Method and system for calculating wind field numerical value of hydromechanics based on high-precision landform

Abstract

The invention relates to the technical field of wind energy resource evaluation, in particular to a method and a system for calculating a hydrodynamics wind field numerical value based on high-precision landform, and the method comprises the steps: generating a three-dimensional unstructured grid for CFD wind field simulation based on high-precision landform data; analyzing an atmospheric boundary layer structure, and establishing a turbulence calculation model; according to the turbulence calculation model, the influence of atmospheric stability on the mountain flowing wind acceleration factor is researched, and a mountain flowing model is developed; performing CFD wind field simulation according to the three-dimensional unstructured grid and the mountain flow model, and correcting parameters of the mountain flow model; a refined grid is made through terrain elevation data; and according to the refined grid, driving the corrected mountain flow model to carry out numerical simulation, and carrying out wind power plant wind resource evaluation. Through the method, the complex characteristics of the wind field can be reflected more comprehensively, the precision and the calculation efficiency of wind resource evaluation are remarkably improved, and the efficiency and the accuracy of numerical simulation of the complex terrain wind field are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wind energy resource assessment, and in particular to a computational fluid dynamics wind field numerical method and system based on high-precision topography. Background Art

[0002] Accurate wind field simulation is crucial for wind energy resource assessment and wind farm design. While traditional mesoscale meteorological models (such as WRF) can provide meteorological data over a wide range, their resolution is typically a few kilometers, making them unable to capture microscale wind field characteristics (tens to hundreds of meters), especially in areas with complex terrain and large variations in surface roughness. Surface roughness significantly affects wind fields. Surface roughness elements such as vegetation, built-up areas, and soil surfaces can significantly alter wind flow characteristics, thereby affecting the distribution of wind speed and direction.

[0003] Although existing CFD methods are capable of simulating wind fields at a microscale, they often rely on manual meshing and simplified assumptions about roughness parameters when dealing with complex terrain and surface roughness, resulting in large deviations between the simulation results and the actual wind field. In addition, existing CFD models have low computational efficiency when processing high-precision terrain and geomorphological data, making it difficult to meet the needs of large-scale wind field simulations. Currently, research on the impact of atmospheric stability on wind turbine power and wakes only focuses on flat terrain or offshore wind farms, and is rarely reported on complex terrain. The Businger-Dyer similarity function, which is widely used in existing numerical simulation studies, can characterize the relationship between the dimensionless vertical gradient of wind speed, the dimensionless turbulent kinetic energy and its dissipation rate, and atmospheric stability. However, under stable conditions, it is limited by the Richard number and may overestimate the vertical gradient of wind speed or underestimate the turbulence intensity, seriously affecting the reliability of the research results.

[0004] Therefore, there is an urgent need for a CFD wind field numerical method that can automatically process high-precision terrain data, consider the influence of surface roughness, and consider the impact of atmospheric stability on complex terrain flow fields, so as to improve the accuracy and computational efficiency of wind field simulation. Summary of the Invention

[0005] The present invention provides a computational fluid dynamics wind field numerical method and system based on high-precision topography, which can effectively solve the problems in the background technology.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] A computational fluid dynamics wind field numerical method based on high-precision topography and landforms, the method comprising:

[0008] Generate 3D unstructured grids for CFD wind field simulation based on high-precision terrain data;

[0009] Analyze the atmospheric boundary layer structure and establish a turbulence calculation model;

[0010] Based on the turbulence calculation model, the influence of atmospheric stability on the wind acceleration factor of mountain flow is studied, and a mountain flow model is developed;

[0011] performing the CFD wind field simulation based on the three-dimensional unstructured grid and the mountain flow model, and correcting parameters of the mountain flow model;

[0012] Refined grid made from terrain elevation data;

[0013] According to the refined grid, the modified mountain flow model is driven to perform numerical simulation and conduct wind resource assessment of the wind farm.

[0014] Furthermore, the analyzing of the atmospheric boundary layer structure and establishing of the turbulence calculation model includes:

[0015] Analyze the vertical stratification structure of the atmospheric boundary layer under different atmospheric stability, construct an atmospheric boundary layer structure model, and establish a similarity function based on the Monin-Obukhov similarity theory;

[0016] The influence of the different atmospheric stabilities on the wind acceleration factor is analyzed by a numerical simulation method, and a turbulence calculation model is established according to the similarity function.

