A method for predicting wind turbine wake velocity in complex terrain

Abstract

The present invention discloses a method for predicting the wake velocity of a wind turbine in complex terrain, comprising the following steps: 1) obtaining relevant parameters of the complex terrain and the wind turbine to be set on the complex terrain; 2) obtaining the first wind field information under the influence of the complex terrain; 3) establishing a wind turbine wake velocity loss model under the influence of the complex terrain to obtain the second wind field information under the influence of the wind turbine and the complex terrain; 4) superimposing the first wind field information and the second wind field information to obtain the wake velocity information after the wind turbine is set on the complex terrain. The present invention constructs a wind turbine wake velocity loss model suitable for complex terrain, taking into account the wake deflection and velocity loss changes caused by the terrain effect, improving the prediction accuracy of the wind turbine wake velocity in complex terrain, and is of great significance for improving the accuracy of wind farm layout optimization, power prediction and coordinated control in complex terrain.

Description

Technical Field

[0001] The invention relates to the technical field of wind power generation, and in particular to a method for predicting the wake velocity of a wind turbine in complex terrain. Background Art

[0002] In the context of building a new power system and accelerating the planning and construction of a new energy system in my country, new energy is booming. Among them, wind power generation has developed rapidly around the world with its advantages of low cost, clean and pollution-free, and significant scale benefits.

[0003] At first, people built wind farms on flat terrain with good wind conditions, because the air flow here is smooth, the turbulence is low, the impact on wind turbines is small, and it is easy to construct, such as the Huaneng Puyang 500MW wind farm and the Huaneng Tangyin 100MW wind farm. However, with the increase in the number of wind farms, the number of such sites available has become fewer and fewer. In addition, mountains dominate the landform types in my country, and choosing mountainous areas to build wind farms has less impact on the social environment. Therefore, wind farms began to be built on complex terrain, such as the Quping 600MW wind farm, the Yalong River Laba Mountain 258MW wind farm, and the China Datang Yunnan Wenshan Jinping West Wind Power Project, which was connected to the grid on December 23, 2023. This marks the completion of the largest plateau mountain wind power base in China with a total capacity of 1.103 million kilowatts.

[0004] Wind farms in complex terrain are mainly affected by the wind turbine wake effect and terrain effect. The wind turbine wake effect mainly refers to the phenomenon that the wind speed of the downstream wind turbine is reduced and the turbulence intensity is increased due to the operation of the upstream wind turbine. Among them, the loss of wind speed can cause a loss of 30%-40% in power generation, and the increase in turbulence intensity can increase the fatigue load by 20%-30%. The terrain effect mainly refers to the pressure gradient change caused by complex terrain, which induces velocity changes, such as the wind acceleration effect at the top of the mountain. In addition, strong flow separation will occur on the leeward side.

[0005] At present, in some complex terrain wind farms that have been built and put into operation, the power generation of individual units is significantly different from that of other units, far from meeting the design standards. The main reason for this phenomenon is that the coupling effect of terrain wake and wind turbine wake was not fully considered at the micro-site selection stage, resulting in flow separation areas at the site selection locations of some units, which directly caused the waste of wind energy resources. Therefore, in-depth understanding of the mechanism of wind turbine wake effect under complex terrain is the key to improving wind farm revenue and reducing failure rates. Establishing a high-precision wind turbine wake model under complex terrain is crucial for layout optimization in the early stage of wind farm construction and power prediction during the operation stage of wind farms. Summary of the invention

[0006] In view of the above-mentioned deficiencies in the prior art, the purpose of the present invention is to solve the problems of low layout optimization and power prediction accuracy, as well as low control efficiency caused by insufficient accuracy of the speed loss model used in complex terrain wind farm layout optimization, power prediction and coordinated control.

[0007] In order to solve the above technical problems, the technical solution adopted by the present invention is as follows: a method for predicting the wind turbine wake velocity in complex terrain, comprising the following steps:

[0008] 1) Obtain relevant parameters of complex terrain and wind turbines to be installed on the complex terrain;

[0009] 2) Obtaining the first wind field information under the influence of the complex terrain;

[0010] 3) Establish a wind turbine wake velocity loss model under the influence of complex terrain to obtain the second wind field information under the influence of wind turbines and complex terrain;

[0011] 4) The first wind field information and the second wind field information are superimposed to obtain prediction information of the wind turbine wake velocity after the wind turbine is set on the complex terrain.

