u i1 ) is based on the inflow wind speed u i1 The wind speed in the free inflow is u k And the wind direction angle is θ l The output power of wind turbine i at the current wind condition at time ; N θ is the total number of wind direction angles corresponding to all wind conditions; N u is the total number of free inflow wind speeds corresponding to all wind conditions, N t is the total number of wind turbines in the wind farm.

[0118] In this embodiment, the total output power of the current wind turbine under all wind conditions can be obtained according to formula (15) based on the output power corresponding to each wind condition and the probability of occurrence of each wind condition.

[0119] In one implementation of the embodiment of the present invention, step S104 may further include calculating the relative loss of the total output power of the current wind turbine generator system according to the following formula (16):

[0120]

[0121] Where wakeloss(i) is the relative loss of the total output power of wind turbine i at present, P i is the total output power of wind turbine i under all wind conditions, P 0 is the total output power of wind turbine i without considering the wake effect, P 0 It can be obtained according to the following formula (17):

[0122]

[0123] u i2 The wind speed in the free inflow is u k And the wind direction angle is θ lThe inflow wind speed in front of the hub of the current wind turbine i under the wind condition at time u i2 =u k ,Power(u i2 ) is based on the inflow wind speed u i2 The wind speed in the free inflow is u k And the wind direction angle is θ l The output power of the current wind turbine i under the wind conditions at time .

[0124] In this embodiment, the relative loss of the total output power of the current wind turbine can be obtained according to formula (17) by applying the total output power of the current wind turbine under all wind conditions and the total output power of the current wind turbine without considering the wake effect.

[0125] In one embodiment, large eddy simulation (LES) data and wind farm measured data can be used to verify the prediction results of the wind farm wake loss prediction method considering the flow turbulence of the embodiment of the present invention. Figure 2 , Attachment Figure 3 and attached Figure 7 , Figure 2 This is a schematic diagram of the Horns Rev wind farm layout; Figure 3 Schematic diagram of thrust curve and power curve of Vestas-V80 wind turbine according to an implementation of an embodiment of the present invention, wherein Figure 3 The horizontal axis is wind speed, one vertical axis is output power, and the other vertical axis is thrust coefficient; Figure 7 Schematic diagram of the arrangement of wind turbines in a wind farm according to an embodiment of the present invention. In this embodiment, the Horns Rev wind farm is selected as a test example. The specific parameters of the Horns Rev wind farm are shown in Table 1, where D is the rotor diameter of the wind turbine, z h is the hub height of the wind turbine, s x and y are the dimensionless unit spacing of wind turbines in the x and y directions, respectively.

[0126] Table 1 Specific parameters of Horns Rev wind farm

[0127] parameter D <![CDATA[z h ]]> <![CDATA[N t ]]> <![CDATA[s x ]]> <![CDATA[s y / s x ]]> HornsRev 80 70 8×10 7 1

[0128] In order to facilitate the comparison with the existing LES results in other studies and the measured power data of the wind farm, the inflow conditions of the wind farm are defined as the inflow wind speed in front of the wind turbine hub is 8m / s and the flow turbulence is 7.7%.

[0129] See attached Figure 4 , Attachment Figure 5and attached Figure 6 , Figure 4 This is a schematic diagram of the flow turbulence cloud diagram in front of the hub at 270 degrees wind down at Horns Rev wind farm based on LES results; Figure 5 It is a schematic diagram of a flow turbulence cloud diagram in front of a hub at 270 degrees wind down in a Horns Rev wind farm according to an implementation of an embodiment of the present invention; Figure 6 It is a schematic diagram comparing the turbulence prediction results in the forward direction of each row of wind turbines in the Horns Rev wind farm at a wind direction of 270 degrees with the LES results according to an implementation of an embodiment of the present invention. Figure 4 and Figure 5 The horizontal and vertical coordinates of are both normalized distances; Figure 6 The horizontal axis is the row of wind turbines in the wind farm, and the vertical axis is the flow turbulence. The curve corresponding to the proposed model is the flow turbulence in front of the wind turbine obtained by the embodiment of the present invention. According to the document "Wu YT, Porte-Agel F. Modeling turbine wakes and power losses within a wind farm using LES: An application to the Horns Rev offshore wind farm [J]. Renewable Energy, 2015, 75 (mar.): 945-955", the LES result of the turbulence cloud map of the Horns Rev wind farm is as follows: Figure 4 ,Depend on Figure 4 , Figure 5 and Figure 6 It can be seen that the predicted value of the flow turbulence in front of the wind turbine is basically consistent with the LES result, which proves the accuracy of the wind farm flow turbulence calculation method of the embodiment of the present invention.

