Wake flow wind speed calculation method, system and device, storage medium and program product
By using the calculation method of equivalent roughness and internal boundary layer height, the problem of inaccurate wake prediction in large-scale dense wind farms by existing wake models is solved, and accurate calculation of wake wind speed and accurate prediction of power generation loss in large-scale wind farms are realized.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-12
- Publication Date
- 2026-04-03
AI Technical Summary
Existing wake models cannot accurately depict the complex mechanism of wake superposition and interaction between the ambient wind field in large-scale dense wind farms, resulting in a large deviation between the wake impact and the predicted power generation loss, which is difficult to meet the actual engineering needs.
By equating the layout of wind turbine clusters to a regular arrangement, the equivalent roughness and the height of the internal boundary layer of the wind field boundary are calculated. Combined with coordinate transformation, the wake wind speed is accurately calculated, taking into account the interaction between the atmosphere and the wind turbines.
It enables accurate calculation of wake wind speed in large-scale wind farms, improves calculation efficiency, and can more accurately predict power generation loss. It is applicable to wind turbine clusters of various sizes, especially large-scale wind turbine clusters.
Smart Images
Figure CN121787313A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of wind power generation technology, and in particular to a method, system, device, storage medium, and program product for calculating wake wind speed. Background Technology
[0002] In the actual operation of wind farms, the spatial distribution of wind resources and airflow characteristics directly affect power generation efficiency, while the wake effect is one of the core factors restricting the overall performance of the wind farm. From the perspective of wake propagation characteristics, onshore wind farms are affected by factors such as terrain friction and atmospheric turbulence, resulting in a faster wake attenuation rate. The wake propagation distance is generally as far as 20-50 times the rotor diameter before the wake wind speed can recover to a level close to the upwind wind speed. However, offshore wind farms have low sea surface roughness and strong atmospheric stability. Even after the wake propagation distance exceeds 100 times the rotor diameter, the wake wind speed is still lower than the upwind wind speed.
[0003] As wind power development moves towards large-scale and intensive operations, wind turbine layouts within wind farms are becoming increasingly compact, with the spacing between turbines constantly shrinking, in order to maximize the utilization of high-quality wind resources. While this layout improves the utilization rate of wind resources per unit area, it also exacerbates the wake superposition effect. The wake generated by upstream wind turbines is transmitted step by step through multiple turbines, causing downstream turbine locations to face multiple wake superposition effects.
[0004] Wake models are key tools for wind farm design, planning, operation optimization, and power generation prediction. However, existing mainstream wake models have significant limitations: their core assumption is that "the wind turbine only forms a local wind speed reduction zone within a limited downstream distance, and does not affect the global environmental wind field characteristics." This simplified assumption is suitable for wake assessment of small, sparsely distributed wind farms, but it cannot accurately depict the complex mechanism of wake superposition and environmental wind field interaction in large, dense wind farms. This results in a large deviation between the wake impact and power generation loss prediction for large-scale wind farms, making it difficult to meet the needs of actual engineering projects. Summary of the Invention
[0005] The technical problem to be solved by this disclosure is to overcome the above-mentioned defects in the prior art and provide a wake wind speed calculation method, system, device, storage medium, and program product.
[0006] This disclosure solves the above-mentioned technical problems through the following technical solution: This invention
[0007] Firstly, a method for calculating wake wind speed is provided, including:
[0008] S101. The layout of the wind turbine group is equivalent to a regular arrangement, and the equivalent roughness of the environment in which the wind turbine group is located is determined according to the layout parameters of the regular arrangement.
[0009] S102. Transform the coordinates of each inflection point contained in the wind field boundary to the first local coordinate system of the target wind turbine contained in the wind turbine group, and determine the distance between the target wind turbine and the wind field boundary in the wind direction based on the coordinates of the inflection points in the first local coordinate system; wherein, the first local coordinate system takes the target wind turbine as the origin and the wind direction as the reference direction; all wind turbines contained in the wind turbine group are within the range enclosed by the wind field boundary;
[0010] S103. Determine the height of the internal boundary layer of the wind field boundary based on the equivalent roughness and the distance;
[0011] S104. Calculate the first wake speed of the target wind turbine in the wind direction based on the hub height of the target wind turbine and the height of the internal boundary layer.
[0012] Optionally, the layout parameters include: the arrangement density of the wind turbine cluster; the equivalent roughness is calculated using the following formula:
[0013] (1)
[0014] (2)
[0015] in, It is the distributed thrust coefficient of the wind turbine cluster. It is the thrust coefficient of the target wind turbine. It is the Kármán constant. It is environmental roughness. D is the average hub height of the wind turbines included in the wind turbine cluster, and D is the arrangement density. It is the equivalent roughness.
