A wind power base flow field simulation method and device, computer equipment and medium

Abstract

The present application relates to the field of new energy, and provides a wind power base flow field simulation method and device, computer equipment and medium. Wherein, the wind power base flow field simulation method comprises: obtaining unit data of each wind farm in the wind power base where the target wind farm is located; calculating the equivalent roughness of each wind farm according to each unit data and a pre-constructed large eddy simulation model; simulating the first preset scale component and the second preset scale component of the target wind farm according to each equivalent roughness. Through the present application, the flow field distribution of the target wind farm is accurately simulated according to the wake effect of multiple wind farms in the wind power base.

Description

Technical Field

[0001] This invention relates to the field of new energy, and in particular to a method, apparatus, computer equipment, and medium for simulating the flow field of a wind power base. Background Technology

[0002] When carrying out the operation and maintenance of new energy power plants, it is necessary to assess the resources of the new energy power plants. In large-scale wind farms, the wake effect and refined simulation technology of large wind power bases are important technical problems that hinder the development of wind power bases.

[0003] Currently, the main simulation and evaluation method for assessing wind resources (flow field characteristics) within large-scale wind farms is the wake superposition method based on the wake of a single turbine. The wake superposition method is commonly used in engineering and has been integrated into wind farm design software such as WindSim and WASP.

[0004] However, in wind power bases, the wake effects of multiple wind farms can influence each other. The wake superposition method based on single-unit wakes only considers the wake effect of a single wind farm and cannot effectively assess the inter-farm wake effects between multiple wind farms, thus making it impossible to accurately simulate the flow field distribution in the area where the wind farms are located. Summary of the Invention

[0005] To accurately simulate the flow field distribution in the area where the target wind farm is located, this invention proposes a method, device, computer equipment, and medium for simulating the flow field of a wind power base.

[0006] In a first aspect, the present invention provides a method for simulating the flow field of a wind power base, the method comprising:

[0007] Obtain the turbine data of each wind farm in the wind power base where the target wind farm is located;

[0008] Based on the data of each unit and the pre-built large eddy simulation model, the equivalent roughness of each wind farm is calculated;

[0009] Based on each equivalent roughness, the first and second preset scale components of the target wind farm are simulated.

[0010] The momentum gained by a single wind farm comes from the momentum difference of the airflow upstream and downstream of the turbine. However, large wind farms can reach several kilometers or even tens of kilometers in size, and the flow direction within the wind farm is stable. In this case, the main momentum absorbed by the wind turbine comes from the vertical transport of momentum across the entire wind farm. Therefore, the flow field distribution of the target wind farm should consider the interaction between multiple wind farms and the atmospheric boundary layer within the wind farm, rather than just the wake effect of a single wind farm. Using the above method, the turbine data of multiple wind farms in the wind power base where the target wind farm is located are input into a high-precision large eddy simulation model to calculate the equivalent roughness of each wind farm. Then, based on the equivalent roughness of multiple wind farms, the first and second preset scale wind volumes in the target wind farm are simulated. The equivalent roughness of multiple wind farms is used to characterize the flow field influence of each wind farm in the wind power base on the target wind farm, and to simulate the wake effect of the target wind farm. Compared with related technologies that only consider the wake effect of a single wind farm, the method provided by this invention takes into account the mutual influence between the flow field distributions of multiple wind farms in the wind power base, thereby improving the accuracy of simulating the flow field distribution of the target wind farm.

[0011] In one alternative implementation, the equivalent roughness of the wind farm is calculated based on unit data and a pre-built large eddy simulation model, including:

[0012] Calculate the total thrust of the wind farm based on the turbine data;

[0013] The equivalent roughness of the wind farm is calculated based on the total thrust of the wind farm and the large eddy simulation model.

[0014] In one optional implementation, the total thrust of the wind farm is calculated based on the turbine data, including:

[0015] Calculate the wall stress of the wind farm based on the turbine data;

[0016] Using wall stress as a boundary condition, the total thrust of the wind farm is calculated using a pre-built actuated disk model.

[0017] In one optional implementation, the equivalent roughness of the wind farm is calculated based on the total thrust of the wind farm and a large eddy simulation model, including:

[0018] Using the total thrust of the wind farm as a boundary condition, the equivalent roughness of the wind farm is calculated using a large eddy simulation model.

