CN110298114B - Wind field power downscaling method and storage medium - Google Patents

Wind field power downscaling method and storage medium Download PDF

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CN110298114B
CN110298114B CN201910588983.8A CN201910588983A CN110298114B CN 110298114 B CN110298114 B CN 110298114B CN 201910588983 A CN201910588983 A CN 201910588983A CN 110298114 B CN110298114 B CN 110298114B
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terrain
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方平治
余晖
汤胜茗
陈佩燕
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Shanghai Institute Of Typhoon Research China Meteorological Administration
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Abstract

The invention provides a wind field power downscaling method and a storage medium, wherein the method comprises the following steps: carrying out numerical simulation on the simplified terrain based on computational fluid mechanics to obtain pneumatic parameters of the simplified terrain; and carrying out redistribution on the wind speed at the angular point position of the mesoscale grid in the downscale grid based on the terrain elevation data, the land utilization type data and the pneumatic parameters to realize the downscale calculation of the wind field. The method is based on two-dimensional simplified terrain aerodynamic parameters, high-resolution terrain elevation data and land utilization type data are added, and a new wind field power downscaling scheme is designed.

Description

Wind field power downscaling method and storage medium
Technical Field
The invention belongs to the technical field of meteorological computing, and particularly relates to a wind field power downscaling method and a storage medium.
Background
In recent years, with the continuous development of computers and the improvement of computing power and computing resources, the horizontal resolution of numerical modes of various mechanisms in the world reaches 2-10 km, and the progress is made toward 1 km. Theoretically, as horizontal resolution increases, the simulation of the boundary layer process by the numerical model should be more refined spatio-temporally and quantitatively more accurate, but the fact may be diametrically opposed (Zhou Bo et al, 2016). In the horizontal resolution range of 1km level, boundary layer convection vortex with the most energy is in a partially resolvable and partially sub-grid state, so that a traditional boundary layer parameterization scheme based on ensemble averaging is not applicable, and Wyngaard (2004) defines the region as a gray region (the horizontal resolution is 100-2000 m). Therefore, under the current technical conditions, the mesoscale numerical model of each global organization does not have the wind field forecasting capability of hundreds of meter level horizontal resolution.
At present, the application of the power downscaling technology is mainly concentrated on specific areas such as wind power plants, cities and the like, the horizontal scale of the technology is usually only tens of kilometers, and the requirement of large-area systems (such as transmission lines, railways and the like) with the horizontal scale of hundreds of kilometers or even thousands of kilometers on a high-resolution wind field cannot be met.
Chinese patent CN108363882A discloses a dynamic downscaling mode-based wind speed calculation method for mountainous power transmission line design, which adopts a mesoscale WRF mode to provide downscaling data with a horizontal resolution of 1km multiplied by 1km, and then interpolates a wind speed simulation result to a project. Firstly, the patent can not realize wind field forecast under complex terrain conditions, and only can realize wind field evaluation and simulation; secondly, the patent does not allow to obtain a high resolution wind field with a horizontal resolution of the order of hundreds of meters, with a horizontal resolution of only 1km × 1 km.
Chinese patent CN107688906A introduces a multi-method fused down-scale analysis system and method for meteorological elements of a power transmission line, which can make accurate prediction for meteorological elements in a small area or at a certain specified point by using a down-scale technique. Firstly, the patent can only realize meteorological element prediction of a small area or a certain fixed point, and cannot predict a large area range with a horizontal scale of hundreds of kilometers or even thousands of kilometers; secondly, the downscaling method of the patent is based on statistical downscaling instead of a dynamic downscaling method, has high dependence on observation data, and cannot be applied to many regions without meteorological observation data in China.
Chinese patent CN106326625A discloses a wind field simulation method coupling WRF and OpenFOAM modes, which can downscale data of several kilometers of horizontal resolution of WRF to 30m resolution data of OpenFOAM. However, as in the existing WRF mesoscale mode nested small-scale CFD mode, the dynamic downscaling method used in the patent is only applicable to an area with a horizontal range of tens of kilometers, and cannot meet a large-area system with a horizontal scale of hundreds of kilometers or even thousands of kilometers; in addition, due to the timeliness problem of the OpenFOAM software calculation, the method is only suitable for simulation and evaluation of the wind field and cannot be suitable for forecasting of the wind field.