[0016] Optionally, the layout of the wind turbine cluster can be equivalent to a regular square arrangement. The calculation formula is as follows:
[0017] (3)
[0018] in, It is the area enclosed by the boundary of the wind field. It is the diameter of the rotor of the target wind turbine. This refers to the number of wind turbines included in the wind turbine cluster. It is the first average spacing between wind turbines along the wind direction. It is the second average spacing between wind turbines along the direction perpendicular to the wind direction.
[0019] Optionally, the coordinates of each inflection point contained in the wind field boundary are transformed to the first local coordinate system of the target wind turbine, including:
[0020] A second local coordinate system is established with the target wind turbine as the origin and the horizontal direction as the reference direction. The coordinates of each inflection point contained in the wind field boundary in the second local coordinate system are obtained.
[0021] The second local coordinate system is rotated by a preset angle θ so that the X-axis of the second local coordinate system is parallel or perpendicular to the wind direction, thus obtaining the first local coordinate system;
[0022] Obtain the coordinates of each inflection point in the first local coordinate system.
[0023] Optionally, determining the distance between the target wind turbine and the wind field boundary in the wind direction based on the coordinates of the inflection point in the first local coordinate system includes:
[0024] Select two adjacent target inflection points that meet preset conditions from the inflection points in the first local coordinate system; wherein, the preset conditions include that the x-coordinates of the two target inflection points are one greater than zero and the other less than zero, and that the y-coordinates of the two target inflection points are at least one greater than zero;
[0025] The intercept of the straight line containing the two target inflection points in the first local coordinate system is determined as the distance between the target wind turbine and the wind field boundary in the wind direction.
[0026] Optionally, in response to the fact that the number of target inflection points is greater than two, the minimum intercept among the intercepts corresponding to any two adjacent target inflection points is determined as the distance of the wind field boundary;
[0027] Alternatively, in response to the number of target inflection points that meet the preset conditions being less than two, the wind field boundary is redrawn and the process returns to S102.
[0028] Optionally, S103 includes:
[0029] F in the following formula is solved using an iterative method:
[0030] (4)
[0031] The height of the inner boundary layer is calculated based on the solution for F and the following formula:
[0032] (5)
[0033] in, It is the height of the inner boundary layer. It is the equivalent roughness. It is the distance mentioned above;
[0034] The first wake velocity is calculated using the following formula:
[0035] (6)
[0036] (7)
[0037] (8)
[0038] in, It is the hub height of the target wind turbine. It is the lowest height within the wind field boundary affected by the wind field wake. It is the height of the first inner boundary layer. It is the height of the second inner boundary layer. This is the wind speed at the target wind turbine without considering the wake effect.
[0039] Optionally, following S101, it also includes:
[0040] Determine whether the equivalent roughness is greater than the environmental roughness;
[0041] In response to the equivalent roughness being greater than the environmental roughness, S102 is executed;
[0042] In response to the equivalent roughness being less than or equal to the environmental roughness, the second wake wind speed of the target wind turbine in the wind direction is calculated using the Jensen wake model.
[0043] Optionally, it also includes:
[0044] The Jensen wake model was used to calculate the second wake speed of the target wind turbine in the wind direction.
[0045] The minimum value between the first wake velocity and the second wake velocity is determined as the final wake velocity of the target wind turbine in the wind direction.
[0046] Secondly, a wake velocity calculation system is provided, including:
[0047] The roughness determination module is used to convert the layout of the wind turbine group into a regular arrangement and determine the equivalent roughness of the environment in which the wind turbine group is located based on the layout parameters of the regular arrangement.
[0048] The distance determination module is used to transform the coordinates of each inflection point contained in the wind field boundary to the first local coordinate system of the target wind turbine contained in the wind turbine group, and to determine the distance between the target wind turbine and the wind field boundary in the wind direction based on the coordinates of the inflection points in the first local coordinate system; wherein, the first local coordinate system takes the target wind turbine as the origin and the wind direction as the reference direction; and all wind turbines contained in the wind turbine group are within the range defined by the wind field boundary.
[0049] A height determination module is used to determine the height of the inner boundary layer of the wind field boundary based on the equivalent roughness and the distance.
[0050] The wake speed determination module is used to calculate the first wake speed of the target wind turbine in the wind direction based on the hub height of the target wind turbine and the height of the internal boundary layer.
[0051] Thirdly, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and used to run on the processor, wherein the processor executes the computer program to implement the wake wind speed calculation method described in any one of the first aspects.
[0052] Fourthly, a computer-readable storage medium is provided, on which a computer program is stored, wherein when the computer program is executed by a processor, it implements the wake wind speed calculation method described in any one of the first aspects.
[0053] Fifthly, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the wake wind speed calculation method as described in any one of the first aspects.
[0054] Based on common knowledge in the field, the above-mentioned preferred conditions can be combined arbitrarily to obtain various preferred embodiments of this disclosure.
