A method for modeling wake of a wind turbine cluster

Abstract

The application provides a wind turbine group wake modeling method, solves the problem of the superposition influence of multiple wind turbine wakes when multiple wind turbines coexist, and the technical scheme of the application is that the upstream and downstream relationship of the wind turbine is established through the direction of the incoming flow, and the superposition influence of the upstream and downstream wind turbines in the wind turbine wake calculation is considered on this basis, so that the accuracy of the wake calculation result when multiple wind turbines exist is improved; meanwhile, the single equation wake model is also inherited, and the advantages of the single equation wake model in the wake calculation are simple form, easy coding and high calculation efficiency; the establishment of the new model can provide more effective support for related applications such as wind turbine array optimization. The application is applied to the technical field of wind power generation.

Description

Technical Field

[0001] This invention relates to the field of wind power generation technology, and in particular to a method for modeling the wake of a wind turbine cluster. Background Technology

[0002] Wind power, due to its clean and renewable characteristics, has become an important component of new energy development and utilization. Wind turbine units are the most common wind power generation devices. However, when wind turbine clusters operate in wind farms, due to the limited scale of the wind farm, some turbines will inevitably be located in the wake of surrounding turbines. Therefore, accurately assessing the velocity distribution in the wake region is of great significance for optimizing turbine layout and improving power generation.

[0003] Currently, analytical wake models have become the most commonly used wake assessment models due to their advantages such as simple principles and fast calculations. Although a great deal of research has been conducted and many classic analytical wake models have been proposed, these models are often only applicable to a single wind turbine. Research on the superimposed effects of wakes from multiple wind turbines coexisting is relatively weak. Summary of the Invention

[0004] The main objective of this invention is to construct a method for modeling the wake of wind turbine clusters, which can fully consider the upstream and downstream relationships between multiple wind turbines and provide accurate wake results when multiple turbines coexist. This improves the prediction accuracy of the flow field in the wake region of wind turbines and provides important technical support for power generation assessment and wind turbine layout optimization.

[0005] This invention provides a method for modeling the wake of a wind turbine cluster, the method comprising the following steps;

[0006] Step 1: Obtain inflow conditions based on the direction of incoming flow. The projected distance s of the fan in the direction of the incoming flow is obtained, and the fans are sorted upstream and downstream according to the projected distance s;

[0007] Step 2: Obtain the wake expansion coefficient k of the upstream fan to all downstream fans; obtain the wind speed u after the fan affects all upstream fans. wi ;

[0008] Step 3: Repeat Step 2 until the wind speed calculation after the wake of n wind turbines is completed, and establish the wake superposition model of the wind turbine group.

[0009] Preferably, the inflow conditions include the spatial coordinates of the fan. Wheel hub height h Hi Fan diameter D i Wind speed u i Wind direction θ i Thrust coefficient C TiFlow direction Roughness z0 or wake expansion coefficient k, where i is the fan number.

[0010] Preferably, the projected distance s refers to the distance based on the direction of the incoming flow. The projected distance s of the fan in the direction of the incoming flow is calculated using the following formula:

[0011]

[0012] In equation (1) This represents the spatial coordinates of the wind turbine in step 3. Indicates the direction of incoming flow The unit vector coordinates.

[0013]

[0014] Preferably, step 2 obtains the wake expansion coefficient k of the upstream fan to all downstream fans;

[0015]

[0016] In equation (3) h H z0 represents the hub height of the wind turbine, and z0 represents the surface roughness.

[0017] Preferably, the wind speed u after the wind turbine affects all upstream wind turbines is obtained. wi , refers to the minimum wake wind speed after all the upstream wind turbines individually cause wind speed loss; to obtain u wi The steps are as follows:

[0018] Step 1: Based on the Park wake model, the wind speed u in the wake region at a distance x downstream of the wind turbine. * The expression is:

[0019]

[0020] In equation (4), u0 is the upstream incoming wind speed, C T R is the turbine thrust coefficient, R is the turbine radius, and k is the wake expansion coefficient.

