Complex terrain wind field refined simulation method based on high-resolution grid

Abstract

The invention relates to the fields of wind engineering, weather forecast, environmental protection and aviation, and provides a complex terrain wind field refined simulation method based on a high-resolution grid. The objective of the invention is to solve the problem of simulation errors caused by different topographic data formats and coordinate systems in complex topographic wind field simulation and to improve simulation precision and efficiency. According to the main scheme, the method comprises the following steps: generating a three-dimensional computational grid of wind mine software according to satellite image elevation data, and obtaining a three-dimensional unstructured grid for wind field CFD simulation; selecting a proper entrance boundary condition type for four side boundary surfaces and a top surface of the target area; and wind mine software is driven to carry out numerical calculation to obtain wind field information data of the refined simulation of the complex terrain. The method is used for wind field characteristic evaluation under complex terrains, and is beneficial to efficient utilization of wind energy, weather forecast, environmental protection and aviation safety.

Description

Technical Field

[0001] The invention relates to wind engineering, weather forecasting, environmental protection and aviation fields, and provides a method for fine-tuning complex terrain wind field simulation based on high-resolution grids. Background Art

[0002] As a clean and renewable energy resource, wind energy has received extensive attention and utilization in recent years. In the development and utilization of wind energy, it is crucial to accurately evaluate the characteristics of wind fields under complex terrain. Complex terrain includes mountains, hills, canyons, etc. These terrains will change the speed, direction and turbulence characteristics of the wind, making the wind speed show great non-uniformity in both space and time, which in turn causes the wind field to become extremely complex. In the field of wind engineering, accurate simulation of wind fields in complex terrain can achieve efficient utilization of wind energy and have an important impact on the site selection, design and operation of wind turbines. In the field of meteorological forecasting, accurate wind field simulation can help predict meteorological changes in mountainous areas and provide a basis for meteorological disaster warnings; in the field of environmental protection, complex terrain wind field simulation helps to better simulate the transmission and diffusion process of atmospheric pollutants; in the field of aviation, accurate simulation of complex terrain wind fields is crucial to ensure flight safety.

[0003] At present, most methods for simulating wind fields in complex terrain use mesoscale meteorological models, which are usually used to simulate meteorological conditions in larger areas and can be applied to simulate wind fields in complex terrain. These models can take into account factors such as terrain, surface cover, atmospheric thermal and dynamic processes, and perform macroscopic simulations of wind fields. By comparing and analyzing the measured data from meteorological monitoring stations, improving the models and methods, and finally obtaining simulation results that meet certain accuracy requirements. The calculation range of mesoscale meteorological models is large, but the resolution is relatively low, and in order to ensure stable calculations in the early stages of the calculation, the terrain needs to be smoothed to a certain extent, which reduces the calculation accuracy of wind field simulations in complex terrain.

[0004] In recent years, with the continuous improvement of computer performance and numerical algorithms, the accuracy and efficiency of CFD simulation have been significantly improved. Numerical simulation based on CFD method is more suitable for the refined simulation of wind fields in complex micro-terrain. By solving the basic equations of fluid mechanics, it can better capture the changes in wind fields caused by complex terrain and obtain detailed information of wind fields, including speed, pressure, turbulence, etc. In recent years, researchers have tried to use commercial software such as Fluent and Windsim to achieve refined simulation of wind fields in complex terrain. However, complex terrain wind field simulation requires high-precision terrain data to accurately describe terrain characteristics. Terrain data from different sources may have different formats and coordinate systems, and need to be converted and processed before they can be used in wind field simulation models. Some commercial software may have specific requirements for the format, range or accuracy of terrain data. Data that does not meet the requirements may not be correctly input or cause simulation errors.