[0055] The positive and progressive effects of this disclosure are as follows: When calculating the wake wind speed of the target wind turbine, this disclosure considers the interaction between the atmosphere and the wind turbine, that is, it introduces the height and equivalent roughness of the internal boundary layer of the wind field boundary, which can realize the accurate calculation of the wake wind speed of wind turbines in large-scale wind farms. Furthermore, by calculating the equivalent roughness through layout equivalence and by calculating the distance between the wind turbine and the wind field boundary in the wind direction through coordinate transformation, the efficiency of calculating the wake wind speed can be greatly improved. Attached Figure Description
[0056] Figure 1a A schematic diagram of a free airflow passing through an internal boundary layer formed by a large-scale wind turbine group, provided as an exemplary embodiment of this disclosure;
[0057] Figure 1b A schematic diagram illustrating an application scenario of a wake loss calculation method provided by existing technology;
[0058] Figure 2 A flowchart illustrating a wake velocity calculation method provided as an exemplary embodiment of this disclosure;
[0059] Figure 3 A flowchart of another wake velocity calculation method provided for an exemplary embodiment of this disclosure;
[0060] Figure 4a A schematic diagram illustrating an application scenario of a wake velocity calculation method provided in an exemplary embodiment of this disclosure;
[0061] Figure 4b This diagram illustrates the correspondence between the relative wake loss determined using the traditional Jensen wake model combined with the square sum wake superposition scheme and SCADA measured data.
[0062] Figure 4c A schematic diagram illustrating the correspondence between the capacity factor and SCADA measured data when using the traditional Jensen wake model combined with the square sum wake superposition scheme;
[0063] Figure 4d A schematic diagram showing the comparison between the capacity coefficients of each machine location determined using the traditional Jensen wake model combined with the square sum wake superposition scheme and the SCADA measured data.
[0064] Figure 4e A schematic diagram illustrating the correspondence between relative wake loss and SCADA measured data, based on the calculation results (first wake wind speed of the wind turbine) obtained using the method provided in this embodiment of the disclosure.
[0065] Figure 4f A schematic diagram illustrating the correspondence between the capacity factor and SCADA measured data determined by the calculation results (first wake wind speed of the wind turbine) using the method provided in this embodiment of the disclosure;
[0066] Figure 4g A schematic diagram showing the comparison between the calculation results (first wake wind speed of the wind turbine) of each turbine location determined by the method provided in this embodiment and the actual SCADA data;
[0067] Figure 4h A schematic diagram illustrating the correspondence between relative wake loss and SCADA measured data, based on the calculation results (final wake wind speed of the wind turbine) obtained using the method provided in this embodiment of the disclosure.
[0068] Figure 4i A schematic diagram illustrating the correspondence between the capacity factor and SCADA measured data determined by the calculation results (final wake wind speed of the wind turbine) using the method provided in this embodiment of the disclosure;
[0069] Figure 4j A schematic diagram showing the comparison between the calculation results (final wake wind speed of the wind turbine) of each turbine location determined by the method provided in this embodiment and the actual SCADA measurement data;
[0070] Figure 5 A schematic diagram of a wake velocity calculation system provided as an exemplary embodiment of this disclosure;
[0071] Figure 6 This is a schematic diagram of the structure of an electronic device provided as an exemplary embodiment of the present disclosure. Detailed Implementation
[0072] The present disclosure is further illustrated below by way of embodiments, but the present disclosure is not limited to the scope of the embodiments described herein.
[0073] The prefixes such as "first" and "second" used in this disclosure are merely for distinguishing different descriptive objects and do not limit the position, order, priority, quantity, or content of the described objects. The use of ordinal numbers and other prefixes used to distinguish descriptive objects in this disclosure does not constitute a limitation on the described objects. The description of the described objects is given in the claims or the context of the embodiments, and should not be construed as an unnecessary limitation. Furthermore, in the description of this embodiment, unless otherwise stated, "multiple" means two or more.
[0074] Studies have shown that large-scale wind turbine deployments interact significantly with ambient winds, altering surface roughness and the wind profile of the planetary boundary layer. For example... Figure 1a As shown, when airflow passes over the leading edge of a large array of wind turbines, an internal boundary layer is formed. This internal boundary layer is further divided into an inner layer and an outer layer based on the material flow process of the internal airflow adjustment. The inner layer is close to the ground surface, and due to changes in surface roughness, the wind profile differs significantly from the original airflow profile. The outer layer, located above the inner layer and extending to the top of the internal boundary layer, is also known as the transition layer. In this layer, the wind profile transitions to the original airflow profile, and at the top of the internal boundary layer, the wind speed is equal to the original airflow speed at the same height.