[0017] Furthermore, the developing of the mountain flow model includes:

[0018] The turbulence calculation model is used to analyze the influence of different atmospheric stability on the wind acceleration factor of mountain flow, and the mountain flow analysis results are obtained;

[0019] The mountain flow analysis results were combined with the flow measurement experiment data of Jingbian Wind Farm and Cooper Ridge flow measurement experiment to optimize the turbulence calculation model and obtain a mountain flow model.

[0020] Furthermore, the established turbulence calculation model is:

[0021]

[0022] Among them, P k is the turbulent kinetic energy generation rate caused by the time-averaged velocity gradient, k is the turbulent kinetic energy, ε is the turbulent dissipation rate, G b is the turbulent kinetic energy generation rate caused by the buoyancy force, Y M is the dissipation effect of volume change on the overall turbulent kinetic energy in compressible turbulence, C 1ε 、C 2ε 、C 3ε is a constant value, σ k is the Prantl number of k, σε is the Prantl number of ε, ρ is the air density, u i is the velocity component, μ is the molecular viscosity, μ t is the turbulent viscosity, S k 、S ε A user-defined source item.

[0023] Furthermore, the formula for turbulent viscosity is:

[0024]

[0025] Among them, C μ are model parameters.

[0026] Furthermore, modifying the parameters of the mountain flow model includes: modifying the model parameters C μ and C 1ε , model parameter C 2ε , σ k and σ ε Use standard values.

[0027] Furthermore, the refined grid produced by the terrain elevation data includes: importing the terrain elevation data into a grid generation tool independently programmed using Python for grid division, and generating a refined grid with a horizontal resolution of 30m.

[0028] Furthermore, driving the modified mountain flow model to perform numerical simulation includes:

[0029] Write scripts to monitor the output of the open source software SOWFA;

[0030] Extract the time series data on the boundary layer generated by the SOWFA through a sampling function, and process the time series data using a python program to obtain boundaryData;

[0031] Input the boundaryData as an inflow condition into the mapping avoidance function of the sowfa to generate an atmospheric boundary turbulence inflow condition for complex mountain simulation;

[0032] Based on the atmospheric boundary turbulent inflow condition and the refined grid, OpenFOAM is driven to perform numerical simulation.

[0033] Furthermore, OpenFOAM is driven to perform numerical simulations, and the calculation adopts a RANS-based unsteady solver to process the initial conditions to run the precursor method based on extracting wind speed and direction from SOWFA.

[0034] A computational fluid dynamics wind field numerical system based on high-precision topography, the system comprising:

[0035] Unstructured grid generation module, based on high-precision terrain data, generates three-dimensional unstructured grids for CFD wind field simulation;

[0036] Turbulence calculation model establishment module, analyzes the atmospheric boundary layer structure and establishes a turbulence calculation model;

[0037] Mountain flow model development module, based on the turbulence calculation model, studies the influence of atmospheric stability on the mountain flow wind acceleration factor and develops a mountain flow model;

[0038] a model parameter correction module, performing the CFD wind field simulation based on the three-dimensional unstructured grid and the mountain flow model, and correcting the parameters of the mountain flow model;

[0039] Refined grid production module, which produces refined grids using terrain elevation data;

[0040] The wind resource assessment module drives the modified mountain flow model to perform numerical simulation based on the refined grid to perform wind resource assessment on the wind farm.

[0041] The technical solution of the present invention can achieve the following technical effects:

[0042] The present invention uses a computational fluid dynamics wind field numerical method based on high-precision terrain and geomorphic data to more comprehensively reflect the complex characteristics of the wind field and significantly improve the accuracy of wind resource assessment. In the numerical simulation of complex terrain wind fields, more realistic inflow conditions are imposed, retaining the geomorphic characteristics of the original terrain over a larger range, reducing the impact of the software and hardware levels in current numerical calculations, and improving the efficiency and accuracy of complex terrain wind field numerical simulations. At the same time, the application of the present invention is extensive and is not only suitable for wind energy resource assessment, but can also be extended to other meteorological and environmental fields to provide support for various renewable energy projects.