[0012] As an optimization, in step 1), the relevant parameters of the complex terrain include the mountain height and the mountain slope, and the relevant parameters of the wind turbine include the thrust coefficient, the hub height and the rotor diameter.

[0013] As an optimization, in step 2), the first wind field information only affected by complex terrain is obtained by CFD numerical simulation method, and the first wind field information includes wind speed and wind deflection angle at the wind turbine position.

[0014] As an optimization, step 3) includes the following steps:

[0015] 301) Establish a wind turbine wake velocity loss model under flat terrain;

[0016] 302) Determine the induction factor of complex terrain and the amount of wake deflection under the influence of complex terrain;

[0017] 303) Introducing the induction factor and the wake deflection amount into the wind turbine wake velocity loss model under flat terrain, establishing the wind turbine wake velocity loss model under the influence of complex terrain, and obtaining the second wind field information under the influence of the wind turbine and complex terrain through the model.

[0018] As an optimization, step 301) includes:

[0019] 3011) Determine the boundary, width development and corresponding parameters of the fan wake:

[0020]

[0021] Where σ is the wake width; k is the wake width expansion coefficient, using the formula Calculate, ε is the initial wake width, using the formula Calculate, where C T is the fan thrust coefficient, I a is the ambient turbulence intensity at the height of the wind turbine hub; D is the wind turbine diameter; x is the horizontal distance from the wind turbine;

[0022] The wind turbine thrust coefficient and the ambient turbulence intensity at the height of the wind turbine hub are determined by measuring the wind speed information at the location where the wind turbine is to be set.

[0023] 3012) Calculate the empirical parameters a, b, and c of speed loss in flat terrain using the following formulas:

[0024]

[0025] 3013) Establish a wind turbine wake velocity loss model under flat terrain:

[0026]

[0027] Where U h is the inflow wind speed at the fan hub height; r is the lateral distribution width of the wake, using the formula Calculate, where H hub is the fan hub height.

[0028] As an optimization, in step 302), the complex terrain induction factor is calculated by the following formula: Among them, H hill is the height of the mountain, L is the height from the height H hill To a height of H hill / 2 horizontal distance.

[0029] As an optimization, step 302) determines the amount of wake deflection induced by the rough terrain including:

[0030] When x≤x0, the near wake deflection is:

[0031]

[0032]

[0033]

[0034]

[0035] When x>x0, the far wake deflection is:

[0036]

[0037]

[0038] Where θ0 is the initial tilt angle, σ0 is the wake width near the wake, and y ′ d is the deflection of the wake during active yaw, y d is the amount of wake deflection caused by the wind direction change of the wind turbine, x is the horizontal distance from the wind turbine, γ is the wind deflection angle at the height of the wind turbine hub; y ′ d0 It is the amount of tail deflection when x=x0.

[0039] As an optimization, step 303) includes: establishing a wind turbine wake velocity loss model under the influence of complex terrain:

[0040]

[0041]

[0042] The model is used to obtain the second wind field information under the influence of wind turbines and complex terrain.

[0043] Compared with the prior art, the present invention has the following advantages: the present invention constructs a wind turbine wake velocity loss model suitable for complex terrain, takes into account the wake deflection and velocity loss changes caused by terrain effects, improves the prediction accuracy of wind turbine wake velocity loss in complex terrain, and is of great significance for improving the accuracy of wind farm layout optimization, power prediction and coordinated control in complex terrain. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic diagram of coordinate transformation in active yaw state and incoming flow deflection;

[0045] Figure 2 It is a schematic diagram of the superposition of wind turbine wake velocity loss and complex terrain velocity field;

[0046] Figure 3 This is the comparison of wind speed in the XZ plane when the slope is 0.17;

[0047] Figure 4 This is the comparison of wind speed in the XY plane when the slope is 0.17;

[0048] Figure 5 This is the comparison of wind speed in the XZ plane when the slope is 0.57;

[0049] Figure 6 This is the comparison of wind speed in the XY plane when the slope is 0.57;

[0050] Figure 7It is a comparison of power calculations of different wake models;

[0051] Figure 8 Power calculation errors of different wake models;

[0052] in, Figure 3-Figure 6 In the figure, the red line represents the numerical simulation result, the blue line represents the prediction result of the present invention, and the green line represents the data result of the Ishihara and Qian wake model. DETAILED DESCRIPTION

