A method and device for modeling dynamic wake of offshore wind farm

Abstract

The offshore wind farm dynamic wake modeling method, device and storage medium provided by the present disclosure, by obtaining the operation data of each wind turbine in the wind farm in a complete year, determining the corresponding relationship between the operation state of each wind turbine and the dynamic wake according to the operation data, obtaining the distribution plan view of the wind turbines in the wind farm, determining the relationship between the speed and direction of the wake and the shielding area of each wind turbine based on the corresponding relationship between the operation state of each wind turbine and the dynamic wake, constructing the full-field model of the dynamic wake of the wind farm based on the relationship between the speed and direction of the wake and the shielding area of each wind turbine, correcting the full-field model of the dynamic wake of the offshore wind farm through simulation and field test data, and obtaining the target full-field model of the dynamic wake of the wind farm. It can be seen that the present application considers the relationship between the dynamic distribution of the wakes among the units in the field, so that the wind farm can effectively control the wind turbines according to the wake model, adjust the wake distribution in the wind farm, optimize the active power output efficiency of the wind farm, and maximize the output efficiency of the wind farm.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of wind power generation, and in particular to a dynamic wake modeling method and device for offshore wind farms, and a storage medium. BACKGROUND

[0002] With the rapid development of the power industry, offshore wind farms are usually composed of dozens or even hundreds of wind turbines arranged in a certain order. Offshore wind farms have the characteristics of large scale, many units, strong wake effect, and complex aerodynamic coupling. The current wind farm control system can only realize limited domain information collection of the wind farm and uses a unified control method for each single machine, ignoring the influence of the dynamic distribution of the wake between the units in the field, resulting in a lack of interaction between wind turbines, group-level coordination and field-level coordination. This causes the measurement consistency and accuracy between wind turbines to be unable to be corrected in time, the safety control in the field cannot be interlocked, and the power generation cannot be maximized. SUMMARY

[0003] The present application provides a dynamic wake modeling method and device for offshore wind farms, and a storage medium, to solve the technical problems in the related art.

[0004] The first aspect of the present application provides a dynamic wake modeling method for offshore wind farms, comprising:

[0005] Obtaining the operating data of each wind turbine in the wind farm for a complete year, and determining the corresponding relationship between the operating state of each wind turbine and the dynamic wake based on the operating data;

[0006] Obtaining a distribution plan view of the wind turbines in the wind farm, and determining the relationship between the speed and direction of the wake and the blocking area of each wind turbine based on the corresponding relationship between the operating state of each wind turbine and the dynamic wake;

[0007] Based on the relationship between the speed and direction of the wake and the blocking area of each wind turbine, a dynamic wake full-field model of the wind farm is constructed;

[0008] The dynamic wake full-field model of the offshore wind farm is corrected through simulation and field test data to obtain a target dynamic wake full-field model of the offshore wind farm.

[0009] The second aspect of the present application provides a dynamic wake modeling device for offshore wind farms, comprising:

[0010] A first obtaining module is configured to obtain the operating data of each wind turbine in the wind farm for a complete year, and determine the corresponding relationship between the operating state of each wind turbine and the dynamic wake based on the operating data;

[0011] A second obtaining module is configured to obtain a distribution plan view of the wind turbines in the wind farm, and determine the relationship between the speed and direction of the wake and the blocking area of each wind turbine based on the corresponding relationship between the operating state of each wind turbine and the dynamic wake.

[0012] constructing a wind farm dynamic wake full-field model based on the relationship between the speed and direction of the wake and the blocking area of each wind turbine;

[0013] correcting the wind farm dynamic wake full-field model through simulation and field test data to obtain a target wind farm dynamic wake full-field model.

[0014] The computer device provided in the third aspect of the present application comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the method in the first aspect.

[0015] The computer storage medium provided in the fourth aspect of the present application stores computer executable instructions, and the computer executable instructions are executed by the processor to implement the method in the first aspect.