[0005] PHengLEI (Platform for Hybrid ENGineering simulation of flows) is a hybrid CFD platform for fluid engineering developed by the China Aerodynamics Research and Development Center (CARDC). The platform is designed with an object-oriented concept and programmed in C++. In December 2020, PHengLEI was officially open sourced nationwide. Compared with other open source CFD software, PHengLEI has the characteristics of strong scalability, low development difficulty, and high computational efficiency. Summary of the invention

[0006] This patent invents a method for fine-tuning simulation of wind fields in complex terrain based on high-resolution grids. Based on real terrain elevation data, a geometric model of three-dimensional complex terrain is constructed to achieve reconstruction of the three-dimensional spatial computational grid of the wind field model, solving the problem of incorrect input or simulation errors caused by terrain data from different sources in different formats and coordinate systems. In addition, this method achieves stable solutions to steady / unsteady flow problems under low-speed conditions while ensuring the calculation accuracy and efficiency of the flow field by constructing a variety of inlet boundary conditions such as fixed value boundaries, wind speed profile boundaries, meteorological data interpolation boundaries, etc., significantly improving the ability to fine-tune simulation of wind fields in complex terrain.

[0007] In order to achieve the above purpose, the present invention adopts the following technical solutions:

[0008] A method for fine-tuning wind field simulation in complex terrain based on high-resolution grids includes the following steps:

[0009] Step 1: Generate the three-dimensional computational grid of the Fenglei software based on the satellite image elevation data, and obtain the three-dimensional unstructured grid for wind field CFD simulation;

[0010] Step 2: Select the appropriate inlet boundary condition type for the four side boundary surfaces and the top surface of the target area;

[0011] Step 3: Drive Fenglei software (Fenglei software is a domestically produced open source CFD software) to perform numerical calculations to obtain wind field information data for refined simulation of complex terrain. (Complex terrain wind field simulation requires high-precision terrain data to accurately describe terrain features. Terrain data from different sources may have different formats and coordinate systems, and need to be converted and processed before they can be used in wind field simulation models. Some commercial software may have specific requirements for the format, range or accuracy of terrain data. Data that does not meet the requirements may not be correctly input or may cause simulation errors. The innovation of this application is that after obtaining the satellite image elevation data, it can automatically generate a computational grid in Fenglei software and drive the calculation).

[0012] In the above scheme, step 1 specifically includes the following steps:

[0013] Step 1.1: Collect satellite image elevation data, obtain elevation data fragments according to the latitude and longitude range of the target area, mosaic and merge, and perform coordinate conversion according to the specific area to obtain the elevation data of the three-dimensional complex terrain in a unified coordinate system. The specific area refers to the target area to be simulated;

[0014] Step 1.2: For the processed elevation data, select the corresponding elevation values ​​within the target accuracy range, reconstruct the surface terrain through the latitude and longitude grids and elevation values, and build a geometric model of the three-dimensional complex terrain of the target area;

[0015] Step 1.2 specifically draws a grid using longitude and latitude as x and y coordinate values, and uses the elevation value of the grid as the z coordinate value to reconstruct the surface terrain. The geometric model of the three-dimensional terrain of the target area is constructed through the x, y, and z coordinates of the grid points.

[0016] Step 1.3: Based on the geometric model of the target area, set the computational domain range and spatial grid size, discretize the entire computational domain into a rectangular grid, and obtain a rectangular grid;

[0017] Step 1.4: Set the object surface unit size, perform adaptive object surface encryption on the rectangular grid obtained in step 1.3, and obtain a spatial rectangular grid;

[0018] Step 1.5: Reconstruct the spatial rectangular grid obtained in step 1.4 to obtain a three-dimensional unstructured grid for wind farm CFD simulation.

[0019] In the above scheme, step 2 specifically includes the following steps:

[0020] Step 2.1: Collect wind field information data in the target area, including mesoscale WRF forecast data type and single-point data type measured by the observation station;

[0021] Step 2.2: Construct corresponding inlet boundary conditions according to the data type of wind field information in the target area, including fixed value boundary, wind profile boundary, and meteorological forecast data interpolation boundary;

[0022] Step 2.3: Select the corresponding inlet boundary conditions for the four side boundary surfaces and the top surface (top surface, four side surfaces, and bottom surface) of the target area.

