CN113687447A - Local area wind field monitoring method based on multiple wind measuring devices - Google Patents
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Abstract
A wind field model building method based on CFD and a local area wind field monitoring method of various wind measuring devices are disclosed, 1) a geographic information model of a service guarantee area is built: according to the requirements of the service guarantee area, properly extending to determine boundary conditions of the service guarantee area, and constructing a geographic information model of the service guarantee area containing information such as elevation and roughness by using accurate geographic information obtained by a GIS (geographic information system) and combining the topographic features of the service guarantee area; 2) constructing a Computational Fluid Dynamics (CFD) wind field simulation model: solving the discrete solution of the hydrodynamics control equation by a numerical method, and carrying out CFD numerical simulation according to the geographic model of the service guarantee area to obtain CFD wind field simulation results with different directions, different wind speeds and different gust characteristics; the selection of the size of the grid of the service guarantee area needs to be determined by combining with the terrain and landform conditions so as to achieve the minimum calculated amount and the optimal simulation result; 3) and (4) carrying out sensitivity analysis on observation points, and 4) establishing a regional wind field monitoring system.
Description
Technical Field
The invention relates to a monitoring method of an atmospheric wind field, in particular to a method for combining an actually measured wind field and a fluid mode to calculate wind field query matching, realizing monitoring of the atmospheric wind field in a local range (about 20km in radius and 5km in height), and providing local real-time monitoring data for aviation flight, military activities and the like.
Background
The wind is a product of the action of heat and power in the atmosphere, and the wind is formed when the air flows under the action of the atmospheric pressure gradient, is generated due to the difference of atmospheric temperature, density and pressure caused by the uneven heating of the sun on the earth surface, and is also influenced by the rotation of the earth, the surface roughness, the terrain change and the like. The wind field information has important effects on analyzing the distribution of the air pressure field, knowing the characteristics of air mass, the generation and dissipation of cloud and fog and the like, and is a key meteorological element which needs to be considered in aviation flight taking off and landing, artillery air defense combat, biochemistry, nuclear weapon defense and the like. High-altitude wind detection in meteorological services generally refers to the measurement of the direction and speed, i.e., wind direction and wind speed, of horizontal airflow at various heights within the height range of thirty kilometers from the ground to the air. The real-time and accurate high-altitude wind detection data is the most basic data for weather analysis and forecast and is also the basic data for military meteorological guarantees such as airdrop and airborne landing, artillery and air defense ballistic correction. In meteorological services, an object (usually a meteorological balloon or a balloon system consisting of the meteorological balloon and a sonde) which drifts with the airflow is usually used as a tracer, and the track of the object moving in the air is used for detecting high-altitude wind, which is called track method wind measurement.
Currently, the following means are mainly adopted to track the balloon: the system comprises an optical wind theodolite, a radio theodolite, a primary wind measuring radar, a secondary wind measuring radar, a GNSS high-altitude detection system, an INS high-altitude detection system and the like. The detection of the optical anemometry theodolite is easily influenced by visibility and low cloud, and the detection height of high-altitude wind is difficult to ensure; the radio theodolite and the wind measuring radar have complex systems, large volume and weight, poor portability and extremely large wind measuring error at low elevation angle; the GNSS wind measurement precision is high, high-power electromagnetic waves are not emitted, the size and the weight are small, but the system positioning depends on the existence and the reliability of a space navigation constellation, and the satellite navigation signal frequency point is public.
In meteorological services, two methods for measuring high-altitude wind can be adopted. The method is a direct detection method, which generally detects high-altitude wind by using the moving track of an object (usually a meteorological balloon or a balloon system consisting of the meteorological balloon and a sonde) which moves along with the air flow, and is called track method wind measurement. The balloon position is usually obtained by using an optical wind theodolite, a wind-measuring radar, a GNSS sounding system (GNSS is a general term for global positioning navigation systems), and the like, so as to detect the high-altitude wind. Because of the cumbersome and costly operations, each weather station typically performs 1 to 2 surveys per day. The other is a ground-based remote sensing detection method, wherein equipment such as a weather radar, a wind profiler, a laser wind measuring radar, a sound radar and the like are installed on some stations at present, so that single-point continuous observation of a high-altitude wind field can be realized, the time resolution and the vertical resolution are both high, but the space detection range is limited, and the horizontal wind field in the vertical direction is mainly measured.