[0016] The technical solutions provided by the embodiments of the present application at least bring the following beneficial effects:

[0017] In the offshore wind farm dynamic wake modeling method, device, and storage medium provided by the present disclosure, the operation data of each wind turbine in a complete year of the wind farm is obtained, and the corresponding relationship between the operation state of each wind turbine and the dynamic wake is determined according to the operation data. A distribution plan view of the wind turbines in the wind farm is obtained, and the relationship between the speed and direction of the wake and the blocking area of each wind turbine is determined based on the corresponding relationship between the operation state of each wind turbine and the dynamic wake. A wind farm dynamic wake full-field model is constructed based on the relationship between the speed and direction of the wake and the blocking area of each wind turbine. The offshore wind farm dynamic wake full-field model is corrected through simulation and field test data to obtain a target wind farm dynamic wake full-field model. Therefore, the wind farm dynamic wake full-field model is constructed based on the relationship between the speed and direction of the wake and the blocking area of each wind turbine, and the relationship of the dynamic distribution of the wakes among the units in the field is considered. The wind farm can effectively control the wind turbines according to the wake model, thereby coordinating the wind energy captured by each unit, adjusting the wake distribution in the wind farm, optimizing the active power output efficiency of the wind farm, and maximizing the output efficiency of the wind farm.

[0018] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0019] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, including the accompanying drawings, in which:

[0020] Figure 1 FIG. 1 is a flowchart of a method for modeling a dynamic wake of an offshore wind farm according to an embodiment of the present application;

[0021] Figure 2 FIG. 2 is a schematic diagram of a device for modeling a dynamic wake of an offshore wind farm according to an embodiment of the present application. DETAILED DESCRIPTION

[0022] Embodiments of the present application are described in detail below with reference to the accompanying drawings, in which like or similar elements or components are denoted by like reference numbers throughout the various drawings. The embodiments described below are exemplary, and are intended to be illustrative of the present application rather than limiting.

[0023] A method and device for modeling a dynamic wake of an offshore wind farm according to an embodiment of the present application are described below with reference to the accompanying drawings.

[0024] Embodiment One

[0025] Figure 1 FIG. 1 is a flowchart of a method for modeling a dynamic wake of an offshore wind farm according to an embodiment of the present application, which can include: Figure 1

[0026] Step 101, obtaining operation data of each wind turbine in a complete year of the wind farm, and determining a corresponding relationship between an operation state of each wind turbine and a dynamic wake based on the operation data.

[0027] In an embodiment of the present application, the operation data of each wind turbine in a complete year of the wind farm can be obtained from a SCADA database, and the operation data can include wind speed, wind turbine power, wind turbine speed, wind turbine yaw angle, and wind turbine pitch angle.

[0028] In an embodiment of the present application, the corresponding relationship between the operation state of each wind turbine and the dynamic wake is determined by analyzing the influence of different power generation of the wind turbine on the wake velocity field under the same wind speed, and then using an existing wake model (e.g., Jensen model, AV wake model) to extend the quantitative relationship between the wake velocity and the distance to a quantitative relationship between the wake velocity and the transmission time, thereby obtaining the corresponding relationship between different parameters in the wind turbine operation data and the dynamic wake. For example, in an embodiment of the present application, different directional wake shapes and coverage areas corresponding to different yaw angles of the wind turbine are obtained. In another embodiment of the present application, wake velocities and coverage areas corresponding to different pitch angles of the wind turbine when reaching rated power are obtained.

[0029] Step 102, obtaining a distribution plan view of the wind turbines in the wind farm, and determining a relationship between the velocity and direction of the wake and the blocking area of each wind turbine based on the corresponding relationship between the operation state of each wind turbine and the dynamic wake.​

[0030] In one embodiment of the present application, the method for obtaining the relationship between the speed and direction of the wake and the blocking area of each wind turbine based on the corresponding relationship between the operating state of each wind turbine and the dynamic wake can include: based on the distribution plan, analyzing the dynamic influence of the wake of the front row of wind turbines on the downstream wind turbines to obtain the relationship between the dynamic distribution change of the wake speed field and the power generation and fatigue of the wind turbines, and further determining the relationship between the speed and direction of the wake and the blocking area of each wind turbine, and calculating the effective controllable interval of the speed and direction of the wake speed field.