[0023] In the above scheme, step 3 specifically includes the following steps:

[0024] Step 3.1: Based on the above inlet boundary conditions, set the solver parameters and turbulence model using the low-speed processing method;

[0025] Step 3.2: Drive Fenglei software to perform numerical solution on the computational domain;

[0026] Step 3.3: After the calculation converges, post-processing is performed to obtain high-resolution wind field distribution data.

[0027] Because the present invention adopts the above technical means, it has the following beneficial effects:

[0028] The complex terrain wind field refined simulation method based on high-resolution grid proposed in this application is based on real terrain elevation data. By solving the technical problems of terrain data format and coordinate system differences, grid generation difficulties and single boundary condition settings, the technical scheme such as steps 1-3 is adopted to realize the rapid subdivision of the three-dimensional space calculation grid for wind field simulation, which can restore the real complex terrain characteristics to the greatest extent. Based on the pre-processing based low-speed pre-processing solver, a variety of inlet boundary conditions such as fixed value boundary, wind speed profile boundary, meteorological data interpolation boundary, etc. are constructed to achieve stable solution of steady / unsteady flow problems under low-speed conditions while ensuring the calculation accuracy and efficiency of the flow field, significantly improving the complex terrain wind field refined simulation capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a simplified diagram of the process of the present invention;

[0030] Figure 2 A geometric model constructed from satellite data of a mountainous area;

[0031] Figure 3 Three-dimensional CFD computational grid division in a mountainous area;

[0032] Figure 4 Wind speed distribution simulation results in a mountainous area. DETAILED DESCRIPTION

[0033] The following is a detailed description of the embodiments of the present invention. Although the present invention will be described and illustrated in conjunction with some specific embodiments, it should be noted that the present invention is not limited to these embodiments. On the contrary, modifications or equivalent substitutions made to the present invention should all be included in the scope of the claims of the present invention.

[0034] In addition, in order to better illustrate the present invention, numerous specific details are given in the following specific embodiments. It will be understood by those skilled in the art that the present invention can also be implemented without these specific details.

[0035] The technology of the present invention aims to highlight the automatic and rapid generation function of high-resolution grids in complex terrain simulation added to CFD software. This function does not require the use of other third-party software to process terrain data from different sources to directly generate high-resolution grids for wind field simulation, thereby solving the problem of incorrect input or simulation errors caused by inconsistent format, range or accuracy of terrain data.

[0036] A method for fine-tuning wind field simulation in complex terrain based on high-resolution grids includes the following steps:

[0037] Step 1: Generate the three-dimensional computational grid of the Fenglei software based on the satellite image elevation data, and obtain the three-dimensional unstructured grid for wind field CFD simulation;

[0038] Step 2: Select the appropriate inlet boundary condition type for the four side boundary surfaces and the top surface of the target area;

[0039] Step 3: Drive Fenglei software (Fenglei software is a domestically produced open source CFD software) to perform numerical calculations to obtain wind field information data for refined simulation of complex terrain. (Complex terrain wind field simulation requires high-precision terrain data to accurately describe terrain features. Terrain data from different sources may have different formats and coordinate systems, and need to be converted and processed before they can be used in wind field simulation models. Some commercial software may have specific requirements for the format, range or accuracy of terrain data. Data that does not meet the requirements may not be correctly input or may cause simulation errors. The innovation of this application is that after obtaining the satellite image elevation data, it can automatically generate a computational grid in Fenglei software and drive the calculation).