[0019] In one optional implementation, simulating a first preset scale component and a second preset scale component of the target wind farm based on each equivalent roughness includes:

[0020] Based on the equivalent roughness, a flow field distribution model for the wind power base is established;

[0021] The flow field distribution model is input into the large eddy simulation model to obtain the first preset scale component of the target wind farm;

[0022] The flow field distribution model is input into the pre-constructed eddy viscosity model to obtain the second preset scale component of the target wind farm.

[0023] In one optional implementation, the large eddy simulation model includes horizontal boundary conditions, top boundary conditions, and bottom boundary conditions of the computational domain. Periodic boundary conditions are used as horizontal boundary conditions of the computational domain, zero vertical velocity and zero stress are used as top boundary conditions of the computational domain, and zero vertical velocity is used as bottom boundary conditions of the computational domain.

[0024] In one alternative implementation, the method further includes:

[0025] The turbine data of the target wind farm are determined based on the first and second preset scale components.

[0026] In one alternative implementation, the unit data includes at least one of unit layout and unit type.

[0027] Secondly, the present invention also provides a wind power base flow field simulation device, the device comprising:

[0028] The acquisition module is used to acquire the turbine data of each wind farm in the wind power base where the target wind farm is located;

[0029] The calculation module is used to calculate the equivalent roughness of each wind farm based on the data of each unit and the pre-built large eddy simulation model.

[0030] The simulation module is used to simulate the first and second preset scale components of the target wind farm based on each equivalent roughness.

[0031] The momentum gained by a single wind farm comes from the momentum difference of the airflow upstream and downstream of the turbine. However, large wind farms can reach several kilometers or even tens of kilometers in size, and the flow direction within the wind farm is stable. In this case, the main momentum absorbed by the wind turbine comes from the vertical transport of momentum across the entire wind farm. Therefore, the flow field distribution of the target wind farm should consider the interaction between multiple wind farms and the atmospheric boundary layer within the wind farm, rather than just the wake effect of a single wind farm. Using the aforementioned device, the turbine data of multiple wind farms in the wind power base where the target wind farm is located are input into a high-precision large eddy simulation model to calculate the equivalent roughness of each wind farm. Then, based on the equivalent roughness of multiple wind farms, the first and second preset scale wind volumes in the target wind farm are simulated. The equivalent roughness of multiple wind farms is used to characterize the flow field influence of each wind farm in the wind power base on the target wind farm, simulating the wake effect of the target wind farm. Compared with related technologies that only consider the wake effect of a single wind farm, the device provided by this invention takes into account the mutual influence between the flow field distributions of multiple wind farms in the wind power base, improving the accuracy of simulating the flow field distribution of the target wind farm.

[0032] In one alternative implementation, the computing module includes:

[0033] The first calculation submodule is used to calculate the total thrust of the wind farm based on the turbine data of the wind farm;

[0034] The second calculation submodule is used to calculate the equivalent roughness of the wind farm based on the total thrust of the wind farm and the large eddy simulation model.

[0035] In one alternative implementation, the first computing submodule includes:

[0036] The first calculation unit is used to calculate the wall stress of the wind farm based on the turbine data of the wind farm.

[0037] The second calculation unit is used to calculate the total thrust of the wind farm by using the wall stress as a boundary condition and a pre-built actuation disk model.

[0038] In one optional implementation, the second computing submodule includes:

[0039] The third calculation unit is used to calculate the equivalent roughness of the wind farm by using the total thrust of the wind farm as the boundary condition and the large eddy simulation model.

[0040] In one alternative implementation, the simulation module includes:

[0041] A submodule is established to create a flow field distribution model for the wind power base based on various equivalent roughnesses;

[0042] The third calculation submodule is used to input the flow field distribution model into the large eddy simulation model to obtain the first preset scale component of the target wind farm.

[0043] The fourth calculation submodule is used to input the flow field distribution model into the pre-constructed eddy viscosity model to obtain the second preset scale component of the target wind farm.

[0044] Thirdly, the present invention also provides a computer device, including a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the steps of the wind power base flow field simulation method of the first aspect or any embodiment of the first aspect.