[0021] Step 2 modifies the model expression. The modified model also assumes that the wake region of the wake model expands linearly and that the radial wind speed in the wake region has a Gaussian symmetric distribution. Then, when the radial radius of the wake is r, the wind speed u is:

[0022]

[0023] In equation (5), A and B are coefficients to be estimated;

[0024] The modified model also satisfies the two assumptions of the Park wake model:

[0025] 1) Assume the radial radius of the wake at position x downstream of the wind turbine is r. x In the radial ±r x If the wind speed at the point of origin returns to the incoming wind speed u0, then:

[0026]

[0027] 2) Assuming the modified model and the Park model have the same wake radius and the same mass flux, then:

[0028]

[0029] Step 3, based on the Gaussian distribution characteristics, in r x When the confidence interval is [-2.58σ, 2.58σ], 99% of the wake velocity values ​​can be calculated. Values ​​exceeding this confidence interval are considered low-probability events. Therefore, we take:

[0030] r x =2.58σ (8)

[0031] Substituting (8) into (6), we get:

[0032]

[0033] because Smaller, can Neglecting the term, we arrive at:

[0034] B = u0 (10)

[0035] Substituting (8) and (10) into (7), we get:

[0036] A+2r x ·u0=u * ·2r x

[0037] A = (u * -u0)·2r x (11)

[0038] Step 4: Substitute (4), (8), (10), and (11) into (6) to obtain:

[0039]

[0040] Preferably, based on the wind speed u in the wake region, the wind speed loss Δu after the wake of the upstream i-th fan on the downstream j-th fan is calculated. wi-j The calculation process is as follows:

[0041]

[0042]

[0043] R wi-j =R i +k i s i-j (15)

[0044]

[0045]

[0046] Where u wi R represents the wind speed of wind turbine i after the influence of the upstream wake. wi-j R is the radial radius of the wake extending from fan i to fan j. i Let k be the impeller radius of fan i. i S is the wake expansion coefficient of fan i. i-j Let j be the projected distance of fan j in the direction of the incoming airflow from fan i. Let i be the spatial coordinates of wind turbine i. Let r be the spatial coordinates of wind turbine j. wi-j Let be the radial radius of the wake at fan j under the influence of the wake of fan i.

[0047] Among them, based on the wind speed loss Δu after the wind turbine wake wi-j Obtain the wind speed u that affects all upstream wind turbines. wi The wind speed u wi This is the minimum wake velocity after all upstream wind turbines individually cause a wind speed loss.

[0048] u wj =u j -max{Δu wi-j |Δu w1-j ,Δu w2-j ,…,Δu wn-j} (18)

[0049] In equation (10), u j The incoming air velocity of fan j; Δu wi-j The wake loss of wind turbine j is calculated after wind turbine i affects downstream wind turbine j. i and j are natural numbers.

[0050] Preferably, step 3: Repeat step 2 sequentially until the wind speed calculation after the wake of n wind turbines is completed, and the wind turbine group wake superposition model is completed. This means that after sequentially calculating the influence of upstream wind turbine i on downstream wind turbine j according to step 2, the wind speed loss Δu after the wake of wind turbine j is calculated. wi-jThen obtain the minimum wake wind speed u after each of the n upstream wind turbines individually causes a wind speed loss. wi The wind turbine cluster wake superposition model is completed when the wind speed calculation after the wakes of n wind turbines is completed.

[0051] This invention provides a method for modeling the wake of a wind turbine cluster, solving the problem of the superimposed influence of the wakes of multiple wind turbines when they coexist. The technical solution of this invention establishes the upstream and downstream relationship of the wind turbines by the direction of the incoming flow, and on this basis, considers the superimposed influence of upstream and downstream wind turbines in the wake calculation, thereby improving the accuracy of the wake calculation results when multiple wind turbines are present. At the same time, it inherits the advantages of the single-equation wake model in wake calculation, such as simple form, easy coding, and high computational efficiency. The new model provides more effective support for the optimization application of wind turbine arrays. Attached Figure Description

[0052] Figure 1 A schematic diagram of a method for modeling the wake of a wind turbine cluster;

[0053] Figure 2 A flowchart illustrating the wake calculation process in an embodiment of a method for modeling the wake of a wind turbine cluster;

[0054] Figure 3 A method for modeling the wake of a wind turbine cluster. Schematic diagram of a wind turbine cluster wake superposition model.