[0040] In the above scheme, step 1 specifically includes the following steps:

[0041] Step 1.1: Collect satellite image elevation data, obtain elevation data fragments according to the latitude and longitude range of the target area, mosaic and merge, and perform coordinate conversion according to the specific area to obtain the elevation data of the three-dimensional complex terrain in a unified coordinate system. The specific area refers to the target area to be simulated;

[0042] Step 1.2: For the processed elevation data, select the corresponding elevation values ​​within the target accuracy range, reconstruct the surface terrain through the latitude and longitude grids and elevation values, and build a geometric model of the three-dimensional complex terrain of the target area;

[0043] Step 1.2 specifically involves drawing a grid using longitude and latitude as x and y coordinate values, and reconstructing the surface terrain using the elevation value of the grid as the z coordinate value. A geometric model of the three-dimensional terrain of the target area is constructed using the x, y, and z coordinates of the grid points.

[0044] Step 1.3: Based on the geometric model of the target area, set the computational domain range and spatial grid size, discretize the entire computational domain into a rectangular grid, and obtain a rectangular grid;

[0045] Step 1.4: Set the object surface unit size, perform adaptive object surface encryption on the rectangular grid obtained in step 1.3, and obtain a spatial rectangular grid;

[0046] Step 1.5: Reconstruct the spatial rectangular grid obtained in step 1.4 to obtain a three-dimensional unstructured grid for wind farm CFD simulation.

[0047] In the above scheme, step 2 specifically includes the following steps:

[0048] Step 2.1: Collect wind field information data in the target area, including mesoscale WRF forecast data type and single-point data type measured by the observation station;

[0049] Step 2.2: Construct corresponding inlet boundary conditions according to the data type of wind field information in the target area, including fixed value boundary, wind profile boundary, and meteorological forecast data interpolation boundary;

[0050] Step 2.3: Select the corresponding inlet boundary conditions for the four side boundary surfaces and the top surface (top surface, four side surfaces, and bottom surface) of the target area.

[0051] In the above scheme, step 3 specifically includes the following steps:

[0052] Step 3.1: Based on the above inlet boundary conditions, set the solver parameters and turbulence model using the low-speed processing method; (The functions are all implemented in C++ code: setting the low-speed preprocessing parameter to 1 means using the low-speed preprocessing method, and setting the turbulence model to "1eq-sa", which is the SA turbulence model.)

[0053] Step 3.2: Drive Fenglei software to perform numerical solution on the computational domain;

[0054] Step 3.3: After the calculation converges, post-processing is performed to obtain high-resolution wind field distribution data.

[0055] The complex terrain wind field refinement simulation method based on high-resolution grid proposed in this application is based on the real terrain elevation data, and the process of automatically generating spatial calculation grids by setting parameters in the Fenglei software can realize the reconstruction of the three-dimensional spatial calculation grid for wind field simulation, which can restore the real complex terrain characteristics to the greatest extent. In addition, this method constructs a variety of inlet boundary conditions such as fixed value boundaries, wind speed profile boundaries, meteorological data interpolation boundaries, etc., to achieve stable solutions to steady / unsteady flow problems under low-speed conditions while ensuring the calculation accuracy and efficiency of the flow field, significantly improving the ability to refine the simulation of complex terrain wind fields.

[0056] Figure 3 This is a wind speed distribution map of a mountainous area obtained by fine-tuning the wind field in complex terrain based on high-resolution grids.

[0057] The present invention proposes a method for fine-tuning simulation of wind fields in complex terrain based on high-resolution grids. Referring to steps 1.3-1.5, the geometric digital model of complex terrain is automatically processed to parametrically construct a three-dimensional spatial grid of complex terrain that supports CFD model calculations. The grid is highly conformal and can truly reflect the characteristics of complex environments. Based on the low-speed preprocessing method solver of Fenglei software, a variety of inlet boundary conditions are realized through a custom function interface, including a fixed value boundary, a wind speed profile boundary, and a meteorological forecast data interpolation boundary. According to the actual situation and calculation requirements, the rationality of the inlet boundary can be guaranteed, and the accuracy of the simulation of wind fields in complex terrain can be further improved.