Surface roughness directly affects the wind distribution with height (i.e., wind profile). The wind moves forward at a steady wind speed when flowing at high altitude, but the wind speed is reduced due to various ground roughness elements (buildings, rivers, hills, etc.) when approaching the ground, and the kinetic energy of the wind is lost. The degree of reduction decreases with increasing height above ground until a certain height is reached, which height is referred to as gradient wind height, the effect of which is negligible. When the surface roughness changes from one type to another, the near-formation wind profile becomes very complex, and after some distance has passed in the downwind direction, the wind can be made to re-adapt to the new roughness and become smooth.
The influence of the topographic fluctuation on the wind characteristics of the atmospheric boundary layer is more important than the roughness of the earth surface, so that the size and the direction of wind can be changed, the stability of the wind is influenced, and a turbulence effect is generated. In the rough terrain, the difference between the wind speed and the wind direction between two adjacent places is large, and the wind profile close to the ground is distorted due to the influence of the ground friction force, and even the wind whirlpool is formed at a certain place. Therefore, under the same weather system, the corresponding wind energy distribution is completely different due to different terrains, and even if the wind energy distribution is in different positions under the same terrains, the wind characteristics can be greatly different.
The existing wind field observation equipment is only arranged in a single point, the arrangement place and the wind measuring data demand position are usually inconsistent in space and time, and different wind measuring equipment has own applicable conditions, so that the existing wind field measurement mode cannot meet the demand. With the high-precision requirements of aviation flight on the wind field monitoring in time and space, the local area wind field monitoring with fine definition and high space-time resolution is urgently needed to be realized. Therefore, the high-spatial-resolution regional wind field monitoring method is constructed by combining the advanced wind field observation system for accurate regional terrain and multipoint distribution control with the computational fluid dynamics model, and high-spatial-resolution meteorological guarantee of the wind field is provided for aviation flight, military activities and the like.
Disclosure of Invention
The invention aims to provide a CFD-based wind field model construction and wind measuring instrument layout scheme design, in particular to a technical scheme for local area wind field monitoring.
The technical scheme of the invention is that a wind field model construction based on CFD and a local area wind field monitoring method of various wind measuring devices are characterized by comprising the following steps of 1) constructing a geographic information model of a service guarantee area: according to the requirements of the service guarantee area, properly extending to determine the boundary conditions of the service guarantee area, and constructing a service guarantee area geographic information model containing information such as elevation and roughness by using accurate topographic information obtained by a GIS and combining topographic features (distinguishing winter, summer, spring and autumn); 2) constructing a Computational Fluid Dynamics (CFD) wind field simulation model: the Computational Fluid Dynamics (CFD) model is a discrete solution for solving a Fluid mechanics control equation by a numerical method, is used for simulating a near-ground wind field, can fully reproduce the flow of air under a complex terrain, and is a development trend of a wind field analysis technology; according to the geographic model of the service guarantee area, CFD numerical simulation is carried out, and CFD wind field simulation results with different directions, different wind speeds and different gust characteristics are obtained; the selection of the size of the grid of the service guarantee area needs to be determined by combining with the terrain and landform conditions so as to achieve the minimum calculated amount and the optimal simulation result;
3) analyzing sensitivity of observation points, and determining the type and the number of wind measuring instruments needing to be distributed and controlled at multiple points in a service guarantee area according to the landform characteristics; the method comprises the steps of adopting a laser wind measuring radar to combine with a ground wind pole, obtaining wind field information of a set detection node, taking the wind field information of one part of nodes as an initial value, taking the wind field information of the other part of nodes as a target value, taking the wind field information of the other part of nodes into the initial value, adjusting parameters of an established CFD wind field simulation model to calculate and obtain the wind field information of the target value, changing the initial value, finding a position with the maximum response to the change of the initial value through sensitivity analysis, namely a most sensitive position, and arranging a corresponding instrument.
And inputting the initial value into the CFD mode, and comparing the output value with the wind field information of the target value. The initial value and the target value have a corresponding relationship.
4) Establishing a regional wind field monitoring system; and 3) constructing a multi-point distribution control wind field observation system according to the sensitivity test result in the step 3), and acquiring wind fields in any horizontal direction and any vertical direction in the area range according to the actually measured wind field observation result by utilizing a CFD wind field simulation model established under the geographic and geomorphic conditions and combining a table look-up mode with an optimization interpolation method.