[0053] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0054] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] It should be noted that similar numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. In the description of the present invention, it should be noted that the orientation or position relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inside", "outside", etc. is based on the orientation or position relationship shown in the drawings, or the orientation or position relationship in which the invention product is usually placed when used, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. In addition, the terms "first", "second", "third", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance. In addition, the terms "horizontal", "vertical", etc. do not mean that the components are absolutely horizontal or suspended, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly tilted. In the description of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0056] Example: See Figures 1 to 8 The goal of the present invention is to solve the problem of low layout optimization and power prediction accuracy, as well as low control efficiency, caused by insufficient accuracy of the speed loss model used in complex terrain wind farm layout optimization, power prediction and coordinated control. A wind turbine wake velocity loss model suitable for complex terrain is provided, which can accurately predict the wind turbine wake velocity loss in complex terrain wind farms, improve the accuracy of complex terrain wind farm layout optimization, power prediction and coordinated control, and improve the power generation and economic benefits of complex terrain wind farms. Specifically, the present invention provides a method for predicting the wake velocity of wind turbines in complex terrain, comprising the following steps:

[0057] 1) Obtaining relevant parameters of the complex terrain and the wind turbine to be installed on the mountain. The relevant parameters of the complex terrain include the mountain height, mountain slope, etc., and the relevant parameters of the wind turbine include thrust coefficient, hub height, wind rotor diameter, etc.

[0058] 2) Obtaining first wind field information under the influence of complex terrain according to the complex terrain related parameters in step 1). Specifically, obtaining first wind field information only under the influence of complex terrain by CFD numerical simulation, wherein the first wind field information includes wind speed, wind deflection angle at the wind turbine position, etc.

[0059] 3) Establish a wind turbine wake velocity loss model under the influence of complex terrain to obtain the second wind field information under the influence of wind turbines and complex terrain.

[0060] Specifically, it includes: 301) establishing a wind turbine wake velocity loss model under flat terrain;

[0061] More specifically, it includes: 3011) Determine the boundary, width development and corresponding parameters of the wind turbine wake:

[0062]

[0063] Where σ is the wake width; k is the wake width expansion coefficient, using the formula Calculate, ε is the initial wake width, using the formula Calculate, where C T is the fan thrust coefficient, I a is the ambient turbulence intensity at the height of the wind turbine hub; D is the wind turbine diameter; x is the horizontal distance from the wind turbine;

[0064] The wind turbine thrust coefficient and the ambient turbulence intensity at the height of the wind turbine hub are determined by measuring the wind speed information at the location where the wind turbine is to be set.

[0065] 3012) Calculate the speed loss related parameters on flat terrain, using the empirical parameters a, b, c, respectively, using the following formulas:

[0066]

[0067] 3013) Establish a wind turbine wake velocity loss model under flat terrain:

[0068]

[0069] Where U h is the inflow wind speed at the fan hub height; r is the lateral distribution width of the wake, using the formula Calculate, where H hub is the fan hub height.

[0070] 302) Determine the induction factor of complex terrain and the amount of wake deflection under the influence of complex terrain;

[0071] The complex terrain induction factor is calculated by the following formula: Among them, Hhill is the height of the mountain, L is the height from the height H hill To a height of H hill / 2 horizontal distance.

[0072] Specifically, the determination of the wake deflection amount includes:

[0073] When x≤x0, the near wake deflection is:

[0074]

[0075]

[0076]

[0077]

[0078] When x>x0, the far wake deflection is:

[0079]

[0080]

[0081] Where θ0 is the initial tilt angle, σ0 is the wake width near the wake, and y ′ d is the deflection of the wake during active yaw, y d is the amount of wake deflection caused by the change of wind direction when the wind turbine is fixed, x is the horizontal distance from the wind turbine, and γ is the wind deflection angle at the height of the wind turbine hub;

[0082] 303) Introducing the induction factor into the wind turbine wake velocity loss model under flat terrain, establishing the wind turbine wake velocity loss model under the influence of complex terrain, and obtaining the second wind field information under the influence of the wind turbine and complex terrain through the model.

[0083] Specifically, a wind turbine wake velocity loss model under the influence of complex terrain is established:

[0084]

[0085]

[0086] The model is used to obtain the second wind field information under the influence of wind turbines and complex terrain.

[0087] 4) The first wind field information and the second wind field information are superimposed to obtain the predicted information of the wind turbine wake speed set on the complex terrain, that is, the complex terrain wind turbine wake speed loss model and the speed that only exists in the complex terrain are superimposed to obtain the real speed of the wind turbine wake under the complex terrain.