Chinese patent CN102930177B discloses a wind speed prediction method for a complex terrain wind farm based on a fine boundary layer numerical mode, which can predict the near-stratum wind speed of 500 square kilometers around the wind farm and the horizontal grid resolution of 100m, and improve the average root mean square error between the prediction of the near-stratum wind speed with the height of 70m and the observation from 3.13m/s to 2.62m/s, and the correlation coefficient from 0.56 to 0.59. However, the fine boundary layer mode adopted by the patent is still only suitable for the wind power station regional range with the horizontal scale of tens of kilometers, and cannot meet the requirement of a large regional system with the horizontal scale of hundreds of kilometers or even thousands of kilometers.
Disclosure of Invention
In view of the above, the present invention provides a wind farm power downscaling method and a storage medium, which are used for designing a new wind farm power downscaling scheme based on two-dimensional simplified terrain aerodynamic parameters and adding high-resolution terrain elevation data and land use type data.
In order to achieve the purpose, the invention provides the following technical scheme:
a wind field power downscaling method based on simplified terrain aerodynamic parameters comprises the following steps:
carrying out numerical simulation on the simplified terrain based on computational fluid mechanics to obtain pneumatic parameters of the simplified terrain;
and carrying out redistribution on the wind speed of the mesoscale grid points in the downscale grid based on the terrain elevation data, the land utilization type data and the pneumatic parameters to realize the downscale calculation of the wind field.
Optionally, the simplified terrain is a two-dimensional simplified terrain, and the two-dimensional simplified terrain includes two basic forms, namely a two-dimensional wind speed upwash and a two-dimensional wind speed downgrade.
Optionally, after performing numerical simulation on the simplified terrain based on computational fluid dynamics to obtain aerodynamic parameters of the simplified terrain, the method further includes: and (5) carrying out wind tunnel test verification numerical simulation to obtain pneumatic parameters of the simplified terrain.
Optionally, before the wind speed at the corner position of the mesoscale grid is re-distributed in the downscale grid to realize the downscale calculation of the wind farm based on the terrain elevation data, the land use type data and the pneumatic parameters, the method further includes: and acquiring a mesoscale wind field of the region based on the regional numerical weather forecast mode.
Optionally, the aerodynamic parameters of the simplified terrain include an average wind speed ratio of a slope midpoint, where the average wind speed ratio satisfies:
Figure BDA0002115362090000021
wherein R isix、RizThe average wind speed ratio, U, of the measured point i in the downwind direction and the vertical direction respectivelyix、UizThe average wind speed, U, of the measured point i in the downwind direction and the vertical direction respectivelyHIs the average wind speed of the incoming flow.
Optionally, the wind speed of the mesoscale grid is re-distributed in the downscale grid based on the terrain elevation data, the land use type data, and the aerodynamic parameter to implement the wind field downscale calculation, including:
and performing downscaling calculation on the average latitudinal wind speed and the average radial wind speed at the specified height of the mesoscale grid based on the mesoscale wind field.
Optionally, the average latitudinal wind speed after the downscaling calculation meets the following requirements:
Figure BDA0002115362090000031
and the radial latitudinal wind speed after the downscaling calculation meets the following requirements:
Figure BDA0002115362090000032
u and v are respectively the average latitudinal wind speed and the average radial wind speed of the ground surface at the designated height in the downscaling wind field, and the corner marks m and n are respectively the mth row and the nth column of the downscaling grid; ri is the average wind speed ratio, N is the downscaling proportion, N is an integer, du is the downscaling correction term of the average latitudinal wind speed, and dv is the downscaling correction term of the average radial wind speed.
Optionally, after the grid resolution meets the downscaling requirement, the wind speed at the corner position of the mesoscale grid is re-distributed in the downscaling grid based on the terrain elevation data, the land use type data, and the pneumatic parameters to implement the wind field downscaling calculation, and the method further includes:
according to the logarithmic rate form of the vertical wind profile, the variation of the average wind speed of the downscaled wind field along the vertical height is expressed as:
Figure BDA0002115362090000033
in the formula, VzIs a height zIs arranged atAverage wind speed of u*For the friction speed,. kappa.is the Karman constant, z0The surface roughness length is psi, the stability correction function of the mean wind speed logarithmic profile is phi, and L is the obuff length.