Further, safety precaution and safety time window information are provided according to specific business requirements, such as flight take-off and landing conditions of different aircraft flight to cross wind, low altitude horizontal wind shear and vertical wind shear, and medium altitude horizontal wind shear and vertical wind shear. Changing initial value, and finding out the position with maximum response to initial value change by sensitivity analysis, i.e. the most sensitive position
Further, the wind field CFD simulation overall process under various terrains is divided into three parts, namely pre-processing, simulation calculation and post-processing. The preprocessing part comprises the work of acquiring and processing topographic data, modeling ground and simulation areas, generating grids and the like, and is a prerequisite for wind field CFD simulation; the simulation calculation part comprises the steps of boundary condition setting (inlet wind profile, outlet self-outflow, wall surface, symmetrical boundary and the like), turbulence model selection, discrete format selection, solver selection, simulation initialization and the like, and is a main solving process of wind field CFD simulation: the post-processing part comprises the extraction and analysis of the simulation result, and aims to carry out qualitative and quantitative inspection on the rationality of the wind field CFD simulation result more intuitively and extract related data on the basis to carry out wind field analysis. The steps in the embodiment are described in detail;
the invention mainly aims at the problem of wind field monitoring, and wind shear identification is carried out on the basis of the wind field monitoring, which is more in need of intensive research.
In order to improve the cost performance, the number of instruments needs to be reduced as much as possible on the premise of the accuracy and effectiveness of regional wind field monitoring.
When other wind measuring instruments (wind profilers, Doppler weather radars and the like) are arranged at the station, the measurement result can also be accessed into the system according to a required data format.
The invention has the beneficial effects that: the invention overcomes the problems that the horizontal wind field can be calculated by VAD algorithm only under the assumption of the horizontal uniform wind field and the error is generated in the area with large topographic relief in the prior art; the problem of wind field information guarantee such as wind shear, crosswind and the like which is required by the flying of the aircraft is solved; the problem that low-altitude wind shear caused by a laser side wind radar and the like in a dead zone of a near ground layer is difficult to observe is solved. The invention realizes the monitoring of high spatial and temporal resolution of the wind field at any position in the spatial range of the region, and solves the problems that the time resolution and the vertical resolution of the wind field on the flight path of the balloon are poor and can only be detected by measuring the wind by the balloon track method in the prior art; the method solves the problems that the measurement space range of equipment such as a single-point laser wind measuring radar and a wind rod is small, the horizontal wind field can be calculated by using VAD algorithm only under the assumption of a horizontal uniform wind field, and errors can be generated in an area with large topographic relief; the problem of wind field information guarantee such as wind shear, crosswind and the like which is required by the flying of the aircraft is solved; the problem that low-altitude wind shear caused by a laser side wind radar and the like in a dead zone close to the ground layer is difficult to observe is solved, and the method has a strong popularization and application prospect.
Drawings
1a and 1b, under a terrain following coordinate system, the assigned wind speed of a CFD boundary; wherein FIG. 1a employs a single WRF profile; FIG. 1b employs multiple WRF profiles. Wherein, the horizontal direction represents the width of the CFD solution domain (0-4km),
the vertical direction represents the height (0-2km) of the CFD solution domain.
2a 1-2 b2 show the terrain profile and simulated wind profiles; wherein FIG. 2a 1-FIG. 2a2 are WRF modes; FIG. 2b 1-FIG. 2b2 are CFD patterns. Where the red circle (light) represents the position of the selected wind profile.
Fig. 3a and 3b show the horizontal distribution of wind vectors, z being 10m AGL; wherein FIG. 3a is the WRF mode; fig. 3b CFD pattern.
Fig. 4 wind field CFD simulation general flow.
Detailed Description
The invention is realized by four steps:
1) and constructing a geographical information model of the guarantee area. According to the requirements of the service guarantee area, the boundary conditions of the area are determined by proper extension, accurate terrain information obtained by a GIS is utilized, and a guarantee area geographic information model containing information such as elevation and roughness is constructed by combining the terrain features of the area (distinguishing winter, summer, spring and autumn).
2) And constructing a CFD wind field simulation model. The Computational Fluid Dynamics (CFD) model is a discrete solution for solving a Fluid mechanics control equation by a numerical method, is used for simulating a near-ground wind field, can fully reproduce the flow of air under a complex terrain, and is a development trend of a wind field analysis technology. And according to the geographic model of the guarantee area, carrying out CFD numerical simulation to obtain CFD wind field simulation results with different directions, different wind speeds and different gust characteristics. The selection of the grid size needs to be determined by combining the terrain and landform conditions so as to achieve the minimum calculation amount and the optimal simulation result.