[0045] Fourthly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the wind power base flow field simulation method of the first aspect or any embodiment of the first aspect. Attached Figure Description

[0046] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0047] Figure 1 This is a flowchart of a wind power base flow field simulation method according to an exemplary embodiment;

[0048] Figure 2 This is a schematic diagram of the calculation method for simulating the flow field at a wind power base, in one example.

[0049] Figure 3 This is a schematic diagram of the structure of a wind power base flow field simulation device according to an exemplary embodiment;

[0050] Figure 4 This is a schematic diagram of the hardware structure of a computer device according to an exemplary embodiment. Detailed Implementation

[0051] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0053] To accurately simulate the flow field distribution in the area where the target wind farm is located, this invention proposes a method, device, computer equipment, and medium for simulating the flow field of a wind power base.

[0054] Figure 1 This is a flowchart of a wind power base flow field simulation method according to an exemplary embodiment. Figure 1 As shown, the wind power base flow field simulation method includes the following steps S101 to S103.

[0055] Step S101: Obtain the turbine data of each wind farm in the wind power base where the target wind farm is located.

[0056] In one alternative embodiment, the wind power base includes multiple wind farms.

[0057] In one optional embodiment, the turbine data of the wind farm includes information such as the spacing between wind turbines in the wind farm, the diameter of the rotor, and the height of the hub, without any specific limitations.

[0058] In one optional embodiment, the target wind farm is a wind farm to be constructed, and the turbine data of the target wind farm can be determined based on the wake effect of the wind power base where the target wind farm is located.

[0059] Step S102: Calculate the equivalent roughness of each wind farm based on the data of each unit and the pre-built large eddy simulation model.

[0060] In one alternative embodiment, the Large Eddy Simulation (LES) model is a numerical simulation research method based on fluid mechanics. The LES model differs from Direct Numerical Simulation (DNS) and Reynolds Equation (RANS) methods by accurately solving for the motion at all turbulent scales above a certain scale. This allows it to capture unsteady data, large-scale effects in non-equilibrium processes, and pseudo-order structures that cannot be described by the Reynolds Equation method. Simultaneously, it overcomes the enormous computational overhead of direct numerical simulation methods, which require solving for all turbulent scales.

[0061] In one alternative embodiment, roughness is one of the indicators for measuring the magnitude of the frictional force between the ground and the wind. Generally, the flatter and smoother the ground, the lower the roughness. In a logarithmic wind profile, roughness represents the height at which the wind speed is zero. If wind turbines are considered as "rough elements," the presence of the wind farm increases the roughness; this roughness is called the equivalent roughness of the wind farm. The equivalent roughness of a wind farm essentially treats the wind farm as a special type of "terrain," and its main influencing factors include the spacing between wind turbines, rotor diameter, hub height, the operating state of the wind turbines, the original ground roughness, and atmospheric stability.

[0062] Step S103: Simulate the first preset scale component and the second preset scale component of the target wind farm according to each equivalent roughness.

[0063] In one optional embodiment, the first preset scale component and the second preset scale component are components of two different scales. Turbulent motion in the flow field is composed of many vortices of varying sizes. Large vortices have a significant impact on the average flow, while small vortices influence large-scale motion through nonlinear effects. A large amount of mass, heat, momentum, and energy exchange occurs through large vortices, while the effect of small vortices is dissipation. The first preset scale component characterizes the turbulent motion within large vortices, and the second preset scale component characterizes the turbulent motion within small vortices.

[0064] In one optional embodiment, the first preset scale wind volume is a large-scale component, also called the flow field distribution component, which is mainly characterized by the velocity field of the wind farm.

[0065] In one optional embodiment, the second preset scale component is a small-scale component, also called the boundary layer structure, which can be characterized by the deviatoric stress of the subgrid stress.