[0075] The core assumption of traditional wake models is that the wind turbine and the ambient wind do not interfere with each other, and the wake wind speed is calculated based on this assumption. Figure 1b This demonstrates a calculation method for a traditional wake model, which mathematically superimposes the wake effects of multiple upstream wind turbines, i.e., the total loss of wind turbine C is... The core principle of this calculation method is that, based on the isotropic nature of turbulent energy dissipation, the kinetic energy loss (turbulent kinetic energy increment) of the incoming wind after passing through the wind turbine is linearly superimposed.
[0076] However, the above assumptions contradict the actual operating conditions of large-scale wind turbine clusters, making it difficult for traditional wake models to accurately describe the wake evolution of large-scale wind turbine clusters. Consequently, it is difficult to reliably assess the wake impact and power generation loss of large-scale wind power projects, thus severely limiting their applicability in large-scale wind power scenarios.
[0077] Based on this, the present disclosure provides a method for calculating wake wind speed, which is applicable to the calculation of wake wind speed of wind turbine groups of various sizes, and is especially applicable to the calculation of wake wind speed of large-scale wind turbine groups.
[0078] Figure 2 A flowchart of a wake velocity calculation method provided for an exemplary embodiment of this disclosure is included, comprising the following steps:
[0079] Step 101: Equivalently arrange the layout of the wind turbine cluster to a regular arrangement, and determine the equivalent roughness of the environment in which the wind turbine cluster is located based on the layout parameters of the regular arrangement.
[0080] In step 101, the layout of the wind turbine cluster can be equivalent to a regular square arrangement, a regular rectangular arrangement, or a regular circular arrangement. The layout parameters include at least one of the following: the arrangement density of the wind turbine cluster, the first average spacing between wind turbines along the wind direction, and the second average spacing between wind turbines along the direction perpendicular to the wind direction.
[0081] Step 102: Transform the coordinates of each inflection point contained in the wind field boundary to the first local coordinate system of the target wind turbine contained in the wind turbine group, and determine the distance between the target wind turbine and the wind field boundary in the wind direction based on the coordinates of the inflection points in the first local coordinate system.
[0082] In this context, the target wind turbine refers to any wind turbine in the wind turbine group whose wake speed needs to be calculated using the method described in this embodiment. The target wind turbine can be any one of the wind turbines in the wind turbine group. The first local coordinate system has the target wind turbine as its origin and the wind direction as its reference direction; all wind turbines in the wind turbine group are located within the area defined by the wind field boundary.
[0083] The wind field boundary is defined / drawn by the user. It should be noted that the wind field boundary must be continuous and without intersections, and should be close to the edge wind turbines of the wind turbine cluster to avoid overestimating the wake effect of the edge turbines. Assume the wind field boundary has a total of... There are several inflection points, and the spatial coordinates of each inflection point are denoted as follows: , , ...,
[0084] In step 102, the inflection point coordinate transformation is performed to facilitate the calculation of the distance between the wind turbine and the wind field boundary in the wind direction, thereby improving the calculation efficiency of the wake wind speed.
[0085] Step 103: Determine the height of the internal boundary layer of the wind field boundary based on the equivalent roughness and distance.
[0086] Step 104: Calculate the first wake speed of the target wind turbine in the wind direction based on the hub height and the height of the internal boundary layer.
[0087] This disclosure considers the interaction between the atmosphere and the wind turbine when calculating the wake wind speed, that is, it introduces the height and equivalent roughness of the internal boundary layer of the wind field boundary, which can realize the accurate calculation of the wake wind speed of wind turbines in large-scale wind farms. Furthermore, by calculating the equivalent roughness through layout equivalence and by calculating the distance between the wind turbine and the wind field boundary in the wind direction through coordinate transformation, the efficiency of calculating the wake wind speed can be greatly improved.
[0088] In one embodiment, the equivalent roughness is calculated using the following formula:
[0089] (1)
[0090] (2)
[0091] in, It is the distributed thrust coefficient of the wind turbine cluster. It is the thrust coefficient of the target wind turbine. It is the Kármán constant. It is environmental roughness. It is the average hub height of the wind turbines included in the wind turbine cluster. It is the arrangement density. It is the equivalent roughness.
[0092] In this embodiment, the change in environmental roughness caused by the wind turbine group is calculated based on the equivalent roughness formula.
[0093] In one embodiment, the layout of the wind turbine cluster is equivalent to a regular square arrangement. The calculation formula is as follows:
[0094] (3)
[0095] in, It is the area enclosed by the boundary of the wind field. It is the diameter of the rotor of the target wind turbine. It refers to the number of wind turbines included in a wind turbine cluster. It is the first average spacing between wind turbines along the wind direction. It is the second average spacing between wind turbines along the direction perpendicular to the wind direction.