Optionally, the value range of the height z is 0-150 m.
A second aspect of the invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the aforementioned method.
The invention has the beneficial effects that: the method is based on two-dimensional pneumatic parameters of simplified terrain; then, high-resolution terrain elevation data and land utilization type data are added, a new wind field power downscaling scheme is designed, and a near-ground wind field with a horizontal grid resolution of hundred meters can be obtained.
Drawings
In order to make the purpose, technical scheme and beneficial effect of the invention more clear, the invention provides the following drawings for explanation:
FIG. 1 is a flow chart of an embodiment of the present invention;
FIG. 2 is a schematic cross-sectional view of a model according to an embodiment of the invention;
FIG. 3 is a schematic view of a pneumatic plane of a wind tunnel according to an embodiment of the present invention;
FIG. 4 is a latitudinal direction downscaling calculation process diagram according to an embodiment of the present invention;
FIG. 5 is a process diagram illustrating downscaling calculation according to an embodiment of the present invention.
Detailed Description
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
A first embodiment of the present invention provides a method for reducing the scale of wind farm power, as shown in fig. 1, the method includes the following steps:
step S1: carrying out numerical simulation on the simplified terrain based on computational fluid mechanics to obtain pneumatic parameters of the simplified terrain;
step S4: and carrying out redistribution on the wind speed at the angular point position of the mesoscale grid in the downscale grid based on the terrain elevation data, the land utilization type data and the pneumatic parameters to realize the downscale calculation of the wind field.
In this embodiment, the aerodynamic parameters of the simplified terrain are obtained by numerically simulating the simplified terrain based on Computational Fluid Dynamics (CFD), including the CFD numerical simulation being performed using commercial software FLUENT. The coupling mode of pressure and speed in the CFD calculation is a SIMPLEC algorithm, the control equation is solved by adopting a separated method (clustered), and the pressure difference mode is PRESTO. The turbulence model adopts a readable k-epsilon model, the convection term of the control equation adopts a second-order windward format, and the residual value of the calculation convergence criterion is 5 multiplied by 10 -4。
A CFD numerical wind field adopts a uniform inflow boundary condition, an inflow surface adopts a speed inlet boundary condition, and an outflow surface adopts a pressure outlet boundary condition. The top surface adopts a symmetrical boundary condition, which is equivalent to a wall surface which slides freely. And non-slip wall surfaces are adopted for the bottom surface of the calculation domain and the surface of the research object.
In the embodiment of the invention, CFD numerical simulation is respectively carried out on two conditions of an ascending slope and a descending slope, and 12 slope angles such as 5 degrees, 10 degrees, 15 degrees, 20 degrees, 25 degrees, 30 degrees, 35 degrees, 40 degrees, 45 degrees, 50 degrees, 55 degrees, 60 degrees and the like are respectively considered for the two conditions.
In the present embodiment, as shown in fig. 2, the simplified terrain in the present embodiment refers to a two-dimensional simplified terrain, that is, two basic forms of an uphill slope and a downhill slope are considered in consideration of a two-dimensional wind speed, with a slope α as a characteristic parameter.
In this embodiment, step S4: before the wind speed at the angular point position of the mesoscale grid is redistributed in the downscale grid to realize the downscale calculation of the wind field based on the terrain elevation data, the land utilization type data and the pneumatic parameters, the method further comprises the following steps: step S3: and acquiring a mesoscale wind field of the region based on the regional numerical weather forecast mode.
The terrain elevation data is data obtained in a space Shuttle Radar terrain mapping Mission (SRTM) performed by the National Aeronautics and Space Administration (NASA) in 2000 in this embodiment, which is referred to as SRTM data for short, and the horizontal resolution is 90 m.
The land use type data employs global 30-meter surface coverage data (GlobeLand30) published by the national basic geographic information center in 2010. The images classified and utilized by the GlobeLand30 are multispectral images with the horizontal resolution of 30 meters, and include american terrestrial resource satellite (Landsat) TM5, ETM + multispectral images and chinese environment disaster reduction satellite (HJ-1) multispectral images. GlobeLand30 data included 10 types in total, each being: cultivated land, forest, grassland, shrub land, water body, wetland, moss, artificial mulching, bare land, glacier and permanent accumulated snow.