[0130] The thrust coefficient of the wind turbine is set to 0.8, and the wake expansion coefficient of the wind turbine can be corrected according to formula (1) to obtain the corrected wake expansion coefficient. According to the coordinates of the wind turbine in the wind farm, the specific parameters in Table 1 are: Figure 3 The thrust curve and power curve of the wind turbine in the wind farm can be used to obtain the wake loss of the wind turbine in the wind farm by applying formula (11), formula (12) and formula (13). Figure 8 , Attachment Fig. 9 , Attachment Fig.10 and attached Fig.11 , Figure 8 It is a schematic diagram comparing actual observed data within a wind direction range of 270°±1° according to an implementation of an embodiment of the present invention and normalized output power obtained by a Jensen wake model, a BP wake model, and an embodiment of the present invention; Fig. 9 It is a schematic diagram comparing actual observed data within a wind direction range of 270°±5° according to an implementation of an embodiment of the present invention and normalized output power obtained by a Jensen wake model, a BP wake model, and an embodiment of the present invention; Fig.10 It is a schematic diagram comparing actual observed data within a wind direction range of 222°±1° according to an implementation of an embodiment of the present invention and normalized output power obtained by a Jensen wake model, a BP wake model, and an embodiment of the present invention; Fig.11 : is a schematic diagram comparing actual observed data within a wind direction range of 222°±5° according to an implementation of an embodiment of the present invention and normalized output power obtained by the Jensen wake model, the BP wake model, and the embodiment of the present invention; wherein Figure 8 , Fig. 9 , Fig.10 and Fig.11 The horizontal axes in the figure are the rows of wind turbines in the wind farm, and the vertical axes are the normalized power. Field measument is the normalized power obtained through actual observation, the curve corresponding to Jensen is the normalized output power obtained through the Jensen wake model, the curve corresponding to BP is the normalized output power obtained through the BP wake model, and the curve corresponding to the Proposed model is the normalized output power obtained through the embodiment of the present invention. In most previous studies, when calculating the wake loss generated by the upstream wind turbines, the wake expansion coefficient is constant. Taking the commonly used Jensen wake model and BP wake model as examples, the wake expansion coefficient is constant when the Jensen wake model and the BP wake model are used to calculate the wake loss. Figure 8 , Fig. 9 , Fig.10 and Fig.11 It can be seen from the figure that the method for predicting the wind farm wake loss taking into account the flow direction turbulence in the embodiment of the present invention can effectively predict the wind farm wake loss.

[0131] It should be pointed out that although the various steps in the above embodiments are described in a specific order, those skilled in the art can understand that in order to achieve the effects of the present invention, different steps do not have to be performed in such an order. They can be performed simultaneously (in parallel) or in other orders. These changes are within the scope of protection of the present invention.

[0132] It is understood by those skilled in the art that the present invention implements all or part of the processes in the method of the above embodiment, and can also be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable storage medium may include: any entity or device, medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory, random access memory, electric carrier signal, telecommunication signal and software distribution medium that can carry the computer program code. It should be noted that the content contained in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable storage media do not include electric carrier signals and telecommunication signals.

[0133] Furthermore, the present invention also provides a control device. In an embodiment of a control device according to the present invention, the control device includes a processor and a storage device, the storage device can be configured to store a program for executing the method for predicting the wake loss of a wind farm taking into account the flow turbulence of the above-mentioned method embodiment, and the processor can be configured to execute the program in the storage device, which includes but is not limited to executing the method for predicting the wake loss of a wind farm taking into account the flow turbulence of the above-mentioned method embodiment. For ease of explanation, only the parts related to the embodiment of the present invention are shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present invention. The control device can be a control device device formed by various electronic devices.