[0066] The momentum gained by a single wind farm comes from the momentum difference of the airflow upstream and downstream of the turbine. However, large wind farms can reach several kilometers or even tens of kilometers in size, and the flow direction within the wind farm is stable. In this case, the main momentum absorbed by the wind turbine comes from the vertical transport of momentum across the entire wind farm. Therefore, the flow field distribution of the target wind farm should consider the interaction between multiple wind farms and the atmospheric boundary layer within the wind farm, rather than just the wake effect of a single wind farm. Using the above method, the turbine data of multiple wind farms in the wind power base where the target wind farm is located are input into a high-precision large eddy simulation model to calculate the equivalent roughness of each wind farm. Then, based on the equivalent roughness of multiple wind farms, the first and second preset scale wind volumes in the target wind farm are simulated. The equivalent roughness of multiple wind farms is used to characterize the flow field influence of each wind farm in the wind power base on the target wind farm, and to simulate the wake effect of the target wind farm. Compared with related technologies that only consider the wake effect of a single wind farm, the method provided by this invention takes into account the mutual influence between the flow field distributions of multiple wind farms in the wind power base, improves the accuracy of simulating the flow field distribution of the target wind farm, and provides a reasonable basis for designing the target wind farm.

[0067] In one example, in step S102 above, the equivalent roughness of the wind farm is calculated through the following steps:

[0068] Step a1: Calculate the total thrust of the wind farm based on the turbine data.

[0069] In an alternative embodiment, total thrust refers to the thrust acting on the fluid generated by the interaction between the fluid and the rotating blades of the wind turbine.

[0070] Step a2: Calculate the equivalent roughness of the wind farm based on the total thrust of the wind farm and the large eddy simulation model.

[0071] In an optional embodiment, in step a1 above, the total thrust of the wind farm is calculated as follows:

[0072] First, the wall stress of the wind farm is calculated based on the turbine data.

[0073] Then, using the wall stress as a boundary condition, the total thrust of the wind farm is calculated using a pre-built actuated disk model.

[0074] In this embodiment of the invention, to calculate the instantaneous local wall stress at each grid point, a wall stress boundary condition is applied on the bottom surface, and the instantaneous wall stress is correlated with the velocity of the first grid point using the standard logarithmic law. The calculated wall stress can be expressed as follows:

[0075]

[0076] Where, τ w (x,y) represents the wall stress at coordinates (x,y), u * Represents friction speed; The local filtering speed represents the speed at which the first horizontal plane is reached. These represent the local flow-averaged velocity and local spanwise average velocity obtained by filtering the velocity field according to the 2Δ size, respectively; z represents the vertical direction; z 0,lo κ represents aerodynamic surface roughness; κ represents the KAMAN constant.

[0077] The actuation disk model assumes that the load is uniformly distributed on the rotor plane and that the generated force is distributed only along the axial direction, neglecting the wake rotation effect. Therefore, in the x-direction, the total thrust acting on the entire wind turbine is:

[0078]

[0079] Among them, F t Represents total thrust; ρ represents fluid density; C T U represents the thrust coefficient. ∞ D represents the incoming airflow velocity; D represents the rotor diameter; U d U represents the speed of the actuator disk. ∞ =U d (1-a), where a represents the axial induction factor, which can be obtained through one-dimensional momentum theory.

[0080] In this embodiment of the invention, the total thrust of the wind farm is obtained by solving for the average actuator disk velocity. Specifically, the total thrust can be calculated using the following formula:

[0081]

[0082] Among them, C T 'Represents the thrust coefficient, C T '=C T / (1-a) 2 C T Represents the Betz limit, 'a' represents the axial induction factor, and C represents the axial induction factor. T =8 / 9, a=1 / 3, C T =2; This represents the average speed obtained by averaging the speed over a certain time period T in the plane region of the wind turbine. The superscript T indicates that the averaging occurs over time T, and the subscript d indicates that the averaging occurs within the plane of the wind turbine; D represents the diameter of the wind turbine.

[0083] In an optional embodiment, in step a2 above, the total thrust of the wind farm is used as a boundary condition, and the equivalent roughness of the wind farm is calculated using a large eddy simulation model.

[0084] In one example, in step S103 above, the first and second preset scale components of the target wind farm are simulated through the following steps:

[0085] Step b1: Establish the flow field distribution model of the wind power base based on the equivalent roughness of each wind farm. That is, based on the obtained equivalent roughness of each wind farm, the flow field distribution of the entire wind power base under the action of multiple wind farms is obtained.

[0086] Step b2: Input the flow field distribution model into the large eddy simulation model to obtain the first preset scale component of the target wind farm. For example, the flow field distribution model is used as the boundary condition in the large eddy simulation model, and the first preset scale component of the target wind farm can be obtained through the large eddy simulation model.