[0031] In one embodiment of the present application, the analysis of the dynamic influence of the wake of the front row of wind turbines on the downstream wind turbines can include the analysis of the influence of the wake of the front row of wind turbines on the front end wind speed drop, wind direction deviation, turbulence increase, power generation drop and fatigue load of the downstream wind turbines.

[0032] Step 103, based on the relationship between the speed and direction of the wake and the blocking area of each wind turbine, a dynamic wake full-field model of the wind farm is constructed.

[0033] In one embodiment of the present application, based on the relationship between the speed and direction of the wake and the blocking area of each wind turbine, the wake model of the wind farm can be constructed based on the analysis of the interaction of multiple wind turbines arranged in series and randomly, and the factors of wind turbine diameter, wind turbine spacing and incoming flow direction.

[0034] In one embodiment of the present application, the method for constructing the dynamic wake full-field model of the wind farm based on the relationship between the speed and direction of the wake and the blocking area of each wind turbine can include: based on the relationship between the speed and direction of the wake and the blocking area of each wind turbine and the brake disc wake model algorithm, the dynamic wake full-field model of the wind farm is constructed.

[0035] Specifically, in one embodiment of the present application, the generalized actuator disc method is a method for establishing a penetrable disc in the flow field instead of the wind wheel, and the selected fluid micro-cluster is applied with a change in momentum to simulate the action of the blade. When the airflow passes through the impeller, it receives axial resistance and tangential induction force. In the actuator disc model, the tangential force and the rotation effect of the wake are ignored, and the pressure difference formed by the axial resistance is used to describe the action of the impeller in the flow field. The pressure difference before and after the impeller can be described by the following formula:

[0036]

[0037] After conversion and derivation, the above formula can be written as:

[0038]

[0039] Where Δp is the pressure difference before and after the impeller; p -P is the pressure after the impeller; p+ is the pressure before the impeller; p is the density; v is the flow velocity; v - P is the velocity after the impeller; C T P is the thrust coefficient. C T The value can be obtained according to the flow wind speed and the thrust curve, and the influence of the wind shear and the radial aerodynamic change of the blade on C T is not considered in calculation. In calculation, the volume force source term is dynamically calculated according to the wind speed change at the front end of the wind wheel combined with the thrust curve. In numerical simulation, the effect of the impeller on the airflow is realized by iteratively solving the momentum equation to which the volume force source term is added.

[0040] In an embodiment of the present application, the above-mentioned actuator disc method can be approximately considered as a spanwise distributed volume force and then uniformly distributed in the tangential direction to form a disc with uniformly distributed volume force, to replace the axial effect of the rotating blade on the flow field. The actuator disc method has lower requirements for the grid and can be valuable in large-scale simulation.

[0041] Further, in an embodiment of the present application, the time series of measurement data needs to be preprocessed. For example, assuming that the measurement data at a given time k is x k , x k is a column vector, including all the data measured at the current time, specifically the axial wind speed of all the measurement points in the three-dimensional flow field. Among them, it is assumed that M measurements are performed in the simulation experiment, and the time interval of every 2 measurements is equal. It is assumed that the flow field in the adjacent 2 time intervals has the following linear dynamics:

[0042] x k+1 = Ax k

[0043] Among them, A in the above formula is a full-dimensional linear state matrix of the flow.

[0044] And, in an embodiment of the present application, for a nonlinear flow field, this linear model is a linear approximation of the nonlinear flow field dynamics, and then the cumulative M measurements are stacked to obtain the following 2 measurement matrices:

[0045] X = [x1, x2…x N-1 ]

[0046] Y = [x2, x3…x N ]

[0047] Then the full-dimensional A matrix can be calculated by the following least square method:

[0048]

[0049] Among them, For the generalized inverse operation, the dimension of the full-dimensional state matrix A is affected by the number of state variables, which has a very high order, and needs to perform eigenvalue decomposition on the measurement matrix to extract the main modal of limited dimension.