The governing equations of CFD are the constraint criteria of the model solution calculations, and are primarily used to describe the fundamental physical laws of fluids, including the laws of mass conservation, momentum conservation and energy conservation.
(1) Conservation of mass equation
The law of conservation of mass is expressed as the increase in mass of a fluid infinitesimal per unit of time is equal to the net mass flowing into that infinitesimal at the same time. The general expression of the conservation of mass equation is:
wherein ρ is the fluid density; u is the vector velocity, uiRepresents the component of the vector u in the i direction; t is time; smIs the source item.
In the simulation of an atmospheric wind field, the fluid is assumed to be incompressible, i.e., the rate of change of the atmospheric density ρ with time is 0, and the source term SmWhen 0, the mass conservation equation is:
(2) equation of conservation of momentum
The law of conservation of momentum is expressed as the rate of change of momentum of a fluid infinitesimal is equal to the sum of all external forces to which the infinitesimal is subjected. The general expression of the conservation of momentum equation is:
wherein, tauijIn order to be a viscous stress,
mu is a viscosity coefficient; p is the pressure on the surface of the fluid microelement; fiAnd giExternal force volume force and gravity volume force in the i direction, respectively.
In the simulation of an atmospheric wind field, the fluid is assumed to be incompressible, its viscosity coefficient μ is constant, and its volume expansion rate
The conservation of momentum equation is then:
wherein nu is a dynamic viscosity coefficient,
energy conservation equation: the law of conservation of energy, which is premised on the first law of thermodynamics, is expressed as the rate of change of energy of a fluid infinitesimal being equal to the sum of the energy of work and heating on that infinitesimal. The general expression of the energy conservation equation is:
wherein, cpIs the specific heat of the fluid; t is the fluid temperature; k is the heat transfer coefficient; srIs a viscous dissipation term.
Solving the CFD control equation can not obtain an analytic solution, so that discretization processing needs to be carried out on a computational domain of the CFD mode. The common discrete methods include finite element method, finite difference method and finite volume method. The CFD mode mainly adopts a finite volume method, combines the advantages of a finite difference method and a finite element method, and optimizes the relation between grid points and variables, so that a discrete equation obtained after grid division always meets three conservation laws.
Introduction of symbols
The basic governing equation can be uniformly expressed as:
each term of the above formula represents a convection term, a transient term, a diffusion term, and a source term, respectively. Wherein in the mass conservation equation, phi is 1, and in the momentum conservation equation, phi is u, v, w; Γ is a diffusion coefficient, where Γ is 0 in the mass conservation equation and μ in the momentum conservation equation.
Integrating the control volume, the basic control equation can be expressed in the form of an integral:
introducing the gaussian divergence theorem, the above formula can be expressed as:
the first term of the left equation represents the outflow of the variable phi along the normal direction outside the control volume due to convection, the second term of the left equation represents the variation of the variable phi in the control volume over time, the first term of the right equation represents the net increase of the variable phi due to diffusion, and the second term of the right equation represents the net increase of the variable phi due to the source term.
In the above derivation, a relevant interpolation method is required to obtain the required physical quantity on the control volume, i.e. in a discrete format. In the CFD mode, common discrete formats are a first-order windward format, a second-order windward format, a central difference format, a mixed format, a QUICK format and the like, and research results show that the QUICK format is more suitable for micro-scale wind field simulation of complex terrain areas.
In the numerical calculation method, an algebraic equation set is obtained after the CFD control equation is discretized, the discrete equation sets cannot be directly solved, and relevant algorithm processing needs to be carried out on the solving mode, the solving sequence and the like of the solved physical variables, namely the numerical calculation method. The numerical calculation method of the discretization control equation is mainly divided into two categories of a separation type solving algorithm and a coupling type solving algorithm.
The coupled solution algorithm is classified into a display solution (simultaneous solution of all variables in a local region), a display and implicit solution (simultaneous solution of partial variables in an entire region), and an implicit solution (simultaneous solution of all variables in an entire region). In general, the coupled solution algorithm is long in machine time and low in calculation efficiency, so that the application is less.