[0087] In an optional embodiment, in the large eddy simulation model, the transient variables of the fluid are divided into two parts by a filtering function: a large-scale component (first preset-scale component) and a small-scale component (second preset-scale component). In the large eddy simulation model, the equations of motion for the first preset-scale component are a continuity equation and an incompressible momentum equation, which are expressed as follows:

[0088]

[0089]

[0090] Among them, ~ represents the use of Physical quantities after scale-space filtering; t represents time; ρ represents fluid density; This represents the velocity field in the i-direction after filtering. This represents the velocity field in the j-direction after filtering (when i = 1, 2, 3, it represents the flow direction x, spanwise y, and perpendicular direction z, respectively). It consists of velocity components in three directions; This represents the correction pressure after filtering. in The pressure deviation for applying the average pressure field; x i x j These are the components pointing towards x in the i-direction and the j-direction, respectively; τ ij Represents subgrid stress, Its deviatoric stress Calculated using a Lagrange-scale related dynamic model; δ ij Represents the Kronecker function, its trace (τ) kk / 3) Included in the corrected pressure, τ kk It is the isotropic part of the subgrid stress; This represents the pressure gradient applied in the x1 direction, used to generate an average inflow perpendicular to the wind turbine plane, through... Define a constant frictional velocity u *hi As a reference value, the speed is obtained via u. *hi Dimensionless, time scale via H / u *hi Dimensionless, p represents the partial derivative in the x-direction. ∞ The pressure value representing infinity, i.e., atmospheric pressure, is represented by P and H; f i This represents volume force and is used to simulate the influence of wind turbines in the momentum equation.

[0091] In the large eddy simulation model, molecular dissipation can be ignored because the Reynolds number at the atmospheric boundary is very high (usually greater than 108), and the viscous flow near the ground is not solved. Therefore, the viscous term is ignored in the momentum equation.

[0092] In one alternative implementation, the large eddy simulation model includes horizontal boundary conditions of the computational domain, top boundary conditions of the computational domain, and bottom boundary conditions of the computational domain.

[0093] In this embodiment of the invention, periodic boundary conditions (PBCs) are used as the horizontal boundary conditions of the computational domain. Periodic boundary conditions reflect how the boundary conditions are used to replace the influence of the surrounding environment on the selected part (system). Exemplarily, periodic boundary conditions can be continuous periodic boundaries, antisymmetric periodic boundaries, Froquet periodic boundaries, cyclic symmetric boundaries, etc., without specific limitations.

[0094] In this embodiment of the invention, zero vertical velocity and zero stress are used as the top boundary conditions of the computational domain, i.e.

[0095]

[0096] in, Represents the partial derivative in the vertical direction; This represents the velocity field in the flow direction and span after passing through the filtering function; This represents the velocity field in the direction perpendicular to the filter function; These represent the velocity components in the flow rate, spanwise direction, and vertical direction after passing through the filtering function, respectively; z represents the vertical direction.

[0097] In this embodiment of the invention, the vertical velocity is zero as the boundary condition at the bottom of the computational domain. A balanced wall model is used at the bottom of the computational domain. Due to the use of staggered meshes, the horizontal velocity is only stored at a distance of Δz / 2 above the surface; therefore, no boundary condition for the horizontal velocity is required at the bottom of the computational domain.

[0098] Step b3: Input the flow field distribution model into the pre-constructed eddy viscosity model to obtain the second preset scale component of the target wind farm.

[0099] In the large eddy simulation model, all turbulent structures larger than the filter size in the filter function are solvable. The effects of unsolvable small-scale eddies on the flow field require modeling and calculation. Subgrid stress represents the influence of small-scale eddies on the equations of motion. Since the velocity fields in the i-direction and j-direction after filtering cannot be simultaneously determined in numerical simulations, the deviatoric stresses of the subgrid stresses in the aforementioned momentum equations are unknown. Therefore, a subgrid stress model needs to be constructed to calculate the deviatoric stresses of the subgrid stresses.