[0050] In addition, in an embodiment of the present application, the method for constructing a dynamic wake field model of a wind farm and realizing the order reduction of the A matrix can include the following steps:

[0051] Step 1, performing r-order eigenvalue decomposition on the measurement matrix X, where r is a real number much smaller than the number of rows of X, that is:

[0052]

[0053] In the formula: Σr is an r×r non-negative diagonal matrix, K is an improved characteristic parameter, and the diagonal value is the eigenvalue of X; U r is the left eigenvector; V r is the right eigenvector, and both are right matrices.

[0054] Step 2, the calculation of the reduced state matrix A r is:

[0055]

[0056] Step 3, calculating the eigenvalue λ of A r and U r T eigenvector ω:

[0057] A r ω=λω

[0058] Step 4, the improved method corresponding to the eigenvalue λ in step 3 can be written as:

[0059] φ=KU r ω

[0060] Step 5, after the calculation is completed, the reduced model can be written as:

[0061] z k+1 =KA r z k

[0062] In the formula: z k is the reduced state variable, which can be obtained by reducing the mapping of the original state variable x k

[0063] Step 6, the equivalent method of the wind farm wake modeling of the model.

[0064] ​For the special situation of offshore wind farm, the wind farm is equivalent to a generator, all wind turbines and wind speed models are retained, the mechanical torque of wind turbines is superimposed and taken as the input of the equivalent generator. The calculation formula of equivalent parameters is:

[0065]

[0066] Step 104, the dynamic wake full-field model of the offshore wind farm is corrected through simulation and field test data, and the target dynamic wake full-field model of the wind farm is obtained.

[0067] In an embodiment of the present application, the dynamic wake full-field model of the offshore wind farm is corrected through simulation and field test data, including: the dynamic wake is simulated and analyzed through the generalized actuator disk theory combined with the CFD method, and the dynamic wake full-field model of the offshore wind farm is corrected combined with the field test data.

[0068] In an embodiment of the present application, the CFD method combines field test wind data and CFD simulation calculation to evaluate the wind condition of the wind farm, and further evaluate the power generation. Specifically, at least 12 inflow wind directions are divided according to the equal angle of wind direction for CFD simulation calculation. The CFD simulation can be completed by using the wind farm flow simulation analysis and wind resource evaluation software developed based on the open source OpenFOAM software.

[0069] Further, in an embodiment of the present application, after the dynamic wake is simulated and analyzed through the CFD method, and the dynamic wake full-field model of the offshore wind farm is corrected combined with the field test data, the target dynamic wake full-field model of the wind farm is obtained.

[0070] In an embodiment of the present application, after the target dynamic wake full-field model of the wind farm is obtained, the control strategy can be obtained by using the target dynamic wake full-field model of the wind farm, so as to coordinate the wind energy captured by each unit, adjust the wake distribution in the wind farm, and maximize the output efficiency of the wind farm.

[0071] The offshore wind farm dynamic wake modeling method, device and storage medium provided by the present disclosure, by obtaining the operation data of each wind turbine in the wind farm for a complete year, determining the corresponding relationship between the operation state of each wind turbine and the dynamic wake according to the operation data, obtaining the distribution plan view of the wind turbines in the wind farm, determining the relationship between the speed and direction of the wake and the shielding area of each wind turbine based on the corresponding relationship between the operation state of each wind turbine and the dynamic wake, constructing a full-field model of the dynamic wake of the wind farm based on the relationship between the speed and direction of the wake and the shielding area of each wind turbine, correcting the full-field model of the dynamic wake of the offshore wind farm through simulation and field test data, and obtaining a target full-field model of the dynamic wake of the wind farm. Therefore, the full-field model of the dynamic wake of the wind farm is constructed based on the relationship between the speed and direction of the wake and the shielding area of each wind turbine, the relationship between the dynamic distribution of the wakes among the units in the field is considered, the wind turbines can be effectively controlled according to the wake model, the wind energy captured by each unit is coordinated, the distribution of the wake in the wind farm is adjusted, the active power output efficiency of the wind farm is optimized, and the maximization of the output efficiency of the wind farm is realized.