The separate solving algorithm does not directly solve simultaneous equations of all variables, but sequentially and orderly solves equation sets of each variable. The application of the separate solving algorithm is more, and the most widely applied method is the pressure correction method. The basic principle of the pressure correction method is that in the process of numerical value iterative solution, an initial assumed value of pressure is given firstly, an assumed velocity field is obtained through the assumed value solution, then a correction equation of the pressure is obtained through derivation according to a continuous equation, the assumed velocity field and the pressure field are corrected, and the iterative solution is carried out to obtain a convergence solution of the velocity field and the pressure field.
In the CFD mode, a commonly used Pressure correction Method is a SIMPLE (Semi-explicit Method for Pressure Linked Equations) algorithm, a modified SIMPLE algorithm, or the like. The specific process of the SIMPLE algorithm is as follows:
(1) establishing a hypothetical pressure field p*；
(2) Solving the momentum equation to obtain a velocity field u*、v*、w*；
(3) Deriving a pressure correction value by using a continuous equation, and solving to obtain p and p;
(4) correcting the velocity field by using the corrected value of the pressure to obtain u, v and w;
(5) and verifying the convergence of the result, and if the result is not converged, taking the obtained simulation result as an initial field, and performing loop iteration to obtain a convergence solution.
And (3) grid modeling, namely discretizing the control equation when solving the control equation, wherein the key technology is to generate a computational domain grid. The grid quality influences the computational accuracy and efficiency of the CFD mode, and for the simulation computation of complex fluid, the grid generation is long in machine-consuming time and easy to make mistakes, so that how to establish a high-quality grid model has an important influence on the wind field simulation of complex terrain.
As preprocessing software for CFD mode, GAMBIT can provide high quality geometric modeling and mesh generation functions. The GAMBIT provides various grid units such as non-structural grids, structural grids and the like, has certain self-adaptability, can adjust the density degree of grids, can generate complex body-fitted grids in a self-adaptive manner on complex terrains, and is suitable for simulation calculation of complex flow fields.
In the complex terrain wind field simulation based on the CFD mode, the computational domain mesh modeling mainly comprises terrain modeling and computational domain meshing. The method mainly utilizes GAMBIT and terrain elevation data to establish a high-quality terrain model, and divides the high-quality terrain model on the basis to obtain a computational domain grid model, so that early preparation is made for micro-scale simulation of a wind field in a complex terrain area.
The modeling principle of GAMBIT is based on the input of a single command: firstly, generating geometric elements in sequence according to the sequence of point-line-surface-body, and then establishing a final body mesh model through operations such as displacement, rotation, division and the like. In the field of wind engineering, a wind environment model is simple, and GAMBIT can directly draw a simple model, but in the wind field simulation of complex terrain, the terrain model is complex, and the workload of single-command input is huge, so that the method is difficult to realize. According to the method, a log file (. jou) is compiled by using an MATLAB program, a Journal file is generated, then a terrain model is automatically generated through a background running function of GAMBIT, and a computational domain grid is obtained through division.
3) And (4) carrying out sensitivity analysis on observation points, and determining the type and the number of wind measuring instruments needing multi-point control. The technology needs a wind measuring instrument accurate in site, and due to the advantages of the laser wind measuring radar, the laser wind measuring radar is mainly combined with a ground wind rod, and when other wind measuring instruments (a wind profiler, a Doppler weather radar and the like) exist in a station, a measuring result can be accessed into the system according to a required data format. In order to improve the cost performance, the number of instruments needs to be reduced as much as possible on the premise of the accuracy and effectiveness of regional wind field monitoring. The method comprises the steps of obtaining wind field information of a set detection node, taking the wind field information of one part of nodes as an initial value, taking the wind field information of the other part of nodes as a target value, combining an established CFD wind field simulation model by bringing the initial value into the target value, calculating to obtain the wind field information of the target value, comparing, finding the most sensitive position, and arranging a corresponding instrument.
4) And establishing a regional wind field monitoring system. And (3) constructing a multi-point distribution control wind field observation system according to the sensitivity test result of the 3) and obtaining the wind field in any horizontal direction and vertical direction in the area range according to the actually measured wind field observation result by utilizing a CFD wind field simulation model established under the geographic and geomorphic conditions and combining a table look-up mode with an optimization interpolation method. And further, safety early warning and safety time window information can be provided according to specific service requirements, such as flight take-off and landing conditions of different aircraft flight to cross wind, low-altitude horizontal wind shear and vertical wind shear, and medium-altitude horizontal wind shear and vertical wind shear.