[0043] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1This is a flow chart of the numerical method for wind field in computational fluid dynamics based on high-precision topography;

[0046] Figure 2 Schematic diagram of the numerical simulation process for driving the revised mountain flow model. DETAILED DESCRIPTION

[0047] 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 only part of the embodiments of the present invention, rather than all the embodiments.

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains. The terms used in this specification are for the purpose of describing specific embodiments only and are not intended to limit the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0049] Example 1:

[0050] like Figure 1 As shown, the numerical method of wind field based on computational fluid dynamics with high-precision topography includes:

[0051] S1: Generate 3D unstructured grids for CFD wind field simulation based on high-precision terrain data;

[0052] Specifically, in order to achieve automated grid division, high-precision terrain data such as satellite terrain data and surface roughness distribution can be used through grid generation tools such as Python scripts to generate three-dimensional computational grids suitable for OpenFOAM to realize automated grid generation, and the encrypted area can be dynamically adjusted according to the curvature and slope values of the terrain.

[0053] S2: Analyze the atmospheric boundary layer structure and establish a turbulence calculation model;

[0054] S3: Based on the turbulence calculation model, study the influence of atmospheric stability on the wind acceleration factor of mountain flow and develop a mountain flow model;

[0055] S4: Perform CFD wind field simulation based on the 3D unstructured grid and mountain flow model, and modify the parameters of the mountain flow model;

[0056] In this embodiment, the established turbulence calculation model performs poorly under complex terrain and stability (for example, the wind speed at the top of the ridge is overestimated by 20%). Numerical experiments can be used to analyze the impact of atmospheric stability on the mountain flow wind acceleration factor, and a new model can be developed based on the initial model. For the newly developed model, CFD wind field simulation can be used to identify the source of errors (such as excessive turbulent viscosity), drive parameter adjustments, and make the model predictions closer to the measured data.

[0057] S5: refined grid made from terrain elevation data;

[0058] S6: Based on the refined grid, the modified mountain flow model is driven to perform numerical simulations and conduct wind resource assessments for wind farms.

[0059] Specifically, the constructed CFD model is applied to actual engineering scenarios, the inflow conditions of a specific wind farm are input, and high-precision wind farm numerical simulations are performed to obtain wind farm details under complex terrain (such as wake effects and local turbulence intensity). The simulation results are then combined to conduct wind resource assessments (such as power generation predictions and wind turbine layout optimization). This step can reduce computational costs while improving the reliability of the results through dynamic coupling boundary conditions and open source tool chains.

[0060] The present invention uses a computational fluid dynamics wind field numerical method based on high-precision terrain and geomorphic data to more comprehensively reflect the complex characteristics of the wind field and significantly improve the accuracy of wind resource assessment. In the numerical simulation of complex terrain wind fields, more realistic inflow conditions are imposed, retaining the geomorphic characteristics of the original terrain over a larger range, reducing the impact of the software and hardware levels in current numerical calculations, and improving the efficiency and accuracy of complex terrain wind field numerical simulations. At the same time, the application of the present invention is extensive and is not only suitable for wind energy resource assessment, but can also be extended to other meteorological and environmental fields to provide support for various renewable energy projects.

[0061] As a preferred embodiment of this invention, analyzing the atmospheric boundary layer structure and establishing a turbulence calculation model includes:

[0062] S21: Analyze the vertical stratification structure of the atmospheric boundary layer under different atmospheric stability, construct an atmospheric boundary layer structure model, and establish a similarity function based on the Monin-Obukhov similarity theory;

[0063] S22: Analyze the impact of different atmospheric stability on the wind acceleration factor through numerical simulation methods, and establish a turbulence calculation model based on the similarity function.

[0064] This example constructs an atmospheric boundary layer structure model, considering the vertical stratification of the atmospheric boundary layer under different stability conditions. It determines the stratification characteristics of the boundary layer (such as the near-surface layer, mixing layer, and free atmosphere thickness) under different stability levels (stable / neutral / unstable). Furthermore, it combines the Monin-Obukhov similarity theory to establish a similarity function suitable for complex terrain. The differences in wind acceleration factors under different atmospheric stability conditions are analyzed. The influence of atmospheric stability on the wind acceleration factor is studied through numerical simulation. Finally, a turbulence calculation model suitable for various terrain characteristics is proposed to adapt to terrain effects such as sudden surface roughness changes and slope.