[0096] For wind turbine clusters arranged in a regular pattern and It's more intuitive, but for irregularly arranged wind turbine clusters, different wind directions... and The calculation method is complex. In this embodiment, the irregularly arranged wind turbine cluster is equivalent to a regularly arranged one, which can significantly improve the calculation efficiency.
[0097] In one embodiment, step 102, which involves transforming the coordinates of each inflection point contained in the wind field boundary to the first local coordinate system of the target wind turbine, includes:
[0098] Step 102-1: Establish a second local coordinate system with the target wind turbine as the origin and the horizontal direction as the reference direction, and obtain the coordinates of each inflection point contained in the wind field boundary in the second local coordinate system.
[0099] In one implementation, the X-axis of the second local coordinate system is parallel to the horizontal direction. In another implementation, the Y-axis of the second local coordinate system is parallel to the horizontal direction.
[0100] Preferably, the X-axis of the second local coordinate system is parallel to the horizontal direction. Assume that for any wind turbine in the wind turbine cluster... The coordinates are The coordinates of each inflection point in this second local coordinate system are: , , ..., ,in , ( ).
[0101] Step 102-2: Rotate the second local coordinate system by a preset angle θ so that the X-axis of the second local coordinate system is parallel or perpendicular to the wind direction, thus obtaining the first local coordinate system.
[0102] Step 102-3: Obtain the coordinates of each inflection point in the first local coordinate system.
[0103] Preferably, the first local coordinate system has the target wind turbine as its origin, and its X-axis is parallel to the wind direction. The coordinates of each inflection point in this first local coordinate system are: , , ..., ,in , , .
[0104] In this embodiment, two coordinate transformations are performed to facilitate the subsequent determination of the distance between the target wind turbine and the wind field boundary in the wind direction based on the coordinates of the inflection point.
[0105] In one embodiment, step 102, determining the distance between the target wind turbine and the wind field boundary in the wind direction based on the coordinates of the inflection point in the first local coordinate system, includes:
[0106] Step 102-4: Select two adjacent target inflection points that meet the preset conditions from the inflection points in the first local coordinate system.
[0107] The preset conditions include that the x-coordinates of the two target inflection points are one greater than zero and the other less than zero, and that the y-coordinates of the two target inflection points are at least one greater than zero.
[0108] In step 102-4, traverse all the inflection points of the wind field boundary, find two consecutive inflection points in the first local coordinate system, and calculate the x-coordinates of these two inflection points. and The values must be one positive and one negative, and the ordinates of these two inflection points must be... and At least one of them has a value greater than 0.
[0109] If two target inflection points are not found, it indicates that the wind turbine... Outside the defined wind field boundary, the wind field boundary needs to be redrawn, and the process should return to step 102 to recalculate the wake wind speed of the target wind turbine using the newly drawn wind field boundary.
[0110] If the number of target inflection points is greater than two, the minimum intercept among any two adjacent target inflection points is the wind turbine. In a certain wind direction Distance from the wind field boundary It should be noted that the intercept represents distance, therefore the intercept must be greater than 0. If the intercept is less than 0, it indicates that the target inflection point is unsuitable and needs to be redefined.
[0111] Step 102-5: Determine the intercept of the straight line containing the two target inflection points in the first local coordinate system as the distance between the target wind turbine and the wind field boundary in the wind direction.
[0112] If the first local coordinate system has the target wind turbine as its origin and its X-axis is parallel to the wind direction, then the Y-intercept of the first local coordinate system is determined as the distance between the target wind turbine and the wind field boundary in the wind direction. If the first local coordinate system has the target wind turbine as its origin and its Y-axis is parallel to the wind direction, then the X-intercept of the first local coordinate system is determined as the distance between the target wind turbine and the wind field boundary in the wind direction.
[0113] In one embodiment, according to the formula Calculate the height of the internal boundary layer .
[0114] Divide both sides by , .
[0115] set up Then there is For any wind turbine In the direction of the incoming wind superior It is a constant greater than zero, therefore It must be greater than zero.
[0116] Therefore, F in formula (4) is solved by iterative method:
[0117] (4)
[0118] Then, based on the solution of F and formula (5), the height of the internal boundary layer can be calculated:
[0119] (5)
[0120] in, It is the height of the internal boundary layer. It is the equivalent roughness. It is the distance from the wind field boundary.
[0121] After obtaining the height of the internal boundary layer, the first wake velocity is calculated according to formula (6):
[0122] (6)
[0123] (7)
[0124] (8)
[0125] in, It is the hub height of the target wind turbine. It is the lowest height within the wind field boundary affected by the wind field wake. It is the height of the first inner boundary layer. It is the height of the second internal boundary layer (corresponding to the transition zone). This is the wind speed at the target wind turbine without considering the wake effect.
[0126] In one embodiment, see Figure 3 After step 101, the method also includes: determining whether the equivalent roughness is greater than the environmental roughness.