[0134] Furthermore, the present invention also provides a computer-readable storage medium. In a computer-readable storage medium embodiment according to the present invention, the computer-readable storage medium can be configured to store a program for executing the above-mentioned method embodiment of the method for predicting the wake loss of a wind farm considering the flow turbulence, and the program can be loaded and run by the processor to implement the above-mentioned method for predicting the wake loss of a wind farm considering the flow turbulence. For ease of explanation, only the parts related to the embodiment of the present invention are shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present invention. The computer-readable storage medium can be a storage device formed by various electronic devices. Optionally, the computer-readable storage medium in the embodiment of the present invention is a non-temporary computer-readable storage medium.

[0135] Further, it should be understood that since the setting of each module is only for illustrating the functional units of the device of the present invention, the physical devices corresponding to these modules may be the processor itself, or a part of the software in the processor, a part of the hardware, or a part of the combination of software and hardware. Therefore, the number of each module in the figure is only schematic.

[0136] Those skilled in the art will appreciate that the modules in the device can be adaptively split or merged. Such splitting or merging of specific modules will not cause the technical solution to deviate from the principle of the present invention, and therefore, the technical solutions after splitting or merging will fall within the protection scope of the present invention.

[0137] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, 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 fall within the protection scope of the present invention.

Claims

1. A method for predicting wind farm wake losses considering flow turbulence, characterized in that: The prediction method comprises: For each wind turbine in the wind farm, according to the flow turbulence in front of the current wind turbine under each wind condition, the wake expansion coefficient of the current wind turbine is corrected to obtain the corrected wake expansion coefficient corresponding to each wind condition; Using a preset wake model and according to the corrected wake expansion coefficient, the inflow wind speed in front of the hub of the current wind turbine generator set under each wind condition is obtained; and according to the inflow wind speed, the output power of the current wind turbine generator set under each wind condition is obtained respectively; According to the output power corresponding to each wind condition and the probability of occurrence of each wind condition, the total output power of the current wind turbine generator set under all wind conditions is obtained; According to the total output power of the current wind turbine generator set under all wind conditions and the total output power of the current wind turbine generator set without considering the wake effect, a relative loss of the total output power of the current wind turbine generator set is obtained, and the wake loss of the wind farm is predicted according to the relative loss; The total output power without considering the wake effect refers to the total output power of the current wind turbine under all wind conditions when the inflow wind speed in front of the hub of the current wind turbine is the free inflow wind speed; The step of "correcting the wake expansion coefficient of the current wind turbine according to the flow turbulence degree in front of the current wind turbine under each wind condition to obtain the corrected wake expansion coefficient corresponding to each wind condition" includes correcting the wake expansion coefficient according to the following formula to obtain the corrected wake expansion coefficient: k wi =2×(0.3837×I i +0.003678) Among them, k wi is the corrected wake expansion coefficient, I i is the flow turbulence in front of the current wind turbine i; The wake model is obtained according to the following formula: Where ΔU is the average speed loss of a single upstream wind turbine at a specified location in the wind farm, and U ∞ is the free inflow wind speed of the wind farm, C T is the thrust coefficient of the single upstream wind turbine, k is the wake expansion coefficient, d1 is the flow distance between the designated position and the single upstream wind turbine, r0 is the rotor radius of the single upstream wind turbine, and r is the radial distance between the designated position and the rotor center of the single upstream wind turbine; The step of "using a preset wake model and according to the corrected wake expansion coefficient to obtain the inflow wind speed in front of the hub of the current wind turbine under each wind condition; and obtaining the output power of the current wind turbine under each wind condition according to the inflow wind speed" includes: Using the wake model and according to the corrected wake expansion coefficient, obtaining, when the designated position is the position of the current wind turbine generator set, an average speed loss of the upstream wind turbine generator set of the current wind turbine generator set at the position of the current wind turbine generator set; According to the average speed loss and the method described in the following formula, the superimposed speed loss at the current location of the wind turbine generator set is obtained: Among them, ΔU i is the superposition velocity loss at the current location of wind turbine i; ΔU ij is the average speed loss of the jth upstream wind turbine at the current wind turbine i; q ij is a binary variable, q is valid if and only if the current wind turbine i is in the wake area generated by the jth upstream wind turbine ij =1, otherwise q ij =0; N p is the total number of wind turbines upstream of the current wind turbine in the wind farm; According to the superposition velocity loss at the location of the current wind turbine generator set and the method described in the following formula, the inflow wind speed in front of the hub of the current wind turbine generator set under each wind condition is obtained: U ip =U 0p -ΔU ip, Among them, U 0p is the free inflow wind speed in front of the hub of the current wind turbine under the pth wind condition; U ip is the inflow wind speed in front of the hub of wind turbine i under the pth wind condition; ΔU ip is the superposition velocity loss at the current location of wind turbine i under the pth wind condition; According to the inflow wind speed in front of the hub of the current wind turbine generator set in each wind condition and the preset power curve of the current wind turbine generator set, the output power of the current wind turbine generator set in each wind condition is respectively obtained; wherein the power curve includes the corresponding relationship between the inflow wind speed in front of the hub and the output power in each wind condition; The step of "obtaining the total output power of the current wind turbine generator set under all wind conditions according to the output power corresponding to each wind condition and the probability of occurrence of each wind condition" includes obtaining the total output power of the current wind turbine generator set under all wind conditions according to the method described in the following formula: Among them, P i is the total output power of wind turbine i under all wind conditions; f(u k ,θ l ) is the free inflow velocity u k And the wind direction angle is θ l The probability of the wind condition occurring at time u i1 The wind speed in the free inflow is u k And the wind direction angle is θ l The inflow wind speed in front of the hub of the current wind turbine i under the wind condition at time u i1 ≠u k ,Power(u i1 ) is based on the inflow wind speed u i1 The obtained free inflow wind speed is u k And the wind direction angle is θ l The output power of wind turbine i at the current wind condition at time ; N θ is the total number of wind direction angles corresponding to all wind conditions; N u is the total number of free inflow wind speeds corresponding to all wind conditions, N t is the total number of wind turbines in the wind farm; The step of "obtaining the relative loss of the total output power of the current wind turbine generator set according to the total output power of the current wind turbine generator set under all wind conditions and the total output power of the current wind turbine generator set without considering the wake effect" includes obtaining the relative loss of the total output power of the current wind turbine generator set according to the following formula: Where wakeloss(i) is the relative loss of the total output power of wind turbine i at present, P i is the total output power of the current wind turbine i under all wind conditions, and P0 is the total output power of the current wind turbine i without considering the wake effect. P0 is obtained according to the following formula: u i2 The wind speed in the free inflow is u k And the wind direction angle is θ l The inflow wind speed in front of the hub of the current wind turbine i under the wind condition at time u i2 =u k ,Power(u i2 ) is based on the inflow wind speed u i2 The obtained free inflow wind speed is u k And the wind direction angle is θ l The output power of the current wind turbine i under the wind conditions at time .