[0065] Based on the above embodiment, developing a mountain flow model includes:

[0066] S31: Use turbulence calculation models to analyze the impact of different atmospheric stability on mountain flow wind acceleration factors and obtain mountain flow analysis results;

[0067] S32: The mountain flow analysis results are combined with the flow measurement experiment data of Jingbian Wind Farm and Cooper Ridge flow measurement experiment to optimize the turbulence calculation model and obtain the mountain flow model.

[0068] Specifically, this step uses the FullRF turbulence model to conduct numerical simulation studies on the impact of atmospheric stability on the wind acceleration factor of simple mountain flows, analyzes the relationship between the wind acceleration factor and atmospheric stability in upslope and downslope flows, and then combines the flow measurement data from the Jingbian wind farm and the Cooper Ridge flow measurement experiments to verify the accuracy of the newly developed turbulence model and propose a mountain flow model that takes atmospheric stability into account.

[0069] Furthermore, the established turbulence calculation model is:

[0070]

[0071]

[0072] Among them, P k is the turbulent kinetic energy generation rate caused by the time-averaged velocity gradient, k is the turbulent kinetic energy, ε is the turbulent dissipation rate, G b is the turbulent kinetic energy generation rate caused by the buoyancy force, Y M is the dissipation effect of volume change on the overall turbulent kinetic energy in compressible turbulence, C 1ε 、C 2ε 、C 3ε is a constant value, σ k is the Prantl number of k, σ ε is the Prantl number of ε, ρ is the air density, u i is the velocity component, μ is the molecular viscosity, μ tis the turbulent viscosity, S k 、S ε A user-defined source item.

[0073] In the RANS method, the velocity components can be written as:

[0074]

[0075] The mass conservation equation and momentum conservation equation are rewritten into Reynolds time-averaged form as follows:

[0076]

[0077] Compared to the transient NS equations, the extra terms in the equations represent turbulence effects. To achieve turbulence containment, the Reynolds stress must be simulated. There are two approaches to modeling the Reynolds stress: one is to use the Boussinesq hypothesis to relate the Reynolds stress to the mean velocity gradient; the other is to derive a transport equation for the Reynolds stress and other related terms, known as the Reynolds stress model.

[0078] The Reynolds stress model is the most complete classical turbulence model. In this model, the eddy viscosity assumption is avoided and the components of the Reynolds stress tensor are directly calculated, which can simulate the anisotropy of turbulence. However, due to its large amount of calculation (seven additional equations need to be calculated), the Reynolds stress model is rarely used in engineering research.

[0079] The Boussinesq hypothesis can be written as follows:

[0080]

[0081] The standard k-ε turbulence model is based on the transport equation of turbulent kinetic energy k and dissipation rate ε. It assumes that the fluid is fully turbulent and ignores the effect of molecular viscosity. Therefore, this equation is only applicable to flows with fully developed turbulence.

[0082] Turbulent kinetic energy generation rate:

[0083]

[0084] Under the Boussinesq assumption, we have:

[0085] P k =μ t S 2 ;

[0086] Where S represents the average strain rate tensor S ij modulus.

[0087] The two definitions are:

[0088]

[0089] Furthermore, the formula for turbulent viscosity is:

[0090]

[0091] Among them, C μ are model parameters.

[0092] On the basis of the above embodiment, modifying the parameters of the mountain flow model includes: modifying the model parameters C μ and C 1ε , model parameter C 2ε , σ k and σ ε Use standard values.

[0093] The parameters of the mountain flow model can be modified as follows:

[0094]

[0095] In order to realize the automation of grid subdivision, the refined grid produced by terrain elevation data includes: importing the terrain elevation data into the grid generation tool independently programmed by Python for grid division, and generating a refined grid with a horizontal resolution of 30m.