[0072] Embodiment two

[0073] Figure 2 For a structure schematic diagram of a life prediction device of an offshore wind turbine according to the present application, as shown in FIG. 2, it can include:

[0074] The first obtaining module 201 is configured to obtain the operation data of each wind turbine in the wind farm for a complete year, and determine the corresponding relationship between the operation state of each wind turbine and the dynamic wake according to the operation data.

[0075] The second obtaining module 202 is configured to obtain the distribution plan view of the wind turbines in the wind farm, and determine the relationship between the speed and direction of the wake and the shielding area of each wind turbine based on the distribution plan view and the corresponding relationship between the operation state of each wind turbine and the dynamic wake.

[0076] The construction module 203 is configured to construct a full-field model of the dynamic wake of the wind farm based on the relationship between the speed and direction of the wake and the shielding area of each wind turbine.

[0077] The correction module 204 is configured to correct the full-field model of the dynamic wake of the offshore wind farm through simulation and field test data, and obtain a target full-field model of the dynamic wake of the wind farm.

[0078] The offshore wind farm dynamic wake modeling method, device and storage medium provided by the present disclosure, by obtaining the operation data of each wind turbine in the wind farm in a complete year, determining the correspondence between the operation state of each wind turbine and the dynamic wake according to the operation data, obtaining the distribution plan of the wind turbines in the wind farm, and determining the relationship between the speed and direction of the wake and the shielding area of each wind turbine based on the correspondence between the operation state of each wind turbine and the dynamic wake, constructing a full-field model of the dynamic wake of the wind farm based on the relationship between the speed and direction of the wake and the shielding area of each wind turbine, correcting the full-field model of the dynamic wake of the offshore wind farm through simulation and field test data, and obtaining the target full-field model of the dynamic wake of the wind farm. Therefore, the full-field model of the dynamic wake of the wind farm is constructed based on the relationship between the speed and direction of the wake and the shielding area of each wind turbine, the relationship of the dynamic distribution of the wakes between the units in the field is considered, the wind turbines can be effectively controlled according to the wake model, the wind energy captured by each unit is coordinated, the distribution of the wake in the wind farm is adjusted, the active power output efficiency of the wind farm is optimized, and the maximization of the output efficiency of the wind farm is realized.

[0079] To achieve the above-mentioned embodiments, the present disclosure further provides a computer device.

[0080] The computer device provided by the embodiments of the present disclosure comprises a memory, a processor and a computer program stored in the memory and executable on the processor; when the processor executes the program, the method shown in Figure 1 can be implemented.

[0081] To achieve the above-mentioned embodiments, the present disclosure further provides a computer storage medium.

[0082] The computer storage medium provided by the embodiments of the present disclosure stores computer executable instructions; after the computer executable instructions are executed by the processor, the method shown in Figure 1 can be implemented.

[0083] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any suitable manner in any one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the present specification and the features of the different embodiments or examples without contradiction.

[0084] Any processes or methods described in the flow charts or otherwise described herein can be understood as representing modules, segments, or portions of code that include one or more executable instructions for implementing the specified logical functions or steps, and the preferred embodiments of the application include additional or fewer steps, in other orders, with other functionality, in implementations of these preferred embodiments of the application. Thus, any of the steps, options, aspects, components, etc. discussed herein can be included or deleted in other embodiments of the application, and yet still be deemed to fall within the scope of the present application.