2. The method for predicting wind farm wake loss considering flow turbulence according to claim 1, characterized in that: The method further comprises calculating the flow turbulence degree in front of the current wind turbine generator set according to the following steps: According to the additional flow turbulence generated by the upstream wind turbine at any position of the wind farm and the method described in the following formula, the additional flow turbulence at any position of the wind farm is obtained: in, The wind direction angle is θ l When , the additional streamwise turbulence at the position (x, y, z) in the wind farm; ΔIu m (x, y, z) is the additional flow turbulence generated by the mth upstream wind turbine at the position (x, y, z); N is the total number of upstream wind turbines at the position (x, y, z) in the wind farm; According to the additional flow turbulence at the location of the current wind turbine and any location of the wind farm and in accordance with the method described below, the point flow turbulence at multiple points in front of the hub of the current wind turbine is obtained: in, The wind direction angle is θ l When the current wind turbine i hub front (x i ,y i , z i ) is the point flow turbulence of the point; I0 ​​is the atmospheric turbulence in front of the hub of the current wind turbine; According to the flow turbulence at multiple points in front of the hub of the current wind turbine generator set, the maximum value of the point flow turbulence among the point flow turbulence at the multiple points is obtained as the flow turbulence in front of the current wind turbine generator set.

3. A control device, comprising a processor and a storage device, wherein the storage device is suitable for storing a plurality of program codes, characterized in that: The program code is suitable for being loaded and run by the processor to execute the method for predicting wind farm wake loss considering streamwise turbulence according to any one of claims 1 to 2.

4. A computer-readable storage medium storing a plurality of program codes, characterized in that: The program code is suitable for being loaded and run by a processor to execute the method for predicting wind farm wake losses considering streamwise turbulence according to any one of claims 1 to 2.

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