[0096] Furthermore, the numerical simulation of the modified mountain flow model includes:

[0097] S61: Write a script to monitor the output of the open source software SOWFA;

[0098] S62: extract the time series data on the boundary layer generated by SOWFA through the sampling function, and use the Python program to process the time series data to obtain boundaryData;

[0099] Specifically, in order to generate high-precision inlet boundary conditions and provide dynamic turbulence input for micro-scale CFD simulations, SOWFA can be used to simulate the evolution of a large-scale wind field, capture the turbulent structure of the atmospheric boundary layer, and extract the time series data (velocity, turbulent kinetic energy) of the SOWFA outlet section (such as the inlet plane) through Python scripts to ensure that the inlet conditions of micro-scale CFD contain real turbulent pulsation information, avoid the errors of traditional steady-state inlet conditions (such as uniform wind speed profiles), and improve the simulation accuracy of wind fields in complex terrain.

[0100] S63: Input boundaryData as the inflow condition into the mapping avoidance function of sowfa to generate the atmospheric boundary turbulence inflow condition for complex mountain simulation;

[0101] In order to achieve mesoscale-microscale data coupling and convert the mesoscale output of SOWFA into the input of the microscale CFD model (OpenFOAM), the mapFields tool or a custom interpolation algorithm can be used to map the regular grid data of SOWFA to the unstructured OpenFOAM inlet grid to generate a boundaryData folder to ensure the spatiotemporal consistency of the dynamic inflow conditions. The microscale CFD model requires time-dependent inlet conditions to resolve the impact of complex terrain on instantaneous flow.

[0102] S64: Based on the atmospheric boundary turbulent inflow conditions and refined grids, OpenFOAM is driven to perform numerical simulations.

[0103] On the basis of the above embodiment, OpenFOAM is driven to perform numerical simulation, and the calculation adopts a RANS-based unsteady solver to process the initial conditions to run a precursor method based on extracting wind speed and direction from SOWFA.

[0104] Example 2:

[0105] A computational fluid dynamics wind field numerical system based on high-precision topography, including:

[0106] Unstructured grid generation module, based on high-precision terrain data, generates three-dimensional unstructured grids for CFD wind field simulation;

[0107] Turbulence calculation model establishment module, analyzes the atmospheric boundary layer structure and establishes a turbulence calculation model;

[0108] Mountain flow model development module, based on the turbulence calculation model, studies the impact of atmospheric stability on the mountain flow wind acceleration factor and develops a mountain flow model;

[0109] Model parameter correction module, which performs CFD wind field simulation based on 3D unstructured grid and mountain flow model, and corrects the parameters of mountain flow model;

[0110] Refined grid production module, which produces refined grids using terrain elevation data;

[0111] The wind resource assessment module drives the modified mountain flow model to perform numerical simulation based on the refined grid and conducts wind resource assessment on the wind farm.

[0112] The above-mentioned adjustment system in the present invention can effectively implement the computational fluid dynamics wind field numerical method based on high-precision topography and landforms, and the technical effects that can be achieved are as described in the above-mentioned embodiments and will not be repeated here.

[0113] Similarly, the above-mentioned optimization schemes for the system can also respectively achieve the corresponding optimization effects of the method in Example 1, which will not be repeated here.

[0114] Although the present application has been described with reference to specific features and embodiments thereof, it is apparent that various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. Accordingly, this specification and drawings are merely illustrative of the present application as defined herein and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. It is apparent that various modifications and variations of the present application may be made by those skilled in the art without departing from the scope of the present application. Thus, the present application is intended to include such modifications and variations as fall within the scope of the present application and its equivalents.

Claims

1. A numerical method for wind field based on computational fluid dynamics with high-precision topography, characterized by: The method comprises: Generate 3D unstructured grids for CFD wind field simulation based on high-precision terrain data; Analyze the atmospheric boundary layer structure and establish a turbulence calculation model; Based on the turbulence calculation model, the influence of atmospheric stability on the wind acceleration factor of mountain flow is studied, and a mountain flow model is developed; performing the CFD wind field simulation based on the three-dimensional unstructured grid and the mountain flow model, and correcting parameters of the mountain flow model; Refined grid made from terrain elevation data; According to the refined grid, the modified mountain flow model is driven to perform numerical simulation and conduct wind resource assessment of the wind farm.