[0100] In this embodiment of the invention, the deviatoric stress of the subgrid stress is calculated using the eddy viscosity model:

[0101]

[0102] in, The deviatoric stress representing the subgrid stress; τ ij Represents subgrid stress; τ kk It is the isotropic part of the subgrid stress; δ ij Represents the Kronecker function; The strain rate tensor represents solvable scale turbulence. Its size is (Strain rate); ν sgs The subgrid eddy viscosity can be obtained using the mixing length approximation method. C s This represents the eddy viscosity coefficient (Smagorinsky coefficient).

[0103] In one example, the method provided by this embodiment of the invention further includes:

[0104] Based on the first and second preset scale components of the target wind farm, the turbine data of the target wind farm is determined. In other words, the first and second preset scale components of the target wind farm are used as the basis for designing the turbine data of the target wind farm, and the spacing distribution of the target wind farm is determined through the obtained preset scale components, etc.

[0105] In one optional embodiment, the turbine data of the target wind farm includes at least one of turbine layout and turbine type. The turbine layout can be either layout density or turbine spacing. For example, when the turbine data includes turbine spacing, the wind farm can be divided into three types according to the turbine spacing: medium-spacing wind farms, wind farms with large flow-direction spacing, and wind farms with large spanwise spacing. The first preset scale component and the second preset scale component characterize the influence of other wind farms in the wind farm base on the wake effect of the target wind farm. The turbine layout spacing of the target wind farm can be determined using the first preset scale component and the second preset scale component.

[0106] Figure 2 This is a schematic diagram illustrating the specific calculation method for simulating the flow field at a wind power base. For example... Figure 2 As shown, the wind power base includes four wind farms: Wind Farm 1, Wind Farm 2, Wind Farm 3, and the target wind farm 4 to be designed. The total thrust of each wind farm is calculated based on the turbine data of Wind Farm 1, Wind Farm 2, and Wind Farm 3. Then, the equivalent roughness of each wind farm is calculated based on the total thrust. The flow field boundary conditions in the large eddy simulation model are determined based on the equivalent roughness of each wind farm. This yields the first preset scale component (flow field component) and the second preset scale component (boundary layer structure) of the target wind farm under the influence of other wind farms. Based on the flow field component and boundary layer structure, the design of the target wind farm is adjusted.

[0107] Based on the same inventive concept, embodiments of the present invention also provide a wind power base flow field simulation device, such as... Figure 3 As shown, the device includes:

[0108] The acquisition module 301 is used to acquire the unit data of each wind farm in the wind power base where the target wind farm is located; for details, please refer to the description of step S101 in the above embodiment, which will not be repeated here.

[0109] The calculation module 302 is used to calculate the equivalent roughness of each wind farm based on the data of each unit and the pre-built large eddy simulation model; for details, please refer to the description of step S102 in the above embodiment, which will not be repeated here.

[0110] The simulation module 303 is used to simulate the first preset scale component and the second preset scale component of the target wind farm according to each equivalent roughness. For details, please refer to the description of step S103 in the above embodiments, which will not be repeated here.

[0111] The momentum gained by a single wind farm comes from the momentum difference of the airflow upstream and downstream of the turbine. However, large wind farms can reach several kilometers or even tens of kilometers in size, and the flow direction within the wind farm is stable. In this case, the main momentum absorbed by the wind turbine comes from the vertical transport of momentum across the entire wind farm. Therefore, the flow field distribution of the target wind farm should consider the interaction between multiple wind farms and the atmospheric boundary layer within the wind farm, rather than just the wake effect of a single wind farm. Using the aforementioned device, the turbine data of multiple wind farms in the wind power base where the target wind farm is located are input into a high-precision large eddy simulation model to calculate the equivalent roughness of each wind farm. Then, based on the equivalent roughness of multiple wind farms, the first preset scale wind volume and the second preset scale wind volume in the target wind farm are simulated. The equivalent roughness of multiple wind farms is used to characterize the flow field influence of each wind farm in the wind power base on the target wind farm, and to simulate the wake effect of the target wind farm. Compared with related technologies that only consider the wake effect of a single wind farm, the device provided in this embodiment of the invention takes into account the mutual influence between the flow field distributions of multiple wind farms in the wind power base, thereby improving the accuracy of simulating the flow field distribution of the target wind farm.

[0112] In one example, the calculation module 302 includes:

[0113] The first calculation submodule is used to calculate the total thrust of the wind farm based on the turbine data of the wind farm; for details, please refer to the description in the above embodiments, and will not be repeated here.