Acquiring a mesoscale wind field of a region based on a regional numerical weather forecast mode, wherein the method comprises the steps of firstly, acquiring global numerical forecast data through a global numerical weather forecast mode; then, through the regional numerical weather forecast mode, the numerical forecast data of the region is obtained, wherein the numerical forecast data comprises a near-ground wind field, namely a mesoscale wind field, and the resolution of a horizontal grid of the regional numerical weather forecast data is kilometer level.
In this embodiment, step S1: after numerically simulating the simplified terrain based on computational fluid dynamics to obtain aerodynamic parameters of the simplified terrain, the method further comprises: and step S2, carrying out wind tunnel test verification numerical simulation to obtain pneumatic parameters of the simplified terrain.
As shown in fig. 3, which is a schematic view of a pneumatic plane of a wind tunnel according to an embodiment of the present invention, the wind tunnel used in this embodiment is a serial connection dual test section return/direct current large-scale multifunctional boundary layer wind tunnel, as shown in fig. 3, a low-speed test section of the wind tunnel has a width of 4.4 meters, a height of 3.0 meters and a length of 24.0 meters, and a maximum wind speed is greater than 30.0 meters/second; the high-speed test section is 2.2 meters wide, 2 meters high and 5.0 meters long, and the maximum wind speed is more than 80.0 meters per second.
In this embodiment, the wind tunnel test is a rigid model pressure measurement test, four models, i.e., M1 models, M2 models, M3 models and M4 models, are fabricated in this embodiment, as shown in fig. 2, and the cross-sectional dimensions of the four models, i.e., M1 models, M2 models, M3 models and M4 models, are shown in table 1:
TABLE 1M 1-M4 model parameters
Model number Angle alpha Characteristic dimension/mm Height of model/mm Clogging rate/%)
M1 15° 500 133.97 4.47
M2 30° 400 230.94 7.70
M3 45° 200 200 6.67
M4 60° 150 259.81 8.66
In the embodiment, a wind tunnel test is adopted to test the wind pressure and the wind speed, and specific test parameters of the wind tunnel test are shown in table 2.
TABLE 2 wind tunnel test technical parameters
Figure BDA0002115362090000051
Figure BDA0002115362090000061
Optionally, in this embodiment, the aerodynamic parameter of the two-dimensional simplified terrain acquired by the CFD numerical simulation and the wind tunnel test is an average wind speed ratio of a midpoint of a slope, and the average wind speed ratio satisfies:
Figure BDA0002115362090000062
wherein R isix、RizThe average wind speed ratio, U, of the measured point i in the downwind direction and the vertical direction respectively ix、UizThe average wind speed, U, of the measured point i in the downwind direction and the vertical direction respectivelyHIs the average wind speed of the incoming flow.
In this embodiment, specific values of the average wind speed ratio under each operating condition are shown in table 3.
TABLE 3 average wind speed ratio under various operating conditions
Figure BDA0002115362090000063
The down-scale calculation in the step S4 is performed based on the mesoscale wind field provided by the regional numerical prediction mode, and the core idea of the calculation process is as follows: and based on the mesoscale wind field, combining simplified terrain aerodynamic parameters (average wind speed ratio), redistributing the wind speed at the angular point position of the mesoscale grid in the grid, thereby realizing the downscaling calculation of the wind field.
Step S4: and based on the terrain elevation data, the land utilization type data and the pneumatic parameters, the wind speed of the mesoscale grid is redistributed in the downscale grid to realize wind field downscale calculation, and the method comprises the following steps:
step S41: and performing downscaling calculation on the average latitudinal wind speed and the average radial wind speed at the specified height of the mesoscale grid based on the mesoscale wind field.
In this embodiment, the height of the measured point is taken as H equal to 10m, the schematic diagrams of the calculation process are shown in fig. 4 and 5, and the specific calculation flow is shown in formulas (1) to (10).