2. The high-precision topography-based computational fluid dynamics wind field numerical method according to claim 1, characterized in that: Analyzing the atmospheric boundary layer structure and establishing a turbulence calculation model includes: Analyze the vertical stratification structure of the atmospheric boundary layer under different atmospheric stability, construct an atmospheric boundary layer structure model, and establish a similarity function based on the Monin-Obukhov similarity theory; The influence of the different atmospheric stabilities on the wind acceleration factor is analyzed by a numerical simulation method, and a turbulence calculation model is established according to the similarity function.

3. The high-precision topography-based computational fluid dynamics wind field numerical method according to claim 1, characterized in that: The development of a mountain flow model includes: The turbulence calculation model is used to analyze the influence of different atmospheric stability on the wind acceleration factor of mountain flow, and the mountain flow analysis results are obtained; The mountain flow analysis results were combined with the flow measurement experiment data of Jingbian Wind Farm and Cooper Ridge flow measurement experiment to optimize the turbulence calculation model and obtain a mountain flow model.

4. The high-precision topography-based computational fluid dynamics wind field numerical method according to claim 1, characterized in that: The established turbulence calculation model is: Among them, P k is the turbulent kinetic energy generation rate caused by the time-averaged velocity gradient, k is the turbulent kinetic energy, ε is the turbulent dissipation rate, G b is the turbulent kinetic energy generation rate caused by the buoyancy force, Y M is the dissipation effect of volume change on the overall turbulent kinetic energy in compressible turbulence, C 1ε 、C 2ε 、C 3ε is a constant value, σ k is the Prantl number of k, σ ε is the Prantl number of ε, ρ is the air density, u i is the velocity component, μ is the molecular viscosity, μ t is the turbulent viscosity, S k 、S ε A user-defined source item.

5. The high-precision topography-based computational fluid dynamics wind field numerical method according to claim 4, characterized in that: The formula for turbulent viscosity is: Among them, C μ are model parameters.

6. The high-precision topography-based computational fluid dynamics wind field numerical method according to claim 5, characterized in that: Modifying the parameters of the mountain flow model includes: modifying the model parameters C μ and C 1ε , model parameter C 2ε , σ k and σ ε Use standard values.

7. The high-precision topography-based computational fluid dynamics wind field numerical method according to claim 1, characterized in that: The refined grid produced by terrain elevation data includes: importing terrain elevation data into a grid generation tool independently programmed in Python for grid division, and generating a refined grid with a horizontal resolution of 30m.

8. The high-precision topography-based computational fluid dynamics wind field numerical method according to claim 1, characterized in that: The numerical simulation of the modified mountain flow model includes: Write scripts to monitor the output of the open source software SOWFA; Extract the time series data on the boundary layer generated by the SOWFA through a sampling function, and process the time series data using a python program to obtain boundaryData; Input the boundaryData as an inflow condition into the mapping avoidance function of the sowfa to generate an atmospheric boundary turbulence inflow condition for complex mountain simulation; Based on the atmospheric boundary turbulent inflow condition and the refined grid, OpenFOAM is driven to perform numerical simulation.

9. The high-precision topography-based computational fluid dynamics wind field numerical method according to claim 8, characterized in that: OpenFOAM is driven to perform numerical simulations, and the calculation uses a RANS-based unsteady solver to handle the initial conditions to run a precursor method based on wind speed and direction extracted from SOWFA.

10. A computational fluid dynamics wind field numerical system based on high-precision topography, characterized by: The system comprises: Unstructured grid generation module, based on high-precision terrain data, generates three-dimensional unstructured grids for CFD wind field simulation; Turbulence calculation model establishment module, analyzes the atmospheric boundary layer structure and establishes a turbulence calculation model; Mountain flow model development module, based on the turbulence calculation model, studies the influence of atmospheric stability on the mountain flow wind acceleration factor and develops a mountain flow model; a model parameter correction module, performing the CFD wind field simulation based on the three-dimensional unstructured grid and the mountain flow model, and correcting the parameters of the mountain flow model; Refined grid production module, which produces refined grids using terrain elevation data; The wind resource assessment module drives the modified mountain flow model to perform numerical simulation based on the refined grid to perform wind resource assessment on the wind farm.

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