[0114] The second calculation submodule is used to calculate the equivalent roughness of the wind farm based on the total thrust of the wind farm and the large eddy simulation model. For details, please refer to the description in the above embodiments, which will not be repeated here.

[0115] In one example, the first computational submodule includes:

[0116] The first calculation unit is used to calculate the wall stress of the wind farm based on the turbine data of the wind farm; for details, please refer to the description in the above embodiments, and will not be repeated here.

[0117] The second calculation unit is used to calculate the total thrust of the wind farm by using the wall stress as a boundary condition and a pre-built actuation disk model. For details, please refer to the description in the above embodiments, which will not be repeated here.

[0118] In one example, the second computational submodule includes:

[0119] The third calculation unit is used to calculate the equivalent roughness of the wind farm using the total thrust of the wind farm as a boundary condition and a large eddy simulation model. For details, please refer to the description in the above embodiments, which will not be repeated here.

[0120] In one example, simulation module 303 includes:

[0121] A submodule is established to build a flow field distribution model for the wind power base based on each equivalent roughness; for details, please refer to the description in the above embodiments, which will not be repeated here.

[0122] The third calculation submodule is used to input the flow field distribution model into the large eddy simulation model to obtain the first preset scale component of the target wind farm; for details, please refer to the description in the above embodiments, which will not be repeated here.

[0123] The fourth calculation submodule is used to input the flow field distribution model into the pre-constructed eddy viscosity model to obtain the second preset scale component of the target wind farm. For details, please refer to the description in the above embodiments, which will not be repeated here.

[0124] In one example, in this device, the large eddy simulation model includes horizontal boundary conditions, top boundary conditions, and bottom boundary conditions of the computational domain. Periodic boundary conditions are used as horizontal boundary conditions, zero vertical velocity and zero stress are used as top boundary conditions, and zero vertical velocity is used as bottom boundary conditions. For details, please refer to the description in the above embodiments, which will not be repeated here.

[0125] In one example, the device also includes:

[0126] The determination module is used to determine the turbine data of the target wind farm based on a first preset scale component and a second preset scale component. For details, please refer to the description in the above embodiments, which will not be repeated here.

[0127] In one example, the unit data acquired in module 301 includes at least one of unit layout and unit type. For details, please refer to the description in the above embodiments, which will not be repeated here.

[0128] The specific limitations and beneficial effects of the aforementioned device can be found in the above description of the flow field simulation method for wind power bases, and will not be repeated here. Each of the above modules can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0129] Figure 4 This is a schematic diagram of the hardware structure of a computer device according to an exemplary embodiment. For example... Figure 4 As shown, the device includes one or more processors 410 and a memory 420, which includes persistent memory, volatile memory, and a hard disk. Figure 4 Taking a processor 410 as an example, the device may also include an input device 430 and an output device 440.

[0130] The processor 410, memory 420, input device 430, and output device 440 can be connected via a bus or other means. Figure 4 Taking the example of a connection between China and Israel via a bus.

[0131] Processor 410 can be a Central Processing Unit (CPU). Processor 410 can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations thereof. The general-purpose processor can be a microprocessor or any conventional processor.

[0132] The memory 420, as a non-transitory computer-readable storage medium, includes persistent memory, volatile memory, and a hard disk. It can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the wind power base flow field simulation method in this embodiment. The processor 410 executes various server functions and data processing by running the non-transitory software programs, instructions, and modules stored in the memory 420, thereby implementing any of the aforementioned wind power base flow field simulation methods.

[0133] The memory 420 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data that is needed and required. Furthermore, the memory 420 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 420 may optionally include memory remotely located relative to the processor 410, and these remote memories can be connected to the data processing device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0134] Input device 430 can receive input digital or character information, and generate signal inputs related to user settings and function control. Output device 440 may include display devices such as a display screen.

[0135] One or more modules are stored in memory 420, and when executed by one or more processors 410, they perform actions such as... Figure 1 The method shown.

[0136] The above-described product can execute the method provided in the embodiments of the present invention, and has the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in this embodiment can be found in [reference 1]. Figure 1 The relevant descriptions in the illustrated embodiments.

[0137] This invention also provides a non-transitory computer storage medium storing computer-executable instructions that can execute the methods described in any of the above method embodiments. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium may also include combinations of the above types of memory.