[0127] In response to the equivalent roughness being greater than the environmental roughness, step 102 is executed.
[0128] In response to the equivalent roughness being less than or equal to the environmental roughness, step 105 is executed.
[0129] Step 105: Calculate the second wake wind speed of the target wind turbine in the wind direction using the Jensen wake model.
[0130] Environmental roughness refers to the surface roughness without wind turbine clusters, and is an aerodynamic parameter that quantifies the surface's obstruction of near-surface wind speed. Equivalent roughness is the combined roughness resulting from the aerodynamic obstruction effect of the wind turbine cluster and the natural surface friction effect when wind turbine clusters are present. Theoretically, the aerodynamic obstruction effect of the wind turbine clusters is superimposed on the surface frictional resistance, leading to an equivalent roughness greater than the environmental roughness. This is the applicable premise for steps 102-104 (core steps of wake calculation) in this embodiment. If the equivalent roughness is less than or equal to the environmental roughness, it indicates that the airflow characteristics in this scenario contradict the applicable premise of steps 102-104, and the Jensen wake model is used instead to calculate the wake wind speed of the wind turbines.
[0131] In one embodiment, the first wake wind speed calculated in step 104 is determined as the wake wind speed of the target wind turbine.
[0132] In one embodiment, the method further includes step 106.
[0133] Step 106: Calculate the second wake speed of the wind turbine in the wind direction using the Jensen wake model.
[0134] Step 107: Determine the minimum value between the first wake wind speed and the second wake wind speed as the final wake wind speed of the wind turbine in the wind direction.
[0135] Wind speed attenuation in wind turbines can be influenced by both "direct wake superposition" and "boundary layer disturbances," but these two types of losses are not simply linearly superimposed (e.g., the direct loss in the wake core region dominates wind speed attenuation, while the additional loss from boundary layer disturbances is relatively small; or vice versa). Determining the minimum of the first and second wake wind speeds as the final wake wind speed of the wind turbine in the wind direction ensures that the final wind speed loss information covers the most severe attenuation scenarios under both mechanisms, thus ensuring the validity of the calculation results.
[0136] The following is based on Figure 4a Taking the wind turbine cluster shown as an example, the method provided in this disclosure and the traditional wake model are evaluated in terms of both the accuracy of wake wind speed attenuation calculation and power generation.
[0137] Figure 4a The wind farm in the area is trapezoidal in shape, with a distance of approximately 11 km parallel to the coastline and an average distance of approximately 11 km perpendicular to the coastline. The planned sea area is 120 km². 2 The wind farm has an installed capacity of 400MW, including 100 offshore wind turbines. Based on actual SCADA operating data (10 minutes) of this wind farm, the results are compared with those calculated using the method provided in this embodiment and a traditional wake model.
[0138] See Figures 4b-4dWhen using only the traditional Jensen wake model combined with a sum-of-squares wake overlay scheme for calculation, it cannot accurately predict the actual capacity coefficient trend of each wind turbine site. It underestimates the power generation of turbines located near the wind farm (such as turbine T37) and overestimates the power generation of turbines within the wind farm that are more severely affected by the wake. The correlation R for relative wake loss is approximately 0.83, and the correlation R for capacity coefficient is approximately 0.84.
[0139] See Figures 4e-4g When the method provided in this embodiment is used to calculate the first wake wind speed of the wind turbine, it can better simulate the actual trend of the capacity coefficient at each turbine location. The power generation of turbine locations located inside the wind farm is significantly lower than that of turbine locations located on the periphery. At this time, the correlation R of the relative wake loss is approximately 0.8, and the correlation R of the capacity coefficient is approximately 0.88. Although the correlation of the relative wake loss calculated using the method provided in this embodiment is lower than that of the traditional model, the correlation of the capacity coefficient is relatively high. Overall, the method provided in this embodiment is more advantageous for predicting power generation.
[0140] See Figures 4h-4j When the final wake wind speed of the wind turbine is calculated using the method provided in this embodiment, the distribution trend of the capacity coefficient of each turbine site can be simulated more accurately. At this time, the correlation R of the relative wake loss is about 0.86, while the correlation R of the capacity coefficient is as high as 0.93, which can already predict the power generation characteristics of all turbine sites well.
[0141] Figure 4b , Figure 4e , Figure 4h The large dots represent the correspondence between the measured wake loss of a certain wind turbine location and the model result, while the small dots are the linear fitting results of the large dots. Figure 4c , Figure 4f , Figure 4i The large dots represent the correspondence between the measured and model results of the capacity coefficient of a certain wind turbine location, while the small dots represent the linear fitting results of the large dots.
[0142] Corresponding to the aforementioned examples of wake velocity calculation methods, this disclosure also provides examples of wake velocity calculation system methods.