[0055] Figure 4 A method for modeling the wake of a wind turbine cluster is presented. A schematic diagram of the radial velocity distribution at 3.0D of the downstream wind turbines in the Shiren Wind Farm is shown.

[0056] Figure 5 A schematic diagram of the radial velocity distribution at 4.0D of the downstream wind turbines in the Shiren Wind Farm, illustrating a method for modeling the wake of a wind turbine cluster.

[0057] Figure 6 A method for modeling the wake of a wind turbine cluster. Schematic diagram of radial velocity distribution at 1.0D for downstream wind turbines in the Donghai wind farm.

[0058] Figure 7 A method for modeling the wake of a wind turbine cluster. Schematic diagram of the radial velocity distribution of downstream wind turbines at 2.0D in the Donghai wind farm. Detailed Implementation

[0059] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the invention as detailed in the appended claims.

[0060] Example 1

[0061] This invention provides a method for modeling the wake of a wind turbine cluster, such as... Figure 1 The method shown includes the following steps;

[0062] Step 1: Obtain inflow conditions based on the direction of incoming flow. The projected distance s of the fan in the direction of the incoming flow is obtained, and the fans are sorted upstream and downstream according to the projected distance s;

[0063] Step 2: Obtain the wake expansion coefficient k of the upstream fan to all downstream fans; obtain the wind speed u after the fan affects all upstream fans. wi ;

[0064] Step 3: Repeat Step 2 until the wind speed calculation after the wake of n wind turbines is completed, and establish the wake superposition model of the wind turbine group.

[0065] In one embodiment, the inflow conditions include the spatial coordinates of the wind turbine. Wheel hub height h Hi Fan diameter D i Wind speed u i Wind direction θ i Thrust coefficient C Ti Flow direction Roughness z0 or wake expansion coefficient k, where i is the fan number.

[0066] In one embodiment, the projected distance s refers to the distance based on the direction of the incoming flow. The projected distance s of the fan in the direction of the incoming flow is calculated using the following formula:

[0067]

[0068] In equation (1) Represents the spatial coordinates of the wind turbine. Indicates the direction of incoming flow Unit vector coordinates;

[0069]

[0070] In one embodiment, step 2 obtains the wake expansion coefficient k of the upstream wind turbine to all downstream wind turbines;

[0071]

[0072] In equation (3) h H z0 represents the hub height of the wind turbine, and z0 represents the surface roughness. In addition, users can also define k, which is usually 0.04 for offshore and 0.075 for land.

[0073] In one embodiment, the wind speed u after the wind turbine affects all upstream wind turbines is obtained. wi The wind speed u wi The minimum wake velocity after all the upstream wind turbines individually cause a wind speed loss;

[0074] Get u wi The steps are as follows:

[0075] Step 1: Based on the Park wake model, the wind speed u in the wake region at a distance x downstream of the wind turbine. * The expression is:

[0076]

[0077] In equation (4), u0 is the upstream incoming wind speed, C T R is the turbine thrust coefficient, R is the turbine radius, and k is the wake expansion coefficient.