[0058] In summary, the complex terrain wind field refined simulation method based on high-resolution grid proposed by the present invention, compared with the prior art: can be based on satellite image elevation data, parameterized to achieve complex terrain three-dimensional space grid automatic segmentation, breaking the limitations of commercial software, and avoiding the cumbersome conversion and processing operation flow of terrain data from different sources to be used in the CFD calculation process. According to the actual situation and needs, the inlet boundary conditions are set, including the fixed value boundary, the wind speed profile boundary, and the meteorological forecast data interpolation boundary. Among them, the wind profile fitting method takes into account the measured data with stronger correlation and higher accuracy. The meteorological forecast data interpolation boundary uses the mesoscale meteorological forecast grid data to interpolate and couple on the boundary, which is more in line with the actual situation, ensures the rationality of the inlet boundary, and further improves the accuracy of complex terrain wind field simulation.

Claims

1. A method for fine-tuning wind field simulation in complex terrain based on high-resolution grids, characterized in that: The following steps are involved: Step 1: Generate the three-dimensional computational grid of the Fenglei software based on the satellite image elevation data, and obtain the three-dimensional unstructured grid for wind field CFD simulation; Step 2: Select the appropriate inlet boundary condition type for the four side boundary surfaces and the top surface of the target area; Step 3: Drive the Fenglei software to perform numerical calculations to obtain wind field information data for refined simulation of complex terrain.

2. The method for fine-tuning wind field in complex terrain based on high-resolution grid according to claim 1 is characterized in that: Step 1 specifically includes the following steps: Step 1.1: Collect satellite image elevation data, obtain elevation data fragments according to the latitude and longitude range of the target area, mosaic and merge, and perform coordinate conversion according to the specific area to obtain the elevation data of the three-dimensional complex terrain in a unified coordinate system. The specific area refers to the target area to be simulated; Step 1.2: For the processed elevation data, select the corresponding elevation values ​​within the target accuracy range, reconstruct the surface terrain through the latitude and longitude grids and elevation values, and build a geometric model of the three-dimensional complex terrain of the target area; Step 1.3: Based on the geometric model of the target area, set the computational domain range and spatial grid size, discretize the entire computational domain into a rectangular grid, and obtain a rectangular grid; Step 1.4: Set the object surface unit size, perform adaptive object surface encryption on the rectangular grid obtained in step 1.3, and obtain a spatial rectangular grid; Step 1.5: Reconstruct the spatial rectangular grid obtained in step 1.4 to obtain a three-dimensional unstructured grid for wind farm CFD simulation.

3. The method for fine-tuning wind field in complex terrain based on high-resolution grid according to claim 1 is characterized in that: Step 2 specifically includes the following steps: Step 2.1: Collect wind field information data in the target area, including mesoscale WRF forecast data type and single-point data type measured by the observation station; Step 2.2: Construct corresponding inlet boundary conditions according to the data type of wind field information in the target area, including fixed value boundary, wind profile boundary, and meteorological forecast data interpolation boundary; Step 2.3: Select the corresponding inlet boundary conditions for the four side boundary surfaces and the top surface of the target area.

4. The method for fine-tuning wind field simulation in complex terrain based on high-resolution grid according to claim 3 is characterized in that: Step 3 specifically includes the following steps: Step 3.1: Based on the above inlet boundary conditions, set the solver parameters and turbulence model using the low-speed processing method; Step 3.2: Drive Fenglei software to perform numerical solution on the computational domain; Step 3.3: After the calculation converges, post-processing is performed to obtain high-resolution wind field distribution data.

5. The method for fine-tuning wind field simulation in complex terrain based on high-resolution grid according to claim 2 is characterized in that: Step 1.2 specifically involves drawing a grid using longitude and latitude as x and y coordinate values, and reconstructing the surface terrain using the elevation value of the grid as the z coordinate value. A geometric model of the three-dimensional terrain of the target area is constructed using the x, y, and z coordinates of the grid points.

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