The overall process of the CFD simulation of the wind field under various terrains is shown in the attached drawing, and the process is divided into three parts, namely pre-processing, simulation calculation and post-processing. The preprocessing part comprises the work of acquiring and processing topographic data, modeling ground and simulation areas, generating grids and the like, and is a prerequisite for wind field CFD simulation; the simulation calculation part comprises the steps of boundary condition setting (inlet wind profile, outlet self-outflow, wall surface, symmetrical boundary and the like), turbulence model selection, discrete format selection, solver selection, simulation initialization and the like, and is a main solving process of wind field CFD simulation: the post-processing part comprises the extraction and analysis of the simulation result, and aims to carry out qualitative and quantitative inspection on the rationality of the wind field CFD simulation result more intuitively and extract related data on the basis to carry out wind field analysis.
And (3) micro-scale wind field simulation scheme columns and boundary condition assignment based on the CFD mode:
and taking the result of the mesoscale wind field of the WRF mode as the boundary condition of the CFD mode, assigning the result to the CFD boundary, and further driving the CFD mode to carry out iterative solution to obtain the microscale wind field of the complex terrain area. In order to better assign the mesoscale wind field result to the CFD boundary of the complex terrain area, the method assigns boundary conditions to the WRF mode wind profile in the terrain following coordinate system, and the lower graph shows the assigned wind speed of the CFD boundary at a certain moment in the terrain following coordinate system. In which fig. 1a and 1b are wind speed distributions obtained by assigning 1 and 5 WRF mode wind profiles (solid black lines) to the CFD boundary, respectively.
FIG. 1 is a diagram of assigned wind velocities at CFD boundaries in a terrain following coordinate system, with a single WRF profile used in FIG. 1 a; FIG. 1b employs multiple WRF profiles. Wherein, the horizontal direction represents the width (0-4km) of the CFD solution domain, and the vertical direction represents the height (0-2km) of the CFD solution domain.
Wind field simulation results based on CFD.
Several wind profiles inside the CFD mode study area are given in fig. 2a 1-2 b2, and compared to the corresponding WRF mode wind profiles, where the red circles indicate the location of the selected wind profiles. As can be seen from the figure, since the WRF mode has a low terrain resolution (fig. 2a1) and is subjected to corresponding smoothing processing, it is difficult to precisely characterize the wind field variation caused by complex terrain, resulting in closer wind speed profile results at various positions (fig. 2a 2); the CFD mode has high terrain resolution (fig. 2b1), and can more precisely describe the wind field change caused by complex terrain, so that the wind speed profile result difference of each position is large (fig. 2b 2).
2a 1-2 b2 terrain profiles and simulated wind profiles (WRF mode in FIGS. 2a1-a 2; CFD mode in FIGS. 2b1-b 2; where red circles indicate the location of selected wind profiles.
Fig. 3a and 3b show the horizontal distribution of wind vectors in the CFD mode, and compared with the corresponding WRF mode results, it can be seen that the WRF mode near the ground is similar to the wind field distribution in the CFD mode, and the prevailing wind directions are northwest. However, the wind field results of the two modes have a larger difference in detail characteristics, wherein the wind field distribution of the WRF mode is more uniform, while the wind field distribution of the CFD mode shows more non-uniform characteristics, and the wind field characteristics of the complex terrain are described in more detail. Plot horizontal distribution of stroke vectors, z 10m AGL fig. 3a) WRF pattern; FIG. 3b) CFD mode
And following the assigned wind speed of the CFD boundary at a certain time under a coordinate system. In which fig. 1a and 1b are wind speed distributions obtained by assigning 1 and 5 WRF mode wind profiles (solid black lines) to the CFD boundary, respectively.