As shown in fig. 4, U is the average latitudinal wind speed at 10m height above the ground surface in the mesoscale wind field, and the downscaling calculation process is as follows:
Figure BDA0002115362090000071
Figure BDA0002115362090000072
Figure BDA0002115362090000073
As shown in fig. 5, V is the average radial wind speed at 10m height above the ground surface in the mesoscale wind farm, and the downscaling calculation process is as follows:
Figure BDA0002115362090000074
Figure BDA0002115362090000075
Figure BDA0002115362090000076
in the calculation process, U is the average latitudinal wind speed of the ground surface at the designated height in the mesoscale wind field, V is the average radial wind speed of the ground surface at the designated height in the mesoscale wind field, and the corner marks i and j are respectively the ith row and the jth column of the mesoscale grid; u and v are respectively the average latitudinal wind speed and the average radial wind speed of the designated height of the earth surface in the downscaling wind field, and the corner marks m and n are respectively the mth row and the nth column of the downscaling grid; ri is an average wind speed ratio, N is a downscaling proportion, N is an integer, and the value range of N in the embodiment is 2-10; du is the downscaling correction term of the average latitudinal wind speed, and dv is the downscaling correction term of the average radial wind speed.
Thus, the average wind speed and wind direction at 10m height of the ground surface in the down-scale wind field can be obtained, which are:
Figure BDA0002115362090000077
Figure BDA0002115362090000081
wherein V10 and phi 10 are the average wind speed and wind direction of 10m height of the ground surface in the down-scale wind field respectively.
After the grid resolution reaches the downscaling requirement, the wind speed at the angular point position of the mesoscale grid is redistributed in the downscaling grid based on the terrain elevation data, the land utilization type data and the pneumatic parameters to realize the wind field downscaling calculation, and the method further comprises the following steps:
Step S42: according to the logarithmic rate form of the vertical wind profile, the variation of the average wind speed of the downscaled wind field along the vertical height is expressed as:
Figure BDA0002115362090000082
in the formula, vzIs a height zToAverage wind speed of u*Kappa is a karman constant, where kappa is 0.40 and z is 0.40 in this example0The surface roughness length is psi, the stability correction function of the mean wind speed logarithmic profile is phi, and L is the obuff length.
Since the 10m altitude mean wind speed V10 is already known, the mean wind speeds at the other altitudes are:
Figure BDA0002115362090000083
the average wind speed V of the ground surface height z is obtainedz. In the embodiment, the value range of the height z is recommended to be 0-150 m.
Based on the technical scheme, the method has the following advantages:
1. the downscaling region is large: because the downscaling method is based on mesoscale grid to perform downscaling calculation, the calculated area is very large, the horizontal range can reach thousands of kilometers, and the requirements of systems such as power grids, railways, roads and the like on large-area wind field forecasting are met; compared with other existing downscaling technologies, the calculation horizontal range of CFD software (FLUENT or OpenFOAM) is generally within several kilometers, the horizontal range of CALMET, WT software and the like is generally within hundreds of kilometers, and the downscaling area of the method is larger.
2. The calculation efficiency is high: the method has the advantages that terrain aerodynamic parameters, namely the average wind speed ratio, are simplified through off-line manufacturing, and a power downscaling method based on a mesoscale grid is adopted, so that the calculation efficiency is very high, compared with a traditional power downscaling scheme, the calculation time of CFD (computational fluid dynamics) software (FLUENT or OpenFOAM) is usually several hours or even several days, the calculation time of CALMET and WT tools is several hours, and the calculation time of the method is only several minutes.
3. The wind field resolution is high: the method realizes refined wind field forecast under the condition of complex terrain, provides important technical support and business support for the construction of typhoon disaster early warning systems in large regional areas such as transmission lines, railways, roads and the like, and is favorable for the development of disaster prevention and reduction work in coastal areas during the landing of typhoons; the horizontal resolution of the downscale wind field obtained by the method is as high as a hundred-meter level, so that the accurate calculation of the wind energy distribution of any geographic position becomes possible; in future life, if the utilization of wind power resources is increased, the method provides technical support for efficient and accurate utilization of the wind power resources, and contributes to clean energy and human sustainable development.