[0078] Step 2 modifies the model expression. The modified model also assumes that the wake region of the wake model expands linearly and that the radial wind speed in the wake region has a Gaussian symmetric distribution. Then, when the radial radius of the wake is r, the wind speed u is:

[0079]

[0080] In equation (5), A and B are coefficients to be estimated;

[0081] The modified model also satisfies the two assumptions of the Park wake model:

[0082] 1) Assuming the radial radius of the wake at position x downstream of the wind turbine is rx, and the wind speed at radial position ±rx recovers to the incoming wind speed u0, then:

[0083]

[0084] 2) Assuming the modified model and the Park model have the same wake radius and the same mass flux, then:

[0085]

[0086] Step 3, based on the Gaussian distribution characteristics, in rx When the confidence interval is [-2.58σ, 2.58σ], 99% of the wake velocity values ​​can be calculated. Values ​​exceeding this confidence interval are considered low-probability events. Therefore, we take:

[0087] r x =2.58σ (8)

[0088] Substituting (8) into (6), we get:

[0089]

[0090] because Smaller, can Neglecting the term, we arrive at:

[0091] B = u0 (10)

[0092] Substituting (8) and (10) into (7), we get:

[0093] A+2r x ·u0=u * ·2r x

[0094] A = (u * -u0)·2r x (11)

[0095] Step 4: Substitute (4), (8), (10), and (11) into (6) to obtain:

[0096]

[0097] In one embodiment, based on the wind speed u in the wake region, the wind speed loss Δu after the wake of wind turbine j is calculated after the upstream i-th turbine on the downstream j-th turbine. wi-j The calculation process is as follows:

[0098]

[0099]

[0100] R wi-j =R i +k i s i-j (15)

[0101]

[0102]

[0103] Where u wi R represents the wind speed of wind turbine i after the influence of the upstream wake.wi-j R is the radial radius of the wake extending from fan i to fan j. i Let k be the impeller radius of fan i. i S is the wake expansion coefficient of fan i. i-j Let j be the projected distance of fan j in the direction of the incoming airflow from fan i. Let i be the spatial coordinates of wind turbine i. Let r be the spatial coordinates of wind turbine j. wi-j Let be the radial radius of the wake at fan j under the influence of the wake of fan i.

[0104] Among them, based on the wind speed loss Δu after the wind turbine wake wi-j Obtain the wind speed u that affects all upstream wind turbines. wi The wind speed u wi This is the minimum wake velocity after all upstream wind turbines individually cause a wind speed loss.

[0105] u wj =u j -max{Δu wi-j |Δu w1-j ,Δu w2-j ,…,Δu wn-j} (18)

[0106] In equation (10), u j The incoming air velocity of fan j; Δu wi-j The wake loss of wind turbine j is calculated after wind turbine i affects downstream wind turbine j. i and j are natural numbers.

[0107] In one embodiment, step 3: Repeat step 2 sequentially until the wind speed calculation after the wake of n wind turbines is completed, and the wind turbine group wake superposition model is completed. This means that after sequentially calculating the impact of upstream wind turbine i on downstream wind turbine j according to step 2, the wind speed loss Δu after the wake of wind turbine j is calculated. wi-j Then obtain the minimum wake wind speed u after each of the n upstream wind turbines individually causes a wind speed loss. wi The wind turbine cluster wake superposition model is completed when the wind speed calculation after the wakes of n wind turbines is completed.

[0108] This invention provides a method for modeling the wake of a wind turbine cluster. By employing the above-mentioned technical solution, the upstream and downstream relationships of the wind turbines are established based on the incoming flow direction. Furthermore, the superposition effect of upstream and downstream wind turbines in the wake calculation is considered, thereby improving the accuracy of the wake calculation results when multiple wind turbines are present. It also inherits the advantages of the single-equation wake model in wake calculation, such as its simple form, ease of coding, and high computational efficiency. The new model provides more effective support for the optimization application of wind turbine arrays.

[0109] Example 2

[0110] This invention provides a method for modeling the wake of a wind turbine cluster, combined with the attached... Figure 2 and Figure 3 As shown, specific embodiments are provided to illustrate the present invention. (See references.) Figure 2 As shown. A method for modeling the wake of a wind turbine cluster, the specific steps are as follows:

[0111] Step 1: Specify the inflow conditions

[0112] Obtain the spatial coordinates of each wind turbine Wheel hub height h Hi Fan diameter D i Wind speed u i Wind direction θ i Thrust coefficient C Ti Flow direction Roughness z0 or wake expansion coefficient k, where i is the fan number.