[0143] Figure 5 This is a schematic diagram of a wake velocity calculation system provided in an exemplary embodiment of the present disclosure. The wake velocity calculation system is used to implement the wake velocity calculation method provided in any of the above embodiments. The system includes:
[0144] Roughness determination module 51 is used to convert the layout of the wind turbine group into a regular arrangement and determine the equivalent roughness of the environment in which the wind turbine group is located based on the layout parameters of the regular arrangement.
[0145] The distance determination module 52 is used to transform the coordinates of each inflection point contained in the wind field boundary to the first local coordinate system of the target wind turbine contained in the wind turbine group, and to determine the distance between the target wind turbine and the wind field boundary in the wind direction based on the coordinates of the inflection points in the first local coordinate system; wherein, the first local coordinate system takes the target wind turbine as the origin and the wind direction as the reference direction; and all wind turbines contained in the wind turbine group are within the range defined by the wind field boundary.
[0146] The height determination module 53 is used to determine the height of the inner boundary layer of the wind field boundary based on the equivalent roughness and the distance.
[0147] The wake speed determination module 54 is used to calculate the first wake speed of the target wind turbine in the wind direction based on the hub height of the target wind turbine and the height of the internal boundary layer.
[0148] For the system embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this disclosure according to actual needs.
[0149] Figure 6 This is a schematic diagram of the structure of an electronic device according to an example embodiment of the present disclosure. The electronic device includes a memory, a processor, and a computer program stored in the memory and used to run on the processor. When the processor executes the computer program, it implements the wake wind speed calculation method described in any of the above embodiments. Figure 6 The electronic device 60 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.
[0150] like Figure 6 As shown, the electronic device 60 can be manifested as a general-purpose computing device, such as a server device. The components of the electronic device 60 may include, but are not limited to: at least one processor 61, at least one memory 62, and a bus 63 connecting different system components (including memory 62 and processor 61).
[0151] Bus 63 includes a data bus, an address bus, and a control bus.
[0152] The memory 62 may include volatile memory, such as random access memory (RAM) 621 and / or cache memory 622, and may further include read-only memory (ROM) 623.
[0153] The memory 62 may also include a program tool 625 (or utility) having a set (at least one) program module 624, such program module 624 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.
[0154] The processor 61 executes various functional applications and data processing by running computer programs stored in the memory 62, such as the wake wind speed calculation method provided in any of the above embodiments.
[0155] Electronic device 60 can also communicate with one or more external devices 64 (e.g., keyboard, pointing device, etc.). This communication can be performed through input / output (I / O) interface 65. Furthermore, electronic device 60 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public network, such as the Internet) via network adapter 66. As shown, network adapter 66 communicates with other modules of electronic device 60 via bus 63. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 60, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems.
[0156] It should be noted that although several units / modules or sub-units / modules of the electronic device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.
[0157] This disclosure also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the wake wind speed calculation method provided in any of the above embodiments.
[0158] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.
[0159] This disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the wake wind speed calculation method described in any of the above embodiments.
[0160] The program code for executing the computer program product of this disclosure can be written in any combination of one or more programming languages, and the program code can be executed entirely on a user device, partially on a user device, as a stand-alone software package, partially on a user device and partially on a remote device, or entirely on a remote device.
[0161] While specific embodiments of this disclosure have been described above, those skilled in the art should understand that these are merely illustrative examples, and the scope of protection of this disclosure is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principles and essence of this disclosure, but all such changes and modifications fall within the scope of protection of this disclosure.
Claims
1. A method for calculating wake velocity, characterized in that, include: S101. The layout of the wind turbine group is equivalent to a regular arrangement, and the equivalent roughness of the environment in which the wind turbine group is located is determined according to the layout parameters of the regular arrangement. S102. Transform the coordinates of each inflection point contained in the wind field boundary to the first local coordinate system of the target wind turbine contained in the wind turbine group, and determine the distance between the target wind turbine and the wind field boundary in the wind direction based on the coordinates of the inflection points in the first local coordinate system; wherein, the first local coordinate system takes the target wind turbine as the origin and the wind direction as the reference direction; all wind turbines contained in the wind turbine group are within the range enclosed by the wind field boundary; S103. Determine the height of the internal boundary layer of the wind field boundary based on the equivalent roughness and the distance; S104. Calculate the first wake speed of the target wind turbine in the wind direction based on the hub height of the target wind turbine and the height of the internal boundary layer.
2. The wake velocity calculation method according to claim 1, characterized in that, The layout parameters include: the arrangement density of the wind turbine cluster; the equivalent roughness is calculated using the following formula: ；（1） ；（2） in, It is the distributed thrust coefficient of the wind turbine cluster. It is the thrust coefficient of the target wind turbine. It is the Kármán constant. It is environmental roughness. D is the average hub height of the wind turbines included in the wind turbine cluster, and D is the arrangement density. It is the equivalent roughness.