[0088] The present invention takes the British Askervein hill and the model wind turbine WIRE-01 as the research objects to test the effect of the wind turbine wake velocity loss model in complex terrain. The wind turbine rotor diameter is 0.15m and the hub height is 0.125m. The incoming wind speed at the hub height is 2.2m / s and the turbulence intensity is 7%; the prediction accuracy is tested when the complex terrain slope is 0.17 and 0.57 respectively.

[0089] The complex terrain wind turbine wake velocity loss model proposed in the present invention is used to predict the wind turbine wake velocity distribution, and the prediction results are compared with the Ishihara and Qian wake model and numerical simulation data results to verify the prediction performance of this model. Figure 1-Figure 6 It is a comparison chart of the velocity distribution, power characteristics and error predicted by the wind turbine wake model when the complex terrain slopes are 0.17 and 0.57 respectively.

[0090] In summary, the present invention constructs a wind turbine wake velocity loss model suitable for complex terrain, takes into account the wake deflection and velocity loss changes caused by terrain effects, improves the prediction accuracy of wind turbine wake velocity loss in complex terrain, and is of great significance to improving the accuracy of wind farm layout optimization, power prediction and coordinated control in complex terrain.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit the technical solution. Those skilled in the art should understand that those modifications or equivalent substitutions of the technical solution of the present invention that do not depart from the purpose and scope of the technical solution should be included in the scope of the claims of the present invention.

Claims

1. A method for predicting wind turbine wake velocity in complex terrain, characterized in that: The steps include: 1) Obtain relevant parameters of complex terrain and wind turbines to be installed on the complex terrain; 2) obtaining first wind field information under the influence of the complex terrain by a CFD numerical simulation method; the first wind field information includes wind speed and wind deflection angle at the wind turbine position; 3) Establishing a wind turbine wake velocity loss model under the influence of complex terrain to obtain the second wind field information under the influence of wind turbines and complex terrain; specifically including the following steps: 301) Establish a wind turbine wake velocity loss model under flat terrain; Among them, the establishment of the wind turbine wake velocity loss model under flat terrain includes: 3011) Determine the boundary, width development and corresponding parameters of the fan wake: Where σ is the wake width; k is the wake width expansion coefficient, using the formula Calculate, ε is the initial wake width, using the formula Calculate, where C T is the fan thrust coefficient, I a is the ambient turbulence intensity at the height of the wind turbine hub; D is the wind turbine diameter; x is the horizontal distance from the wind turbine; The wind turbine thrust coefficient and the ambient turbulence intensity at the height of the wind turbine hub are determined by measuring the wind speed information at the location where the wind turbine is to be set; 3012) Calculate the empirical parameters a, b, and c of speed loss in flat terrain using the following formulas: 3013) Establish a wind turbine wake velocity loss model under flat terrain: Where U h is the inflow wind speed at the fan hub height; r is the lateral distribution width of the wake, using the formula Calculate, where H hub is the fan hub height; 302) Determine the induction factor of complex terrain and the amount of wake deflection under the influence of complex terrain; The complex terrain induction factor is calculated by the following formula: Among them, H hill is the height of the mountain, L is the height from the height H hill To a height of H hill / 2 horizontal distance; The determination of the wake deflection amount comprises: When x≤x0, the near wake deflection is: When x>x0, the far wake deflection is: Where θ0 is the initial tilt angle, σ0 is the wake width near the wake, and y′ d is the deflection of the wake during active yaw, y d is the amount of wake deflection caused by the wind direction change of the wind turbine, x is the horizontal distance from the wind turbine, γ is the wind deflection angle at the height of the wind turbine hub; y′ d0 is the amount of trail deflection when x = x0; 303) The induction factor and the wake deflection amount are introduced into the wind turbine wake velocity loss model under flat terrain, and the wind turbine wake velocity loss model under the influence of complex terrain is established, and the second wind field information under the influence of the wind turbine and complex terrain is obtained through the model; wherein, the wind turbine wake velocity loss model under the influence of complex terrain: The model is used to obtain the second wind field information under the influence of wind turbines and complex terrain; 4) The first wind field information and the second wind field information are superimposed to obtain the wake velocity prediction information after the wind turbine is set on the complex terrain.

2. The method for predicting the wind turbine wake velocity in complex terrain according to claim 1, characterized in that: In step 1), the relevant parameters of the complex terrain include mountain height and mountain slope, and the relevant parameters of the wind turbine include thrust coefficient, hub height, and wind rotor diameter.

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