On the basis of the foregoing embodiments, another embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the method in the foregoing embodiments.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are only for description, and do not represent the advantages and disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (6)

1. A wind field power downscaling method is characterized in that: the method comprises the following steps:
carrying out numerical simulation on the simplified terrain based on computational fluid mechanics to obtain pneumatic parameters of the simplified terrain;
the wind speed of the mesoscale grid points is redistributed in the downscale grid based on the terrain elevation data, the land utilization type data and the pneumatic parameters to realize wind field downscale calculation;
before the wind speed at the angular point position of the mesoscale grid is redistributed in the downscale grid to realize the downscale calculation of the wind field based on the terrain elevation data, the land utilization type data and the pneumatic parameters, the method further comprises the following steps: acquiring a mesoscale wind field of the region based on a region numerical weather forecast mode;
the pneumatic parameters of the simplified terrain comprise the average wind speed ratio of the middle point of the slope, and the average wind speed ratio meets the following requirements:
Figure FDA0003572585500000011
Wherein R isix、RizThe average wind speed ratio, U, of the measured point i in the downwind direction and the vertical direction respectivelyix、UizThe average wind speed, U, of the measured point i in the downwind direction and the vertical direction respectivelyHIs the average wind speed of the incoming flow;
and based on the terrain elevation data, the land utilization type data and the pneumatic parameters, the wind speed of the mesoscale grid is redistributed in the downscale grid to realize wind field downscale calculation, and the method comprises the following steps:
performing downscaling calculation on the average latitudinal wind speed and the average radial wind speed at the specified height of the mesoscale grid based on the mesoscale wind field;
and the average latitudinal wind speed after the downscaling calculation meets the following requirements:
Figure FDA0003572585500000012
the average radial wind speed after the downscaling calculation meets the following requirements:
Figure FDA0003572585500000013
u and v are respectively the average latitudinal wind speed and the average radial wind speed of the ground surface at the designated height in the downscaling wind field, and the corner marks m and n are respectively the mth row and the nth column of the downscaling grid; ri is the average wind speed ratio, N is the downscaling proportion, N is an integer, du is the downscaling correction term of the average latitudinal wind speed, and dv is the downscaling correction term of the average radial wind speed.
2. The method of claim 1, wherein: the simplified terrain is a two-dimensional simplified terrain, and the two-dimensional simplified terrain comprises two basic forms of a two-dimensional wind speed coming flow ascending slope and a two-dimensional wind speed coming flow descending slope.
3. The method of claim 1, wherein: after numerically simulating the simplified terrain based on computational fluid dynamics to obtain aerodynamic parameters of the simplified terrain, the method further comprises: and (5) carrying out wind tunnel test verification numerical simulation to obtain the pneumatic parameters of the simplified terrain.
4. The method of claim 1, wherein: after the grid resolution reaches the downscaling requirement, the wind speed at the angular point position of the mesoscale grid is redistributed in the downscaling grid based on the terrain elevation data, the land utilization type data and the pneumatic parameters to realize the wind field downscaling calculation, and the method further comprises the following steps:
according to the logarithmic rate form of the vertical wind profile, the variation of the average wind speed of the downscale wind field along the vertical height is expressed as:
Figure FDA0003572585500000021
in the formula, VzIs a height zToAverage wind speed of u*For the friction speed,. kappa.is the Karman constant, z0The surface roughness length is psi, the stability correction function of the mean wind speed logarithmic profile is phi, and L is the obuff length.
5. The method of claim 4, wherein: the value range of the height z is 0-150 m.
6. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107390298A (en) * 2017-07-19 2017-11-24 云南电网有限责任公司电力科学研究院 A kind of analogy method and device of Complex Mountain underlying surface strong wind

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KR100921575B1 (en) * 2009-09-02 2009-10-12 한국에너지기술연구원 Atmospheric flow simulation method considering influence of terrain elevation data resolution

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107390298A (en) * 2017-07-19 2017-11-24 云南电网有限责任公司电力科学研究院 A kind of analogy method and device of Complex Mountain underlying surface strong wind

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
基于WRF-CALMET的精细化方法在大风预报上的应用研究;李俊徽等;《气象》;20170821(第08期);第1007-1009页 *
山脊地形上的风场简化模型;刘志强等;《可再生能源》;20080815(第04期);24-26页 *

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