3. The wake velocity calculation method according to claim 2, characterized in that, The layout of the wind turbine cluster can be equivalent to a regular square arrangement. The calculation formula is as follows: ；（3） in, It is the area enclosed by the boundary of the wind field. It is the diameter of the rotor of the target wind turbine. This refers to the number of wind turbines included in the wind turbine cluster. It is the first average spacing between wind turbines along the wind direction. It is the second average spacing between wind turbines along the direction perpendicular to the wind direction.
4. The wake velocity calculation method according to claim 1, characterized in that, Transform the coordinates of each inflection point contained in the wind field boundary to the first local coordinate system of the target wind turbine, including: A second local coordinate system is established with the target wind turbine as the origin and the horizontal direction as the reference direction. The coordinates of each inflection point contained in the wind field boundary in the second local coordinate system are obtained. The second local coordinate system is rotated by a preset angle θ so that the X-axis of the second local coordinate system is parallel or perpendicular to the wind direction, thus obtaining the first local coordinate system; Obtain the coordinates of each inflection point in the first local coordinate system.
5. The wake velocity calculation method according to claim 4, characterized in that, Determining the distance between the target wind turbine and the wind field boundary in the wind direction based on the coordinates of the inflection point in the first local coordinate system includes: Select two adjacent target inflection points that meet preset conditions from the inflection points in the first local coordinate system; wherein, the preset conditions include that the x-coordinates of the two target inflection points are one greater than zero and the other less than zero, and that the y-coordinates of the two target inflection points are at least one greater than zero; The intercept of the straight line containing the two target inflection points in the first local coordinate system is determined as the distance between the target wind turbine and the wind field boundary in the wind direction.
6. The wake velocity calculation method according to claim 5, characterized in that, In response to the fact that the number of target inflection points is greater than two, the minimum intercept of any two adjacent target inflection points is determined as the distance to the wind field boundary. Alternatively, in response to the number of target inflection points that meet the preset conditions being less than two, the wind field boundary is redrawn and the process returns to S102.
7. The wake velocity calculation method according to claim 1, characterized in that, S103 includes: F in the following formula is solved using an iterative method: ；（4） The height of the inner boundary layer is calculated based on the solution for F and the following formula: ；（5） in, It is the height of the inner boundary layer. It is the equivalent roughness. It is the distance mentioned above; The first wake velocity is calculated using the following formula: ；（6） ；（7） ；（8） in, It is the hub height of the target wind turbine. It is the lowest height within the wind field boundary affected by the wind field wake. It is the height of the first inner boundary layer. It is the height of the second inner boundary layer. This is the wind speed at the target wind turbine without considering the wake effect.
8. The method for calculating wake velocity according to any one of claims 1-7, characterized in that, Following S101, it also includes: Determine whether the equivalent roughness is greater than the environmental roughness; In response to the equivalent roughness being greater than the environmental roughness, S102 is executed; In response to the equivalent roughness being less than or equal to the environmental roughness, the second wake wind speed of the target wind turbine in the wind direction is calculated using the Jensen wake model.
9. The method for calculating wake velocity according to any one of claims 1-7, characterized in that, Also includes: The Jensen wake model was used to calculate the second wake speed of the target wind turbine in the wind direction. The minimum value between the first wake velocity and the second wake velocity is determined as the final wake velocity of the target wind turbine in the wind direction.
10. A wake velocity calculation system, characterized in that, include: The roughness determination module is used to convert the layout of the wind turbine group into a regular arrangement and determine the equivalent roughness of the environment in which the wind turbine group is located based on the layout parameters of the regular arrangement. The distance determination module is used to transform the coordinates of each inflection point contained in the wind field boundary to the first local coordinate system of the target wind turbine contained in the wind turbine group, and to determine the distance between the target wind turbine and the wind field boundary in the wind direction based on the coordinates of the inflection points in the first local coordinate system; wherein, the first local coordinate system takes the target wind turbine as the origin and the wind direction as the reference direction; and all wind turbines contained in the wind turbine group are within the range defined by the wind field boundary. A height determination module is used to determine the height of the inner boundary layer of the wind field boundary based on the equivalent roughness and the distance. The wake speed determination module is used to calculate the first wake speed of the target wind turbine in the wind direction based on the hub height of the target wind turbine and the height of the internal boundary layer.
11. An electronic device comprising a memory, a processor, and a computer program stored in the memory and for running on the processor, characterized in that, When the processor executes the computer program, it implements the wake wind speed calculation method according to any one of claims 1 to 9.
12. A 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 wind speed calculation method according to any one of claims 1 to 9.
13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the wake wind speed calculation method as described in any one of claims 1-9.