[0113] Step 2: Determine the upstream and downstream of the fan based on the incoming flow direction. Calculate the projected distance 's' of the fan in the direction of the incoming flow, and sort the fans upstream and downstream based on this distance. The smaller the 's', the more upstream the fan. Figure 2 As shown.

[0114]

[0115] In formula (1) Represents the spatial coordinates of the wind turbine. Indicates the direction of incoming flow Unit vector coordinates;

[0116]

[0117] Step 3: Calculate the wake effect of the upstream wind turbine on all its downstream wind turbines.

[0118] 3.1 Calculate the wake expansion coefficient k

[0119] When the user calculates using roughness z0

[0120]

[0121] In equation (3) h H Z0 represents the hub height of the wind turbine, and Z0 represents the surface roughness. Users can also directly input K, which is usually 0.04 for offshore and 0.075 for onshore.

[0122] 3.2 After calculating the impact of upstream fan i on downstream fan j, the wind speed loss Δu after the wake of fan j. wi-j .

[0123] First, according to the Park wake model, the wind speed u in the wake region at a distance x downstream of the wind turbine is... * The expression is:

[0124]

[0125] In equation (4), u0 is the upstream incoming wind speed, C T R is the turbine thrust coefficient, R is the turbine radius, and k is the wake expansion coefficient.

[0126] Then, the above model expression is modified. Again, it is assumed that the wake region of the wake model expands linearly, but the radial wind speed in the wake region exhibits a Gaussian symmetric distribution. Therefore, the wind speed u when the radial radius of the wake is r is:

[0127]

[0128] In equation (5), A and B are coefficients to be estimated.

[0129] This revised model also satisfies the two assumptions of the Park wake model:

[0130] 1) Assuming the radial radius of the wake at position x downstream of the wind turbine is rx, and the wind speed at radial position ±rx recovers to the incoming wind speed u0, then:

[0131]

[0132] 2) Assuming the modified model and the Park model have the same wake radius and the same mass flux, then:

[0133]

[0134] Secondly, based on the Gaussian distribution characteristics, within the confidence interval of rx [-2.58σ, 2.58σ], 99% of the wake velocity values ​​can be calculated; values ​​outside this interval are considered low-probability events. Therefore, we take:

[0135] r x =2.58σ (8)

[0136] Substituting (8) into (6), we get:

[0137]

[0138] because Smaller, can Neglecting the term, we arrive at:

[0139] B = u0 (10)

[0140] Substituting (8) and (10) into (7), we get:

[0141] A+2r x ·u0=u * ·2r x

[0142] A = (u * -u0)·2r x (11)

[0143] Finally, substituting (4), (8), (10), and (11) into (5), we obtain:

[0144]

[0145] Based on the above method, after calculating the impact of upstream wind turbine i on downstream wind turbine j, the wind speed loss Δu after the wake of wind turbine j is calculated. wi-j The calculation process is as follows:

[0146]

[0147]

[0148] R wi-j =R i +k i s i-j (15)

[0149]

[0150]

[0151] Where u wi R represents the wind speed of wind turbine i after the influence of the upstream wake. wi-j R is the radial radius of the wake extending from fan i to fan j. i Let k be the impeller radius of fan i. i S is the wake expansion coefficient of fan i. i-j Let j be the projected distance of fan j in the direction of the incoming airflow from fan i. Let i be the spatial coordinates of wind turbine i. Let r be the spatial coordinates of wind turbine j. wi-j Let be the radial radius of the wake at fan j under the influence of the wake of fan i.

[0152] For the first fan, the wind speed is the wind speed before the wake. For the calculation of the wind speed for the other fans, please refer to step four.

[0153] Step 4: Calculate the wind speed u of the wind turbine after considering the influence of all its upstream wind turbines. wi This wind speed is the minimum wake wind speed after all the wind turbines upstream individually cause wind speed loss.

[0154] u wj =u j -max{Δu wi-j |Δu w1-j ,Δu w2-j ,…,Δu wn-j} (18)

[0155] In equation (18), u j The incoming air velocity of fan j; Δu wi-j The impact of fan I on downstream fan J

[0156] Step 5: Repeat steps 3 and 4 until the wind speed calculation after the wake of all fans is completed.