[0085] Although the embodiments of the present application have been shown and described above, it should be understood by those ordinary skilled in the art that the above embodiments are exemplary and cannot be construed as limiting the present application, and those ordinary skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

Claims

1. A method of dynamic wake modelling for an offshore wind farm, characterized in that, The method comprises: obtaining operation data of each wind turbine in a wind farm in a complete year, and determining a corresponding relationship between the operation state of each wind turbine and dynamic wake based on the operation data; obtaining a distribution plan view of wind turbines in the wind farm, and determining a relationship between the speed and direction of the wake and the blocking area of each wind turbine based on the corresponding relationship between the operation state of each wind turbine and the dynamic wake, wherein the relationship comprises: based on the distribution plan view, analyzing the dynamic influence of the wake of the front row of wind turbines on the downstream wind turbines to obtain the relationship between the dynamic distribution change of the wake speed field and the power generation and fatigue of the wind turbine, determining the relationship between the speed and direction of the wake and the blocking area of each wind turbine, and calculating the effective controllable interval of the speed and direction of the wake speed field, wherein the dynamic influence comprises analyzing the influence of the wake of the front row of wind turbines on the front end wind speed drop, wind direction deviation, turbulence increase, power generation drop and fatigue load of the downstream wind turbines; based on the relationship between the speed and direction of the wake and the blocking area of each wind turbine, constructing a dynamic wake full-field model of the offshore wind farm, comprising: based on the relationship between the speed and direction of the wake and the blocking area of each wind turbine and the brake disc wake model algorithm, constructing a dynamic wake full-field model of the offshore wind farm; the dynamic wake full-field model of the offshore wind farm is corrected through simulation and field test data to obtain a target dynamic wake full-field model of the offshore wind farm.

2. The method of claim 1, wherein, The operation data includes wind speed, wind turbine power, wind turbine speed, wind turbine yaw angle, and wind turbine pitch angle.

3. The method of claim 1, wherein, The dynamic wake full-field model of the offshore wind farm is corrected through simulation and field test data, comprising: simulating and analyzing the dynamic wake by the generalized actuator disc theory combined with the CFD method, and correcting the dynamic wake full-field model of the offshore wind farm combined with the field test data.

4. The method of claim 1, wherein, The method further comprises: using the target dynamic wake full-field model of the offshore wind farm to obtain a control strategy to coordinate the wind energy captured by each unit, adjust the wake distribution in the wind farm, and maximize the output efficiency of the wind farm.

5. An offshore wind farm dynamic wake modelling apparatus, characterized in that, The device comprises: a first obtaining module for obtaining operation data of each wind turbine in a wind farm in a complete year, and determining a corresponding relationship between the operation state of each wind turbine and dynamic wake based on the operation data; a second obtaining module for obtaining a distribution plan view of wind turbines in the wind farm, and determining a relationship between the speed and direction of the wake and the blocking area of each wind turbine based on the corresponding relationship between the operation state of each wind turbine and the dynamic wake, wherein the relationship comprises: based on the distribution plan view, analyzing the dynamic influence of the wake of the front row of wind turbines on the downstream wind turbines to obtain the relationship between the dynamic distribution change of the wake speed field and the power generation and fatigue of the wind turbine, determining the relationship between the speed and direction of the wake and the blocking area of each wind turbine, and calculating the effective controllable interval of the speed and direction of the wake speed field, wherein the dynamic influence comprises analyzing the influence of the wake of the front row of wind turbines on the front end wind speed drop, wind direction deviation, turbulence increase, power generation drop and fatigue load of the downstream wind turbines; a construction module for constructing a dynamic wake full-field model of the offshore wind farm based on the relationship between the speed and direction of the wake and the blocking area of each wind turbine; The correction module is configured to correct the dynamic wake full-field model of the offshore wind farm by simulation and field test data, and obtain a target dynamic wake full-field model of the offshore wind farm. The construction module is further configured to: construct the dynamic wake full-field model of the offshore wind farm based on the relationship between the speed and direction of the wake and the blocking area of each wind turbine and the brake disc wake model algorithm.

6. The apparatus of claim 5, wherein, The operation data include wind speed, wind turbine power, wind turbine speed, wind turbine yaw angle, and wind turbine pitch angle.

7. A computer device, comprising: The computer program is stored in the memory and executable on the processor, and the processor executes the program to implement the method of any one of claims 1-4.

8. A computer storage medium, wherein, The computer storage medium stores computer executable instructions; the computer executable instructions are executed by the processor to implement the method of any one of claims 1-4.

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