[0138] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0139] The above are merely specific embodiments of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for simulating the flow field in a wind power base, characterized in that, The method includes: Obtain the turbine data of each wind farm in the wind power base where the target wind farm is located; Based on the data of each unit and the pre-constructed large eddy simulation model, the equivalent roughness of each wind farm is calculated. Based on the equivalent roughness described above, simulate the first and second preset scale components of the target wind farm; Based on the aforementioned equivalent roughness, the simulation of the first and second preset scale components of the target wind farm includes: Based on the equivalent roughness described above, a flow field distribution model for the wind power base is established. The flow field distribution model is input into the large eddy simulation model to obtain the first preset scale component of the target wind farm; The flow field distribution model is input into a pre-constructed eddy viscosity model to obtain the second preset scale component of the target wind farm.

2. The method according to claim 1, characterized in that, Based on the unit data and the pre-constructed large eddy simulation model, the equivalent roughness of the wind farm is calculated, including: Calculate the total thrust of the wind farm based on the turbine data of the wind farm; The equivalent roughness of the wind farm is calculated based on the total thrust of the wind farm and the large eddy simulation model.

3. The method according to claim 2, characterized in that, Based on the turbine data of the wind farm, calculate the total thrust of the wind farm, including: Calculate the wall stress of the wind farm based on the turbine data of the wind farm; Using the wall stress as a boundary condition, the total thrust of the wind farm is calculated using a pre-built actuation disk model.

4. The method according to claim 2, characterized in that, Based on the total thrust of the wind farm and the large eddy simulation model, the equivalent roughness of the wind farm is calculated, including: Using the total thrust of the wind farm as a boundary condition, the equivalent roughness of the wind farm is calculated using the large eddy simulation model.

5. The method according to claim 1, characterized in that, The large eddy simulation model includes horizontal boundary conditions, top boundary conditions, and bottom boundary conditions of the computational domain. Periodic boundary conditions are used as horizontal boundary conditions of the computational domain, zero vertical velocity and zero stress are used as top boundary conditions of the computational domain, and zero vertical velocity is used as bottom boundary conditions of the computational domain.

6. The method according to claim 1, characterized in that, The method further includes: The turbine data of the target wind farm are determined based on the first preset scale component and the second preset scale component.

7. The method according to claim 1, characterized in that, The unit data includes at least one of the following: unit layout and unit type.

8. A wind power base flow field simulation device, characterized in that, The device includes: The acquisition module is used to acquire the turbine data of each wind farm in the wind power base where the target wind farm is located; The calculation module is used to calculate the equivalent roughness of each wind farm based on the data of each unit and the pre-built large eddy simulation model. The simulation module is used to simulate the first preset scale component and the second preset scale component of the target wind farm according to the equivalent roughness. The simulation module includes: A submodule is established to build a flow field distribution model of the wind power base based on the equivalent roughness of each of the aforementioned components. The third calculation submodule is used to input the flow field distribution model into the large eddy simulation model to obtain the first preset scale component of the target wind farm; The fourth calculation submodule is used to input the flow field distribution model into the pre-constructed eddy viscosity model to obtain the second preset scale component of the target wind farm.

9. The apparatus according to claim 8, characterized in that, The computing module includes: The first calculation submodule is used to calculate the total thrust of the wind farm based on the turbine data of the wind farm. The second calculation submodule is used to calculate the equivalent roughness of the wind farm based on the total thrust of the wind farm and the large eddy simulation model.

10. The apparatus according to claim 9, characterized in that, The first calculation submodule includes: The first calculation unit is used to calculate the wall stress of the wind farm based on the turbine data of the wind farm. The second calculation unit is used to calculate the total thrust of the wind farm by using the wall stress as a boundary condition and a pre-built actuation disk model.

11. The apparatus according to claim 9, characterized in that, The second calculation submodule includes: The third calculation unit is used to calculate the equivalent roughness of the wind farm by using the total thrust of the wind farm as a boundary condition and the large eddy simulation model.

12. A computer device, characterized in that, The method includes a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the steps of the wind power base flow field simulation method according to any one of claims 1-7.

13. 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 steps of the wind power base flow field simulation method as described in any one of claims 1-7.

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