[0157] Step 6: Based on the above steps, establish a wake superposition model of the wind turbine cluster (the new model is named M2D-PARK model), and calculate the wake wind speed under the M2D-PARK model.

[0158] In one embodiment, such as Figure 4 The effectiveness of the model is verified at the Shiren Wind Farm and Dongwan Wind Farm in Hebei Province.

[0159] 6.1 The data for the Shiren Wind Farm in Hebei Province comes from the paper "Research and Analysis of Characteristics of Multi-Turbine Wake Interference Model" by Liu Zhiyi et al. This wind farm contains two wind turbines with identical hub heights. The wind speed before the wake of both the upstream and downstream turbines is 7.92 m / s, the wake expansion coefficient is 0.15, the distance between the turbines is 6.419 times the rotor diameter, the rotor diameter is 77 m, and the thrust coefficients are 0.777 and 0.892 respectively. At 3 and 4 times the rotor diameter of the downstream turbine, the predicted results and measured results of the model in this invention are as follows: Figure 4 and Figure 5 As shown, the results are basically consistent.

[0160] 6.2 Data from the Hebei Dongwan Wind Farm, based on the paper "Research and Analysis of Characteristics of Multi-Turbine Wake Interference Model" by Liu Zhiyi et al. This wind farm contains two wind turbines with identical hub heights. The wind speed before the wake of both the upstream and downstream turbines is 7.68 m / s, the wake expansion coefficient is 0.195, the distance between the turbines is 5 times the rotor diameter, the rotor diameter is 54 m, and the thrust coefficient is 0.930. At a distance of 1 to 62 times the rotor diameter of the downstream turbine, the predicted results and measured results of the model in this invention are as follows: Figure 6 and Figure 7 As shown, the results are basically consistent.

[0161] Comparative experimental results show that the wake model provided by this invention, compared with the traditional single wind turbine wake model, takes into account the wake superposition when multiple wind turbines coexist in a complex wind turbine group, which improves the accuracy of the calculation results and the prediction accuracy of the wake, while inheriting the advantages of engineering models such as simple form, easy coding and high calculation efficiency.

[0162] This invention provides a method for modeling the wake of a wind turbine cluster. By employing the above-mentioned technical solution, the upstream and downstream relationships of the wind turbines are established based on the incoming flow direction. Furthermore, the superposition effect of upstream and downstream wind turbines in the wake calculation is considered, thereby improving the accuracy of the wake calculation results when multiple wind turbines are present. It also inherits the advantages of single-equation wake models in wake calculation, such as simplicity, ease of coding, and high computational efficiency. The new model can provide more effective support for related applications such as wind turbine array optimization.