Claims (7)
1. A wind field model building method based on CFD and a local area wind field monitoring method of various wind measuring devices are characterized by comprising the following steps of 1) building a geographic information model of a service guarantee area: according to the requirements of the service guarantee area, properly extending to determine the boundary conditions of the service guarantee area, utilizing the accurate topographic information obtained by the GIS, combining the topographic features of the service guarantee area, distinguishing winter, summer, spring and autumn, and constructing a geographic information model of the service guarantee area containing information such as elevation and roughness; 2) constructing a Computational Fluid Dynamics (CFD) wind field simulation model: a Computational Fluid Dynamics (CFD) model is a discrete solution to a Fluid mechanics control equation solved by a numerical method; according to the geographic model of the service guarantee area, CFD numerical simulation is carried out, and CFD wind field simulation results with different directions, different wind speeds and different gust characteristics are obtained; the selection of the size of the grid of the service guarantee area needs to be determined by combining with the terrain and landform conditions so as to achieve the minimum calculated amount and the optimal simulation result;
3) analyzing sensitivity of observation points, and determining the type and the number of wind measuring instruments needing to be distributed and controlled at multiple points in a service guarantee area according to the landform characteristics; the method comprises the steps that a wind measuring instrument which is accurate in site is adopted, a laser wind measuring radar is combined with a ground wind pole, wind field information of a set detection node is obtained, the wind field information of one part of the node is used as an initial value, the wind field information of the other part of the node is used as a target value, the initial value is brought in, parameters of an established CFD wind field simulation model are adjusted, the wind field information of the target value can be obtained through calculation, then the initial value is changed, the position which has the maximum response to the change of the initial value is found through sensitivity analysis, namely the most sensitive position, and a corresponding instrument is arranged;
4) establishing a regional wind field monitoring system; and 3) constructing a multi-point distribution control wind field observation system according to the sensitivity test result in the step 3), and acquiring wind fields in any horizontal direction and any vertical direction in the area range according to the actually measured wind field observation result by utilizing a CFD wind field simulation model established under the geographic and geomorphic conditions and combining a table look-up mode with an optimization interpolation method.
2. The CFD-based wind farm model building and local area wind farm monitoring method of various wind measuring devices according to claim 1, wherein safety precaution and safety time window information are provided according to specific business needs, such as flight take-off and landing conditions of different aircraft flights to cross wind, low altitude horizontal wind shear and vertical wind shear, medium altitude horizontal wind shear and vertical wind shear.
3. The method for constructing a wind field model based on CFD and monitoring the local area wind field of a plurality of wind measuring devices according to claim 1, wherein the CFD of the wind field under various terrains simulates the overall process, and the process is divided into three parts, namely pre-processing, simulation calculation and post-processing. The preprocessing part comprises the work of acquiring and processing topographic data, modeling ground and simulation areas, generating grids and the like, and is a prerequisite for wind field CFD simulation; the simulation calculation part comprises the steps of boundary condition setting (inlet wind profile, outlet self-outflow, wall surface, symmetrical boundary and the like), turbulence model selection, discrete format selection, solver selection, simulation initialization and the like, and is a main solving process of wind field CFD simulation: the post-processing part comprises the extraction and analysis of the simulation result, and aims to carry out qualitative and quantitative inspection on the rationality of the wind field CFD simulation result more intuitively and extract related data on the basis to carry out wind field analysis.
4. The method for constructing a wind field model based on CFD and monitoring the local regional wind field of a plurality of wind measuring devices according to claim 1, wherein the number of instruments is reduced as much as possible on the premise of accuracy and effectiveness of regional wind field monitoring in order to improve cost performance.
5. The method for constructing a wind field model based on CFD and monitoring the local area wind field of various wind measuring devices according to claim 1, wherein when other wind measuring instruments (a wind profiler, a Doppler weather radar and the like) are arranged at a station, the measurement result can be accessed into the system according to a required data format.
6. The method for constructing a wind field model based on CFD and monitoring the local area wind field of a plurality of wind measuring devices according to claim 1, wherein the initial value is changed, and the position with the maximum response to the change of the initial value is found through sensitivity analysis, namely the most sensitive position.
7. The Method for constructing a wind field model and monitoring the local area wind field of various wind measuring devices according to claim 1, wherein in the CFD mode, the commonly used Pressure correction Method is SIMPLE (Semi-empirical Method for Pressure Linked Equations) algorithm, improved SIMPLE algorithm, etc. The specific process of the SIMPLE algorithm is as follows:
(1) establishing a hypothetical pressure field p*；
(2) Solving the momentum equation to obtain a velocity field u*、v*、w*；
(3) Deriving a pressure correction value by using a continuous equation, and solving to obtain p' and p;
(4) correcting the velocity field by using the corrected value of the pressure to obtain u, v and w;
(5) and verifying the convergence of the result, and if the result is not converged, taking the obtained simulation result as an initial field, and performing loop iteration to obtain a convergence solution.
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