Claims

1. A method for modeling the wake of a wind turbine cluster, characterized in that, The method includes the following steps: Step 1: Obtain the inflow conditions. Based on the inflow direction α, obtain the projected distance s of the fan in the inflow direction, and sort the fans upstream and downstream according to the projected distance s. Step 2: Obtain the wake expansion coefficient k of the upstream fan to all downstream fans; obtain the wind speed u after the fan affects all upstream fans. wi ; The wind speed u after obtaining the influence of the wind turbine on all upstream wind turbines is obtained. wi , refers to the minimum wake wind speed after all the upstream wind turbines individually cause wind speed loss; to obtain u wi The steps are as follows: Step 2.1 Based on the Park wake model, the wind speed u in the wake region at a distance x downstream of the wind turbine. * The expression is: In equation (4), u0 is the upstream incoming wind speed, C T R is the turbine thrust coefficient, R is the turbine radius, and k is the wake expansion coefficient. Step 2.2 modifies the model expression. The modified model also assumes that the wake region of the wake model expands linearly and that the radial wind speed in the wake region has a Gaussian symmetric distribution. Then, when the radial radius of the wake is r, the wind speed u is: In equation (5), A and B are coefficients to be estimated; The modified model also satisfies the two assumptions of the Park wake model: 1) Assume the radial radius of the wake at position x downstream of the wind turbine is r. x In the radial ±r x If the wind speed at the point of origin returns to the incoming wind speed u0, then: 2) Assuming the modified model and the Park model have the same wake radius and the same mass flux, then: Step 2.3 Based on the Gaussian distribution characteristics, in r x When the confidence interval is [-2.58σ, 2.58σ], 99% of the wake velocity values ​​can be calculated. Values ​​exceeding this confidence interval are considered low-probability events. Therefore, we take: r x =2.58σ (8) Substituting (8) into (6), we get: because Smaller, can Neglecting the term, we arrive at: B = u0 (10) Substituting (8) and (10) into (7), we get: A+2r x ·u0=u * ·2r x A=(u * -u0)·2r x (11) Finally, substituting (4), (8), (10), and (11) into (6), we obtain: Based on the wind speed u in the wake region, after calculating the impact of upstream fan i on downstream fan j, the wind speed loss Δu after the wake of fan j is calculated. wi-j The calculation process is as follows: R wi-j =R i +k i s i-j (15) Where u wi R represents the wind speed of wind turbine i after the influence of the upstream wake. wi-j R is the radial radius of the wake extending from fan i to fan j. i Let k be the impeller radius of fan i. i S is the wake expansion coefficient of fan i. i-j Let j be the projected distance of fan j in the direction of the incoming airflow from fan i. Let i be the spatial coordinates of wind turbine i. Let r be the spatial coordinates of wind turbine j. wi-j Let be the radial radius of the wake at fan j under the influence of the wake of fan i. Step 3: Repeat Step 2 until the wind speed calculation after the wake of n wind turbines is completed, and establish the wake superposition model of the wind turbine group.

2. The method for modeling the wake of a wind turbine cluster according to claim 1, characterized in that, The inflow conditions include the spatial coordinates of the fan. Wheel hub height h Hi Fan diameter D i Wind speed u i Wind direction θ i Thrust coefficient C Ti Flow direction Roughness z0 or wake expansion coefficient k, where i is the fan number.

3. The method for modeling the wake of a wind turbine cluster according to claim 1, characterized in that, The projected distance s refers to the distance based on the direction of the incoming flow. The projected distance s of the fan in the direction of the incoming flow is calculated using the following formula: In equation (1) Represents the spatial coordinates of the wind turbine. Indicates the direction of incoming flow Unit vector coordinates; 4. The method for modeling the wake of a wind turbine cluster according to claim 1, characterized in that, Step 2 obtains the wake expansion coefficient k of the upstream wind turbine to all downstream wind turbines; In equation (3) h H z0 represents the hub height of the wind turbine, and z0 represents the surface roughness.

5. The method for modeling the wake of a wind turbine cluster according to claim 1, characterized in that, Based on the wind speed loss Δu after the fan wake wi-j Obtain the wind speed u after the wind turbine affects all upstream wind turbines. wi The wind speed u wi The minimum wake velocity after all the upstream wind turbines individually cause a wind speed loss; u wj u j -max{Δu wi-j |Δu w1-j ,Δu w2-j ,…,Du wn-j } (18) In equation (18), u j The incoming air velocity of fan j; Δu wi-j Let i be the wake loss of wind turbine j after wind turbine i affects downstream wind turbine j. Let i and j be natural numbers.

6. The method for modeling the wake of a wind turbine cluster according to claim 1, characterized in that, Step 3: Repeating Step 2 sequentially until the wind speed calculation after the wake of all wind turbines is completed, and the wind turbine group wake superposition model is established, refers to the wind speed loss Δu after the wake of wind turbine j after sequentially calculating the impact of upstream wind turbine i on downstream wind turbine j according to Step 2. wi-j Then obtain the minimum wake wind speed u after each of the n upstream wind turbines individually causes a wind speed loss. wi The wind turbine cluster wake superposition model is completed when the wind speed calculation after the wakes of n wind turbines is completed.

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